ROAD DEICING SALT IMPACTS ON URBAN WATERQUALITY

A THESIS

SUBMITTED TO THE FACULTY OF THE GRADUATE SCHOOL

OF THE UNIVERSITY OF MINNESOTA

BY

Eric Vladimir Novotny

IN PARTIAL FULFILLMENT OF THE REQUIREMENTS

FOR THE DEGREE OF

Doctor Of Philosophy

September, 2009

c© Eric Vladimir Novotny 2009

ALL RIGHTS RESERVED

Acknowledgements

I would like to acknowledge all of the people who have helped me in the completion of

this thesis. I would first and foremost like to acknowledge my advisor Dr. Heinz G.

Stefan for his guidance throughout my graduate studies. I know that the knowledge

and experience gained under his direction has prepared me well for my future and has

contributed significantly to the researcher and person I have become over the past 5

years.

I would also like to acknowledge the co-PI of my research project, Dr. Omid Mohseni,

and the three members of my PhD committee, Dr. John Gulliver, Dr. Paul Capel and

Dr. Bruce Wilson, for their contributions and suggestion to help improve my thesis.

Many other people have also contributed to my studies. I would like to acknowledge

Chris Ellis and Ben Erickson, of the St. Anthony Falls Laboratory at the University

of Minnesota, for their design expertise in building, setting up and installing lake-

monitoring equipment. Karen Jensen at the Metropolitan Council for helping obtain

data from area waste water treatment plants. Amy Myrbo and Kristina Brady at the

LacCore facility at the University of Minnesota for their help in obtaining and analyzing

sediment cores. The members of my technical advisory panel including Wayne Sand-

berg, Connie Fortin, Biz Colburn, Andrew Kubista, Debra Fick, Kathleen Schaefer,

Norm Ashfeld, Greg Felt, Jeff Goetzman, Eric Macbeth, Tom Struve, and Ann McLel-

lan. And my co-workers Andrew Sander, Ben Janke, Jeremiah Jazdzewski and the rest

of the staff and students at the St. Anthony Falls Laboratory for helping me with many

aspects of the project.

i

I would also like a acknowledge all of the sources of funding that have allowed me

to pursue my research goals. This includes the Minnesota Local Road Research Board

(LRRB), which funded a two-year study on environmental effects of road salt in the state

of Minnesota. Also the Silberman fellowship, University of Minnesota Doctoral Disser-

tation Fellowship and the University of Minnesota - Civil Engineering summer graduate

student fellowship, all of which provided me with the financial means to conduct my

research.

ii

Dedication

I dedicate this thesis to the people closest to me. First to my wife Susan. With out

you by my side this accomplishment would never have been possible. Thank you for

being there when I needed you, for being brutally honest when it was warranted and

for keeping me focused on what really mattered.

I also dedicate this to my parents Lynn and Vladimir and my brother Paul. Thank

you for making me the person I am today and providing me with guidance and support

throughout the years. The examples you set for me have been a guiding light towards

my accomplishments.

iii

ROAD DEICING SALT IMPACTS ON URBAN WATER QUALITY

by Eric Vladimir Novotny

ABSTRACT

Salt is widely used for ice and snow control on roads in the US, Canada and other

parts of the world affected by adverse winter driving conditions. The primary product

applied in North America for deicing of roads is sodium chloride (NaCl), a readily avail-

able and inexpensive material. The use of sodium chloride as a road deicing chemical

has increased dramatically in the northern areas of the United States over the last 50

years with about 23 million tons used in 2005.

The primary objective of my research was to determine how road salt applications

influenced the water quality in a major metropolitan area (Twin Cities metropolitan

area (TCMA) of Minneapolis/St Paul, Minnesota, USA). This objective was met by

collecting and analyzing data from area lakes, streams and rivers and through the de-

velopment 0 Dimensional (0D) and 1 Dimensional (1D) models.

It was determined that on average over 70% of the chloride applied annually in the

TCMA was retained in the watershed instead of entering the Mississippi River and

eventually exported to the Gulf of Mexico. Salinity cycles were observed in area lakes

with high concentration in the winter followed by lower concentrations in the spring

and summer. Mean annual concentrations in 38 lakes in the TCMA rose on average 1.4

mg/L per year over 22-years matching a similar trend in the amount of rock salt the

state of Minnesota purchased over the same time period.

Salt water inflows changed the natural mixing behavior of area lakes. In some lakes

monomictic behavior developed with mixing events only occuring in the fall. The pres-

ence of a saline layer at the bottom of the lake prohibited dissolved oxygen from reaching

the benthic water layer in the spring extending the anoxic period of this water layer by

iv

6 months. Simulations conducted without the presence of a saline layer showed com-

plete mixing and oxygenation of the benthic layers in the spring and fall. Rising Cl

concentrations in lakes are expected to continue. If the annual inputs of salt to the

lakes were stopped it would take 10 to 30 years to reach chloride concentrations equal

to predevelopment concentration.

Chloride retention in urban areas where road salt is applied should cause much concern.

Mitigation measures, best management practices (BMPs) for road salt application and

alternatives to NaCl need to be examined.

v

Contents

Acknowledgements i

Dedication iii

Abstract iv

List of Tables x

List of Figures xi

1 Overview 1

1.1 Problem Definition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

1.2 Background Information . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

1.2.1 Biota . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

1.2.2 Heavy metal transport . . . . . . . . . . . . . . . . . . . . . . . . 7

1.2.3 Soil chemistry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

1.2.4 Lakes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

1.3 Study Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

1.4 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

1.5 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

1.6 Overall Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

2 Chloride ion transport and mass balance in a metropolitan area using

road salt 19

2.1 Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

vi

2.2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

2.3 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

2.3.1 Metro area chloride balance . . . . . . . . . . . . . . . . . . . . . 22

2.3.2 Inflows and outflows . . . . . . . . . . . . . . . . . . . . . . . . . 25

2.3.3 Chloride sources . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

2.3.4 Chloride balances in sub-watersheds . . . . . . . . . . . . . . . . 28

2.4 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

2.4.1 Inflows and outflows of chloride in the major rivers . . . . . . . . 29

2.4.2 Metro area chloride sources . . . . . . . . . . . . . . . . . . . . . 31

2.4.3 Metro area chloride balance calculation . . . . . . . . . . . . . . 33

2.4.4 Sub-watershed chloride balance calculation . . . . . . . . . . . . 35

2.4.5 Sodium retention . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

2.4.6 Sensitivity of the results . . . . . . . . . . . . . . . . . . . . . . . 38

2.4.7 Comparison to other metro areas . . . . . . . . . . . . . . . . . . 41

2.4.8 Chloride retention in the TCMA watershed . . . . . . . . . . . . 41

2.5 Summary and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . 44

3 Increase of urban lake salinity by road deicing salt 46

3.1 Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

3.2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

3.3 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

3.3.1 Data collection . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

3.3.2 Data analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54

3.4 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

3.4.1 Ionic composition and relationship to specific conductance . . . . 56

3.4.2 Seasonal salinity cycles and salinity stratification . . . . . . . . . 58

3.4.3 Effects of salinity on seasonal mixing and dissolved oxygen . . . 61

3.4.4 Salinity in lake sediment cores . . . . . . . . . . . . . . . . . . . 61

3.4.5 Salinity trends in TCMA lakes . . . . . . . . . . . . . . . . . . . 63

3.4.6 Relationships between lake salinity and watershed characteristics 64

3.5 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66

3.5.1 Comparison of ionic composition with other freshwaters . . . . . 66

vii

3.5.2 Indicators of the salinity sources . . . . . . . . . . . . . . . . . . 68

3.5.3 Salinity, temperature and dissolved oxygen stratification . . . . . 69

3.5.4 Seasonal flushing of salt from the TCMA lakes . . . . . . . . . . 70

3.5.5 Convective mixing of saline lake water with pore water in the

sediments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71

3.5.6 Salinity trends in TCMA lakes . . . . . . . . . . . . . . . . . . . 72

3.5.7 Relationships between lake salinity, lake bathymetry and water-

shed characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . 73

3.6 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74

4 A 0-D modeling approach to study long-term chloride concentration

in lakes receiving runoff containing road salt 76

4.1 Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77

4.2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78

4.3 Lake Chloride Model Fomulation . . . . . . . . . . . . . . . . . . . . . . 79

4.3.1 Zero-dimensional model formulation . . . . . . . . . . . . . . . . 79

4.3.2 Daily time scale model . . . . . . . . . . . . . . . . . . . . . . . . 79

4.3.3 Annual time scale model . . . . . . . . . . . . . . . . . . . . . . . 82

4.3.4 Model assumptions . . . . . . . . . . . . . . . . . . . . . . . . . . 83

4.4 Lake data collection and model calibration . . . . . . . . . . . . . . . . . 84

4.5 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86

4.6 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91

4.6.1 Model Sensitivity . . . . . . . . . . . . . . . . . . . . . . . . . . . 91

4.6.2 Model projections . . . . . . . . . . . . . . . . . . . . . . . . . . 92

4.7 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93

5 Road salt impact on vertical lake mixing 95

5.1 Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96

5.2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97

5.3 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99

5.3.1 Field Investigation: Data Collection/Sampling Site . . . . . . . . 99

5.3.2 Model Formulation: Simulation of Summer Stratification in a

Lake with a Benthic Saline Layer . . . . . . . . . . . . . . . . . . 100

viii

5.3.3 Model Simulation of Dissolved Oxygen Transfer in a Lake with a

Saline Benthic Layer . . . . . . . . . . . . . . . . . . . . . . . . . 108

5.4 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111

5.4.1 Saline Layer Formation: Continuous lake monitoring results . . . 111

5.4.2 Lake Stratification: Model calibration results . . . . . . . . . . . 115

5.4.3 Lake Stratification and Vertical Mixing: Model simulation results 116

5.4.4 Dissolved Oxygen Modeling Results . . . . . . . . . . . . . . . . 122

5.5 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126

5.5.1 Interpretation of Measurements (2007-2009) and Simulation Re-

sults (2007-2008) . . . . . . . . . . . . . . . . . . . . . . . . . . . 126

5.5.2 Effects of Benthic Saline Layer Formation on Lake Water Quality 128

5.6 Summary and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . 129

References 131

Appendix A. Data Sets 146

ix

List of Tables

2.1 Names of sampling points and data collection organizations . . . . . . . 24

2.2 Estimates of average chloride concentrations, flow rates, and total mass

of Cl in effluents from major WWTPs . . . . . . . . . . . . . . . . . . . 32

2.3 Stream watershed information and road salt application rates within each

sub-watershed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

3.1 Lake and watershed information . . . . . . . . . . . . . . . . . . . . . . 52

3.2 Median ionic concentrations of water sampled from 9 lakes . . . . . . . . 56

3.3 Salinity (Cl-) cycles in TCMA lakes. . . . . . . . . . . . . . . . . . . . . 60

3.4 Historical average, trend and maxima of chloride concentrations, and

bathymetric and watershed data for 38 TCMA lakes . . . . . . . . . . . 65

3.5 Correlation coefficients of chloride concentrations with lake and water-

shed parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66

3.6 Ionic composition (mg/L) of selective surface waters in North America

and the nine lakes studied in 2006/2007. . . . . . . . . . . . . . . . . . . 67

4.1 Lakes modeled . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85

4.2 Model parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86

4.3 Maximum and minimum chloride concentrations at equilibrium . . . . . 88

4.4 Chloride loading rates, flushing flow rate and flushing rate . . . . . . . . 91

5.1 Comparison of specific conductance recorded by the Buoy system to val-

ues measured with the YSI Model 63 probe . . . . . . . . . . . . . . . . 112

5.2 Best fit parameters from model calibration . . . . . . . . . . . . . . . . . 115

x

List of Figures

1.1 Sodium chloride deicing salt used for the United states and the state of

Minnesota . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

1.2 Density current intrusion of snowmelt water into a lake (schematic). . . 11

2.1 Watershed boundaries of the Twin Cities metropolitan area and major

rivers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

2.2 Median concentrations of sodium and chloride from the two major rivers 29

2.3 Flow-weighted average monthly chloride concentrations and flow rates at

the inflow and outflow of the major rivers . . . . . . . . . . . . . . . . . 30

2.4 Grab sample chloride concentrations from the effluents of the four WWTPs 32

2.5 (A) Monthly chloride fluxes (t/yr) from point sources entering or exiting

the Twin Cities metropolitan area watershed (B) Monthly differences

between the Outflow and the Inflow + WWTP . . . . . . . . . . . . . . 34

2.6 Average annual chloride concentrations vs. amount of chloride applied

per watershed area for the 10 subwatershed streams . . . . . . . . . . . 37

2.7 (A) Daily averages of specific conductance from 15-minute continuous

monitoring (B) Cumulative normalized distribution functions of daily

specific conductance values. . . . . . . . . . . . . . . . . . . . . . . . . . 39

2.8 Chloride concentrations in two streams of the Twin Cities metropolitan

area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

2.9 Chloride concentration in wells located throughout the Twin Cities Metropoli-

tan area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

3.1 Chloride concentrations in Battle Creek . . . . . . . . . . . . . . . . . . 49

3.2 Locations and watersheds of lakes sampled . . . . . . . . . . . . . . . . . 51

3.3 Relationship between chloride and specific conductance . . . . . . . . . 57

xi

3.4 Chloride concentrations in each lake . . . . . . . . . . . . . . . . . . . . 58

3.5 Seasonal salinity (Cl-) cycles . . . . . . . . . . . . . . . . . . . . . . . . 59

3.6 Chloride concentration, dissolved oxygen concentration and water tem-

perature vs. depth in Tanners Lakes . . . . . . . . . . . . . . . . . . . . 62

3.7 Ionic composition of pore water in sediment cores . . . . . . . . . . . . . 63

3.8 Average normalized specific conductance in 38 Twin Cities Metro Area

lakes and total rock salt purchases by the State of Minnesota. . . . . . . 64

4.1 Modeled and observed chloride concentrations . . . . . . . . . . . . . . . 87

4.2 Projected future chloride concentrations . . . . . . . . . . . . . . . . . . 89

5.1 Lake location and bathymetry for Tanners Lake . . . . . . . . . . . . . . 99

5.2 Schematic of Buoy set up . . . . . . . . . . . . . . . . . . . . . . . . . . 101

5.3 Weather parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109

5.4 Specific conductance for uncorrected and corrected data . . . . . . . . . 112

5.5 Recorded temperature and specific conductance . . . . . . . . . . . . . . 113

5.6 Specific conductance data and weather data for buoy system. . . . . . . 114

5.7 Modeled and observed water temperature and specific conductance . . . 117

5.8 Temperatures and specific conductance at the surface, at mid-depth and

at the bottom of Tanners Lake . . . . . . . . . . . . . . . . . . . . . . . 118

5.9 Root mean square error between modeled and observed data . . . . . . 119

5.10 Data used as initial conditions for simulations . . . . . . . . . . . . . . . 120

5.11 Time vs. depth plot of model simulation results . . . . . . . . . . . . . 121

5.12 Profiles of density gradients caused by salinity and temperature . . . . . 123

5.13 Daily hypolimnetic eddy diffusion coefficients near the lake bed . . . . . 124

5.14 Results from the case study dissolved oxygen simulation . . . . . . . . . 125

xii

Chapter 1

Overview

1

2

1.1 Problem Definition

In the snow-belt regions of the U.S. and other northern countries deicing agents are

applied to remove snow and ice from roadways in winter in order to increase driving

safety. The primary agent used for this purpose is rock salt consisting mainly of sodium

chloride (NaCl). Other agents in the road salt mixture, such as ferrocyanide, which is

used as an anti-clumping agent, and impurities consisting of trace elements (phosphorus,

sulphur, nitrogen, copper and zinc), can represent up to 5% of the salt weight [1].

In the U.S. annual rock salt use for road de-icing increased from 163,000 tons in

1940 to over 23 million tons in 2005 according to the United Stated Geological Survey

(USGS) mineral yearbooks [2, 3]. In the state of Minnesota annual rock salt purchases

increased during the same time period from 60,000 tons to over 900,000 tons [2](Figure

1.1. Other deicing agents are available (e.g. calcium or magnesium chloride (CaCl2)

or potassium acetate), but because of a large difference in cost NaCl is applied most

frequently [4].

Road salt applications keep roads free of ice for safe winter travel in northern climate

zones, however this practice comes at a cost to the infrastructure and the environment,

especially in urban areas with high road densities. The rock salt applied to the roads

dissolves in the melting snow and ice separating into sodium and chloride ions. The

salt- containing water runs off into streams, lakes or storm sewers or infiltrates into the

soil eventually reaching the groundwater. It affects the chemistry and biota in the soil

and water [5]. The overall scope of my PhD research project was to analyze the fate and

transport of road deicing salt (NaCl) in the environment and the water quality issues

associated with road salt applications in a major metropolitan area (Minneapolis/St.

Paul Twin Cities Metropolitan Area, Minnesota, United States).

1.2 Background Information

1.2.1 Biota

Chloride and sodium levels can influence terrestrial and aquatic biota. Chloride levels

of 1000 mg/l can have lethal or sub-lethal affects on aquatic plants and invertebrates

[6]. Continuous levels as low as 250 mg/L have been shown to be harmful to aquatic life

3

0.0

0.2

0.4

0.6

0.8

1.0

1.2

0

5

10

15

20

25

1930 1940 1950 1960 1970 1980 1990 2000 2010 M

inn

es

ota

Ro

ck

Sa

lt U

se

(M

illi

on

to

ns

)

Un

ite

d S

tate

s R

oa

d S

alt

Us

e (

Mil

lio

n t

on

s)

United States Road Salt Use

Minnesota Rock Salt Use

Figure 1.1: Total amount of sodium chloride (NaCl) used as deicing salt throughoutthe United States and the annual amount of rock salt (NaC) purchased by the state ofMinnesota [2].

4

and to render water non-potable for human consumption [6]. In the state of Minnesota

chloride standards of 860 mg/L for acute exposure events and 230 mg/L for chronic

exposure have been established by the Minnesota Pollution Control Agency (MPCA)

for surface waters designated as important for aquatic life and recreation (Minnesota R.

Ch. 7050 and 7052). The groundwater standard for chloride has been set at 250 mg/L

by the USEPA and is a secondary standard relating to the taste of the water.

Increases in sodium and chloride concentrations have been show to decrease the bio-

diversity in wetland areas and waterways [7, 8]. Wood frog species richness in wetlands

in northwestern and southwestern Ontario have been negatively impacted by increased

stress, increased mortality, and altered development resulting from acute and chronic

exposure to road salts [9]. Fish diversity and richness also decreased as sodium and

chloride concentrations increased along with an increase in impervious surfaces in river

watersheds in the Twin Cities area [10]. Macroinvertebrates on the other hand are not

affected by levels of chloride found in wetlands [11, 12]. Chloride ranks third among

chemical ion species for the regulation of diatom species, and is therefore used by paleo-

limnologists to reconstruct chloride levels in lakes from sediment cores [13, 14].

Microorganisms and bacteria can also be influenced by the salinity of the water.

Microorganisms are classified into four groups based on how they react to salt concen-

trations [15]. The first two groups are classifications for nonhalophiles. Nonhalophiles

can be either salt sensitive or salt tolerant. Salt sensitive bacteria can only grow in

media containing less that 2 percent salt (20,000 mg/L). On the other hand salt tol-

erant bacteria grow best in media containing less that 2 percent salt, but will grow in

media containing more that 2 percent. Halophiles can also be classified in two groups:

facultative and obligate. Facultative halophiles will grow in media containing less that

2 percent salt, but will grow best in media containing more that 2 percent. Obligate

on the other hand can only grow in media containing more that 2 percent growth.

These four groups are also known as nonhalophiles, halotolerant bacteria, halophiles

and extreme halophiles respectively [16].

The presence of salts influences the waters activity (amount of water available for

biological processes). Water activity is defined as the ratio between the vapor pressure

of a solution to the vapor pressure of pure water resulting in a value of 1 for pure

water and 0.98 for seawater (3.5% salinity) [16]. Water flows from regions of low solute

5

concentrations to regions of high solute concentration through osmosis [16].

In most bacteria the cytoplasm of a cell has a higher concentration of solutes than

the surrounding environment resulting in a flow of water into the cell[16]. If the salinity

outside the cell causes the activity of the water to be lower than that of the cytoplasm

inside the cell, the flow will reverse will happen causing dehydration of the bacteria.

The loss of water from the cytoplasm results in the fastest and most lethal consequence

high salinity can have on a bacteria [17]. Most freshwater and marine organisms are

stenohaline, i.e. they can not handle wide fluctuations in salinity, but some organisms

have the ability to withstand increases in salinity from their normal environment with

a reduction in growth rates (halotolerant)[17].

In order to adjust to the decrease in water availability in the media around the cell,

most halotolerant and halophilic bacteria must maintain a cytoplasm with a much lower

salt concentration then their surrounding environment. The bacteria accomplish this

by creating low molecular weight organic compounds that help provide osmotic balance

between the medium and the cell cytoplasm [18]. The low molecular weight solutes

accumulate in the cytoplasm creating a high intracellular concentration allowing for the

flux of water to continue to flow into the cell. These solutes are preferred due to their

protective nature against inactivation, inhibition, and denaturalization of enzymes and

macromolecular structures [17].

The solutes that respond to external osmotic pressures are called osmotica. Osmotica

share three main qualities, they are polar, highly soluble molecules and show only

limited interactions with proteins. Polyols (glyceral, arabitol, mannitol, erythritol)

sugars (sucrose, trehalose), hetersides (glucosylglycerol), betaines (trimethylammonium

compounds) thetines (dimethylsulfonium comounds), amino acids (proline, glutamate,

glutamine and derivates), glutamine amide derivative, and ectoines are some of the

most important know osmotica [18]. The ability of the cells to create these osmotica

allows them to regulate the solute concentration inside the cell according to the salt

concentration outside the cell. This change in solute concentration can be achieved

rapidly when the outside concentration is changed allowing these bacterial to withstand

fluctuations in salt concentration.

High salinity concentration can also influence the solubility of proteins. They can

create a ’salting out’ or ’salting in’ effect depending on the anions or cations in the

6

medium. Salting out ions strengthen the hydrophobic bonds in proteins causing them

to become less soluble. Salting in ions do the opposite, making the proteins more soluble

by decreasing the hydrophobic bonds [17]. The changes in solubility of proteins can also

influence the hydrophobic and hydrophilic interactions responsible for the stability of

the lipid bilayers in the cell. The ions can dehydrate this layer by out competing the

lipids for water. Some solutes can even partition into the hydrophobic domain [17].

In general all halophilic and halotolerant bacteria have a certain number of adapta-

tions that are required to survive in environments with high fluctuations in salt concen-

trations. These include having the ability to adjust the solute concentration inside the

cytoplasm of the cell causing a reduction in the water availability that closely matches

the osmotic pressure in the outside medium. With out this ability the cell could either

burst with a sharp reduction in salinity in the outside medium or dehydrate with a

sharp increase salinity. The second adaptation that all halophilic bacteria have is the

ability to prevent toxic ions such as sodium and chloride from entering the cell into the

cytoplasm.

A third property of halophilic bacteria is that they have created adaptations to their

external structures such as the cell wall, membranes, and extra cellular and membrane

enzymes. This third adaptation of halophilic bacteria represents the greatest difference

between bacteria that can live in high salt environments and other non-salt tolerant

species [17]. This adaptation is due to the evolutionary process that changes the syn-

thesis of structural molecules. This adaptation also explains how halophilic bacteria are

dependent on high salt concentrations since the extra cellular materials are irreversibly

adapted to salt [17].

If a small stream receives snowmelt runoff directly from roadways treated with salt

(NaCl), concentrations of sodium and chloride will spike during the winter and spring

months, and decline quickly once the salt application has stopped [19]. In the state of

Minnesota data are available showing high concentrations of chloride traveling through

streams and storm sewers during the winter months. The large fluctuation in salinity

could negatively effect organisms that are not able to adapt quickly to the salinity

change reducing the biodiversity in the stream.

Four streams (Shingle Creek, Nine Mile Creek, Beavens Creek and Battle Creek)

7

in the Minneapolis/St. Paul Twin Cities Metropolitan Area (TCMA) have been desig-

nated in 2008 as impaired waters and placed on the Clean Water Act section 303d Total

Maximum Daily Load (TMDL) list because of salt pollution [20]. In one of those streams

(Shingle Creek) the highest recorded concentration of chloride reached 12,000 mg/L in

the winter [21]. Median concentrations at the same locations were 150 mg/L and mini-

mum concentrations were 64 mg/L during the summer months. Chloride concentrations

in grab samples of storm sewer effluents reached 35,000 mg/L during the winter [20]. In

storm sewers emptying into the Mississippi River, concentrations of chloride reached 900

mg/L during January while the maximum concentrations were less that 130 mg/L in

the summer. Other regions have shown similar elevated chloride concentrations [22, 4].

Chloride concentrations in urban streams of the northeastern United States have been

measured as high as 5000 mg/L during the winter months [23].

1.2.2 Heavy metal transport

NaCl is not the only constituent in snowmelt runoff that can have environmental conse-

quences. In urban environments, specifically on roadways, heavy metals are deposited

by automobile traffic. Sources of the metal pollutants are tire wear, engine and break

parts, fluid leakage, vehicular component wear, atmospheric depositions and road sur-

face abrasion [24, 25]. These metals are transported by runoff from rainfall or snowmelt

into receiving water bodies resulting in the contamination of soils, lakes, streams, wet-

lands and groundwater. Heavy metal concentrations in stormwater runoff can reach

levels high enough to be toxic or even severely toxic to biota especially in runoff from

major highways [26]. Copper, zinc, lead, cadmium, sediments, PAHs, and deicing salts

represent the main source of pollution found in runoff from roads [27]. Heavy metals are

the most consistent pollutants in roadside runoff [28] ], and the highest concentrations

of metals come from major highways [29].

Heavy metals accumulate in the snowpack and on roadways during the winter

months. This accumulation combined with the increased corrosion of metals and wear

on the roadways in winter results in both higher concentrations and a higher total load

of metals during snowmelt compared to rainfall [24, 30, 26, 31, 32]. Concentrations of

metals in snowmelt runoff can be two to four times higher than during rainfall; the

8

highest concentrations occurring during rainfall on a snow pack [32]. The higher con-

centrations of heavy metals and the presence of deicing salts in snowmelt runoff cause a

larger number of toxic and severely toxic events to occur compared to rainfall events [26].

This increase in toxicity can reduce the diversity in the benthic and plant communities

[33].

De-icing salts, mostly NaCl, and temperature increase the mobility of metals in soil

environments [34]. The increase is caused by a change in the partitioning coefficients

between the dissolved and particulate phases of the metals especially cadmium, zinc,

and copper. When the salinity is increased or the temperature drops, the partitioning

coefficients decrease resulting in an increase of the bioavailable dissolved phase portion

of the metals to increase [35, 34, 36]. Increased mobility of metals, such as Cd Cu, Fe,

Pb, due to road salt applications has been observed in the environment.

Cd and Zn mobilization is affected by metal-chloride complexation as well as ion

exchange with Na, Ca or H [37, 38, 39]. The transport of Pb and Cu on the other

hand are influenced by the dispersion of organic matter and colloid-assisted transport

[40, 37, 39]. The increase in colloid-assisted transport was caused by the presence of high

concentrations of sodium attached to the soil particles. Soils with high concentrations of

sodium swell due to the relative size of the Na ion compared to Ca or Mg. This swelling

results in the breakup of the soils, a reduction in the soils hydraulic conductivity and

an increase in colloid dispersion [41]. Colloidal facilitative transport can be a dominant

process in the transport of strong sorbing materials [42].

In Sweden Pb, Cu, and Zn were found to be suceptable to increased mobilization

in roadside soils and leaching into the groundwater where high concentrations of NaCl,

reducing conditions and lowered pH were present [43]. In Germany Cd and Zn concen-

trations in roadside soils in winter and fall were observed to be extremely different from

those in summer and spring due to leaching from applications of deicing salts (NaCl)

[36].

At the sediment/water interface of a small pond near a major highway in Ontario,

Canada, Cl and Na concentration were measured greater than 3 and 2 g/L respectively.

These concentrations decreased gradually with depth into the sediments, but 40 cm

into the sediments Cl concentrations were still 1.5 g/L. These high concentrations in the

sediment pore waters increased the dissolved concentrations of Cd resulting in increased

9

toxicity of the water to benthic organism [44].

Concentrations of metals in snowmelt runoff are related to the runoff hydrograph.

Dissolved pollutants (50%-90%) are transported primarily in the first fraction of the

snowmelt runoff while most of the particulate matter, and the metals adsorbed to those

particles, are found in the last part of the snowmelt runoff [45][46]. A higher percentage

of metals in the snowmelt runoff are incorporated in the particulate phase, while the

majority of metals in rainfall events are in the dissolved phase. This is mostly due to

the higher concentrations of suspended solids and particulate matter in snowmelt runoff

compared to rainfall, except for high intensity, short duration, rainfall events [32].

1.2.3 Soil chemistry

Soil particles have a net negative charge for two reasons: 1) isomorphic substitution of

Al by Mg or Fe or Si by Al, resulting in a permanent change on the clay particles [47]

and 2) organic matter functional groups such as carboxyls, and or surface hydroxyls of

inorganic material, resulting in a variable change dependent on pH and ionic strength of

the soil solution [48]. Isomorphic substitution is the replacement of an atom by another

atom of similar size in the clay structure. In the case of Al being substituted by Mg,

the sizes of the atoms are similar but the charges are different. Al has a net charge of

+3 and Mg has a net positive charge of +2 resulting in a net negative charge on the

clay particle after substitution. The variable charge forms by the donation of protons

from the organic matter functional groups or surface hydroxyls. When the pH of the

soil environment increases the weak acid functional groups donate a hydrogen proton

resulting in a net negative charge.

The net negative charge on the soil particles is balanced by the adsorption of cations

consisting mostly of Ca, Mg, Na and K but also H, Fe, and Al. Typically Ca and Mg

are preferred over Na due to the smaller size of the ions and the divalent change, but

when water with high concentrations of sodium infiltrates the soils, sodium becomes pre-

ferred inducing ion exchange between the sodium and primarily calcium and magnesium

[49][50][38][41][45]. The process increases the concentration of calcium and magnesium

in surface and groundwater and decreases the Na/Cl ratio.

In a study on Mirror Lake, NH, the Na/Cl ratio was 1.01 from 1970 to 1975. After the

construction of an interstate highway in the watershed, highway deicing salts caused a

10

fourteen fold increase in Cl and a decrease in the Na/Cl ratio to 0.68 [51]. Ion exchange

can increase the mobility of hydrogen ions and decrease the pH of the water in the

process [38][45]. The change to soil chemistry by road salt applications is typically

restricted to a distance of 10 m from the road. The most significant soil exchange

processes occur within 6 m of salt applications [41]. The sodium continues to exchange

with calcium, magnesium and even potassium until equilibrium is reached; from then

on sodium will act conservatively [50].

The adsorption of the sodium ions onto the clay particles influences the properties of

the soils. Due to the relatively large size, single electrical charge and hydration status of

sodium ions, when sodium replaces calcium and magnesium the forces binding the soils

particles are disrupted causing separation, dispersion and swelling [52]. Soil dispersion

hardens soils and blocks water infiltration by causing clay particles to plug soil pores

reducing soil permeability. Soil dispersion also reduces the hydraulic conductivity of the

soil, i.e. the rate at which water flows through the soil [52]. In general, clays containing

mostly Na-ions are sticky and impervious while clays containing mostly Ca-ions are

workable and permeable [53]. Because sodium can change the permeability of soils,

brines are used in reservoirs to convert calcium clays to sodium clays in order to make

the bottom sediments less permeable [53].

1.2.4 Lakes

Streams and storm sewers capturing snowmelt water from roadways are likely to cause

seasonal salinity variations in lakes into which they discharge. Salt concentrations in

urban streams during the winter months are sufficiently high to cause density currents

and chemical stratification in the receiving lakes (Figure 1.2). This phenomenon has

been documented in Minneapolis where a saline density current, occurring synoptically

with above freezing air temperatures and snowmelt runoff, proceeded to the deepest

part of a small lake where it remained until spring [54]. A NaCl concentration of 1

g/L (Cl concentration of 600 mg/L) can increases the specific gravity of water by

approximately 0.0008 [55]. This density change by salinity is significant in relation to

a temperature-induced density change, especially at low temperatures. For example,

a temperature change from 4o to 5o C produces the same specific gravity change as a

salt concentration increase of 10 mg/L [55]. A saline water layer can cause a lake to

11

become permanently density stratified at the bottom. In such a meromictic lake, the

bottom waters never mix completely with the surface waters. Naturally meromictic lakes

exist in dry regions of the world and the consequences often include dissolved oxygen

depletion and high concentrations of phosphate, ammonia, and hydrogen sulfide at the

sediment water interface. Small lakes and deep lakes are more vulnerable to becoming

meromictic; large lakes have more fetch and therefore experience more powerful wind

mixing [6]. Shallow lakes require a smaller amount of wind energy to fully mix than

deep lakes.

Figure 1.2: Density current intrusion of snowmelt water into a lake (schematic).

The formation of meromixis in a lake is of concern because it can have many con-

sequences. Chemical stratification impedes vertical mixing preventing dissolved oxygen

(DO) from reaching the benthic layers of the lake. The low DO conditions that develop

below the chemocline can result in the loss of all but the most resilient deep water species

[6]. Meromixis can also limit transfer of DO and other solutes at the sediment/water

interface. This is significant because phosphorus and heavy metals are more readily

released from anoxic sediments [6]. Elevated salinity decreases the partition coefficient

of some metals, thus causing a release of soluble toxic metal forms from the sediment

[4]. These issues can become important for lakes receiving runoff from snowmelt that

contains road salt.

Road salt applications have been shown to increase the salinity in lakes near major

roadways especially in urban watersheds [14, 51, 56]. Extreme cases have been reported:

chloride concentrations reached up to 5190 mg/L in a pond draining a major urban

highway in Canada; other ponds showed concentrations up to 3000 mg/L during the

12

winter [57, 58, 44]. Road salt applications in rural areas have affected lakes within a few

hundred meters. In urban environments, the presence of storm sewer can increase the

distance of this influence [6]. A more comprehensive summary of existing research on

this subject can be found in a summary report commissioned by Environment Canada

and Health Canada [59].

1.3 Study Objectives

This PhD dissertation examines road salt transport in an urban environment. The study

is conducted in the urban watershed of the Twin Cities metropolitan area (TCMA) of

Minneapolis/St. Paul in Minnesota. Four major questions are addressed in separate

chapters:

• How much of the roadsalt (NaCl) applied on TCMA roadways each year is leaving

the watershed by the Mississippi River, and how much Is accumulating in the lakes

and groundwater of the TCMA?

• What are current and historical chloride concentration dynamics in different lakes

of the TCMA?

• What are the projections for future salinity levels in lakes of the TCMA?

• How is a saline water layer formed at the bottom of a lake, and how does this

saline water layer influence vertical lake mixing dynamics?

The research was motivated by the overall hypothesis that an excessive accumulation

of roadsalt (NaCl) in surface waters and groundwater could have serious, and possibly

unacceptable consequences (e.g. violations of water quality standards) by changing the

chemistry and ecology of these waters. Road salt practices may have to be changed

to avoid the formation of monomictic lakes and widespread exceedances of chronic and

acute water quality standards in urban lakes.

1.4 Methodology

Metro area chloride budget: Road salt application data were obtained from cities,

counties and state agencies in the TCMA, flow rates and effluent chloride concentrations

13

from wastewater treatment plants in the TCMA, and flow and chloride data from area

streams and rivers were assembled for the years 2000-2008. With this data the rates of

total annual salt (chloride and sodium) imports to the TCMA, rates of salt addition and

transport within the TCMA, and rates of salt exports from the TCMA in the Mississippi

River were calculated and analyzed. The difference between total annual rate of salt

import and export gives an estimate of how much road salt is retained in the TCMA,

i.e. stored in the soils, the lakes and the groundwater throughout the TCMA. This

component of the overall salt budget can cause progressive environmental degradation.

Sub-watershed chloride budgets: Chloride budgets for 10 sub-watersheds within

the TCMA, were analyzed in a similar way. None received input from a wastewater treat-

ment plant. The sole chloride input was from road salt applied in each sub-watershed.

Historical data analysis: Historical water quality data for lakes and streams

including sodium and chloride concentrations were assembled and analyzed. Data sets

were obtained from the MPCA environmental data access database for 72 lakes in the

Twin Cities metropolitan area (TCMA). Of those 72 lakes 39 had at least 10 years of

data over the last 22 years. These data sets were normalized with the average concen-

tration between 2001 and 2005 and averaged together to obtain a time series of lake

chloride concentrations. The results could then be correlated with the amount of rock

salt purchased by the state of Minnesota over the same time period. Other historical

data were obtained from other Minnesota State Agencies and the Metropolitan Council.

Lake profiling: Profiles of water temperature and specific conductance in 9 area

lakes were measured every 6 weeks between January 2006 and November 2008. A rela-

tionship between chloride concentrations and specific conductance was determined using

water samples taken in these lakes. Using the conductivity vs. chloride relationship the

profiles of specific conductance were converted to chloride profiles to see chemical strat-

ification. Seasonal changes in stratification and volumetric concentration averages were

then obtained for each lake.

Continuous lake monitoring: To get a data set of high temporal resolution, sen-

sors and recording equipment were installed under a buoy in one of the lakes (Tanners

Lake near I-94 in Oakdale) to continuously monitor temperature and specific conduc-

tance at 2-minute intervals from November 2008 to August 2009. Thirteen temperature

and specific conductance probes were connected to a data logger that stored the data

14

and could be interrogated by remote access. The data collected were used to analyze the

intrusion of saline runoff into the lake during the winter, and vertical lake-mixing during

the following open water season. The data were correlated to weather parameters.

Lake modeling: Two deterministic and unsteady lake simulation models were

developed to analyze and project lake chloride concentrations at two timescales. The

first model was a 0-D model simulating the accumulation and flushing of salt at a weekly

time scale in lakes receiving runoff containing road salt. Seven lakes were simulated and

each lake was treated as completely mixed with accumulation of salt occurring in winter

and early spring, and flushing by runoff from rainfall in late spring, summer and fall.

Specific conductance profiles measured every 4-6 weeks over 3 to 5 years were used to

calibrate the model. Simulations were run with the calibrated model to predict future

chloride concentration under difference salt loading scenarios, i.e. road salt application

practices.

The second simulation model was created to simulate vertical lake mixing during

the summer stratification period using a 1-D model and a daily time scale. This model

predicted vertical profiles of temperature, specific conductance (salinity) and dissolved

oxygen (DO) at a daily timestep using daily weather parameters and lake bathymetry

as inputs. Initial temperature and salinity profiles were taken after ice out. The model

was applied to Tanners Lake and simulations predicted temperature, salinity and DO

profiles throughout the ice-free period of the lake.

1.5 Results

Results of the field data collection, analysis of historical and recent data, and simulations

of 7 TCMA lakes with the 0D model, and of Tanners Lake with the 1D model provided

answers to the four questions posed earlier.

In chapter 2 the retention of chloride from road deicing salt (NaCl) application in the

watershed encompassing the TCMA was examined. A chloride budget for the TCMA

watershed, including river inflows and outflows, and major salt inputs from household,

industrial, commercial and road salt applications was prepared at an annual timescale. It

was found that 317,000 metric tons of road salt (NaCl) are applied annually In the seven

county TCMA (4150 km2 surface area). The TCMA watershed Is a little smaller and

15

accounts for a smaller amount of roadsalt. Length of roads, not surface area, were used

to make the adjustment. 77% of the chloride in this amount of road salt is retained in the

TCMA watershed. Salt retention depends foremost on the hydrologic drainage system,

which in the TCMA includes many lakes, wetlands, and detention/infiltration basins,

along with an extensive storm sewer system, many small streams, and an extensive

groundwater system of shallow and deep confined aquifers. Chloride concentrations in

many TCMA surface water bodies are now considerably higher than the pre-settlement

background levels of less than 3 mg/L. Wastewater treatment plants receiving most of

the NaCl used in water softeners, industrial and commercial applications, have effluent

Cl concentrations on the order of 200 to 400 mg/L. Chloride concentrations in some wells

of the surficial aquifers were as high as 2000 mg/L. Chloride concentrations reported for

wells in the TCMA aquifer system indicate a decrease of chloride concentrations with

depth below the surface, and with distance from major roadways.

In chapter 3 salinity and temperature profiles from lakes located throughout the

Minneapolis/St. Paul Twin Cities Metropolitan area (TCMA) were examined. Thir-

teen lakes in the TCMA were studied over 46 months to determine if and how they

respond to the seasonal applications of road salt. Sodium and chloride concentrations

in these lakes were 10 and 25 times higher, respectively, than in other non-urban lakes

in the region. Seasonal salinity/chloride cycles in the lakes were correlated with road

salt applications: high concentrations in the winter and spring, especially near the bot-

tom of the lakes, were followed by lower concentrations in the summer and fall due

to flushing of the lakes by rainfall runoff. The seasonal salt storage/flushing rates for

individual lakes were derived from volume weighted average chloride concentration time

series. The seasonal flushing rate ranged from 9 to 55% of a lakes minimum salt con-

tent. In some of the lakes salt concentrations near the lake bottom were high enough

to stop spring turnover preventing oxygen from reaching the benthic sediments in sum-

mer. Salt concentrations in the water layer above the sediments were high enough to

induce convective penetration of the denser saline water into the fresher sediment pore

water. A regional analysis of historical water quality records of 38 lakes in the TCMA

showed increases in average chloride concentrations of 1.4 mg/L per year from 1984 to

2005. These increases were highly correlated with the amount of rock salt purchased

by the State of Minnesota. Chloride concentrations in individual lakes were positively

16

correlated with the percent of impervious surface area in the watershed and inversely

with lake volume.

In chapter 4 a 0-D model was developed to simulate the seasonal chloride cycle of

loading and flushing, as well as the long-term accumulation of chloride in seven urban

lakes receiving runoff from roads. The model was used to determine steady state concen-

trations under different loading conditions. The model was calibrated using five years

(2004-2008) of monthly salinity profiles from the lakes in the TCMA, four model pa-

rameters and an initial concentration. Three of the seven lakes are headed towards year

round volume averaged chloride concentrations above the 230 mg/L chronic standard

for impairment to aquatic habitat. The two lakes with the lowest projected equilibrium

concentrations of chloride have already reached equilibrium. It was projected that one

lake will take up to 40 years to reach equilibrium. If road salt application rates are

reduced in future winters, lakes will respond with noticeably lower Cl concentrations

within 5 to 10 years. If road salt applications were discontinued altogether, chloride

concentrations should reduce to nearly natural levels within 10 to 30 years in all seven

lakes.

In chapter 5 three questions were addressed: How is a saline layer formed at the

bottom of a lake, how does a saline water layer at the bottom of a lake influences vertical

lake mixing dynamics, and how is the vertical transfer of dissolved oxygen influenced by

these mixing dynamics? The continuous specific conductance and temperature records

recorded at 2-minute interval in Tanners Lake give a detailed picture of saline water

build-up at the bottom of the lake. The saltwater intrusion and the resulting build-up

of the benthic saline layer occur in episodes correlated with warm weather periods and

snow melting. The very last salt water intrusion occurs after ice-out presumably due to

a lag in watershed runoff processes. Spring turnover after ice-out is not able to erode

the chemocline completely. The chemocline is weakened throughout the summer, but

the seasonal thermocline a few meters below the lake surface removes much of the wind

energy necessary to do the hypolimnetic mixing. The dynamic 1-D lake temperature and

salinity model was developed and matched to data from records of specific conductance

and temperature. The model was able to reproduce measurements from 2007 and 2008.

In 2007 the lake mixed completely in both spring and fall. In 2008 the lake did not mix

in spring allowing the saline layer to persist throughout the summer. In the fall of 2008

17

due to weakening of the saline layer and warming of the benthic waters, the lake was

able to completely mix. In 2009 the observed lake stratification behavior was similar to

2008. Inclusion of the lake number in the calculation of the hypolimnetic eddy diffusion

parameter made the mixing in the hypolimnion stronger when the lake was unstable in

the fall and spring and weaker in the summer when thermal stratification had formed.

Density stratification after ice out is dominated by salinity, but is quickly overtaken by

temperature stratification as the epilimnion warms. The existence of the saline layer

after ice out is strong enough to prevent oxygen from reaching the deeper water layers

in the lake. The presence of the saline layer causes the lake to switch from dimictic

behavior to monomictic behavior. As a result the lake sediments are oxygenated by

mixing of above only once per year at the fall turnover of the lake.

1.6 Overall Conclusions

Road salt is used to increase driving safety in the Twin Cities metropolitan area (TCMA)

of Minnesota. In this dissertation data for the TCMA area of 4150 km2 and a population

of 2.8 Million were collected and analyzed. Simulation models were developed to project

some of the consequences of road salt application for the water resources in the TCMA.

The results, as well as the methods by which they were obtained, are presented in detail

in Chapters 2 to 5 of this dissertation. Highlights are:

(1) A chloride budget for the TCMA watershed based on data from 2000 to 2008

revealed that of the 142,000 metric tonnes (t) of chloride applied annually in the TCMA

as road salt, only 23% (33,000 t) were exported through the Mississippi River and

109,000 t or 77% were retained in the TCMA watershed. Chloride budgets for 10 sub-

watersheds within the TCMA, analyzed in a similar way, gave an average retention rate

of 72% for road salt.

(2) The salt imported in the TCMA but not exported by the Mississippi River has to

be accumulating in the area soil, lakes and groundwater. Evidence of chloride retention

is widespread in the TCMA. Four streams in the TCMA are on the MPCAs 2008 list

of chloride-impaired surface waters. Salinity cycles have been observed in TCMA lakes

with high concentrations in the winterand spring followed by lower concentrations in the

summer and fall. Mean annual concentrations in 38 lakes in the TCMA have been rising

18

on average 1.4 mg/L per year over a 22-year period with current median concentrations

in the surface waters at 87 mg/L. This trend matched a similar trend in the amount of

rock salt the state of Minnesota has purchased over the same time period.

(3) The saline water input is changing the natural mixing behavior of some TCMA

lakes. In some lakes monomictic behavior has occurred with full turnover only happening

in the fall. The presence of a saline layer at the bottom of the lake inhibits dissolved

oxygen from reaching the deep lake sediments in the spring extending the anoxic period

of this water layer by several months. Simulations conducted without the presence of

a saline layer showed two turnover events (dimictic behavior) and oxygenation of lake

sediments in spring and fall.

(4) A few TCMA lakes will reach average chloride levels in violation of current

state standards for chronic exposure if current road salt application rates are continued.

Lakes in the TCMA can recover from current salinity levels in periods of 10 to 30

years if road salt applications are stopped completely. Groundwater, especially deep

groundwater will recover much more slowly, and may take hundreds and thousands of

years to recover.

(5) Chloride retention in urban areas where road salt (NaCl) is applied should cause

concern. Mitigation measures, best management practices (BMPs) for road salt appli-

cation and alternatives to NaCl need to be examined. If no changes are made some area

lakes and groundwater wells would be expected in the foreseeable future to exceed the

current water quality standards set by the USEPA.

Chapter 2

Chloride ion transport and mass

balance in a metropolitan area

using road salt

Eric V. Novotny, Andrew R. Sander, Omid Mohseni, and Heinz G. Stefan

St. Anthony Falls Laboratory,

Department of Civil Engineering, University of Minnesota

Minneapolis, Minnesota 55414

c© 2009 by AGU.org

19

20

2.1 Abstract

In the Twin Cities metropolitan area (TCMA) of Minneapolis/St.Paul, Minnesota, USA,

an estimated 317,000 metric tonnes (t) of road salt were used annually for road de-icing

between 2000 and 2005. To determine the annual retention of road salt, a chloride

budget was conducted for a 4150 km2 watershed encompassing the populated areas of

the TCMA. In addition to inflows and outflows in the major rivers of the TCMA, mul-

tiple sources of chloride were examined, but only road salt and wastewater treatment

plant (WWTP) effluents were large enough to be included in the analysis. Accord-

ing to the chloride budget 235,000 t of chloride entered the TCMA annually with the

Mississippi and Minnesota Rivers, and 355,000 t exited through the Mississippi River.

Of the 120,000 t of chloride added annually to the rivers inside the TCMA watershed

boundaries, 87,000 t came from WWTPs and 33,000 t came from road salt. Of the

142,000 t of chloride applied annually in the TCMA watershed as road salt (241,000 t

NaCl), only 23% (33,000 t) were exported through the Mississippi River and 109,000 t

or 77% were retained in the TCMA watershed. Chloride budgets for 10 sub-watersheds

within the TCMA analyzed in a similar way, gave an average chloride retention rate of

72%. The retention is occurring in the soils, surface waters (numerous lakes, wetlands

and ponds) and in the groundwater. Chloride concentrations in many of these urban

water bodies are now considerably higher than the pre-settlement background levels of

less than 3 mg/L with concentrations as high as 2000 mg/L in shallow groundwater

wells. The continued accumulation of chloride in the groundwater and surface waters is

a cause for concern.

21

2.2 Introduction

It has been reported that 21 million metric tonnes (t) of road salt were used in the United

States in 2005 to improve driving safety in the winter [2]. In the seven county Twin

Cities metropolitan area (TCMA) of Minneapolis/St.Paul, Minnesota, an estimated

317,000 t of road salt were used annually for road de-icing between 2000 and 2005 [60].

Road salt (mostly NaCl) is highly soluble in water resulting in the sodium and chloride

ions dissociating from one another when snowmelt occurs. Chloride and sodium ions are

both transported from roads to receiving waters along three pathways: 1) a rapid runoff

pathway from impervious surfaces, 2) a shallow subsurface pathway through the soil, and

3) a deeper and slower pathway through underground aquifers [4]. All three pathways

can result in the retention of sodium and chloride in the surface water and groundwater

of a watershed [61]. In addition to the accumulation that can occur in the surficial and

deep groundwater aquifers, small amounts of chloride and more so sodium could also

be retained through interactions with soils and organic matter [40, 62, 50, 63]. The

major factors influencing retention in soils and groundwater include soil permeability,

vegetation cover, topography, and roadside drainage techniques [64].

The accumulation of sodium and chloride ions in the environment degrades the wa-

ter quality in a watershed [64, 6, 61]. Increased chloride concentrations decrease the

biodiversity of waterways and roadside vegetation [6]. If chloride reaches the groundwa-

ter it can contaminate drinking water supplies [65]. Not only has chloride been shown

to affect organism, it can also increase the transport and bioavailability of heavy metals

such as cadmium, lead, chromium, copper and even mercury in the environment, which

are also harmful to biota [4]. Other secondary consequences of road salt applications

in lakes include the ability to inhibit or delay natural mixing events limiting the oxy-

genation of benthic waters and sediments and facilitating the release of heavy metals,

mercury and phosphorus stored in the sediments [64].

Elevated and/or increasing chloride concentrations attributable to road salt applica-

tions are present in groundwater and surface waters in urban environments in northern

climate regions[66, 67, 68, 69, 22, 23, 70, 38, 1, 71, 5]. Mass balance studies on in-

dividual streams with watershed areas less than 450 km2 indicate that between 27%

and 65% of the road salt applied was retained within the individual urban watersheds

22

[72, 73, 74, 75, 76].

Unlike previous studies, which analyzed small watersheds located in urban environ-

ments, this study examines an entire metropolitan area encompassing a surface area of

4,150 km2 including rural, suburban, and urban communities. By examining an entire

metropolitan area, a better understanding of the total retention and the holistic effect

of road salt applications on groundwater and surface waters can be obtained. This

study also used data collected over an 8-year period. Potential environmental damage

will affect the entire metropolitan area, and policies on road salt applications cannot

be developed by extrapolation from small sub-watersheds. Overall this study draws at-

tention to a developing problem that will affect around 3 Million people in a 4,150-km2

area and provides insight for other major metropolitan areas on the affects of road salt

applications.

The purpose of the study was to examine the spatial and temporal chloride transport

dynamics and to develop a chloride budget for an entire metropolitan area. This analysis

was used to estimate how much of the road salt applied annually is exported from the

watershed by the Mississippi River and how much is retained in the soils, groundwater

and surface waters.

2.3 Methods

2.3.1 Metro area chloride balance

The Minneapolis/St. Paul Twin Cities metropolitan area (TCMA) is an urbanized area

with a population of 2.8 million [77], many watercourses and 950 lakes. Located in the

north central U.S., the TCMA experiences cold climate with an average annual snowfall

of 1420 mm between November and April [78]. The hydrologic drainage system of the

TCMA includes many small streams, lakes and wetlands along with an extensive storm

sewer systems and hundreds of detention and infiltration basins. Under the TCMA

is a system of several aquifers, some of which are used for urban water supply. Two

major rivers, the Minnesota and the Mississippi, flow through the TCMA. The combined

watersheds of these two rivers encompass 4,150 km2 of the seven-county metropolitan

area, and provide the natural boundaries for a control volume to be used in a chloride

mass balance (Figure 2.1).

23

Figure 1: Watershed boundaries (bold gray lines) of the Twin Cities metropolitan area and major

rivers (Mississippi, Minnesota and St. Croix). Numbers label each of the data collection or

sampling points listed in Table 1. Data from unlabeled chloride sampling points were not used in

the budget analysis, but to plot Figure 2.

Figure 2.1: Watershed boundaries (bold gray lines) of the Twin Cities metropolitanarea and major rivers (Mississippi, Minnesota and St. Croix). Numbers identify each ofthe data collection or sampling points listed in Table 2.1. Data from unlabeled chloridesampling points were used in Figure 2.2, but not used in the budget analysis

24

Table 2.1: Names of sampling points and data collection organizations for flow ratesand chloride concentrations used in the budget analysis. Locations are shown in Figure2.1.Number Name Organization

1 05330000 Minnesota River at Jordan U.S. Geological Survey2 05288500 Mississippi River at Anoka U.S. Geological Survey3 05331000 Mississippi River at St. Paul U.S. Geological Survey4 Upper Mississippi River Mile 871.6 Metropolitan Council5 Minnesota River Mile 39.6 Metropolitan Council6 Upper Mississippi River Mile 815.6 Metropolitan Council7 Blue Lake WWTP Metropolitan Council8 Seneca WWTP Metropolitan Council9 Metro WWTP Metropolitan Council10 Eagle Point WWTP Metropolitan Council

The chloride ion, known to be harmful to biota [64, 61] and more conservative in

water than sodium [40, 62, 50, 63], was chosen to develop an annual chloride mass

balance (Eq. 2.1) for the TCMA control volume.

I +Mp +Mnp −O = S(t/yr), (2.1)

Where I is the total annual inflow (t/yr) through the Mississippi River at Anoka and

the Minnesota River at Jordan, Mp and Mnp represent the total annual mass of chloride

added inside the watershed from point sources and non-point sources respectively, O is

the total annual mass of chloride exported through the Mississippi River at Hastings

and S is the annual retention of chloride (t/yr) in the TCMA. Chloride is highly soluble

in water, and has been treated as conservative once it is in solution.

Once the water reaches the Minnesota or Mississippi Rivers storage potential is

limited. It is expected that the mass of chloride entering the TCMA at the inflow

stations will exit at the outflow stations. Likewise, all of the chlorides discharged directly

to the rivers through point sources are expected to reach the outflow station. However,

the hydrological transport from nonpoint sources of chloride is unknown. Non point

sources of chloride can infiltrate into soils, can accumulate in wetlands or lakes, can

travel through storm sewers or can reach the groundwater. Only some of the salt

applied as a non-point source in the TCMA is expected to reach the Mississippi River.

Therefore, chloride can only be retained in the watershed if it comes from a non-point

25

source. This assumption allows for the rearrangement of Eq. 2.1 to (Eq. 2.2).

O − I −Mp = mnp(t/yr) (2.2)

Where mnp = Mnp S. We first calulated mnp and then S knowing Mnp. The value of

mnp represents the amount of chloride from non-point sources that entered the river

system and was flushed out of the watershed system at the Mississippi River outflow

station.

2.3.2 Inflows and outflows

Sodium and chloride concentrations as well as river flow rates were measured by state

and federal agencies at gauges and sampling points on the Mississippi and the Min-

nesota Rivers (Figure 2.1). The Metropolitan Council Environmental Services (MCES)

collected grab samples for chemical analyses at six locations along the Mississippi River

and two locations on the Minnesota River two to five times per month between January

2000 and December 2007. For the same time period, daily average, and monthly average

flow rates were obtained from the United States Geological Survey (USGS).

The watershed area upstream from the grab sampling station at Anoka is 48,900 km2,

while the watershed area upstream from the USGS stream gauging station is 49,500 km2,

a difference of only 1.2%. Therefore, the flow rates and the grab sample concentrations

were used together without adjustment. The USGS St. Paul gauging station is located

38 km upstream from the outflow grab sample location at Hastings. The watershed

areas for these two locations are 95,300 km2 and 95,900 km2 respectively, or a difference

of 0.6%. The only major inflow between these two points is the Metro wastewater

treatment plant (WWTP). The river outflow rate from the TCMA was therefore taken

to be the flow rate at St. Paul plus the outflow from the Metro WWTP. Using the daily

flow data and grab sample concentrations from 2000 to 2007, flow weighted monthly

average chloride concentrations were calculated. Each of these concentrations (mg/L)

were multiplied by the associated mean monthly flow rate (m3/s) to estimate the mean

monthly chloride mass transport rate (t/yr).

26

2.3.3 Chloride sources

Sodium and chloride sources include natural weathering of minerals, natural deposition

from rainfall, processing of agricultural products, industrial production of chemicals

and food, processing in the metal-, paper-, petroleum-, textile-, and dying-industries,

household uses, water softening, and road salt applications of NaCl [79]. Point sources

of chloride in the watershed include WWTP effluents and industrial discharges to the

Mississippi or Minnesota Rivers. Most industrial sources of chloride are connected to

the WWTPs and are included in the point-source discharges from the WWTPs. Non-

point sources of chloride are natural sources (atmospheric deposition, weathering), rural

household septic systems, fertilizer applications, and snowmelt runoff containing road

salt.

Point sources: Wastewater treatment plants (WWTPs). Effluents from

WWTPs are a significant source of chloride from domestic (foods and water softening)

and industrial NaCl uses. Chloride concentrations in effluent grab samples were mea-

sured by the Metropolitan Council (MCES) from June 2007 to June 2008 in two-week

intervals at the four major wastewater treatment plants within the TCMA watershed.

Locations of the WWTPs are shown in Figure 1. The annual average chloride con-

centrations and the annual average flow rates determined from daily WWTP effluent

flow data were used to determine the mean annual rates (t/yr) of chloride input to

the rivers from the four WWTPs. The majority of industries and 2.4 million of the

2.8 million people living in the TCMA contribute wastewater through sanitary sew-

ers to the four-wastewater treatment plants discharging within the boundaries of the

TCMA watershed. The majority of the other 400,000 people are either located outside

the boundaries of the watershed or contribute to one of the three other wastewater

treatment plants that do not discharge within the control volume. Combined sewers in

the TCMA have been reduced to a minimum. Therefore, all household and industrial

sources of chloride within the control volume boundaries in the TCMA are included in

the effluent values from the four major wastewater treatment plants.

Non-point sources: Natural sources. Natural sources of chloride and sodium,

in general, include mineral salt deposits, weathering of geological formations, and wet

deposition from ocean evaporation[3]. Mineral salt deposits and geological sources of

chloride are negligible in the TCMA. The annual average concentration of chloride in

27

rainwater was measured at a site in the northern part of the TCMA from 2000 to 2007

to be 0.07 mg/L [80]. This value combined with an annual average rainfall of 747 mm

was used to estimate natural source loads of chloride.

Septic systems of rural households. In 1997 around 70,000 households in the 7

county TCMA were using a septic system [81]. Of those 70,000 household around 60%

were located outside of the watershed boundaries. This population estimation was used

to determined chloride loads from private septic systems.

Agricultural sources of chloride. Farming in the outskirts of the TCMA is lim-

ited to 19% (77,000 ha) of the total watershed area. This percentage was calculated

using land use data from 2005 provided by the Metropolitan Council. For the produc-

tion of corn 36 kg/ha of potassium chloride are required according to the Minnesota

Department of Agriculture [82] A value of 49.9 kg/ha per year was used in a study of

fertilizer and manure contributions to streams in Sweden [5].

Road salt. The total mass of road salt (NaCl) applied annually (2000 to 2005 aver-

age) to roads and parking lots within the seven-county TCMA by government agencies

and commercial/private users was estimated to be 317,000 t/yr [60]. 241,000 or 76%

came from public applications (i.e. city, county and state agencies), the other 24% or

76,000 t was estimated to come from commercial/private applications. The commercial

percentage provided by the American Salt Institute for the years 2005 and 2006 was

based on market share information for road salt purchases. Commercial/private appli-

cations were determined to be the amount of bulk salt purchased by non-government

agencies plus the amount of package deicing salt purchased by both homeowners and

commercial applicators.

The TCMA watershed boundaries do not coincide with the political TCMA bound-

aries (Figure 2.1). For that reason the amount of road salt applied within the political

seven county TCMA had to be adjusted using road kilometers. City, county and state

road data were obtained from the GIS database of the Metropolitan Council. Road

lengths were divided by government entity into total kilometers of city roads for each

city, of county roads for each county and state road. Fractions (percent) of road lengths

inside the watershed vs. the total length inside a municipality, county, or state jurisdic-

tion were multiplied by the total mass of road salt applied by each individual agency

to estimate the total mass of salt applied in the watershed. The total mass of road salt

28

applied by private and commercial uses on parking lots, sidewalks etc. was added to the

public road salt applications by using a value equal to 24% of the total salt applications.

2.3.4 Chloride balances in sub-watersheds

The chloride budget study for the entire TCMA was supplemented by a chloride budget

study for 10 sub-watersheds of small streams located entirely within the TCMA. This

study was done to determine if salt retention rates obtained at a geographic scale of less

than on tenth the TCMA were comparable to those obtained for the entire TCMA.

The analysis of the sub-watersheds was based on Eq. 2.1. The inflow (I) for the

sub-watersheds was based on the estimated chloride concentration in the streams that

would be expected if road salts were not applied in the watershed. This value is different

from the overall TCMA study and was defined as the background concentration in the

stream. The background concentration was estimated from a linear relationship between

the annual average chloride concentrations in the streams vs. the mass of chloride from

road salt applied per ha per year within the watersheds. The background concentration

was found by extrapolating the linear relationship to a chloride application rate of zero.

The background concentration was multiplied by the annual average discharge (flow)

from the watershed to obtain the inflow loading (I).

The only internal chloride source (M) in the watershed was from road salt appli-

cations. No WWTP effluents or other chloride sources besides road salts were being

applied in the sub-watersheds. The mass of road salt applied to the roads was deter-

mined using the methods described for the TCMA watershed analysis explained above.

The percentage of the watershed covered by impervious surfaces and the total watershed

areas were found using GIS data from the University of Minnesota Remote Sensing and

Geospatial Analysis Laboratory (http://land.umn.edu/index.html).

To calculate the annual export rate of chloride mass (O) exiting each sub-watershed,

daily average flow data and grab sample data, collected by the Metropolitan Council

Environmental Services (MCES) two to five times per month between 1/1/2000 and

12/31/2007, at the outflow from each sub-watershed were used.

29

2.4 Results and Discussion

2.4.1 Inflows and outflows of chloride in the major rivers

The hydrologic transport of sodium and chloride in the TCMA was inferred from the

concentrations in its major rivers. Average annual concentrations measured in these

rivers show significant changes with distance through the TCMA (Figure 2.2). Increased

Na+ and Cl− concentrations in the Mississippi River were most pronounced downstream

from the confluence with the Minnesota River and the Metro WWTP where mean annual

chloride concentrations increased from 16 mg/L to 33 mg/L. The Minnesota River

arrived in the TCMA with higher concentrations than the Mississippi River. Discharges

into the Minnesota River include effluents from the Blue Lake and the Seneca WWTPs

as well as surface runoff from populated areas, resulting in a mean annual chloride

concentration increase from 30 mg/L to 42 mg/L. The St. Croix River is outside the

TCMA and carries much lower chloride concentrations ( 5 mg/L) because the watershed

is largely undeveloped. Inflow from the St. Croix River caused a decrease in chloride

concentrations in the Mississippi River downstream from the TCMA. In all three rivers

sodium and chloride follow similar concentration distributions with distance.

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Figure 2: Median chloride concentrations (2000-2008) of sodium and chloride in grab samples (2000-2007)

from the two major rivers of the Twin Cities Metropolitan Area. Arrows denote locations of WWTP

discharges or river junctions. Figure 2.2: Median concentrations of sodium and chloride in grab samples (2000-2007)from the two major rivers of the Twin Cities Metropolitan Area. Arrows denote loca-tions of WWTP discharges or river junctions.

Where the Mississippi enters the TCMA at Anoka mean monthly flow weighted

chloride concentrations were between 15 and 20 mg/L (Figure 2.3). Individual grab

30

samples showed only small variations for a particular month with the exception of Jan-

uary, February and November. In the Minnesota River inflow to the TCMA at Jordan,

mean monthly chloride concentrations ranged from 20 to 40mg/L (Figure 2.3). Flow

weighted mean monthly concentrations were highest between December and February

and lowest from March to August. Variability between individual grab samples for a

given month were highest in February.

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Figure 3: Flow-weighted average monthly chloride concentrations and flow rates at the inflow and

outflow of major rivers in the TCMA watershed (2000 - 2007). Figure 2.3: Flow-weighted average monthly chloride concentrations and flow rates atthe inflow and outflow of the major rivers in the TCMA watershed (2000 - 2007).

At the Mississippi River outflow station in Hastings mean monthly concentrations

ranged between 20 and 50 mg/L with a strong seasonal variation (Figure 2.3). The

high concentrations occurred between January and March, and the lows between April

to July. Individual grab sample concentrations varied the most in March, and the least

in June.

Estimates were made for the total mass of chloride passing through the inflow and

31

outflow observation points in Figure 2.3 for every month. The annual mass (rates)

of chloride entering the TCMA by the Minnesota and Mississippi River inflows were

determined to be 119,000 and 116,000 t/yr, respectively. The mass (rate) of chloride

flowing out of the TCMA watershed with the Mississippi River was found to be 355,000

t/yr. Roughly 50% more chloride was found to be exiting the watershed than what was

entering with the Mississippi and Minnesota Rivers combined.

2.4.2 Metro area chloride sources

Point sources: The only point source of chloride in the TCMA is the wastewater

discharged from four wastewater treatment plants 2.4. Effluent chloride concentrations

increased during the winter months at the Metro WWTP. Domestic and industrial

waste loads to the wastewater treatment system were expected to remain fairly con-

stant throughout the year, as was shown for the other three WWTPs. Therefore, the

increase at Metro during the winter was attributed to the addition of road salt to the

system through car washes, a small number of combined sewers and possible seepage

into the sanitary sewer system. To avoid double counting road salt inputs, the average

Cl− concentration between June and November was used for the entire year in the an-

nual chloride budget. Although the other three WWTPs did not display a significant

concentration increase in winter, the same procedure was used for consistency. The

(June 2007-Nov 2007) average chloride concentrations in the WWTP effluents and the

annual average effluent flow rates are shown in Table 2.2. The associated mass (rate)

of chloride entering the river system from the four WWTPs, including domestic and in-

dustrial wastewater, but excluding chloride from road salt applications, was estimated

to be 87,000 t/yr.

Non-point sources: Non-point chloride loads from natural sources, septic systems,

agricultural sources and road salt were evaluated. Using recorded rainfall amounts

and measured concentrations of chloride in precipitation in the TCMA, the chloride

contribution from natural sources was estimated to be around 220 t/yr.

The majority of people within the TCMA watershed boundaries are connected to one

of 7 WWTPs by sanitary sewers and a majority of the households using a private septic

system are located outside the watershed boundaries. If as many as 60,000 people,

i.e. the number of people connected to the Eagle Point WWTP, were using septic

32

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Figure 4: Chloride concentrations from grab samples from the effluents

of the four WWTPs. Dates are MM/DD/YY. Figure 2.4: Grab sample chloride concentrations from the effluents of the four WWTPs.Dates are MM/DD/YY.

Table 2.2: Estimates of average chloride concentrations, flow rates and total mass of Cl-in effluents from major WWTPs in the TCMA each year. Average chloride concentra-tions are flow weighted and for the period June 2006 to June 2007 excluding the wintermonths. Average flow rates are from 2000 to 2007.Name of WWTP Chloride (mg/L) Flow (m3/s) Mass (t/yr)Metro 227 8.63 62000Blue Lake 387 1.18 14000Seneca 280 1.01 9000Eagle Point 348 0.18 2000Total 11.00 87000

33

systems within watershed boundaries the 2000 t of chloride discharged annually from

this WWTP would be a reasonable estimate of chloride releases from septic tanks (Table

2.2). For agricultural loads, using a value of 49.9 kg/ha of chloride from fertilizer and

manure results in only 3,800 t of chloride added to the watershed. If all of the designated

agricultural land were instead only used to grow corn this value would only be 2,800

t/yr of chloride.

The largest non-point source of chloride in the TCMA was road salt. It was deter-

mined that 241,000 t of the 317,000 t of road salt applied annually in the seven county

metropolitan area was applied within the watershed boundaries shown in Figure 2.1.

This translates to a non-point source input of 142,000 t/yr of chloride from road salt

applications. It was determined that natural deposition, agricultural inputs and septic

sewer systems would only contribute an additional 1-3%, depending on the calcula-

tion method, to the total chloride load (from point and non-point sources). Therefore

the loads from these sources were neglected, leaving road salt applications as the only

significant non-point source of chloride within the watersheds boundaries.

2.4.3 Metro area chloride balance calculation

The individual chloride balance components (Mississippi River inflow, Minnesota River

inflow, Mississippi River outflow, road salt application, WWTP effluents) presented in

the previous sections were combined in a chloride mass balance using equation (2.1) on

a monthly timescale.

Mean monthly mass fluxes (t/month) of chloride entering or exiting the TCMA wa-

tershed from the two major rivers and the four WWTPs are illustrated in Figure 2.5A.

Dashed lines in Figure 2.5A give cumulative contributions by month from WWTP efflu-

ents, the Minnesota River and the Mississippi River, up to the total Inflow + WWTP

curve. The Outflow curve is from the Mississippi River outflow station in Hastings. Fig-

ure 2.5A is a graphical representation of Equation 2.2, showing the difference between

the mass of chloride exiting the watershed (O) and the sum of the amount entering the

watershed (I) and the amount added by point sources (Mp). Figure 2.5B represents the

amount of chloride added to the river system from non-point sources (mnp in Eq 2.2.).

Since road salt is the only significant non-point source of chloride inside the watershed

Figure 2.5B also represents the monthly mass of chloride from road salt applications

34

exported by the Mississippi River from the TCMA watershed. The monthly non-point

source chloride contribution to the Mississippi River outflow was highest (Figure 2.5B)

during the winter months when road salt was being applied to the roads. The high De-

cember to April values can be interpreted as the direct impact of road salt applications

and snowmelt water runoff through systems of storm sewers and small streams to the

big rivers. Delays occur because winter is a low flow season, and only when snowmelt

sets in does the routing processes accelerate. The small contributions in late summer

can be attributed to the flushing of chloride from lakes and wetlands [71] or to delayed

transport to the rivers through interflow or groundwater flow [4].

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Figure 5: (A) Monthly rates (mass) of chloride fluxes (t/yr) from point sources entering or exiting the Twin cities metropolitan

area watershed. Shaded areas between dashed lines give monthly contributions from four wastewater treatment plant (WWTP)

effluents, the Minnesota River and the Mississippi. Values are additive up to the total "Inflow + WWTP" curve. The

"Outflow" curve is from the Mississippi River outflow station in Hastings, downstream from the Twin Cities metropolitan

area. (B) Monthly differences between the “Outflow” and the “Inflow + WWTP” (solid lines) from panel A. Panel B gives the

algebraic sum of monthly inflow, outflow and point source loads of chloride to the river. By virtue of the mass balance in Eq.

(1) the plotted values also give the monthly amounts of non-point source chloride exported by the river as well as the

uncertainties in the mass balance.

Figure 2.5: (A) Monthly chloride fluxes (t/yr) from point sources entering or exitingthe Twin Cities metropolitan area watershed. Shaded areas between dashed lines givemonthly contributions from four WWTP effluents, the Minnesota River and the Mis-sissippi. Values are additive up to the total ”Inflow + WWTP” curve. The ”Outflow”curve is from the Mississippi River outflow station in Hastings, downstream from theTwin Cities metropolitan area. (B) Monthly differences between the Outflow and theInflow + WWTP (solid lines) from panel A. By virtue of the mass balance in Eq.(2.2)the plotted values give the monthly amounts of non-point source chloride exported bythe river as well as the uncertainties in the mass balance.

In March the difference between the mass of chloride exported and the mass im-

ported had a maximum. Road salt applied in the TCMA watershed accounted for

34% of the chloride passing the Mississippi River outflow station in March, WWTPs

contributed 19%, and the inflows from the Mississippi and Minnesota Rivers into the

TCMA watershed provided 47% (Figure 2.5A). The total amount of chloride exported

from the system during this month was 13,000 t (Figure 2.5B). By adding the values

35

for all months in Figure 2.5B, the annual mass of chloride from road salt exiting the

control volume (the TCMA watershed) was found to be 33,000 t/yr. It had previously

been estimated that 142,000 t of chloride/yr were applied as road salt to the TCMA

watershed area. If 33,000 of the 142,000 t were carried away by the Mississippi then

109,000 t or 77% of the chloride applied annually had to stay behind in the TCMA

watershed system (S in Eqs 2.1 and 2.2).

2.4.4 Sub-watershed chloride balance calculation

The average annual chloride concentrations in the 10 small streams within the larger

TCMA watershed ranged from 37 mg/L in Carver Creek to 185 mg/L in Shingle Creek;

annual average flow rates were from 0.093 m3/s in Riley Creek to 1.685 m3/s in Min-

nehaha Creek (Table 2.3). The total watershed area, the percentage covered by imper-

vious surfaces and the mass of road salt applied annually were also determined (Table

2.3). Chloride application rates in the 10 sub-watershed ranged from 0.08 to 0.82 t/ha

per year.

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12,5

0072

37

A background concentration of 18.6 mg/L (+/- 34.9 mg/L at the 95% confidence

interval) was determined using a linear regression analysis between annual average Cl-

concentrations in the stream (mg/L) and total Cl- applied (t/yr) per watershed area

(Figure 2.6; R2 = 0.79). The background concentration of 18.6 mg/L matched with

concentrations in the Mississippi River before it entered the TCMA. Retention of chlo-

ride in each individual sub-watershed was calculated to be from 55% to 83% (Table 2.3).

The total combined mass of chloride applied in the 10 sub- watersheds was 45,300 t/yr,

which represents 32% of the amount applied in the entire TCMA watershed. The total

amount of chloride exported from the 10 sub-watersheds was estimated at 12,500 t/yr.

This means that only 28% of the salt applied was exported from the 10 sub-watersheds

each year, and therefore 72% was retained. Due to the large confidence interval around

the background concentrations an analysis was conducted by setting the background

concentration to 0 mg/L. This represents a scenario where all of the chloride exiting the

watershed in a given year is from road salt applications during that year. This analysis

resulted in the lowest possible retention rate. If the background concentration was set

to 0 mg/L the amount of road salt exiting the watershed would be raised to 15,900 t/yr

reducing the retention rate to 65%. The retention estimates of 72% and 65% are lower

than the 77% value obtained for the entire TCMA watershed, but comparable.

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B17C53",D"EA9?"9="4@35473"422C4A"<FA951>3"<92<32?54?1928"@8"4G9C2?"9="<FA951>3""

4HHA13>"H35"I4?358F34>"4534"=95"?F3"$&"8CJI4?358F3>"8?534G8'""K2?35<3H?"I48"

C83>"48"J4<L759C2>"<92<32?54?192"12"?F3"8C>I4?358F3>"JC>73?"424A!818'"Figure 2.6: Average annual chloride concentrations vs amount of chloride applied perwatershed area for the 10 sub-watershed streams. Intercept was used as backgroundconcentration in the sub-watershed chloride budget analysis

38

2.4.5 Sodium retention

The retention of chloride from road salt applications in a watershed encompassing the

Twin Cities metropolitan area was determined to be around 77%. While an analysis was

not conducted on the other ion in rock salt, sodium, due to its slightly less conservative

behavior a value equal to or higher than 77% would be expected. Sodium interacts

more readily with soils through ion exchange allowing for the possibility that higher

amounts could be stored in the soil column [40, 50]. The assessment of chloride (road

salt) retention was made with the best information available, however assumptions,

which had to be made, do influence the results obtained. The sensitivity of the findings

to the assumptions was therefore investigated.

2.4.6 Sensitivity of the results

The assessment of chloride (road salt) retention was made with the best information

available, however assumptions, which had to be made, do influence the results ob-

tained. The sensitivity of the findings to three assumptions and procedures used was

therefore investigated: the sampling frequency of the grab samples at the inflow and

outflow stations, the method of calculations for chloride exported from the watershed,

and the estimations method for the non-point sources of chloride.

Sampling Frequency

An analysis was conducted to determine if continuous monitoring or more frequent

sampling was needed to capture chloride concentrations in snowmelt events of short

duration at the inflow and outflow stations on the Mississippi and Minnesota Rivers

[75]. To test the sensitivity to sampling frequency, records of daily average specific

conductance in the Mississippi River near Hastings (outflow station) were used from a

continuous monitoring station maintained by the Metropolitan Council (Figure 2.7A).

Although a direct relationship between chloride and specific conductance could not be

obtained, due to the dampening of the chloride signal in relation to other ions from the

high flow rates, snowmelt events could be clearly detected by fluctuations in specific

conductance during the winter. A Comparison was conducted between the continuous

time series of daily specific conductance values and the specific conductance and chloride

39

values recorded on the grab sample dates. This analysis provided evidence that a suit-

able representation of the chloride dynamics was obtained with the biweekly sampling

frequency used (Figure 2.7A). Furthermore, the cumulative distributions of specific con-

ductance values obtained from the continuous daily time series and the values on the

days when chloride grab samples were taken were virtually identical (Figure 2.7B). It

was concluded that the sampling frequency used was adequate to estimate the annual

load of Cl- (salt) exiting or entering the TCMA watershed over the study period.

10

20

30

40

50

60

70

80

90

100

110

120

130

140

150

160

170

0

100

200

300

400

500

600

700

800

900

1/1/00 1/1/01 1/1/02 1/1/03 1/1/04 1/1/05 1/1/06 1/1/07

Ch

lorid

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/L) Sp

ecific

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(µ

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F.29"7#2>'*G,'C$:$/.9"1&'73%:./"H&8'8"29%"A$9"37'4$769"372'34'8."/0'25&6"4"6'6378$69.76&'1./$&2>'I@&'23/"8'/"7&'%&5%&2&792'9@&'25&6"4"6'

6378$69.76&'1./$&2'37/0'43%'8.02'?@&7'.'6@/3%"8&'#%.A'2.:5/&'?.2'9.B&7>'I@&'8.2@&8'/"7&'$2&2'.//'8."/0'1./$&2'2@3?7'"7'+>'Figure 2.7: (A) Daily averages of specific conductance from 15-minute continuous mon-itoring (solid line). Days when chloride grab samples were taken (top). Chloride con-centrations from grab samples (bottom). Data are from the Mississippi River outflowstation in Hastings. (B) Cumulative normalized distribution functions of daily specificconductance values. Specific conductance values only for days when a chloride grabsample was taken (solid line) and all daily values shown from panel A (dashed line).

Chloride export

Other pathways of chloride export such as airborne transport of salt particles or chlori-

nation of natural organic matter were not analyzed. Salt particles can become airborne

behind vehicles and during strong winds, however they are typically deposited within

100 m of the road [83]. Cl- has also been found to interact with natural organic matter

forming chlorinated organic matter when transported through soils [84]. It is therefore

possible that some of the Cl− from road salt applied in the TCMA was exported in the

Mississippi River while attached to organic matter and is thus not accounted for. Our

40

budget analysis did not include airborne or organic matter transport mechanisms. If

incorrect, this assumption would cause an overestimation of chloride retention in the

watershed. If as much as 10% of the road salt applied in the TCMA were exported

by alternative and not included transport mechanisms, the total export would rise to

47,800 t/yr from 33,000 t/yr, and the road salt retention estimate for the TCMA would

be lowered to 64%.

Non-point chloride sources in the TCMA

Only road salt was considered as a significant non-point source of chloride in the water-

shed. Others sources, such as natural deposition, septic tank seepage from residences

not connected to a WWTP or fertilizer applications, were assumed negligible. If an

additional 3% (4,500 t) of chloride were added to the system by outside processes, the

estimated Cl- retention in the watershed would increase slightly.

The 24% commercial road salt application rate was taken from market share infor-

mation provided by the American Salt Institute for the entire United States. While

this value is based on national statistics it is the best estimate for a large metropolitan

area for a number of reasons. The diversity in area including suburban, urban and rural

land uses and the size of the watershed studied allow for a comparison with the national

scale. National trends in municipal salt purchases match Minnesota trends in rock salt

purchases [60]. Finally, obtaining information from commercial road salt appliers and

estimating application rates or areas where road salt was applied commercially is very

difficult. The results from this analysis would likely include more error than accurate

national sales data. If the 24% commercial road salt application rate were lowered to

10%, a value reported in a Canadian study[6], the chloride contribution from road salt

applications would be reduced to 122,000 t/yr, the water-borne export rate from the

TCMA would be raised to 27%, and the retention rate in the watershed would only

drop to 73%.

If all effects reducing the retention rate were combined (commercial application

rate reduced from 24 to 10% of total application rate; increased export of 10% of the

applied amount) the application rate would be lowered to 122,000 t/yr, and the export

rate would be raised to 33,000 + 12,200 = 45,200 t/yr. The total export rate would

then be 37% and the retention rate 63%. In other words, even with extremely favorable

41

assumptions for road salt flushing from the TCMA the estimated retention rate remains

high.

2.4.7 Comparison to other metro areas

Other studies have shown significant retention of chlorides in urban watersheds, but

the estimated retention percentages vary significantly. Most studies were conducted in

small, urbanized watersheds ranging in size from 104 to 435 km2. Retention percentages

were found to be 55% in a stream watershed in the greater Toronto, Canada area [73],

50 - 65% in Helsinki, Finland [75], 28 - 45% in Chicago, Illinois, USA [76], 59% in

Rochester, New York, USA [72] and 35% in Boston, Massachusetts, USA [74].

In Toronto, Ontario, Canada the accumulation of salt in the watershed due to deicing

practices has seriously compromised the shallow aquifers [65]. In Waterloo, Ontario

chloride concentrations in the aquifers had not reached equilibrium after 57 years of

road salt applications. It was estimated that on the order of another 100 years will be

required to reach equilibrium concentrations under current conditions [85]. In shallow

aquifers near Chicago, Illinois, chloride concentrations have increased since 1960. 24%

of the wells studied in the 1990s had concentrations above 100 mg/L, when median

values before 1960 were less than 10 mg/L, and 15% of the wells had rate increases

greater than 4 mg/L per year [70]. The accumulation of salt in shallow groundwater

also affects base flow concentrations in streams [1]. Baseline salinity in urban streams

and streams near roadways have been increasing in the northeastern part of the United

States [22, 23], in the Greater Toronto Area, Canada [68] and in Sweden[38, 5].

2.4.8 Chloride retention in the TCMA watershed

Evidence of significant chloride retention within the TCMA watershed is provided in

streams lakes and aquifers. Four streams (Minnehaha Creek, Battle Creek, Shingle

Creek and Nine Mile Creek) in the TCMA are on the MPCAs 2008 list of impaired

waters for chloride [20]. Pulses of very high chloride concentrations occur in these and

other small streams of the TCMA during the winter months (Figure 2.8).

Volume-weighted average chloride concentrations in 38 lakes of the TCMA have

increased from 1984 to 2005 by an average of 1.5 mg/L per year (range of 0.1 to 15 mg/L

42

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4566#()!%((3)

Figure 8: Chloride concentrations in two streams of the Twin Cities metropolitan area from grab

samples obtained by the Metropolitan Council Environmental Services (MCES). Both streams are

on the 2008 list of chloride impaired waters (Minnesota Pollution Control Agency 2008).

Figure 2.8: Chloride concentrations in two streams of the Twin Cities metropolitanarea from grab samples obtained by the Metropolitan Council Environmental Services(MCES). Both streams are on the 2008 list of chloride impaired waters [20].

per year), following a pattern similar to the mass of road salt purchased by the state

of Minnesota over that same time period [71]. Median concentrations, in the surface

waters of the 38 lakes from 2001-2005, of 87 mg/L (range 31 to 505 mg/L) [71] were

much higher than the estimated presettlement concentrations of 3 mg/L [14]. In urban

lakes of the TCMA chloride concentrations tend to fluctuate seasonally, with maximum

in February or March and minimum in October or November. In the long term, a mean

annual equilibrium concentration is reached when all of the chloride added to a lake

during the winter season is flushed out during the summer and fall season. There was

an indication that smaller lakes with high summer flushing rates have already reached

equilibrium, while larger lakes and lakes with low flushing rates can be expected to have

rising mean annual chloride concentrations for years to come. If salt applications were

stopped completely, the recovery of many urban lakes would take from 10 to 30 years

[86].

Chloride concentrations in surficial sand and gravel aquifers throughout the state of

Minnesota vary substantially with land-use. Median chloride values were of 46 mg/L

were found in urban areas, 17 mg/L in agricultural areas, and 1.2 mg/L in forested area

[69]. 3% of the water samples taken from wells in the TCMA were found to exceed

the USEPA secondary chloride standard of 250 mg/L [69]. In a cross section of the

surficial aquifer in a northwestern subburb of Minneapolis, directly down gradient from

a high traffic roadway, chloride concentrations ranged from 200 mg/L at the watertable

3m below the soil surface, to 590 mg/L at a depth of 13.5m below the soil surface

43

1

10

100

1000

10000

0 20 40 60 80 100 120

Chlo

ride (

mg/L

)

Well Depth (m)

2004 2005

Figure 9: Chloride concentration in wells located throughout the

Twin Cities Metropolitan area in 2004 and 2005. Information was

collected by the Minnesota Pollution Control Agency. Figure 2.9: Chloride concentration in wells located throughout the Twin CitiesMetropolitan area in 2004 and 2005. Information was reported by the Minnesota Pol-lution Control Agency.

[67]. Concentrations of 380 470 mg/L were also measured downgradient from a major

Interstate Highway (I-94) in summer and late fall pointing towards a longterm storage

of road salt in the surficial aquifer [67]. Data collected by the Minnesota Pollution

Control Agency (MPCA) throughout the seven-county TCMA showed that the highest

chloride concentrations in groundwater, up to 2000mg/L, were found in shallow wells

(Figure 2.9).

Elevated chloride concentrations in aquifers may be delayed due to storage in the

subsurface [85, 70]. Shallow wells respond first resulting in some to have already reached

concentrations above state standards. The storage potential of the TCMA aquifer sys-

tem is very large. If road salt applications were completely stopped today, chloride

concentrations in deep wells may continue to increases for many years until subsurface

saline transport has reached equilibrium [85, 70]. Residence times in the aquifers can

be high ranging from tens to hundreds of years in the upper and surficial aquifers to

thousands of years in the deep aquifers. Residence times in lakes are smaller, on the

order of 3 to 14 years, but still provide a means of chloride storage [86]. The TCMA has

hundreds of lakes and wetlands, and hundreds of man-made detention and infiltration

44

basins. Policy has been to delay runoff from rainfall and snowmelt, and to increase infil-

tration by routing storm sewers into these systems. Although very useful in stormwater

management, these practices could be adding to the accumulation of road salt in the wa-

tershed by promoting retention of surface runoff and/or infiltration of the contaminated

water into the groundwater.

2.5 Summary and Conclusions

Road salt is used to increase driving safety in the Twin Cities metropolitan area (TCMA)

of Minnesota. A chloride budget for the TCMA watershed (Figure 2.1) with data from

2000 to 2007 revealed the final destinations of the road salt after it was dissolved in the

snowmelt water. The TCMA watershed analyzed covered an area of 4150 km2 with a

population of 2.8 Million. According to the annual chloride budget 235,000 t of chloride

entered the TCMA annually in the Mississippi and Minnesota Rivers, and 355,000 t

exited through the Mississippi River resulting in 120,000 t being added to the Mississippi

and Minnesota Rivers as they traveled through the TCMA. Of the 120,000 t of chloride

added annually 87,000 t came from the four WWTPs (point sources) and 33,000 t came

from road salt (non-point source). Of the 142,000 t of chloride applied annually in the

TCMA as road salt, only 23% (33,000 t) were exported through the Mississippi River

and 109,000 t or 77% were retained in the TCMA watershed. Chloride budgets for 10

sub-watersheds within the TCMA analyzed in a similar way, gave a retention rate of

72% for road salt.

Evidence of chloride retention is widespread in the TCMA. Four streams in the

TCMA are on the MPCAs 2008 list of Cl- impaired waters, 38 lakes in the TCMA

had a rising mean annual Cl- concentration over a 22-year period [71], and elevated

Cl- concentrations in groundwater have been measured [67, 69] Chloride retention in

urban areas where road salt (NaCl) is applied should cause much concern. Mitigation

measures, best management practices (BMPs) for road salt application and alternatives

to NaCl need to be examined.

Aknowledgements

45

We acknowledge and thank the following individuals and institutions: the Minnesota

Local Road Research Board (LRRB) in cooperation with the Minnesota Department of

Transportation (Mn/DOT) and the University of Minnesota for providing the funding

for this research; the Technical Advisory Panel, lead by Wayne Sandberg of Washington

County, for input and suggestions to our research; Karen Jensen of the Metropolitan

Council Environmental Services, the Metropolitan Council (MCES) and the United

States Geological Survey (USGS) for providing data used in this study; numerous indi-

viduals in cities, counties and Mn/DOT for providing data on road salt applications.

Chapter 3

Increase of urban lake salinity by

road deicing salt

Eric V. Novotny, Dan Murphy and Heinz G. Stefan

St. Anthony Falls Laboratory,

Department of Civil Engineering, University of Minnesota

Minneapolis, Minnesota 55414

c© 2008 by Elsevier.com

46

47

3.1 Abstract

Over 317,000 tonnes of road salt (NaCl) are applied annually for road de-icing in the

Twin Cities Metropolitan Area (TCMA) of Minnesota. Although road salt is applied to

increase driving safety, this practice influences environmental water quality. Thirteen

lakes in the TCMA were studied over 46 months to determine if and how they respond

to the seasonal applications of road salt. Sodium and chloride concentrations in these

lakes were 10 and 25 times higher, respectively, than in other non-urban lakes in the

region. Seasonal salinity/chloride cycles in the lakes were correlated with road salt

applications: high concentrations in the winter and spring, especially near the bottom

of the lakes, were followed by lower concentrations in the summer and fall due to flushing

of the lakes by rainfall runoff. The seasonal salt storage/flushing rates for individual

lakes were derived from volume weighted average chloride concentration time series.

The rate ranged from 9 to 55% of a lakes minimum salt content. In some of the lakes

studied salt concentrations were high enough to stop spring turnover preventing oxygen

from reaching the benthic sediments. Concentrations above the sediments were also

high enough to induce convective mixing of the saline water into the sediment pore

water. A regional analysis of historical water quality records of 38 lakes in the TCMA

showed increases in lake salinity from 1984 to 2005 that were highly correlated with

the amount of rock salt purchased by the State of Minnesota. Chloride concentrations

in individual lakes were positively correlated with the percent of impervious surfaces

in the watershed and inversely with lake volume. Taken together, the results show a

continuing degradation of the water quality of urban lakes due to application of NaCl

in their watersheds.

48

3.2 Introduction

In the snow-belt regions of the United States de-icing agents are used to increase driving

safety on public roads in the winter. The primary agent used for this purpose is rock

salt consisting mainly of sodium chloride (NaCl). Its cost is considered moderate, and

storage, handling and dispersing on surfaces are relatively easy [4]. Other agents in

the road salt mixture, such as ferrocyanide, which is used as an anti-clumping agent,

and impurities consisting of trace elements (phosphorus, sulphur, nitrogen, copper and

zinc), can represent up to 5% of the salt weight [1].

In the U.S., annual rock salt use for road de-icing increased from 163,000 tons in

1940 to over 23 million tons in 2005 according to the United States Geological Survey

(USGS) mineral yearbooks [2, 3]. In the state of Minnesota annual rock salt purchases

increased during the same time period from 60,000 tons to over 900,000 tons [2]. Other

deicing agents are available (e.g. calcium or magnesium chloride (CaCl2) or potassium

acetate), but because of a large difference in cost, NaCl is applied most frequently [4].

Road salt applications can keep roads free of ice for safe winter travel; however

this practice comes at a cost to the infrastructure and the environment, especially in

urban areas with high road densities. Much of the rock salt applied to the roads is

dissolved in the melting snow and ice. The salt containing water runs off into streams,

lakes or storm sewers or infiltrates into the soil eventually reaching the groundwater

affecting the chemistry and biota in the soil and water [5]. Organisms in streams and

shallow, small lakes and ponds are particularly vulnerable to road salt application and

chloride pollution [6]. Chloride standards of 860 mg/L for acute events and 230 mg/L

for chronic pollution have been established for surface waters designated as important

for aquatic life and recreation by the Minnesota Pollution Control Agency (MPCA)

Minnesota Rules Chapter 7050 and 7052.

Small streams flowing through urban areas are known to exceed the chronic and

acute chloride levels periodically [23, 19]. If a stream receives snowmelt runoff directly

from roadways treated with salt (NaCl), concentrations of sodium and chloride will

spike during the winter months and spring thaw, and decline quickly once the salt

application has stopped [19]. In the state of Minnesota, data are available showing high

concentrations of chloride traveling through streams and storm sewers during the winter

49

months (Figure 3.1). Four streams (Shingle Creek, Nine Mile Creek, Beavens Creek and

Battle Creek) in the Minneapolis/St. Paul Twin Cities Metropolitan Area (TCMA) have

been designated as impaired waters and placed on the Clean Water Act section 303d

Total Maximum Daily Load (TMDL) list [20] because of salt pollution. Other regions

have shown similar elevated chloride concentrations[22, 4] including the northeastern

United States where chloride concentrations in an urban stream were recorded as high

as 5000 mg/L [23]. In Sweden chloride concentrations in runoff from roadways has also

reached 3500 mg/L in the winter compared to values averaging 15.6 mg/L during the

summer [24].

0200400600800

100012001400

2001 2002 2003 2004 2005 2006 2007 2008 2009

Chl

orid

e (m

g/L)

Figure 3.1: Chloride concentrations in Battle Creek (3.5 km from its outlet into Mis-sissippi River). Battle Creek drains portions of East St. Paul (Metropolitan Councildata).

Streams and storm sewers capturing snowmelt water from roadways are likely to

cause seasonal salinity variations in lakes into which they discharge. Road salt applica-

tions have been shown to increase the salinity in lakes near major roadways of urban

watersheds [14, 5, 59, 51, 56]. Road salt applications in rural areas have been found

to affect lakes several hundred meters away [6]. In urban environments where runoff is

collected in storm sewers, the impact could be felt at much larger distances. The ap-

plication of road salt has been show to cause chemical stratifications in small lakes and

ponds strong enough to prolong or prevent lake mixing [87, 88]. In this study multiple

50

lakes throughout a metropolitan area will be examined to determine regional trends and

how different lakes react to road salt applications.

The Minneapolis/St. Paul Twin Cities Metropolitan area (TCMA) in the state of

Minnesota provides a perfect setting to study how lakes are influenced by road salt

applications. The seven county TCMA is an urbanized area with a population of 2.7

million that contains many watercourses and 950 lakes. Located in the north central

U.S., the TCMA experiences cold climate in the winter with a total annual snowfall of

1.4 meters [78], falling between the months of November to March. Due to these climate

conditions an estimated amount of 350,000 short tons (317,000 tonnes) of road salt/year

is used in the TCMA for winter road maintenance [60]. With an expanding population

and road system, more and more lakes in the TCMA are susceptible to pollution from

storm water and snowmelt runoff. This paper focuses on how road salt applications are

changing lake water quality; it has five objectives: 1) develop a relationship between

chloride and specific conductance in lake waters, and to determine if sodium and chloride

are the dominate ions causing observed changes and fluctuations in specific conductiv-

ity; 2) determine if observed concentrations of sodium and chloride in lakes receiving

runoff from major roadside environments are elevated above background concentrations,

and if these elevations can be contributed to road salt applications; 3) understand how

individual lakes are influenced by road salt applications in terms of chemical stratifica-

tion, seasonal salinity cycles and convective transport of NaCl into lake sediments; 4)

examine regional trends in lake chloride concentrations and 5) determine if relationships

exist between these concentrations and watershed/lake parameters.

3.3 Methods

3.3.1 Data collection

Two sets of lake water quality data from the TCMA were analyzed to meet the ob-

jectives of the study. The first set was collected by the authors and the second was a

historical data set. In addition, sediment cores were extracted from two lakes.

Lake data collection (Data Set 1) The first lake data set includes 13 lakes which

51

were selected to meet four criteria: 1) receive runoff from a major highway or road-

way through storm sewers, streams or overland flow; 2) have a maximum depth large

enough so that stratification, i.e. a seasonal thermocline and/or chemocline could form;

3) have previously been monitored by a public agency, e.g. by the Metropolitan Coun-

cil, Minnesota Pollution Control Agency (MPCA) or area watershed district, so that

long term unbiased information is available; 4) have data on bathymetry and water-

shed available. Locations of the selected lakes and their watersheds in the TCMA are

shown in Figure 3.2. Lakes are listed in Table 3.1 along with characteristics of each lake

and its watershed. Bathymetric data were obtained from the Minnesota Department of

Natural Resources and watershed delineations were gathered using GIS data obtained

from the Metropolitan Council. Impervious surface areas in the lakes watersheds in

2002 were obtained using GIS data from the University of Minnesota Remote Sensing

and Geospatial Analysis Laboratory (http://land.umn.edu/index.html).

Bryant

Cedar Isles

Brownie

Parkers

Bass

Medicine SweeneyGervais

McCarron

Johanna

Tanners

LegendMajor Roads

Lakes

Lakesheds´

Ryan

Minneapolis

St Paul

10Kilometers

Figure 3.2: Locations and watersheds of the 13 lakes sampled (Data Set 1) from 2004-2007 in the Minneapolis-St. Paul Twin Cities Metropolitan Area (TCMA).

52T

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53

These 13 lakes were sampled every 4-6 weeks during two sampling periods. All

of the lakes studied are natural lakes with inflows coming from streams and/or storm

sewers. Two of the lakes have special conditions: Brownie Lake and Sweeney Lake.

Brownie Lake has been known to be meromictic since 1925. It is a very small and

wind sheltered lake. The construction of a channel connecting Brownie Lake to Cedar

Lake and road construction drastically reduced the lakes surface area, resulting in a

low surface area to depth ratio[89, 90]. Road salt, while not the original cause, has

contributed to the current meromictic conditions. Sweeney Lake, on the other hand,

has an aeration system, which makes it an artificially mixed lake. In April 2007 this

system was shut off for the purpose of conducting a phosphorus TMDL study.

From 2/15/2004 to 4/13/2005 eight lakes were sampled: Bass, Cedar, Lake of the

Isles, Johanna, McCarron, Medicine, Ryan and Brownie. From 1/15/2006 to 11/15/2007

four of the previous lakes were sampled (Ryan, Cedar, Brownie and McCarron) and

5 new lakes were added (Tanners, Parkers, Bryant, Gervais, and Sweeney). Parkers

Lake was added on 5/7/2006 and Sweeney Lake, Tanners Lake and Lake Gervais were

added on 8/8/2006. Lakes that did not show strong salinity stratification after the

first sampling period were dropped, and other lakes with a high likelihood of salinity

stratification were added. Lake selection was thus biased towards lakes that would

receive high salinity runoff. Cedar Lake was kept as a reference lake that showed little

stratification.

In total, 173 specific conductivity/temperature profiles were measured in the 13 lakes

at 4- to 6- week intervals over a 46-month period. These measurements were made in

the water column every 0.5 meters at approximately the deepest location in each lake

using an YSI Model 63 probe [91]. Water samples were collected during the winter

(22 February 2007) when sodium and chloride concentrations are highest and in the

fall (15 November 2007) when maximum flushing of the lakes due to summer rainfall

has occurred. Water samples were taken 1 m below the waters surface and 1 m above

the bottom at approximately the deepest location in the 9 lakes sampled from 2006 to

2007. Samples were analyzed for major ion concentrations in the laboratory of Geology

and Geophysics at the University of Minnesota-Twin Cities. Anions were analyzed on a

Dionex ICS-2000 ion chromatography system consisting of an AS19 analytical column,

ASRS Ultra II suppressor, AS40 autosampler, and integrated dual piston pump and

54

conductivity detector. Cation samples were acidified with HCl to a pH of 2 and ana-

lyzed on a Dionex ICS-2000 ion chromatography system consisting of a CS16 analytical

column and guard column, CSRS Ultra suppressor, AS40 autosampler, and integrated

dual piston pump and conductivity detector.

Historical lake data(Data Set 2) The second set of lakes examined for this study

includes lakes sampled by watershed districts, consulting companies, and government

agencies in the TCMA, typically during the ice free months of May November with

limited data available during the winter months. This data set is available on the

MPCA Environmental Data Access website (http://www.pca.state.mn.us/data /eda/)

used to store environmental data from water bodies around the state. Historical chloride

concentrations in 38 TCMA lakes were selected based on the length and continuity of

the data set. Information on individual lakes was gathered from the same sources as

data set 1.

Lake sediment cores In order to examine if the salt water concentrating at the

bottom of the lakes in winter and spring is seeping into the lake sediments, and possibly

into the groundwater, sediment cores were extracted from two lakes. Tanners lake,

which displayed high concentrations of chloride at the bottom during the winter months

and Lake McCarron, which displayed much lower chloride concentrations. These two

lakes were chosen to make a comparison between the two conditions. One 1.2 m long

sediment core was extracted from each lake at the deepest part of the lake during the

winter (2/28/2007). The cores were separated into 4-centimeter sections and the pore

water was extracted using a centrifuge and filtered through a standard 0.045 µm filter.

The 4-centimeter sections allowed for the extraction of enough pore water to be used in

ion analysis. Five samples evenly distributed through the sediment core were analyzed

to give a representation of how ion concentrations are changing with depth.

3.3.2 Data analysis

A relationship was developed between specific conductance and all the major ions in

the water samples to determine which ions were dominant. Chloride concentration

and specific conductance data from different lakes, water depths and times throughout

the year were available (data set 2, in addition to our own water samples taken on

2/22/2007 and 11/15/2007 in 9 lakes) to create a robust relationship between specific

55

conductance and chloride concentration. The relationship was used to convert specific

conductance profiles measured in the lakes to chloride concentration profiles. Chloride

is a conservative ion with minimal natural sources in the TCMA and therefore useful

as an indicator of road salt.

Data set 1 was used to analyze objectives 2 and 3. The chloride vs. depth profile time

series were used to determine stratification patterns as well as seasonal cycles in the 13

monitored lakes. Volume-weighted average concentrations, using the bathymetric data,

were determined for each measured chloride profile in each lake and each measurement

date. For a more comprehensive view of the salinity cycles in the lakes, the volume-

weighted average concentrations for each survey date were normalized. The average

concentrations for each lake from May 2004 to April 2005 or from Sept 2006 to August

2007 were used as the reference for normalization of the 2004/2005 and 2006/2007 data

sets, respectively. This normalization was calculated by dividing the time series by

the reference value. The normalized data sets for all lakes were then combined, i.e.

averaged, for each sampling date to get a seasonal cycle for all the lakes combined.

Volume-weighted average concentrations were also used to determine the seasonal

storage and flushing of salt in the lakes. This normalized flushing rate is equal to

the maximum minus the minimum volume-weighted average chloride concentrations of

a lake for a particular year. This difference in concentrations multiplied by the lake

volume would give an idea of how much salt (tonnes/year) is being flushed through

a particular lake in the course of a year. This amount of salt was also expressed as

a fraction (percentage) by dividing the difference of maximum and minimum average

concentrations by the minimum concentration.

Profiles in specific conductance, temperature and dissolved oxygen were analyzed

for Tanners Lake. This lake was chosen because it changed from monomictic behavior

in 2006 to dimictic behavior in 2007. We sampled Tanners Lake starting on 8/8/2006

taking profiles of temperature and specific conductance. Profiles of dissolved oxygen

for the entire time period and temperature and specific conductance from 5/11/2006

to 7/12/2006 were available from the Minnesota Pollution Control Agency (MPCA)

Environmental Data Access; the measurements were made by the Ramsey-Washington

Watershed District.

Data set 2 was used for objectives 4 and 5. Annual average specific conductivity

56

values for the top 3 meters and annual maximum values were determined for each lake

and date of survey to obtain an estimate of how the salinity of the 38 lakes has been

changing over time. The time series for the top 3 meters between 1984 and 2005 was

used for a trend analysis. Each lake was normalized individually using the average

annual concentrations from 2001-2005 as a reference. Once a time series was developed

for each individual lake a combined time series was calculated by averaging each of these

series together resulting in a single time series of normalized specific conductance for

all 38 lakes. Correlations were also calculated between lake watershed and bathymetric

parameters with chloride concentrations.

3.4 Results

3.4.1 Ionic composition and relationship to specific conductance

The ionic composition in the lake water samples collected in 2007 (Table 3.2) shows

a difference between the winter (February) after some snowmelt water has entered the

lake and the fall (November) after the summer flushing of the lake by rainfall events.

Correlation coefficients between the specific conductance values and the individual ionic

concentrations for chloride, sodium, sulfate, potassium, calcium and magnesium were

0.99, 0.97, -0.09, 0.93, 0.12 and 0.28, respectively.

Table 3.2: Median ionic concentrations of water samples from 9 lakes in data set one.Water samples were taken in February and in November 2007. All concentrations arein mg/L. SC represents specific conductance (µs/cm). Top represents samples taken 1meter below the water surface and bottom represents samples taken 1 meter from thebottom.

2/22/2007 11/15/2007Top Bottom Top Bottom

Ca2+ 48 51 42 43Mg2+ 17 18 14 14Na+ 73 105 59 59K+ 3 3 3 3NH+

4 1 2 0 0SO2−

4 14 16 13 13Cl− 132 186 109 109SC 745 988 612 639

57

Using historical data from numerous other lakes in the TCMA in addition to the

above water sample data, a linear relationship between chloride and specific conductance

(Eq.3.1 with R2 = 0.94) was created (Figure 3.3).

[Cl−] = 0.25 ∗ SC − 37.25, (3.1)

where [Cl-] is the chloride concentration in mg/L and SC is the specific conductance

in µS/cm. This equation was used to convert specific conductance measurements in the

lakes to chloride concentrations.

y = 0.25x - 37.25

0

200

400

600

800

1000

1200

0 1000 2000 3000 4000 5000

Ch

lori

de (

mg

/L)

Specific Conductance (µS/cm)

Parkers McCarron

Cedar Carver

Diamond Gervais

Spring Pond Tanners

Loring pond Powderhorn

Como Battle Creek

Snail Valentine

2/22/2007 11/15/2007

Figure 3.3: Relationship between chloride and specific conductance. Individual lakevalues were obtained from the Minnesota Pollution Control Agency (MPCA) Environ-mental Data Access website and were sampled by government agencies or consultingcompanies in the TCMA. Data points marked 11/15/2007 and 2/22/2007 are watersamples from the 9 lakes monitored between January 2006 and September 2007.

58

3.4.2 Seasonal salinity cycles and salinity stratification

Lake surface waters had often lower specific conductance than lake bottom waters.

To document this stratification we plotted chloride concentrations measured at 0.5 m

depth below the lake surface and at 0.5 m above the lake bottom of each lake. Figure

3.4 documents the measurements taken from the 9 lakes sampled between 2006 and

2007. Volume-weighted average chloride concentrations were also plotted. For the lakes

sampled between 2004 and 2005 plots similar to Figure 3.4 are presented and discussed

in detail in [92]. Salinity stratification can be seen in all 13 lakes studied. The strongest

salinity stratification was found in Brownie Lake, Parkers Lake, Tanners Lake and Ryan

Lake; the least in Bass Lake and Cedar Lake.

0

200

400

Chl

orid

e C

once

ntra

tion

(mg/

L)

0

200

400

1/06 7/06 1/07 7/070

200

400

1/06 7/06 1/07 7/07 1/06 7/06 1/07 7/070 400 800

BottomTopAverage

Sweeney Tanners Ryan

GervaisMcCarronParkers

Cedar Bryant Brownie

Figure 3.4: Chloride concentrations 0.5 m below the surface and 0.5 m above the bottomof a lake, and volume-weighted average chloride concentrations in each lake sampledfrom January 2006 to September 2007. The dark lines on the x-axis represent monthswhen snowfall can be expected to accumulate on the ground (November March).

59

The combined normalized volume-weighted average chloride concentration time se-

ries gives a comprehensive view of seasonal salt accumulation and flushing from a lake

(Figure 3.5). How the numbers were obtained is described in the methods section. Al-

though the data are for two different time periods and lake sets, the results converge

nicely: the highest normalized concentrations occur in the winter - when road salt is

being applied - and the lowest concentrations occur in the summer and fall when fresh

rainwater runoff entered the lakes and flushed some of the salt away, except for the

meromictic Brownie lake where the seasonal salinity dynamics occur only above the

chemocline.

0.7

0.8

0.9

1

1.1

1.2

Jan-04 Jan-05 Jan-06 Jan-07 Jan-08Nor

mal

ized

Vol

ume-

Wei

ghte

d [C

l-]

MeanMedian

Figure 3.5: Seasonal salinity (Cl-) cycles illustrated by normalized (volume-weighted)average chloride concentrations, averaged for all lakes in each time period (Data set 1).Bars represent the standard deviation for the set of lakes.

Seasonal salinity cycles, expressed in terms of the amount of salt passing through a

lake in a year relative to its minimum salt content in that year, were present in all lakes

studied, but were more pronounced in some of the lakes than others. The strength of

the seasonal salinity cycle was calculated and analyzed (Table 3.3). Brownie Lake, Ryan

Lake, Lake of the Isles and Sweeney Lake had the strongest seasonal salinity cycles of all

the lakes studied. The highest annual salt turnover (accumulation and flushing) rates in

three years of observation were 54% and 55% of the minimum salt content in Sweeney

Lake and Lake of the Isles. The lowest annual salt turnover rates were obtained for

Bryant Lake and Parkers Lake; they were 9% and 11%.

60T

able

3.3:

Salin

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inT

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727

61

3.4.3 Effects of salinity on seasonal mixing and dissolved oxygen

In addition to the salinity dynamics in the surface and bottom waters of each lake

it is of interest to consider the complete measured temperature, chloride and dissolved

oxygen profiles, and to study chemoclines, thermoclines and dissolved oxygen picnoclines

in relation to each other (Figure 3.6). Tanners Lake, with a chemocline capable of

preventing a full lake turnover in the spring but not in the fall, can be used to illustrate

the seasonal stratification cycles in more detail. Tanners Lake does not appear to be

meromictic, but monomictic at times. During the early spring and summer of 2006,

chemical stratification was present in Tanners Lake. Erosion of the chemocline through

the fall, due to cooling of the lakes surface, allowed for some of the chloride to be flushed

from the lake. During the winter months the chemocline reformed in the deepest portion

of the lake. The highest concentrations of chloride and the thickest layer of saline water

are seen in April. This is significant because the thermocline had already begun to

form. If the spring overturn of the lake were triggered by density differences due to

temperature only, the lake would have fully mixed by April. Similar patterns are seen

in Parkers Lake (Novotny et al. 2007).

Chloride concentration profiles in the other lakes studied (McCarron, Cedar, Bryant,

Ryan, Gervais) indicate that these lakes received salt, but not enough, to prevent full

mixing either in the spring or fall [93]. Inflows of salt water to the bottom of these

lakes during the winter can be inferred from the observed changes in chemical strati-

fication. This chemical stratification is not as strong as in Tanners Lake and Parkers

Lake. Sweeney Lake on the other hand acts more like a well-mixed body of water with

concentrations in the whole lake increasing in the winter and decreasing in the summer

and fall [93]. This behavior is caused by an artificial lake aeration/mixing system.

3.4.4 Salinity in lake sediment cores

To see if the saline water layer at the lake bottom is connected to the pore water in the

lake sediments, sediment cores were extracted from Lake McCarron and Tanners Lake.

In Tanners Lake the saline layer above the bottom of the lake is up to 7 m thick and

has chloride concentrations reaching 400 mg/L compared to maximum concentrations

of 240 mg/L chloride in Lake McCarron. The cores were sectioned and the pore water

62

!

Chloride (mg/l)

0 250

-12

-8

-4

0

De

pth

(m

)

5/1

1/2

00

6

0 250

6/1

4/2

00

6

0 250

7/1

2/2

00

6

0 250

8/8

/20

06

0 250

9/2

5/2

00

6

0 250

11

/8/2

00

6

0 2501

/24

/20

07

0 250

2/2

1/2

00

7

0 250

4/1

/20

07

0 250

5/1

7/2

00

7

0 250

7/1

3/2

00

7

0 250

9/1

7/2

00

7

0 250

11

/16

/20

07

Figure 3.6: Chloride concentration, dissolved oxygen concentration and water tempera-ture vs. depth in Tanners Lakes from May 2006 to Nov 2007. The Ramsey WashingtonWatershed District gathered all dissolved oxygen profiles along with specific conductiv-ity and temperature profiles between May and July 2006. The authors monitored allother data points for specific conductance and temperature between August 2006 andNovember 2007.

63

was extracted and analyzed for major ions. The profiles (Figure 3.7) show sodium

and chloride concentrations decreasing more or less exponentially with depth in the

sediments of both Lake McCarron and Tanners Lake. The chloride profiles in the pore

water start at the sediment surface with concentrations equal to those of the saline

water layer at the bottom of the lake. The concentrations of the other ions in the pore

water appear to stay about constant with depth into the sediment, but sodium and

chloride do not. The concentrations of sodium and chloride start at around 250 and

410 mg/L, respectively, in Tanners Lake and around 113 and 186 mg/l, respectively, in

Lake McCarron. Over the length of the core (1.2 m) these values are reduced to 36 and

78 mg/L in the Tanners Lake core and to 14 and 34 mg/L in the Lake McCarron core,

respectively.

-120

-70

-20

30

80

0 100 200 300 400Concentration (mg/L)

Dis

tanc

e ab

ove

and

belo

w

sedi

men

t wat

er in

terfa

ce (c

m) Tanners Lake

0 100 200 300 400Concentration (mg/L)

ChlorideSodiumCalciumMagnesiumSulfatePotasium

Lake McCarron

Figure 3.7: Ionic composition of pore water in sediment cores extracted from the deepestpoints of Lake McCarron and Tanners Lake. Values of chloride concentrations rightabove the sediments are also shown. Sediment cores were extracted on 2/28/2007.

3.4.5 Salinity trends in TCMA lakes

To determine if long-term changes in lake salinity are occurring, the average annual

specific conductance values of the 38 lakes from 1984 to 2005 (data set 2) were plotted

against time along with the amount of rock salt purchases by the state of Minnesota

from 1930 to 2005 (Figure 3.8). The trends for both the specific conductance (salinity)

of TCMA lakes and for the rock salt purchases by the state are strikingly similar. Both

64

time series show an increase from 1984 to 2005 and a correlation coefficient of 0.72.

Road salt applications vary somewhat from year to year with the number of snowfall

events [60]. To remove this variability, the correlation analysis was repeated with 5-year

running averages of the two time series, resulting in a correlation coefficient of 0.93.

y = 0.018x - 34.794

0.3

0.5

0.7

0.9

1.1

1.3

1930 1940 1950 1960 1970 1980 1990 2000 2010

Ave

rage

Nor

mal

ized

Spe

cific

Con

duct

ance

0

0.2

0.4

0.6

0.8

1

1.2

Min

neso

ta R

ock

Sal

t Use

(Mill

ion

tons

)

TC Metro area lakesMinnesota rock salt use

Figure 3.8: Time series of average normalized specific conductance in 38 Twin CitiesMetro Area lakes (Data Set 2) and total rock salt purchases by the State of Minnesota.

3.4.6 Relationships between lake salinity and watershed characteris-

tics

By collecting lake bathymetry, watershed information and chloride concentrations for

each of the 38 lakes in data set 2 (Table 3.4) correlations can be made with chloride

concentrations (Table 5). Lake surface area and lake depth, and even watershed area,

taken as single independent variables, have a very low correlation with chloride concen-

tration parameters in the lakes. The highest correlation was between lake surface area

65

and the chloride trend with a correlation coefficient of -0.44. Chloride concentrations

correlate better with the percentage of impervious surface areas in the watershed (Table

3.5). The ratio of impervious surface area in the watershed to a proxy for lake volume

(expressed as the product of lake surface area * lake depth) has the strongest correlation

with lake chloride concentrations (Table 3.5).

Table 3.4: Historical average, trend and maxima of chloride concentrations, and bathy-metric and watershed data for 38 TCMA lakes (Data Set 2). Chloride concentrations forthe top 3 meters are annual average value for the period 2001-2005. Trend is based onthe time series of annual average concentrations from 1984 - 2005 for the top 3 metersof each lake and normalized with the average value from 2001-2005 to get a percentchange per year. Annual Max chloride concentration is the average of the maximumconcentration in the lake for each year between 2001 and 2005, measured at any depth.

Years of [Cl-] top 3 Lake Max Watershed Percentdata meters Trend [Cl-] max area Depth area impervious

Lake (years) (mg/L) (%/year) (mg/L) (ha) (m) (ha) (%)Bald Eagle 22 42 0.6 87 513 11.0 2843 9Beaver 22 90 1.8 117 26 3.4 1446 26Bennet 22 63 2.2 100 9 2.7 293 36Brownie 15 105 2.1 798 5 14.3 136 33Calhoun 18 103 1.2 158 162 25.0 1408 35Cedar 18 84 0.8 142 68 15.5 537 28Como 22 89 2.1 166 25 4.6 591 32Diamond 17 142 2.1 467 47 1.8 268 44Gervais 22 100 2.4 178 95 12.5 1144 30Harriet 18 93 1.2 119 136 26.5 737 28Hiawatha 17 91 1.7 221 22 10.1 2378 45Independence 12 43 0.1 71 342 17.7 1630 3Island South 22 44 1.1 77 24 3.4 77 20Isles 18 87 1.0 134 44 9.4 252 29Johanna 22 107 2.2 167 86 13.1 1188 39Josephine 21 48 1.7 81 47 13.4 350 23Keller 21 87 2.4 113 29 2.4 329 23Kohlman 22 87 1.7 160 30 2.7 629 27Long NB 22 99 2.3 202 74 9.1 3781 25Loring 11 340 2.7 760 3 4.9 144 77Mccarron 22 85 1.7 189 28 17.4 549 24Medicine 14 88 1.4 204 359 14.9 4380 30Nokomis 18 66 1.1 99 83 10.1 1467 36Otter 18 25 0.6 50 134 6.4 382 7Owasso 22 44 1.2 81 141 11.3 1047 24Phalen 22 89 2.3 127 80 27.7 580 30Powderhorn 13 86 0.7 361 5 6.7 94 44Round 22 94 2.4 231 12 2.4 251 29Snail 22 57 2.4 102 61 9.1 477 22Spring 10 505 3.0 1018 2 2.1 30 47Tanners 11 104 1.1 288 28 14.0 214 33Turtle 22 42 1.2 70 166 8.5 316 12Valentine 20 117 2.5 208 24 4.0 664 33Wabasso 22 36 1.2 74 19 20.1 103 32Wakefield 22 97 2.9 178 9 3.0 563 32Weaver 11 53 0.7 85 60 17.4 203 17West Silver 21 57 2.2 225 29 14.3 208 30White Bear Lake 22 31 0.9 43 978 25.3 3059 11

66

Table 3.5: Correlation coefficients of chloride concentrations with lake and watershedparameters (Data Set 2). PI (percent impervious), SA (lake surface area), D (lake maxdepth).

Lake watershed PI/ PI *area Depth area Percent (SA*D) D/SA(ha) (m) (ha) Imperv. (1/m3) (1/m)

[Cl-] top 3 m -0.25 -0.29 -0.18 0.67 0.94 0.57[Cl-] ave. annual max -0.28 -0.26 -0.24 0.66 0.79 0.78Trend -0.44 -0.40 -0.18 0.54 0.43 0.26

3.5 Discussion

3.5.1 Comparison of ionic composition with other freshwaters

Are sodium and chloride concentrations measured in the urban lakes really different

from those measured in lakes and rivers outside the metropolitan area? If differences

in measured sodium and chloride concentration can be documented, are there similar

differences in other major ions? Answers to these two questions can be provided by

comparing the results in Table 3.2 for 9 urban lakes to similar measurements in other

water bodies. The comparison with six different natural waters is made in Table 3.6.

The ionic strengths measured in the 9 urban lakes after a summer and partial fall

season, are listed in the last column of Table 3.6 for comparison. It is apparent that

the urban lakes have much higher sodium and chloride concentrations than any of the

other waters, including the Mississippi and Minnesota Rivers which are by no means

pristine even before they enter the TCMA. Ionic strengths of other ions, such as calcium,

magnesium and potassium, sulfate and nitrate in the 9 urban lakes are comparable to

or lower than those in other surface water bodies. It can be concluded that the sodium

and chloride concentrations measured in the urban lakes are not found in other surface

water bodies.

67T

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K+

0.1

-0.

5–

31

35

3N

H4+

0.1

-0.

5–

––

––

0.1

SO42

-1

-3

–14

2017

162

13C

l-0.

2-

20.

34

817

3410

9N

O3-

0.4

-1.

3–

–1

0.8

60.

6

68

3.5.2 Indicators of the salinity sources

What is the source of the elevated sodium and chloride concentrations in the urban

lakes? The TCMA has minimal natural sources of chloride. Consequently, under natural

conditions Cl- concentrations would be expected to be low. Indeed, the median Cl-

concentration in TCMA lakes in 1800 and 1750 was estimated to be 3 mg/L by using

diatom assemblages in sediment cores [14]. Under current land use conditions lakes

in the North Central Hardwood Forests ecoregion of Minnesota, which includes the

TCMA as well as less developed areas surrounding the TCMA, have 4-10 mg/L of

chloride based on the inter-quartile 25th 75th percentile [95]. The increased sodium and

chloride concentrations in urban lakes of the TCMA are also apparent in a comparison

with lakes located throughout the state of Minnesota [94]. This set includes 91 lakes

overall, excluding lakes in western Minnesota where high specific conductance is due to

rich sulfur bearing minerals (gypsum and pyrite) and lakes in northeastern Minnesota

(Canadian shield area) with very low specific conductivity values. Chloride and sodium

concentrations in the TCMA lakes are between 10 and 25 times higher than in these

other lakes (Table 3.6). By comparison, calcium concentrations in the TCMA lakes are

only 1.4 times higher than in the other lakes throughout Minnesota. Overall, the nine

urban lakes in the TCMA appear to be chloride and sodium dominated waters differing

from other water bodies in the region, which are either calcium or sulfate dominated

[94, 96].

Because the TCMA has minimal natural sources of chloride, an anthropogenic salt

source has to be suspected. Since both Cl- and Na+ ions in urban lake waters are

elevated, it can be suspected that the common source is sodium chloride (NaCl). If Cl- is

derived solely from NaCl, a stoichiometric requirement is that the molar concentrations

of Cl- and Na+ should be in a 1:1 relationship. In the lake water samples gathered on

2/22/2007 and 11/15/2007 the molar ratio of Cl- to Na+ was 1.13:1. It is speculated

that the molar relationship is not exactly 1:1 because Na+ ions are known to adsorb

onto particles whereas Cl- is not (Lofgren 2001; Norrstrom and Bergstedt 2001; Oberts

2003). The molar ratio is, however close enough to 1: 1 to confirm that NaCl is the

likely source of elevated Na+ and Cl- concentrations in the TCMA lakes.

In addition to road salt use, domestic salt use for water softening and industrial/commercial

uses have to be considered. A major use of NaCl in the TCMA is for water softening but

69

a majority of the saline water from water softeners in the TCMA is discharged through

sanitary sewers into WWTPs and eventually into the Mississippi River bypassing any

lakes.

The presence of a seasonal lake salinity cycle points towards road salt as the source

of lake salinity. Snowmelt runoff containing dissolved road salt in winter and spring,

and rainfall runoff without road salt content in summer and fall would be expected to

cause a seasonal salinity cycle in lakes and streams. This pattern has been observed in

all 13 lakes studied (Figures 3.4 and 3.5 and Table 3.3). This same pattern was seen in

a lake in Sweden and modeled using estimated road salt applications, precipitation and

evaporation in the lakeshed [97].

3.5.3 Salinity, temperature and dissolved oxygen stratification

In all of the lakes studied the formation of a chemocline occurred in the winter coin-

cident with observed peak salt concentrations in streams of the TCMA (Figure 3.1).

The location and strength of the chemocline varied between individual lakes and from

year to year. The variability is associated with many parameters including the number

of snowfall events and snowfall amounts in a winter season, influencing the amount of

road salt applied, in addition to climate parameters such as air temperatures and solar

irradiance, influencing the timing and amount of runoff. Wind speed and direction as

well as surface cooling, which cause convective circulation to break the chemical strati-

fication in fall or spring when thermal stratification is weak, can also add to temporal

inconsistencies. Lake stratification simulations operating at high temporal resolution

can be used to relate salt inputs, lake mixing, temperature stratification and weather

patterns.

Among the nine individual lakes in Figure 3.4 five (Parkers, Tanners, Ryan, Brownie,

and McCarron) appear to have a stronger chemical stratification then the other four.

These five lakes also have the smallest surface area to depth ratios. It is interesting

to note, that a very similar parameter, the lake geometry ratio defined as the ratio of

maximum lake depth to the fourth root of the lake surface area was introduced [98] as

an indicator of the strength of temperature stratification of lakes. This parameter has

been very useful to distinguish between dimictic and polymictic temperature stratified

lakes [99, 100].

70

It is clear from the data that the chemical stratification in some of the lakes can be

strong enough to prevent mixing during either the fall or spring turnover periods or at

least delay the lake from fully mixing. In two lakes, Tanners Lake and Parkers Lake,

monomictic behavior was observed. In Tanners Lake mixing was prevented in the spring

of 2006 resulting in anoxia of the benthic waters (Figure 3.6). When the lake mixed in

the fall oxygen was circulated again over the full lake depth. In the following spring

of 2007 the turnover period was delayed due to the existence of chemical stratification,

but occurred later in the season.

The prevention or delay of the full lake turnover (vertical mixing), when the water

reaches maximum density of freshwater at 4oC, can adversely affect the lakes water

quality, especially near the lakebed. Oxygenation of the benthic waters is an impor-

tant process in the health of a lake. It is well known that phosphorus is released from

anoxic sediments into the water above at much higher rates than when the sediments

are well aerated. With longer anoxic periods more phosphorus could be released from

the sediments stimulating algal blooms in the surface mixed layer when the lake fi-

nally overturns. Certain fish typically migrate to deeper waters during the hot summer

months. If mixing is prevented in the fall the anoxic zone could be increased reducing

the inhabitable space for fish in the lake. Prolonged anoxic periods are shown in Figure

3.6 for the year 2006 when mixing was prevented in the fall. The next full mixing of

Tanners Lake occurred before the 5/17/2007 sampling period resulting in oxygenation

of the benthic waters.

3.5.4 Seasonal flushing of salt from the TCMA lakes

The strength or amplitude of the seasonal salinity cycle in the urban lakes (Table 3.3)

appear to be loosely related to the size of a lake relative to its depth, watershed area

and impervious area in the watershed (Tables 3.3 and 3.4). Sweeney, Brownie, Isles,

and Ryan Lakes have the highest seasonal flushing rate (percent change). The strongest

salinity cycle is seen in Sweeney Lake, which has a large watershed area to lake area ratio

and drains Interstate 394 and Highway 100, both heavily traveled roadways. Sweeny

Lake is artificially mixed throughout the year and has a small depth to surface area ratio

and a larger watershed area to lake surface area ratio, all of which appear to increase

the flushing (salt removal) from the lake. Seasonal salinity cycles had already been

71

found in grab samples collected from the surface of lakes near highways in the TCMA

from 1982-1987 [101]. That study was, however, limited to grab samples from the lakes

surface and did not include volumetric average concentrations or concentrations near

the bottom of the lake.

Seasonal fluctuations in chloride concentrations can also influence the aquatic life in

a lake. The chronic standard of 230 mg/L chloride required for the protection of aquatic

life was exceeded at some point in time in 5 of the 13 lakes studied (Tanners, Parkers,

Brownie, Ryan, Sweeney). These elevated concentrations were typically found during

the winter and spring months and occurred in the deepest portion of the lakes. Only

one lake (Sweeney) displayed chloride concentrations above the standard throughout the

entire water column because it was artificially mixed by an aeration system to control

eutrophication. The presence of this high salinity water for prolonged periods of time

could be changing the aquatic community in each of these lakes. Increases in sodium

and chloride concentrations have been shown to decrease the biodiversity in wetland

areas and waterways [7, 8]. Shifts in diatom communities to more salt tolerant species

have also been observed with increasing chloride concentrations in lakes [14].

3.5.5 Convective mixing of saline lake water with pore water in the

sediments

The presence of a high salinity layer at the bottom of the lake causes the convective pen-

etration of saltwater into the pore system of the lake sediments. It is the same process,

induced by density instabilities, that mixes the surface waters of a lake during cooling,

except that in the surface waters the density differences are caused by temperature and

not salinity differences, and no pores are present. Leakage of saline water into the less

dense pore water of lake sediments can be inferred from Figure 3.7. Similar chloride

profiles were found in a study of the benthic sediments of a stormwater detention pond

receiving runoff from a major roadway. In this detention pond chloride concentrations

were 3000 mg/L at the sediment-water interface and 1500 mg/L at a depth of 0.4m into

the sediment core [44]. The convective mixing in the sediment pore system of a lake or

pond receiving road salt runoff is driven by density instability. If the density of the saline

water above the sediments is higher than the density of the water in the pore system,

finger-like intrusions of the denser saline water into the fresher (lighter) pore water will

72

form; in turn the fresher (lighter) water will rise in finger-like formations through the

pore system. This process is slow, but persistent, and referred to as convective mixing.

As a result pore water with a low salt concentration and density moves upward and is

replaced by water with a higher salinity moving downwards into the sediment pores.

Convective transport of solutes into the sediment bed occurs also in estuaries when

the density of the overlaying water is greater then the sediment pore water [102]. Convec-

tive transport has been observed in laboratory experiments and in numerical simulations

of saline lakes. Instabilities created by density differences cause increased transport of

salt into the groundwater [103, 104, 105, 106]. The process was also found in tests of

sulfate reduction in sediment cores from Devil Lake, South Dakota [107]. Due to the

density differences between the overlying water and the sediment pore water the effec-

tive diffusion (dispersion) coefficient was found to be much larger then the molecular

diffusion coefficient.

These observations suggest that a loss of chloride into the sediments occurs during

the winter and early spring when saline water accumulates at the bottom of a lake. The

loss would be expected to continue until an impermeable sediment layer or stability

between the layers of water is reached. The penetration of saline water into the lake

sediments can cause the release of metals from the solids. Increased transport of heavy

metals (Zn, Cd, Cu and Pb) coincident with road salt applications have been observed

in road side soils in Germany, Sweden and the United States due to chloride complexes,

ion exchange, and even increased colloidal dispersion [39, 37, 38, 36, 40]. High NaCl

concentrations decrease the partitioning coefficients between the dissolved and particu-

late phases of these metals resulting in higher mobility and bioavailability [35, 34, 36].

By increasing the concentrations of metals in the dissolved phase they are free to move

with the water either further into the sediments due to convective mixing or to diffuse

into the overlying lake waters.

3.5.6 Salinity trends in TCMA lakes

Salt concentrations in the urban lakes are increasing. Short-term trends of chloride

concentrations in individual lakes can be seen in Table 3.3. Two of the four lakes

(Cedar Lake and Lake McCarron) analyzed for the entire field study period (2004-2007)

show increases in the annual minimum and maximum concentrations from year to year.

73

This increase represents an accumulation of salt in both lakes over time. Bryant Lake

displays the same pattern, but has only been studied for two years. These findings

give only a hint of increasing lake salinities. Long-term and regional trends are seen

in Figure 3.8. The slope of the normalized specific conductance in Figure 3.8 is 0.018

or 1.8% per year, i.e. specific conductivity in lakes of the TCMA increases annually

and on average by 1.8% (The reference value is the average chloride concentration for

the period 2001 to 2005). Trend values for individual lakes range from 0.1% to 3.0%

(Table 3.4). The average trend seems reasonable because hind-casting projects the year

of minimum (near zero) chloride concentration to be about 1950. This is the time when

road salt application began to increase dramatically throughout the state (Figure 3.8).

By extending the trend into the future a doubling of specific conductivity, and

therefore chloride concentrations in the 38 lakes, would occur in about 50 years, i.e.

around 2060. Chloride concentrations would increase from a current median value of

87 mg/L to 174 mg/L. In 100 years the average chloride concentration in many TCMS

lakes would exceed the current chronic chloride standard year round and throughout the

water column. Current efforts to reduce road salt use by public agencies, commercial

and private users, may be balanced by continued urban growth and possible increased

snowfall due to climate change (Seeley 2003) so that the trends seen in Figure 3.8 could

continue for some time into the future.

3.5.7 Relationships between lake salinity, lake bathymetry and water-

shed characteristics

Although trends and increased chloride concentrations are occurring throughout the

region, the magnitude of these parameters appear to be dependent on both lake and

watershed characteristics of the individual lakes. Table 3.4 gives parameters for the 38

individual lakes in database 2. Chloride concentrations in the surface layer throughout

the TCMA ranged from 31 mg/l in White Bear Lake, a large lake located in the northern

suburbs to 505 mg/l in Spring Lake which is a small lake receiving large amounts of

runoff from I-394 in downtown Minneapolis. The highest chloride concentrations all

occurred during the winter months and near the bottom of the lakes. These values

ranged from 43 mg/L in White Bear Lake to 1,018 mg/L in Spring Lake. Each of the

38 individual lakes shows an increasing trend in average annual chloride concentrations

74

(Table 3.4). Although small lakes, and lakes near major roadways seem to have the

strongest upward trends, the increase in chloride and sodium concentrations in urban

lakes due to road salt applications appears to be regional and not specific to a small

number of lakes located close to highways.

The strongest correlations between chloride parameters and lake or watershed pa-

rameters were found by examining what percentage of the watershed is impervious.

This is to be expected since road salt is applied to impervious surfaces such as streets

and parking lots and as this percentage is increased not only is more salt being applied

but a more direct route is available for the runoff to reach the lakes. When including

the proxy for lake volume the correlation was even higher. As the volume of the lake

increases there is more water to dilute the snowmelt runoff causing lower concentrations.

3.6 Conclusions

The water quality of urban lakes in the Twin Cities Metropolitan Area (TCMA) of Min-

nesota has been investigated to identify and quantify impacts of road salt applications in

their watersheds. Lakes in the TCMA especially near major roads have elevated chloride

and sodium concentrations compared to other non-urban Minnesota lakes. The almost

1:1 molar relationship between chloride and sodium in the lake waters points towards

sodium chloride (NaCl) as the source. Since natural sources of NaCl in the geology of

the TCMA and Minnesota in general are very limited or rare, the source of the NaCl

must be anthropogenic. In the TCMA sodium chloride (NaCl) is used predominantly

for water softening and road deicing. The seasonal cycles of lake chloride concentrations

(high in winter/early spring and low in fall) point to road salt applications as the cause

of lake salinity in the urban lakes.

Specific conductance in the TCMA lakes is strongly correlated with Cl- and Na+

ions. Specific conductance profiles showed chemical stratification in almost all urban

lakes investigated. Over the course of a year, specific conductance, Cl- and Na+ con-

centrations are cyclic, both in the surface and the bottom waters of the urban lakes.

Volume-weighted average chloride concentrations give the amount of seasonal salt stor-

age/flushing. In the 13 urban lakes investigated, the annual storage/flushing rate ranged

from 9 to 55% of the minimum salt content in the lake. Smaller lakes with larger

75

watershed areas and a higher percentage of impervious surfaces had higher seasonal

storage/flushing rates, as to be expected.

There are physical, chemical and biological consequences of increased lake salinity. In

two of the lakes (Tanners and Parkers Lake) chemical stratification near the lake bottom

was strong enough to prevent the lake overturn in spring of 2006. This behavior prevents

dissolved oxygen from reaching the lake sediments. Complete lake mixing resumed in fall

2006 and spring 2007 In several individual lakes chloride concentrations were observed

to exceed the chronic water quality standard for aquatic life. High salt concentrations

were also found in the sediments of Tanners Lake which can cause the release of heavy

metals from the solids into the pore water from where they are transported further into

the sediments or into the overlaying water.

Historical chloride concentration data from 38 lakes in the TCMA show an annual

average increase of 1.8% (range from 0.1 to 3.0%) throughout the TCMA. The increase

is strongly correlated with the amount of road salt purchased annually by the state of

Minnesota since the 1950s. Chloride concentrations in individual lakes are positively

correlated with the percent of impervious surface area in the watershed, and inversely

correlated to lake volume. Overall, the results show a progressive degradation of the

water quality of urban lakes due to application of NaCl in their watersheds. Road salt

is used to increase driving safety in winter, but current road salt application practices

do impair lake water quality in urban lakes.

Aknowledgements

We acknowledge and thank the Minnesota Local Road Research Board (LRRB) and

the Minnesota Department of Transportation (Mn/DOT) for providing the funding for

this research. We also thank the Technical Advisory Panel, lead by Wayne Sandberg of

Washington County, for input and suggestions to our research. We thank Amy Myrbo

and Kristina Brady of the Limnological Research Center (LacCore Facility) at the Uni-

versity of Minnesota, Department of Geology and Geophysics, for providing equipment

and expertise for the extraction and sectioning of the lake sediment cores. Karen Jensen

of the Metropolitan Council (MCES) provided valuable information on lake watershed

delineations and water quality information.

Chapter 4

A 0-D modeling approach to

study long-term chloride

concentration in lakes receiving

runoff containing road salt

Eric V. Novotny and Heinz G. Stefan

St. Anthony Falls Laboratory,

Department of Civil Engineering, University of Minnesota

Minneapolis, Minnesota 55414

76

77

4.1 Abstract

Chloride concentrations in lakes located in urban environments using road deicing salts

are increasing to levels that are changing natural lake mixing behavior and influencing

aquatic life. A 0-D model was developed to project the seasonal cycle of loading and

flushing of chloride as well as the long-term accumulation of chloride in urban lakes

receiving runoff from roads to determine steady state concentrations under different

loading conditions. The model was calibrated using five years (2004-2008) of monthly

salinity profiles from 7 lakes in the Minneapolis/St. Paul Twin Cities Metropolitan Area

of Minnesota, USA, four model parameters and an initial concentration. Three of the

seven lakes appear headed towards year-round volume averaged chloride concentrations

above the 230 mg/L chronic standard for impairment to aquatic habitat. The two lakes

with the lowest projected equilibrium concentrations of chloride have already reached

equilibrium. It is projected that one lake will take up to 40 years to reach equilibrium.

If road salt application rates are reduced in future winters, it is projected that the lakes

will respond with noticeably lower Cl- concentrations within 5 to 10 years. If road salt

applications are discontinued altogether, chloride concentrations are projected to reduce

to natural levels within 10 to 30 years in all seven lakes.

78

4.2 Introduction

Rising chloride concentration are present in many lakes located in urban environments

or near major roadways due to the application of road salt in the watershed [56, 87, 51,

108, 109, 97, 71]. Snowmelt runoff flows into these lakes through storm sewers, small

streams, overland flow and interflow. Road salt applications in rural areas can affect

lakes a few hundred meters away [6]. In urban environments runoff into the lakes is

extended by the presence of impervious surfaces and storm sewers providing a direct

path to the surface waters.

With increased chloride concentrations comes damage to the aquatic life. Ele-

vated chloride concentrations decrease the biodiversity of diatoms in lakes resulting

in halophilic taxa to increase in relative abundance [110]. Tadpoles of woodland frogs

have significantly lower survivorship, decreased time to metamorphosis, reduced weight

and activity, and increased physical abnormalities with increased salt concentrations

pointing to effects that could be affecting amphibians as a whole [9]. Flathead minnows

are affected at chronic concentrations as low as 298 mg/L [111]. Other aquatic species

have impacts at chronic levels ranging between 194 mg/L for sensitive species such as

various daphnia taxa, to 327 mg/L for the snail, Physa gyrina, to 561 mg/L for cad-

dis flies, Anaobolia nervosa and lemnephilis stigma, to 1,036 mg/L for bluegill sunfish

[59]. Not only are surface water communities affected, but also the biodiversity in lake

benthic sediments [109].

Over 317,000 tons of NaCl is being applied to the roads in the Minneapolis/St. Paul

Twin Cities Metropolitan Area (TCMA) with over 70% of the chloride being retained

and not flushed through runoff into the Mississippi River [112]. One of the sinks for

chloride in the watershed are lakes with seasonal chloride stratification and rising vol-

umetric chloride concentrations [71]. Background chloride concentrations before urban

development were around 3-10 mg/L [14]. From 1970 to 2000 in the TCMA significant

changes in lake chloride concentrations were detected using diatom assemblages with a

strong correlation to the percent of urban developments in each of the watersheds stud-

ied [13]. Similar increasing trends in chloride concentrations (an average of 1.5mg/L

per year and a range between 0.1 to 15 mg/L per year) were detected in 38 lakes of the

Twin Cities Metropolitan Area. That trend was correlated with the amount of rock salt

79

purchases by the state of Minnesota [71]. Median concentrations in the 38 lakes in 2005

were 87 mg/L well above the 3-10 mg/L observed during predevelopment times [71].

The objective of this study is to investigate chloride concentration trends in lakes

from a mechanistic point of view and determine if a 0-D lake chloride model can be

used to project seasonal salinity fluctuations and future lake chloride concentrations

based on recently acquired year round monitoring data. While chemical stratification

is common in lakes receiving runoff with high concentrations of salts our main interest

is not in the spatial distribution of chloride in lakes, but in the total amount of chloride

contained in each lake, and the variation of this chloride content over time. A water

quality model simulating inflow, accumulation and flushing of Cl- was created. The

model formulation, validation and model projections will be described. Lakes located

in the TCMA were used to simulate seasonal salinity cycles, long-term trends, ultimate

equilibrium chloride levels, and responses to reduced road salt application rates using

this model.

4.3 Lake Chloride Model Fomulation

4.3.1 Zero-dimensional model formulation

A model simulating the volume-weighted average chloride concentration C(t) in a lake

was formulated and used. The total amount of chloride (kg) in a lake is the volume-

weighted average concentration C(t) multiplied by the volume of the lake. The behavior

of C(t) in a lake can be reproduced by a 0-dimensional (0-D) model simulating inflow,

accumulation and flushing of Cl- over time. 0-D models have been used extensively

and very successfully to simulate phosphorus management scenarios for eutrophication

control of lakes [113, 114].

4.3.2 Daily time scale model

Chloride is a highly soluble substance that is not easily removed by chemical reactions

or biological processes once it is solution. In the model Cl- is therefore treated as a

conservative substance and the lake is treated as being fully mixed at all times. It is

assumed that chloride is added at a constant rate to the lake during the months when

80

snowmelt runoff occurs and that flushing occurs during the open water season at a

constant flowrate. The equations used (Eq. 4.1 and 4.2) for this model represent a fully

mixed continuous flow reactor for a conservative material (chloride) that is added at a

constant rate during one period and flushed at a constant rate during another.

Loading phase :dC

dt=M/D

V(4.1)

Flushing phase :dC

dt= −K ∗ C (4.2)

where M is the mass (g) of chloride added to the lake in the winter. D is the number

of days during which chloride is added to the lake, V is the lake volume (m3), K is

the flushing rate coefficient equal to 1/T, where T = V/Q is a hydraulic residence time

(days), and C is the volume-weighted average chloride concentration (mg/L). Solving

the differential equations (4.1) and (4.2) for these two phases with their respective initial

conditions results in equations (4.3) and (4.4).

@ t = tmin, C = Cmin : C(t) =M/(tmax − tmin)

V(t− tmin) + Cmin (4.3)

@ t = tmax, C = Cmax : C(t) = Cmaxe− 1

T(t−tmax) (4.4)

where t (days) is the day number in a particular year (t = 1 represents Jan 1 and

t = 365 represents Dec 31), tmax is the day number when the maximum concentration

(Cmax) is reached after all of the loading has occurred and tmin is the day number when

the minimum concentrations (Cmin) is reached after all of the flushing has occurred.

The other two variables M (g) and T (days) are mass and residence time, respectively,

as defined previously.

Equations (4.3) and (4.4) describe the seasonally cyclic nature of the Cl- concentra-

tion in the lake, starting at a minimum concentration in the late fall, accumulating to a

maximum concentration in the late winter and then flushing the salt out to a minimum

concentration in the following fall. By setting an initial value for Cmin, solving equation

(4.3) until the day equals tmax the value for Cmax can be obtained for equation (4.4).

This equation can then be solved until the day equals tmin thus obtaining the new Cmin

81

value to be used in equation (4.3). This cycle is repeated describing a time series (with

a daily time step) of chloride concentrations in the lake based on the mass of chloride

M that is entering the lake in a cold season, the lakes material residence time T, and

the dates when loading and flushing begin, tmin and tmax, respectively.

Two informative values in equations (4.3) and (4.4) are the minimum and maximum

concentrations. They tell the lowest and highest chloride values that can be reached in

a lake for a particular year. These parameters can be used to assess the stresses on the

aquatic life within a lake due to chloride, both the maximum concentration the aquatic

life will have to live in and the sustained concentration that will be felt throughout the

entire year. Equation (4.3) and (4.4) can be adjusted to an annual time step and solved

for the maximum and minimum concentrations in each year.

Setting C = Cmax and t = tmax in equation (4.3), setting C = Cmin and t = tmin in

equation (4.4), and introducing Tf = (tmin - tmax ) (the number of days in a year that

flushing occurs), allows the conversion of equations (4.3) and (4.4) to equations (4.5)

and (4.6) which define the maximum and minimum concentrations that can be obtained

in a particular year i.

Cmax(i) =M

V+ Cmin(i−1) (4.5)

Cmin(i) = Cmax(i)e−

TfT (4.6)

Equations (4.5) and (4.6) can be used to determine how the maximum and minimum

concentrations in a lake change from year to year based on the mass of chloride M(g)

entering the lake, the volume of the lake V(m3), and the length of a lakes flushing period

Tf = (tmin - tmax) relative to the hydraulic residence time T, i.e. Tf /T.

If the annual salt loading of a lake and the summertime flushing remain the same

year after year, each of the lakes will eventually come to a point where the amount of

salt entering that lake during the snowmelt runoff is equal to the mass of salt leaving the

lake due to flushing. At this point the minimum and maximum concentrations reached

from year to year will be the same. When this equilibrium is reached Cmin(i) will equal

Cmin(i−1) and equations (4.5) and (4.6) can be solved for Cmax(i) and Cmin(i) that are

then defined as the equilibrium concentrations Cmax(eq) and Cmin(eq) in equations (4.7)

82

and (4.8).

Cmax(eq) =M/V

1− e−Tf /T(4.7)

Cmin(eq) =M/V

eTf /T − 1(4.8)

The long-term effect of salt applications within a lakes watershed can be determined

from equations (4.7) and (4.8) if the total amount of salt M (g) entering the lake in a

winter season and the lakes hydraulic residence time (T ) are known and are constant.

Residence time (T) is related to lake volume (V) and water outflow rate (Q) from a

lake as T =V/Q. Since volumes of individual lakes in the TCMA are fairly constant

in the long term, except under severe drought conditions, the hydrology of a lakes

watershed has to remain fairly unchanged to assure a constant residence time T. How

the equilibrium concentrations would change based on reductions or increases in salt

applications in a lakes watershed can also be studied using the above equations.

4.3.3 Annual time scale model

The lake can also be modeled at an annual time scale. How the annual average con-

centration in the lake is changing from year to year can be determined from equation

(4.9).

VdC

dt= M∗ −QC (4.9)

where V (m3) is the volume of the lake, M∗(g/yr) is the total mass (rate)of chloride

added to the lake each year, Q is the total outflow from the lake and C is the current

annual average concentration in the lake. This equation can be solved with the initial

condition @ t = 0, C = Co. The solution is in equations (4.10 and 4.11).

ln

[M∗

V T − Co

M∗

V T − C

]=

t

T(4.10)

C =M∗

VT −

(M∗

VT − Co

)e−t/T (4.11)

83

where T = V/Q is again the residence time. At equilibrium, where dC/dt =0, the

annual average concentration would be:

CE =M∗

VT (4.12)

Equation 4.11 can be solved for the time necessary to reach x% of the equilibrium

concentration. (x = 100% requires an infinite amount of time, and x = 97% is a

considered a reasonable approximation). By substituting equation 4.12 and solving

equation 4.11 when C = .97 * CE @ t = tE equation 4.13 is created. This equation can

be used to find an estimate of the time it will take for a lake to reach an equilibrium

chloride concentration.

tE = ln

[CE − Co

0.03CE

]T (4.13)

4.3.4 Model assumptions

The five-parameter zero-dimensional model simplifies the actual lake processes consid-

erably, yet will be shown to capture the principal behavior of the time-variable chloride

concentrations. It is appropriate to briefly describe the actual inflow, mixing and out-

flow processes that produce the observed flow-weighted chloride concentrations, in order

to highlight the model simplifications.

The first minor shortcoming of the model is that the water budget is ignored, and a

constant lake volume is assumed. During the loading phase (tmin to tmax ) only dissolved

material (chloride), but no water is added to the lake. It is assumed that there is a net

inflow of chloride into the system during this phase and that any exported chloride is

outweighed by the mass entering the lake. The water flow rates into and out of the lake

are assumed to be equal. The outflow of water from the lake during the flushing phase

is also not explicitly accounted for although it is assumed to be equal to any inflow,

and the lake water budget is again ignored. A volumetric water outflow rate is hidden

in the residence time T of the chemical, which is equal to the hydraulic residence time,

i.e. the ratio of lake volume V divided by the water outflow rate, because the chemical

is conservative. During this flushing phase a net export of chloride is assumed, and

any delayed inflow of chloride through subsurface flows into the lake is assumed to be

84

outweighed by the flushing of chloride from the system.

The second assumption is that concentrations in the model are volume-weighted

averages for the entire lake, as if the lake were completely mixed all the time. How-

ever, strong chloride concentration gradients have been observed in TCMA lakes in

spring. The deepest lake waters typically have the highest chloride concentrations be-

cause snowmelt runoff containing dissolved sodium chloride flow to the bottom of a

lake as a density current [93, 71]. Since lake outflows are typically from the surface,

the saline water at the bottom cannot be flushed out until the lake has become fully

mixed vertically. Chloride-laden salt water at the bottom of a lake can also penetrate

by convective mixing into the pore system of lake sediments [71]. Some of this salt can

re-enter the water column after lake-mixing events. The net effect is an extension of the

residence time T of chloride in a lake when compared to the water residence time.

These assumptions would point towards the need of a 1-D model that accounts

for vertical stratification. However, a 0-D model is a very useful tool and sufficient

for the analysis of seasonal and long-term trends in overall lake salinity. Phosphorus

management in lakes for the control of eutrophication has benefited from 0-D modeling

since the 1970s. 0-D phosphorus models have been applied to lakes as large as the

Laurentian Great Lakes [113, 114].

Our 0-D lake salinity model has five parameters: the mass of chloride from road salt

(NaCl) entering the lake (M), the material residence time (T), the day (tmin) when the

average concentration in the lake has reached a minimum and new salt begins to enter

the lake, the day (tmax) when the concentration in the lake has reached a maximum and

flushing starts to dominate over salt accumulation, and the initial concentration (Co)

before the first year simulated. To obtain values of the five parameters for seven lakes

in the TCMA, the model was fitted to data (16 to 33 data points per lake) collected

over up to 5 years.

4.4 Lake data collection and model calibration

Field data from 13 lakes of the Twin Cities Metropolitan were available for periods

of up to five years [93, 71]. The model was applied to seven of the lakes with the

longest records and the characteristics given in Table 4.1 [93, 71]. Lakes were sampled

85

every 4-6 weeks between 2/15/2004 and 10/20/2008. All of the lakes were natural lakes

with inflows coming from streams, storm sewers or overland flow. Vertical profiles of

specific conductance were measured in the water column every 0.5 meters at the deepest

location in each lake using a YSI Model 63 probe [91]. A relationship between specific

conductance and chloride was previously determined [71], and the measured specific

conductance values were converted to chloride concentrations using that relationship.

This relationship existed because chloride and sodium ions were the dominant drivers

in changes in salinity. All other ions remained relatively constant throughout the year.

Table 4.1: Lakes modeledMaximum Lake Impervious

Lake Lake Lake Surface Watershed watershedname Volume Depth Area area area

(m3) (m) (ha) (ha) (%)Bryant 3,245,000 13.7 65.2 901 24Cedar 4,433,000 15.5 68.4 537 28McCarron 2,151,000 17.4 27.6 549 24Parkers 1,414,000 11.3 36.9 340 27Ryan 295,000 11 7.6 77 34Sweeney 952,000 7.6 26.7 1512 37Tanners 1,848,000 14 28.3 214 33

Volume weighted average chloride concentrations were determined for each of the

sampling dates [93]. The four model parameters (M, T, tmin tmax) were estimated

by fitting the model to the data. An initial concentration (Co) set at time tmin of

the first year of data was also determined. Least square errors between measurements

and model results were used to determine the best-fit model. A program was created

to cycle through permutations of the four parameters plus the initial concentration

until a combination was found that had the lowest root mean square error (Eq. 4.14)

between the model values and the measured values using the entire time series of the

measurements.

RMSE =

√(Cmodel(t)− CObserved(t))2

N − 1(4.14)

Numerical solutions of equations (4.3) and (4.4) with a time step of 1 day were used

for this simulation. Cmin and Cmax were calculated by applying equations (4.3) and

86

(4.4) sequentially. Once the best-fit parameters had been determined, simulations were

extended in time to project how chloride concentrations may change in the future, and

what maximum concentrations are expected if current loading and flushing conditions

continue. Estimations were made for the equilibrium concentrations using equations

(4.7) and (4.8) along with the time required to reach concentrations within 97% of

equilibrium if conditions were to remain constant. Finally simulations were run to

determine how changes in the amount of NaCl entering the lakes would influence the

final equilibrium concentrations of chloride.

4.5 Results

The best-fit model parameters for the seven simulated lakes are given in Table 4.2. tmin,

tmax, M and T and the initial concentration Cmin,o at the beginning of the simulation,

i.e. in the fall of the first simulated year (i = 1), is shown. Model simulations and

data are displayed in Figure 4.1 for all seven of the lakes. Identical patterns of chloride

accumulation in the cold season and flushing in the summer are apparent. With the

best-fit parameters, the model was used to project future equilibrium concentrations in

the seven lakes under different salt loading conditions.

Table 4.2: Model parameters. Cmin,o is the chloride concentration at the beginning ofthe simulation in fall (tmin) of the first simulated year (i=1). RMSE (%) is the ratioof root mean square error to average concentration over the record length. N is thenumber of data points used for model fitting.

tmin tmax M T Cmin,o RMSE N(mo/day) (mo/day) t/yr (yrs) (mg/L) (%)

Bryant 25-Dec 11-Feb 58 14 80 2.8 21Cedar 20-Oct 25-Feb 81 7 87 3.4 26McCarron 15-Dec 14-Feb 44 8 97 2.9 33Parkers 17-Oct 18-Mar 78 4.5 98 6.3 18Ryan 20-Oct 11-Feb 7 4 94 9.5 27Sweeney 17-Nov 14-Mar 104 3 113 7.7 16Tanners 23-Nov 21-Feb 37 7 145 3.5 16Average 14-Nov 24-Feb 58 6.8 102 5.16 22

Figure 4.2 illustrates how the chloride concentrations change with time, and how

87

21

Figure 4.1: Modeled and observed chloride concentrations in seven lakes of the TwinCities metropolitan area, Minnesota.

88

equilibrium is reached under four different chloride (salt) loading scenarios. The sce-

narios are: (a) current conditions continue in the future (1M), (b) loading is increased

by 50% (1.5M), (c) loading is decreased by 50% (0.5M) and (d) salt applications are

stopped and loading is reduced to 0 (0M). Figures 4.1 and 4.2 were created by using

the best-fit parameters for M, T, tmin and tmax (Table 4.2) in equations (4.3) and (4.4).

Cmax and Cmin for every year (i) were obtained from equations (4.5) and (4.6).

Equilibrium concentrations were determined by solving equations (4.7) and (4.8)

with the parameters listed in Table 4.2 and are given in Table 4.3. Another important

parameter is the time it will take to reach equilibrium. To obtain this value the con-

centrations were examined at an annual time scale. An initial concentration (Co) was

determined by averaging the simulated data from equation 4.3 and 4.4 between 1/1/2008

and 12/31/2008. The annual average equilibrium concentrations were also calculated

using the parameters in Table 4.2 and equation 4.12. These values were then inserted

into equation 4.13 to determine how long it would take for the lake to reach a concentra-

tion within 3% of the equilibrium concentration. Values obtained were between 0 and

41 years. If the equilibrium concentration was lower than the initial concentrations it

was assumed that the lake had already reached equilibrium and the time to equilibrium

was set to 0.

Table 4.3: Maximum (Cmax(eq)) and minimum (Cmin(eq) ) chloride concentrations atequilibrium determined by equations (4.7) and (4.8). C2008 is the average annual chlorideconcentration in the lake between 1/1/2008 and 1/1/2009 and is used as Co in equations(4.13) to find the time required to reach equilibrium (tE).

Cmax(eq) Cmin(eq) C2008 CE tE

(mg/L) (mg/L) (mg/L) (mg/L) (yrs)Bryant 259 241 114 250 41Cedar 137 119 111 128 10McCarron 174 154 131 164 15Parkers 277 222 178 248 10Ryan 107 84 103 95 0Sweeney 385 276 257 328 6Tanners 150 130 150 140 0

The observed seasonal patterns of lake chloride concentrations matched the model

results with an RMSE between 2.8 and 9.5%. On average, accumulation of chloride

89

22

Figure 4.2: Projected future chloride concentrations under four road salt loading condi-tions. Current loading (1M), 50% increase in loading (1.5M), 50% decrease in loading(0.5M) and zero loading (0M).

90

in the lakes started on Nov 14, and ended about 3 months later on Feb 24. Flushing

was evident during the remaining nine months in spring, summer and fall. Annual

fluctuations between maximum and minimum chloride concentrations are from 18 to 23

mg/L in five of the lakes, 55 mg/L in Parkers Lake and 109 mg/L in Sweeney Lake.

In five of the lakes (Cedar, McCarron, Parkers, Sweeney, and Bryant) volume-

weighted average chloride concentrations have been rising, both in the simulations and

the data. This shows that the lakes have not reached equilibrium with the amount of

salt applied in their watersheds annually. Two of the lakes have slight decreasing trends

(Tanners and Ryan) indicating that chloride concentrations had reached equilibrium

and fluctuations are possibly occurring due variations in salt application rates from

year to year. Current concentrations in Ryan and Tanners Lakes are slightly above (by

8 and 10 mg/L) their volume-weighted projected equilibrium Cl- concentrations of 95

mg/L and 140 mg/L, respectively. Two lakes (Cedar and McCarron) are currently 17

and 33 mg/L below their equilibrium concentrations of 128 and 164 mg/L, respectively.

Three lakes (Parkers, Bryant and Sweeney) are currently 70 to136 mg/L below their

equilibrium concentrations of 248, 250 and 328 mg/L, respectively. With current road

salt application rates, the two lakes (Tanner and Ryan) with the lowest equilibrium con-

centrations have already reached equilibrium, four will reach it in about 5 to 15 years,

and Bryant Lake with the second highest equilibrium concentration will take more than

40 years to reach it.

Three equilibrium concentrations for current road salt application rate are above

the 230 mg/L chronic level for impairment to aquatic life. Even though the other four

lakes are not projected to reach such high concentrations throughout the water column,

the standards may be exceeded at the bottom of the lake in winter and spring due to

salinity stratification. In Tanners Lake, for example, current volume-weighted chloride

concentrations are on average 150 mg/l, but concentrations as high as 400 mg/L have

been measured near the bottom of the lake after snowmelt events [71].

It is also of interest to examine how model parameters relate to watershed and

lake characteristics. Annual chloride loading (M ) of the seven lakes obtained from the

model fit are between 7 and 104 t/yr. Watershed areas range from 77 ha (Ryan) to

1512 ha (Sweeney) of which 24 to 37% are impervious surfaces. Road salt is applied

on impervious areas, and chloride loading rates per unit impervious watershed area are

91

given in Table 4.4 for each of the seven lakes. The annual salt application rates on

the impervious areas vary from 186 kg/ha to 850 kg/ha with an average of 445 kg/ha.

This is much lower then the average application rates in the major streamsheds each

of the lakes are located in of 2200 kg/ha impervious area [112]. The flushing rates are

really small, ranging from 2.3 to 20 L/s. This corresponds to only 60 to 370mm per

year with an average of 204mm per year of runoff from the impervious areas. This

is much lower than the typical annual precipitation of about 800 mm/yr in the Twin

Cities metropolitan area.

Table 4.4: Chloride loading rates (M) per impervious watershed area (Aimp) , flushingflow rate (Q = V/T ), and flushing rate (Q) per impervious watershed area, determinedby fitting of model parameters to measured lake chloride concentrations.

M/Aimp Q=V/T V/(T Aimp)(kg ha−1 yr−1) (L s−1) (mm/yr)

Bryant 269 7.3 110Cedar 540 20.1 150McCarron 333 8.5 120Parkers 850 10 340Ryan 267 2.3 280Sweeney 186 10.1 60Tanners 524 8.4 370Average 445 10.1 204

4.6 Discussion

4.6.1 Model Sensitivity

The maximum chloride concentration in a lake due to road salt applications depends

on three parameters: the annual mass of chloride entering the lake M, the material

residence time T and the lake volume V (Equations 4.7 and 4.8). Changes in any of

these parameters would influence chloride concentrations in the lake. For a lake with the

same residence time and volume, doubling the entering chloride mass M would cause a

doubling of the equilibrium concentrations. Likewise if the mass entering the lake were

cut in half the equilibrium concentration would be cut in half. These changes in the

mass of chloride entering the lake are shown in Figure 4.2.

92

The residence time T has a large influence on the final equilibrium concentrations in

the lake. In Lake McCarron the entering mass/volume (M/V) ratio is 20 mg/L while in

Bryant Lake that ratio is 18 mg/L. Even though the amount of chloride entering Lake

McCarron per lake volume every year is larger, the equilibrium concentration is much

lower, i.e. 174 mg/L and 259 mg/L for Lake McCarron and Bryant Lake respectively.

The equilibrium concentration is proportional to residence time (equation 4.12).

Lake volume has an inverse relationship with the equilibrium concentrations. If two

lakes had the same residence times and the same mass of chloride entering the lake, but

one lake had twice the volume, the equilibrium concentrations in the larger lake would

be half as high as in the smaller lake (equation 4.12).

In summary, changes in any of the three model parameters ( M, V and T) in the

future would influence the final equilibrium concentrations. Therefore, projections of

lake concentrations have been made with the assumption that current conditions will

continue in the future.

4.6.2 Model projections

While increasing chloride concentrations in 38 Twin Cities area lakes were observed

between 1984 to 2005 [71], if the application rates and lake parameters remain constant

the chloride concentration in these lakes would level off in the future eventually reaching

equilibrium. The assumption of constant application rates and lake parameters may

be correct for inner city lakes where development and road expansion have reached

a maximum, however, expanding roadways and increasing population densities in the

suburbs may push road salt application rates in some lake watersheds higher.

Climate, population, urban development and road salt application rates are dynamic

variables that can influence future chloride concentrations in urban lakes. Increased

precipitation in Minnesota is expected under climate change scenarios [115, 116]. More

days with precipitation and increased intensity of rainfall events in Minnesota are pre-

dicted resulting in more runoff reaching the lakes. The elevated runoff volume would

enhance the flushing of lakes causing lake residence times and equilibrium concentra-

tions to decrease. However, increased snowfall amounts and more snowfall events are

also projected causing higher road salt application rates and increased lake equilibrium

concentrations.

93

In addition, changes in populations and/or impervious surfaces in the lake water-

sheds would influence the final equilibrium concentrations. In the Twin Cities metropoli-

tan area the population is expected in rise by 30% from 2.8 million in 2008 to 3.6 million

by 2030 [117]. With this expansion come more roads and wider highways elevating the

amount of salt applied in the lake watersheds and exposing new lakes to chloride loads.

Impervious surfaces would also cover larger areas leading to higher flowrates entering

into the lakes, possibly decreasing the lakes residence times, but also increasing the flow

of salt into the lakes.

Another factor influencing the final equilibrium concentrations in the urban lakes is

training and awareness of best management practices (BMPs) designed to reduce the

amount of salt applied in a watershed. With added awareness of the environmental

impact of road salt applications, BMPs on how to more effectively apply road salt or

reduce its impact on water bodies, and alternative deicers that do not contain chloride,

decreases in road salt application rates could be expected. If practices were changed,

chloride concentrations in the lakes would quickly decrease since the hydraulic residence

time (T) in the Twin Cities urban lakes is typically small (3 to 14 years). It is uncertain

how much of the salt is being stored in the sediments or how much is also being stored

in the groundwater feeding the lakes, however rapid changes would still be expected if

the mass of salt entering the lakes were dramatically reduced. As shown in Figure 2,

if road salt applications were eliminated it would take only 10 to 30 year for chloride

concentrations to reach the level of predevelopment values of 3-10 mg/L [14]. Even

if chloride applications were reduced by only 50%, concentrations in all seven lakes

would be reduced to levels below the chronic standard (Figure 4.2). Current stormwater

management in the Twin Cities favors the routing of surface runoff to lakes and wetlands.

If the runoff is from rainfall, this practice may be favorable, although water quality

has to be considered. If the runoff is snowmelt water, the practice has unfavorable

consequences.

4.7 Conclusions

A model was successfully used to simulate the chloride seasonal cycle of loading and

flushing as well as the long-term accumulation of chloride in urban lakes affected by

94

road salt applications. With monthly data from several years, the 5-parameter model

was used to determine long-term equilibrium concentrations in a lake if hydrologic con-

ditions and salt loading rates remain constant as well as simulations based on either

reduction or increased loading. Seven lakes in the Twin Cities metropolitan of Min-

nesota area were modeled. Using five years (2004-2008) of monthly salinity profiles,

four model parameters and an initial concentration were determined and subsequently

used to project future chloride concentration in each of the lakes under several road salt

application scenarios. The following average model parameters were determined from

the lake data: an annual chloride loading rate of 445kg per ha of paved surface in the

watershed, a hydraulic residence time of 6.8 yrs, and an average flushing rate of 10 L/s

in the seven lakes studied. From the simulation it was determined that 3 of the 7 lakes

will reach chloride concentrations year round throughout the water column above the

230 mg/L standard for chronic impairment to biota under current salt loads. If road salt

applications were stopped or the high salinity water from snowmelt events was diverted

from the lake concentrations could be reduced to predevelopment concentrations of 3-10

mg/L within 10-30 years.

Aknowledgements

Funding for the project, especially the data collection, was provided by the Local Road

Research Board, St. Paul, MN and the James L. Record Fund, University of Minnesota.

The University of Minnesota provided a Doctoral Dissertation Fellowship for the senior

author.

Chapter 5

Road salt impact on vertical lake

mixing

Eric V. Novotny and Heinz G. Stefan

St. Anthony Falls Laboratory,

Department of Civil Engineering, University of Minnesota

Minneapolis, Minnesota 55414

95

96

5.1 Abstract

Runoff from roadways on which road salt (NaCl) has been applied for driving safety

in winter can form a saline water layer at the bottom of a lake, pond, reservoir or

river impoundment. Natural vertical mixing of such lentic surface water bodies can be

hindered by this benthic saline layer. To study the formation and disappearance of the

saline layer temperature and specific conductance profiles were measured intermittently

over two years (2007, 2008) in eight urban lakes of the northern temperate region and

recorded at high frequency during one year (2009) in one lake. A deterministic dynamic

1-D lake temperature and salinity model was developed and used to simulate the summer

stratification and mixing dynamics in Tanners Lake, Oakdale, Minnesota. Erosion of the

saline layer in the spring occurred in only one of the three years examined (2007). In the

other two years (2008 and 2009), the saline layer persisted throughout the summer, and

was destroyed only by fall turnover and mixing between the epilimnion and hypolimnion

when thermal stratification was at a minimum. Density stratification was dominated

by salinity after ice-out, but was quickly overtaken by temperature stratification as the

epilimnion warmed. Inclusion of the lake number in the calculation of the hypolimnetic

eddy diffusion parameter made the mixing in the hypolimnion stronger when the lake

stratification became unstable in the fall and spring and weaker in the summer after

thermal stratification had formed. It was demonstrated that the saline benthic layer

prevents dissolved oxygen from reaching the lake sediments. Overall the results show

how salinity from road salt applications can influence water quality and natural mixing

in urban lakes.

97

5.2 Introduction

Sodium and chloride concentrations have been on the rise in lakes, streams and ground-

water in northern regions where road deicing salt (NaCl) is applied [85, 65, 3, 88, 23, 118,

71, 86, 112, 51, 97, 5]. Lakes receive sodium and chloride from roadways by snowmelt

runoff directly through overland flow, streams and storm sewers within the watershed,

or indirectly through the soil and groundwater. Salt concentrations in urban streams

and drainage systems are sufficiently high during the winter months to cause density

currents and chemical stratification in the receiving water bodies, especially lakes, deten-

tion ponds and reservoirs. This phenomenon occurred synoptically with above freezing

air temperatures and snowmelt runoff in a Minneapolis lake. The saline water flowed to

the deepest part of a small lake where it remained until spring [54]. The density change

caused by dissolved NaCl is small, but significant in relation to temperature-induced

density changes. For example, a temperature change from 4 to 5oC produces the same

specific gravity change as a NaCl concentration of 10 mg/L [55].

A saline water layer can cause a lake to become permanently density stratified. In

such a meromictic lake the bottom waters never mix with the surface waters. The con-

sequences of a meromictic lakes often include dissolved oxygen depletion in the benthic

saline layer and high concentrations of phosphate, ammonia, and hydrogen sulfide at

the sediment water interface. Small lakes and deep lakes are more vulnerable to be-

coming meromictic than large lakes and shallow lakes [6]. The formation of meromictic

conditions due to road salt applications has been reported for a few individual small

lakes or ponds [87, 88]. No meromictic lakes due to road salt application have been

found in the Twin Cities metropolitan area of Minnesota, but monomictic behavior has

been observed [71]. In these monomictic lakes full mixing is prevented during the spring

overturn period, but not during the fall. The formation of meromixis or even monomixis

is important because it can have serious ecological consequences for a lake.

In addition to monomictic behavior, rising overall concentrations and seasonal cy-

cles of sodium and chloride ion concentrations have been observed in lakes of the Twin

Cities metropolitan area [71]. A 0-D model was previously developed and used to

98

project long-term salinity trends and seasonal salinity cycles [86]. The 0-D model cap-

tured volumetrically-averaged salinity concentrations, but a 1-D model lake stratifica-

tion model is needed to capture the dynamics of vertical salinity stratification in a lake

from the high concentrations at the bottom to the low salinity in the surface waters.

The main objective of this paper was to demonstrate the influence of saline water

inflow from road salt applications on the stratification dynamics of a freshwater lake.

This includes (1) the formation of a benthic saline layer, (2) the effect on the vertical

mixing mechanics of a lake including the disruption of natural turnover events, (3)

the dissipation of the saline layer during the summer and fall seasons, and (4) the

consequences of the saline layer for oxygen transfer dynamics throughout the water

column. To pursue these objectives a combined field study and modeling approach was

adopted. The field study had two components: (1) measuring monthly temperature and

salinity profiles over a period of several years and (2) continuous sensing and recording

of vertical temperature and salinity profiles. Both research components were conducted

in a lake located near a major interstate highway in the Twin Cities metropolitan area.

The simulation study also had two components: (1) simulate lake stratification and

vertical mixing in a lake during the open water season following a winter in which a

saline benthic layer had formed and (2) simulate vertical dissolved oxygen transfer in a

lake with a benthic saline layer had formed.

In the deterministic model simulations, principles and governing equations previ-

ously used in 1-D lake temperature simulation models were applied and extended. The

extended model was based on the MINLAKE hydrothermal model, which has been

used successfully to simulate lake temperature stratification in many individual lakes

[119, 120, 121, 122]. The model was extended to include density gradients due to salinity

and the Lake Number [123] in the calculation of effective hypolimnetic diffusion coeffi-

cients. To illustrate the consequences of the benthic saline layer on lake water quality,

the dissolved oxygen profiles in a lake without and with a saline layer were simulated.

99

5.3 Methods

5.3.1 Field Investigation: Data Collection/Sampling Site

Data were collected in Tanners Lake in the eastern Twin Cities metropolitan area (Oak-

dale, MN). Tanners Lake is located next to Interstate Highway I-94 and a high volume

county road (Figure 5.1a). The lake receives runoff from a 214 ha watershed area of

which 33% is covered by impervious surfaces [71]. The lake has a surface area of 30 ha

(0.30 km2), littoral area of 11 ha (0.11 km2) and a maximum depth of 14 m [124]. The

depth area profile for Tanners Lake is shown in Figure 5.1b.

TannersLake

´ 0.5Kilometers

§̈¦I-94

")120

(a)

!"!!#

$"!!#

%"!!#

&'"!!#

&("!!#

!"!!# &!"!!# '!"!!# )!"!!# $!"!!#

!"#$%&'()&

*+",&'%,)&

(b)

Figure 5.1: (a) Tanners Lake location in Oakdale, Minnesota and (b) Bathymetry ofTanners Lake

Data were collected in Tanners Lakes in two phases. In the years 2007 and 2008

specific conductivity/temperature profiles were measured in Tanners Lake, and eight

other lakes in the Twin Cities metropolitan area, at 4- to 6-week intervals [71]. These

measurements were made in the water column every 0.5 meters at approximately the

100

deepest location in each lake using a YSI Model 63 probe [91]. Supplemental data

for Tanners Lake collected by the Ramsey-Washington Watershed District in Tanners

Lake were obtained from the Minnesota Pollution Control Agency Environmental Data

Access website (http://www.pca.state.mn.us/data/edaWater/index.cfm). The District

takes profiles every two weeks between May and October.

In November 2008 a buoy system connected to a chain of sensors was installed in

Tanners Lake to monitor continuously temperature and specific conductance (Figure

5.2). Fourteen Sensorex CS150TC probes, installed at depth intervals from 0.5 m to

1.5 m with a higher concentration of probes in the bottom half of the lake, measured

temperature and specific conductance every two minutes. These sensors were connected

to a Campbell Scientific 32- channel relay multiplexor, which was connected to a Camp-

bell scientific CR-10X data logger. A Garmin GPS device was attached to the buoy

to record any movement from its original position at the end of the ice cover period.

Remote data access was installed for easy data retrieval from the laboratory.

The Sensorex probes measure voltage across resistors, which is converted to conduc-

tivity or temperature. The conductivity and temperature values were used to find the

specific conductance value at 25 oC. The probes were calibrated before being placed in

Tanners Lake. While the probes were operating in the lake, a verification/recalibration

was conducted. Temperature and conductivity profiles in the lake next to the buoy were

measured independently using a handheld YSI Model 63 probe. Profiles were taken on

11/19/2008, 2/24/2009 and 5/11/2009. These profiles were used to estimate creep in

the values recorded by the Sensorex probes. Temperature probes did not need to be

recalibrated.

5.3.2 Model Formulation: Simulation of Summer Stratification in a

Lake with a Benthic Saline Layer

Basic heat and salinity transfer equations

The 1-D temperature and salinity model is based on the following diffusion equations.

A∂T

∂t=

∂

∂z

(KzA

∂T

∂z

)+

Hn

ρwCp(5.1)

A∂C

∂t=

∂

∂z

(KzA

∂C

∂z

)(5.2)

101

Antenna Raven XTV CDMA Digital Cellular Modem

CR 10X Data Logger

AM16/32B Delay Multiplexer

Sensorex CS150 TC Temp/ Conductivity Probes

GPS16-HVS Geographical position receiver

SC932A interface

GPS516 – HVS RJ45 Cable

COAXSM-L cable (6ft)

Figure 5.2: Schematic of data acquisition and transmission system (”Buoy set-up”)to continuously record specific conductance and temperature profiles in Tanners Lake.Buoy has connection for remote data access.

102

where T(z, t) is the temperature of a water layer (oC) at time t (days) and depth z (m),

C is the total salinity expressed as specific conductance (µS/cm), A is the horizontal

area of the water layer (m2), Kz is the vertical effective diffusion coefficient (m2/d), Hn

is the strength of internal heat sources (kJ m−3 d−1), ρw is the density of the water

(kg/m3), Cp is the specific heat of the water (kJ/oC). Equations (5.1) and (5.2) include a

number of important assumptions: (1) Salinity is treated as conservative with no losses

of solute by chemical or biological processes. (2) changes in lake salinity are dominated

by the sodium and chloride ions derived from road salt. Previous studies [71] justify this

assumption. (3) Vertical transport of heat and of solute (salt) are analogous, i.e, the

same effective diffusion coefficient Kz can be used. (4) Because the salt layer is located

at the bottom of the lake and is associated with the colder heavier water during most

of the open water season double diffusion [125] can be ignored.

The boundary conditions include the heat flux across the lake surface between water

and air and the heat flux between water and sediments at the bottom of the lake. The

surface heat flux has to be calculated from daily weather data. The bottom heat flux

was ignored by imposing an adiabatic boundary condition at the bottom of the lake.

Computations progressed in daily time steps in the following sequence: The first

step was the computation of the surface heat flux using weather parameters and wa-

ter surface temperatures from the previous time step. This was followed by solving

equations (5.1) and (5.2) for vertical mixing by an effective diffusion coefficient (Kz).

Equations (5.1) and (5.2) were solved numerically in daily time steps and 0.5 m depth

increments using an explicit numerical scheme. Next, convective mixing was simulated

to remove density instabilities. If a layer had a greater density than the layer below

the two layers were mixed. Net convective mixing proceeded from the surface to the

bottom until the density profile was stabilized. Finally wind mixing was simulated to

determine the surface mixed layer depth.

Surface heat transfer

The air-water heat exchange at the lake surface can be estimated by equation (5.3)

[126].

Hn = Hsn +Han −Hc −He −Hbr (5.3)

where Hn is the strength of internal heat sources, Hsn is the difference between incoming

103

short-wave radiation and reflected short wave radiation, Han is the difference between

incoming long-wave atmospheric radiation and reflected atmospheric ration, Hc is the

heat loss from the water by conduction, He is the heat loss from the water body by

evaporation and Hbr is longwave back-radiation from the water to the atmosphere. The

net short wave radiation (Hsn) is defined by equations (5.4) to (5.6) [120].

Hsn(0) = (1− r)βHs (kJ m−2 day−1) (5.4)

Hsn(i) = Hsn(i− 1)exp(−µ∆z) (kJ m−2 day−1) (5.5)

µ = 1.84(ZSD)−1 (5.6)

Where Hs is the incoming solar radiation (kJ m−2 day−1), r is the reflection coefficient

defined by the albedo of the water surface (= 0.087; [127]), β is the surface absorption

factor (= 0.4; [128]), Hsn is the solar radiation at the top of each layer of water and µ

is the total shortwave radiation attenuation coefficient, which is related to secchi depth

ZSD by equation (5.6) [120]. The effect of long wave radiation was calculated using

equations (5.7) and (5.8).

Ha = σ∗εaT4a (kJ m−2 day−1) (5.7)

εa = (1− 0.261exp[−7.77 ∗ 10−4T 2a ])(1 + 0.17CC2) (5.8)

Where σ∗ is the Stefan Boltzmann constant (= 4.895*10-6 kJ m−2 K−4 day−1), Ta is

the air temperature (oK), εa is the atmospheric emissivity, and CC is the percent cloud

cover. The heat loss from convection was calculated using equations (5.9 and 5.10.

Hc = 0.47f(Ua)(Ts − Ta) (kJ m−2 day−1) (5.9)

f(Ua) = 86.32(9.2 + 0.45WFCTW2) (kJ m−2 mmHg−1 day−1) (5.10)

where f(Ua) is the wind function [126], Ts is the surface water temperature, WFCT is

the wind function coefficient to account for wind sheltering on the lake and W is the

104

daily average wind speed (m/s). The heat loss from evaporation was calculated by using

equations (5.11) to (5.13).

He = βbf(Ua)(Ts − Td) (kJ m−2 day−1) (5.11)

βb = 0.35 + 0.015Tm + 0.0012T 2m (mmHgC−1) (5.12)

Tm = (Ts + Td)/2 (5.13)

Where βb is the slope used to convert vapor pressures to temperatures [126] and Td is

the dew point temperature. Equation (Eq 5.14) was used to calculate back radiation.

Hb = εσ∗(Ts + 273.15)4 (kJ m−2 day−1) (5.14)

Where ε is the emissivity of water (=0.97).

Internal hypolimnetic mixing

The hypolimnetic effective diffusivity (Kz) was based on the maximum hypolimnetic

effective diffusivity and the stability frequency (N2) as expressed in equations (5.15)

and (5.16) [120].

Kz = 0.017Kzmax(N2)−0.43 (m2/day) (5.15)

N2 =g

ρ

(∆ρ∆z

)(s−2) (5.16)

Kzmax =α

LN(5.17)

where Kzmax is the maximum hypolimnetic eddy diffusion coefficient for a particular

day. Kzmax is dependent on α, a calibrated parameter, and the lake number (LN ). The

Lake Number is a dimensionless parameter relating the stabilizing forces from density

stratification to the destabilizing forces from wind and cooling [129]. The addition of the

Lake Number allows for Kzmax to change daily as wind speed varies and stratification

stability of a lake increases or decreases due to changes in temperature and salinity

profiles. The Lake Number has been used in other studies and models to simulate

105

hypolimnetic effective diffusion [130, 131]. The Lake Number is defined by equations

(5.18) and (5.19) [123].

LN =gSt(1− Zt/Zm)

ρmU∗2A0.5m (1− Zg/Zm)

(5.18)

St =1Am

∫ Zm

0(z − Zg)Az(1001− ρz)dz (5.19)

where St is the Schmidt Stability (kg m m−2), Zt is the thermocline height (m) defined

as the depth above the bottom of the lake with the largest density gradient, Zm is the

maximum depth of the lake (m), ρm is the density of the water at the surface (kg/m3),

U* is the water friction velocity due to wind stress (m/s) given later by equation (5.28),

Am is the surface area of the lake (m2), Zg is the center of lake volume in (m) above the

lake bottom, z is the height above the bottom (m), Az is the area of the lake a height

z (m2), and ρz is the density of water at depth z (kg/m3).

A Kz value was determined for each layer and then used in equations (5.1) and

(5.2) in an explicit numerical analysis scheme to solve for temperature and salinity

distribution with time. The minimum possible value for Kz is equal to the molecular

diffusion coefficient of heat in water (0.0125 m2/d) and the maximum value (0.216

m2/d) is determined from equation (5.20) using a relationship with lake surface area

[120]. This value is different from Kzmax in that Kzmax changes daily and can be lower,

but not higher than maxKz.

maxKz = 7.06 ∗ 10−3(Am)0.56(0.000075)−0.43 (5.20)

Convective mixing

Density instabilities throughout the water column develop during cooling of the lake

water from the surface. They lead to convective mixing in the water column. The

density of the water was determined using both temperature and salinity (equation

5.21).

ρw = ρT + ρS (5.21)

where ρT is the density of pure water based on its temperature and ρS is the density

increment of the water due to salinity. The change in density of pure water by temper-

ature alone is represented by equation (5.22) where T is the temperature of the water

106

[132]. This equation gives a maximum density of pure water at 3.98 oC temperature.

ρT = 999.869+6.6741∗10−2T−8.8556∗10−3T 2+8.2303∗10−5T 3−5.516∗10−7T 4 (5.22)

Salinity, i.e. the amount of dissolved salt in the water, adds to the density of pure

water. Salinity can be determined from a relationship with specific conductance given

by equations (5.23) and (5.24) [132]. Equation (5.23) is for high salinity (above 2000

mg/L) and equation (5.24) ) adjusts the value obtained in equation (5.23) for low salinity

(0 2000 mg/L). Equations (5.23) and (5.24) are for the ionic composition of sea water,

but are used here because, as in seawater, the major fluctuating solutes in Tanners Lake

are sodium and chloride [71].

S = 0.0080− .1692R0.5t + 25.3851Rt + 14.0941R1.5

t − 7.0261R2t + 2.7081R2.5

t (5.23)

S = S − 0.0081 + 1.5 ∗ 400Rt + (400Rt)2

(5.24)

where Rt is the ratio between the specific conductance values at 25 oC and the conduc-

tivity of standard seawater with a salinity of 35 g/L at 25 oC. Once the salinity of the

water is determined based on conductivity measurements the density increment due to

salinity can be determined from equation (5.25) [132].

ρS =S ∗ (0.824493− 4.0899 ∗ 10−3T + 7.6438 ∗ 10−5T 2 − 8.2467∗

10−7T 3 + 5.3875 ∗ 10−9T 4 + S1.5(−5.72466 ∗ 10−3 + 1.0277∗ (5.25)

10−4T − 1.6546 ∗ 10−6T 2) + 4.8314 ∗ 10−4S2

Convective mixing occurs if the density of water is greater in a layer above another

layer. This condition is unstable and induces convective mixing between the two layers.

Mixing continues downward until the density of the water increases from lowest to

highest throughout the water column going from the water surface to the lake bottom.

On occasion, the water temperature of a layer in the lake can increase or decrease

past the temperature of maximum density (TMD) during the daily time step to the point

where the new density of the layer is lower than that of the water layer below. This

apparent results masks the fact that during the period of cooling or heating the layers

temperature would have reached the point of maximum density resulting in instability-

induced mixing of the water layer of higher density above with the lower density layer

107

below it. This convective mixing could be missed due to the length of the time step

in the computations. Therefore a routine was added to the computations to check if

water temperature increased or decreased past TMD; if it did, convective mixing was

induced until the temperature of the overlaying layer reached a temperature past TMD

or until the density of the lower layer was higher than the density of the water at TMD.

Using equations (5.22) through (5.25), a linear approximation between TMD and specific

conductivity (C) was developed (equation 5.26).

TMD = 3.981− 1.22 ∗ 10−4C (5.26)

where TMD is in (oC) and C is specific conductivity in (/muS/cm ). According to

equation (5.26) a 0.22 oC decrease in the temperature of maximum density occurs for

every 1000 mg/L ( 1800 µS/cm) of salinity increase.

Surface wind mixing

The depth of the wind-mixed layer from the lake surface was determined from an en-

ergy balance consideration [133]. The ratio R (equation 5.27) is essentially the energy

transferred from the wind to the lake surface relative to the lifting work required to

deepen the mixed layer.

R =ρwWSCTU

∗3A∆tVm∆ρg(Zm − Zg)

(5.27)

U∗ = 0.0343W√CZ (5.28)

where ∆t is the time interval of one day, A is the surface area affected by wind, ρw is

the density of water, Vm is the volume of the surface mixed layer, ∆ρ is the density

difference between the mixed layer and the layer immediately below the mixed layer,

Zm is the depth of the mixed layer, Zg is the center of gravity of the mixed layer, CZ

is a drag coefficient on the water surface given by CZ = 0.0005√W when W < 15 m/s

or CZ=0.0026 when W >= 15 m/s [133]. U* is the wind induced water shear velocity,

W is the wind speed (m/s) and WSCT is the wind sheltering coefficient. When R is

greater that 1.0 mixing between the layers occurs. When R reaches a value below 1.0

wind mixing has reached it maximum depth.

108

Model calibration

Four model parameters were calibrated by minimizing the error between model results

and lake data. These parameters are WSCT , WFCT , α and ZSD. They appear in equa-

tions (5.27), (5.10), (5.17) and (5.6) respectively. The parameters WSCT and WFCT are

functions of wind sheltering. They represent the effective wind speed reduction for the

convective or evaporative heat transfer at the water surface, and for wind mixing at the

lake surface, respectively. The parameter α is used to determine the maximum vertical

effective diffusivity in the hypolimnion. The Secchi depth (ZSD) measures water trans-

parency, and is used to determine the attenuation coefficient of short wave radiation in

the lake water.

Simulations were run to obtain the best fit between the observed and modeled data

by changing the four calibration parameters. The set of parameter values that gave

the best combination of NSC-values between observed and modeled temperature and

specific conductance profiles was retained. This calibration was conducted with data

from the ice-free periods of 2008. The calibrated model parameter values were used for

model validation with data from 2007.

Weather data used as model input for the years 2007 and 2008 were obtained from the

Minneapolis/St. Paul International Airport (courtesy of Dr. X. Fang). The weather

station is about 19.8 km from the lake site. The weather data provided were daily

average values of air temperature (oF), dew point temperature (oF), solar radiation

(Langleys), wind speed (mph), and cloud cover (%). The values were converted to (oC)

for the temperatures, kj/m2 for radiation and m/s for wind speed (Figure 5.3).

5.3.3 Model Simulation of Dissolved Oxygen Transfer in a Lake with

a Saline Benthic Layer

Simulations were made to show how dissolved oxygen concentration profiles would

change in the lake under the following scenarios 1) uniform salinity concentrations

throughout the water column 2) observed salinity concentrations for 2008. The weather

data for the year 2008 were used along with the initial temperature profile. The initial

salinity profile was used for scenario 2 and a constant salinity was used for scenario 1.

A simplified dissolved oxygen model was used to simulate the vertical dissolved oxygen

109

0

10

20

30

Air

Tem

p (!

C)

-10

0

10

20

Dew

Poi

nt T

emp

(!C

)

5

10

Win

d sp

eed

(m

/s)

2,000

4,000

6,000

8,000

Sol

ar ra

diat

ion

(Kca

l/m2 )

04/18/07 07/27/07 11/04/070

0.5

1

Clo

ud C

over

(%

)

04/18/08 07/27/08 11/04/08

Figure 5.3: Weather parameters recorded at the Minneapolis/St. Paul InternationalAirport. and used as model input.

110

profile in the lake.∂O

∂t=

1A

∂

∂z

(AKz

∂O

∂z

)− SSOD (5.29)

where A, Kz and z are previously defined in equations 5.1 and 5.2, O is the dissolved

oxygen concentration (mg/L) and SSOD is the sediment oxygen demand (mg L−1 day−1).

All other sources and sinks of dissolved oxygen such as photosynthesis, plant respiration

and biochemical oxygen demand are ignored. Sediment oxygen demand (SSOD) is

defined by equations (5.30) and (5.31).

SSOD =Sb

A

∂A

∂z(5.30)

Sb = Sb20θT−20S (5.31)

where Sb is the sediment oxygen demand per unit area (g O m−2 day−1), A is the

horizontal lake area at a particular depth, and ∂A∂z is an estimate of the amount of

sediment surface area that is in contact with a particular water layer. A SSOD value

is calculated for each water depth. The Sb value is calculated using equation (5.31)

where Sb20 is an estimate of the sediment oxygen demand at 20 oC, θS is a temperature

adjustment coefficient and T is the temperature at the particular water depth. Sb20 is

estimated based on the trophic state of the lake. Tanners Lake is a mesotrophic lake. A

value of 1 g O m−2 day−1 was used for the value of Sb20 [134, 135]. Values for θS used

were 1.065 for T>10 oC and 1.130 for T <= 10 oC [136].

As a boundary condition, the DO concentration in the top layer of the lake was

always set to the saturation concentration of dissolved oxygen in water (equations (5.32)

and (5.33)) [136].

ln(CSO) =− 139.34411 +1.575701 ∗ 105

T− 6.642308 ∗ 107

T 2(5.32)

+1.2438 ∗ 1010

T 3− 8.621949 ∗ 1011

T 4

CS = CSO ∗ (1.0− 0.000035∆H) (5.33)

where T is the water temperature CSO is the saturation concentration at sea level and

CS is the dissolved oxygen saturation concentration adjusted for the elevation of the lake

111

above sea level (∆H (ft)). ∆H was set to 293.6 m [124]. The initial concentration profile

was set to 0 throughout the water column except for the surface layer, which was set to

the saturation concentration. In the computation of the DO profiles convective mixing

due to density instability and wind mixing in the surface layer were also accounted

for in separate computational steps, the same as in the transfer of salinity and heat

(temperature).

5.4 Results

5.4.1 Saline Layer Formation: Continuous lake monitoring results

The continuous record of water temperature and specific conductance profiles collected

in Tanners Lake from Nov 28 2008 to July 31 2009 showed the formation of a saline

water layer on the bottom of an urban lake in winter and the dissipation in spring

and summer. The conductivity probes experienced significant creep while in the lake.

Profiles were taken with the YSI Model 63 probe on Nov 19 2008, Feb 24 2009 and May

11 2009 and compared with daily average concentrations recorded by the Buoy (Table

5.1). ). On a plot of YSI data vs. buoy data a slope was determined representing the

daily creep for each of the buoy sensors. This daily creep value for individual probes

was subtracted from the recorded value for individual probes to produce the corrected

specific conductance values (Figure 5.4).

The water temperature and salinity record displayed the influence that runoff con-

taining road salt can have on a lake (Figure 5.5). In late fall of 2008 the salinity, defined

as the (specific conductance of the water,) was uniform throughout the water column.

As the winter progressed a saline water layer began to formed at the bottom of the lake.

The accumulation of saline water continued throughout the winter months resulting in

the formation of a saline layer approximately 5 meters thick above the bottom sediments

by April 2009.

The thickness of the saline benthic layers increased abruptly at certain times coin-

cident with daily average air temperatures above 0 oC (Figure 6 points A, B and C).

When the average daily air temperature reached above freezing causing the existing

snowpack to melt, the specific conductance (salinity) of the bottom waters in Tanners

Lake increased and/or the thickness of the saline layer expanded.

112

Table 5.1: Comparison of specific conductance recorded by the Buoy system to valuesmeasured with the YSI Model 63 probe. A slope representing the daily creep of theprobes was calculated using the difference between the values from the buoy system andthe values from a YSI Model 63 probe.Depth 11/19/08 2/24/08 5/11/08 Difference Slope

Buoy Probe Buoy Probe Buoy Probe 11/19 2/24 5/111.22 818 815 899 838 948 825 -4 61 123 0.732.13 818 814 897 838 889 829 -4 59 60 0.383.05 818 811 900 839 953 833 -7 61 120 0.736.1 818 820 935 864 978 842 2 71 136 0.787.62 818 804 927 890 933 850 -14 37 83 0.569.14 818 826 1064 965 1097 876 8 99 221 1.2210.36 818 821 1176 1070 1159 950 3 106 209 1.1810.91 818 818 1274 1140 1226 1000 0 134 226 1.3111.58 818 831 1388 1240 1412 1070 13 148 342 1.8812.19 818 815 1399 1300 1423 1230 -4 99 193 1.1312.8 818 830 1468 1340 1535 1320 11 128 215 1.1713.41 818 814 1491 1394 1583 1335 -4 97 248 1.44

!""#

$""#

%"""#

%&""#

%'""#

%!""#

%%(%$("$# "%(&)("*# "'(")("*# "!(%!("*#

!"#$%&%$'()*+,$-.*$#'/µ!0$12'

%+&&#,-./0#

%&+%*#,-./0#

%+&&#

%&+%*#

Figure 5.4: Specific conductance recorded at depths of 1.22 m and 12.19 m . Solid linesrepresent raw data collected by the probes. Dashed lines represent corrected data afterrecalibration.

113D

ep

th (

m)

11/28/08 01/07/09 02/16/09 03/28/09 05/07/09 06/16/09

2

4

6

8

10

12

Specific

Conducta

nce (!

S/c

m)

700

800

900

1000

1100

1200

1300

1400

1500

Dep

th (m

)

11/28/08 01/07/09 02/16/09 03/28/09 05/07/09 06/16/09

2

4

6

8

10

12

Tem

pera

ture

( !C

)

5

10

15

20

25

Figure 5.5: Isopleths of recorded (measured) specific conductance (top) and isotherms(bottom) in a depth vs. time plot. Values recorded in Tanners Lake from 28 Nov 2008to 31 July 2009.

114

600800

1000120014001600

Sur

face

wat

erC

ondu

ctan

ce

(!S

/cm

)

8001,0001,2001,4001,600

Ben

thic

wat

erC

ondu

ctan

ce(!

S/c

m)

Nov Jan Mar May0

0.5

1

Pre

cipi

tatio

nW

ater

Equ

ival

ent

(inch

es)

5

10

Sno

w D

epth

(inch

es)

0

20

40

Dai

ly A

vera

geA

ir Te

mpe

ratu

re("

C)

A B C D

Figure 5.6: From top to bottom: Specific conductance at the surface of the lake (seriesdepths from surface 1.2, 2.1, 3.0. 6.1 meters), Specific conductance at the bottom of thelake (series depths from surface in order of highest observed specific conductance valuesto lowest 13.4, 12.8, 12.2, 11.6, 11.0, 10.4, 9.1), daily average air temperature, dailyaverage snow depth, and precipitation water equivalent. Points A, B and C representstimes when accumulation of saline water occurred at the bottom of the lake. Point Drepresents when a fresh water intrusion was observed in the lakes surface water. Weatherdata were collected by the Minnesota Climatology working group.

115

The accumulation of salt laden (snowmelt) runoff water at the bottom of the lake

continued until ice-out. Ice-out occurred between March 31 and April 2, based on ice-out

dates of similar sized lakes located near Tanners Lake (Kohlman, Gervais, and Harriet;

[137]).

Right before ice-out a water intrusion occurred in the surface waters of the lake

(Figure 5.6 point D). During this time a layer with low specific conductance and tem-

peratures that reached 7 oC formed below the ice surface (Figure 5.4). The water for

these intrusions came from a few snowfalls that quickly melted and rainfall that oc-

curred from March 23 to April 1. The air temperatures during this period were above

freezing and likely most of the road salt had already been washed away allowing a warm

and less saline layer to form under the ice cover.

Shortly after the ice layer on the lake had melted, the lake began to mix (spring

overturn). Only the top 10 meters of the 14 m deep lake mixed after ice-out, resulting

in a saline water layer of about 4 m thickness at the bottom of the lake. The density

of this saline layer was strong enough to resist the convective and wind mixing events

right after ice out, i.e. the lake had become monomictic.

After ice-out the salinity of the benthic layers increased even though road salt ap-

plications had stopped. Shortly after the erosion of the saline layer began. This erosion

continued, but was not strong enough to remove the saline layer. By July 31st Tanners

Lake still has a saline benthic layer.

5.4.2 Lake Stratification: Model calibration results

The best-fit model parameters obtained by model calibration are given in Table 5.2.

WSTR and WFCT are wind-sheltering coefficients. Typical values for wind sheltering

coefficients range from 0.1 to 1 [120]. The value of 0.25 for Tanners Lake is low pointing

towards a well-sheltered lake.

Table 5.2: Best fit parameters from model calibrationWSTR 0.25WFCT 0.44Zsd (m) 3.00α (m2/day) 0.19

116

A maximum hypolimnetic effective diffusivity (Kzmax) was also determined by cali-

bration. The best-fit value for this parameter was 0.19 m2/day.

The Secchi depth determined by model calibration was 3 m. It matched the mea-

sured average Secchi depth in 2007 and 2008 in Tanners Lake of 3 meters with a range

from 1.8 to 5 m [124].

The temperature and specific conductance profiles obtained from the calibrated

model for the year 2008 were comparable to the observed values (Figure 5.7). Com-

parisons between observed and modeled values at three depths including the waters

surface, the mid-depth of the lake and the lake bottom depth are given in Figure 5.8.

Values obtained were consistent for temperature and salinity at the three depths. Dif-

ferences between the two years were significant. In 2007, values in the middle of the

lake decreased rapidly and remained even with the surface concentrations shortly after

ice out. The deep layer also eroded quickly, compared to the values in 2008, resulting

in the removal of the chemocline shortly after ice out for most of the water column. In

2008 the chemocline persisted until fall.

The average RMSE values for the temperature profiles in 2007 and 2008 were 1.06

and 1.10 oC respectively. The average RMSE values for the specific conductance profiles

in 2007 and 2008 were 57 and 60 µS/cm respectively. The temperature profiles for

both 2007 and 2008 compare well with the observed values throughout the year 5.9.

Calibration was only conducted with the 2008 data, yet the RMSE values for the 2007

temperature series are comparable to the 2008 values. The RMSE values for the specific

conductance are also consistent throughout the year 5.9. For the 2008 simulation, RMSE

values hover between 50 and 60 µS/cm. In 2007 values around 50 µS/cm are observed

during the first 5 months of the simulation, but increase beyond that point. In the later

months of the simulation concentrations in the surface waters of the observed dataset

are reduced in 2007. This is likely caused by freshwater inflows from rainfall. Rainwater

inflows are not included in the model resulting in an increase in RMSE values in the

epilimnion.

5.4.3 Lake Stratification and Vertical Mixing: Model simulation re-

sults

Temperature and specific conductance profiles

117

0

5

10

07-May-2008 30-May-20080

5

10

30-Jul-2008

Dep

th (m

)

15-Aug-2008

0 10 20

0

5

10

1525-Sep-2008

800 1,200 1,600 0 10 2023-Oct-2008

800 1,200 1,600

Temperature !C Conductance "S/cm Temperature !C Conductance "S/cm

Figure 5.7: Vertical profiles of measured (dashed line) and simulated (solid line) watertemperatures and specific conductance in Tanners Lake in 2008.

118

4/22/07 6/11/07 7/31/07 9/19/07 11/7/07

600

800

1000

1200

1400

1600

1800

Con

duct

ivity

(!S

/cm

)

0 m7 m14 m0 m14 m7 m

4/22/07 6/11/07 7/31/07 9/19/07 11/7/070

5

10

15

20

25

30

Tem

pera

ture

(!C

)

4/22/08 6/11/08 7/31/08 9/19/08 11/7/08

600

800

1000

1200

1400

1600

1800

Con

duct

ivity

(!S

/cm

)

4/22/08 6/11/08 7/31/08 9/19/08 11/7/080

5

10

15

20

25

30

Tem

pera

ture

(!C

)

Figure 5.8: Time series of specific conductance (left) and water temperatures (right) atthe lake surface (0m), at mid-depth (7m) and at the bottom (14m) of Tanners Lake,measured and simulated for 2007 (top) and 2008 (bottom).

119

!"

#!"

$!!"

$#!"

%!!"

%#!"

&!!"

&#!"

'!!"

(%"

($)#"

($"

(!)#"

!"

!)#"

$"

$)#"

%"

'*%+" ,*$," -*#" .*%'" $$*$&" !"#$%&'(#&)*+µ,-&./*

0).1)2('%2)*+"!/*

/012"!-" /012"!+" 3456"!-" 3456"!+"

Figure 5.9: Root mean square error (RMSE) between modeled and observed watertemperature and specific conductance profiles in 2007 and 2008.

Model simulations were made for the ice-free periods of 2007 and 2008. The initial

conditions used in the model for temperature and specific conductance were obtained

from field measurements using an YSI Model 63 probe (Figure 5.10). Initial values were

acquired as close to the ice-out date as possible on 1 April 2007 and 22 April 2008.

Estimates of ice-out dates in Tanners Lake are March 26-27, 2007 and April 1821, 2008

respectively. These ice out dates were determined from similar sized lakes located near

Tanners Lake (Kohlman, Gervais, and Harriet; [137]).

The two initial conductivity profiles are approximately similar but the two initial

temperature profiles are different. The temperature of the surface waters in 2008 were

much warmer than in 2007, but the deeper layers were colder in 2008 than in 2007.

In 2008 the saline layer persisted throughout the summer and diluted gradually by

effective diffusion into the overlying water. By fall the density of the bottom layer was

reduced due to heating and gradual mixing with hypolimnetic water, allowing for com-

plete mixing (Figure 5.11). In 2007 the chemocline eroded quickly after ice-out resulting

in an almost completely mixed water column (Figure 5.3).

Stratification stability

Density gradients caused by temperature differences and those caused by salinity were

120

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%"

&"

'!"

'#"

'$"

'%"

!" (!!" '!!!" '(!!" #!!!"

!"#$%&'()&

*#"+,-,+&+./01+$2/+"&'µ*3+()&

!" #" $" %" &" '!"

4"(#"52$15"&'.6)&

$)')!*"

$)##)!&"

Figure 5.10: Measured specific conductance (dashed line) and temperature (solid line)profiles used as initial conditions for simulations of the open water periods 2007 and2008.

calculated separately to evaluate the contribution of the salinity to lake stratification

(Figure 5.12).

In April, after ice-out, the density stratification in the lake was mostly caused by

salinity. On April 1 2007 all of the density stratification in the lake was from the salinity.

The largest salinity induced density gradient was located at 13 m and was equal to 0.17

Kg/m4. On April 22 2008 temperature stratification was present up to a depth of 4

m and the strongest density gradient (equall to 0.15 Kg/m4) caused by temperature

stratification was at a depth of 4m. Salinity stratification began at a depth of 8 m.

The strongest salinity induced density gradient (also equal to 0.15 Kg/m4) was at 10 m

depth .

121Depth (m)

4/01

/07

6/01

/07

8/01

/07

10/0

1/07

0 2 4 6 8 10 12 14

Specific Conductance (!S/cm)

600

700

800

900

1000

1100

1200

1300

1400

1500

1600

Depth (m)

4/01

/08

6/01

/08

8/01

/08

10/0

1/08

0 2 4 6 8 10 12 14

Specific Conductance (!S/cm)

600

700

800

900

1000

1100

1200

1300

1400

1500

1600

Depth (m)

4/01

/07

6/01

/07

8/01

/07

10/0

1/07

0 2 4 6 8 10 12 14

Temperature ( !C )

0510152025

Depth (m)

4/01

/08

6/01

/08

8/01

/08

10/0

1/08

0 2 4 6 8 10 12 14

Temperature ( !C )

0510152025

Fig

ure

5.11

:Is

ople

ths

ofsi

mul

ated

spec

ific

cond

ucta

nce

(top

)an

dis

othe

rms

(bot

tom

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ade

pth

vsti

me

plot

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ngth

eic

e-fr

eepe

riod

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ight

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122

In May the density gradients were dominated by temperature. In 2007 a slight chem-

ical stratification was present in the bottom 11 meters, but almost all salinity induced

density gradients had disappeared. Temperature-induced density gradient reached 0.7

Kg/m4. In 2008 a more pronounces salinity layer was present in May, but the density

gradients caused by the salinity only reached 0.06 kg/m4 while temperature stratifica-

tion caused a maximum density gradient of 0.5 kg/m4.

In July the temperature stratification in both 2007 and 2008 caused density gradients

to reach up to 1.4 kg/m4. Salinity stratification was non-existent in July of 2007, but

it was still present in July of 2008 starting at about 8 meters.

In October of 2008 salinity stratification had been reduced to a maximum value of

0.03 kg/m4 at 7 m. Temperature stratification was reduced to about 0.4 kg/m4 for both

2007 and 2008.

Hypolimnetic effective diffusivity

In order to get the variable results between 2007 and 2008 the Lake Number had to

be included in the calculation of the hypolimnetic effective diffusivity. With out the

inclusion of this parameter either to much mixing occurred in the summer months when

temperature stratification was strong or to little mixing occurred in the early spring

and late fall months when temperature stratification was reduced.

Without the Lake Number the hypolimnetic Kz values would be constant throughout

the year year if no localized density stratification was present at that particular depth.

The Lake number changes with strength of the overall lake stratification as well as

with wind speed. In summer when thermal stratification was strong the Lake number

increased causing the maximum hypolimnetic eddy diffusion (Kz) to decrease (Figure

13). In fall and spring when density gradients were absent or weak mixing was increased

in the hypolimnion. When wind speeds are high and more wind energy was applied at

the lake surface Kz values increased

5.4.4 Dissolved Oxygen Modeling Results

Simulations were run using the 2008 temperature and salinity profiles to determine how

dissolved oxygen (DO) profiles in Tanners Lake would respond to the presence of a

benthic saline layer. Under the first scenario with no vertical salinity gradient (Figure

123

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Figure 5.12: Profiles of density gradients caused by salinity (solid line) and temperature(dotted line).

124

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Figure 5.13: Simulated effective hypolimnetic diffusion coefficients near the lake bed(depth of 14m) plotted vs time.

5.14)the lake is dimictic, i.e. it turns over in fall and spring and the entire water column

is oxygenated on both occasions. In midsummer the lake bottom goes anoxic for about

100 days from July 10 to Oct 20.

Under the second scenario, using identical weather conditions, but introducing a

saline layer at the bottom of the lake produced a very different result. The benthic

saline layer reduced vertical mixing especially near the lake bed. In spring the benthic

saline layer prevented the complete convective mixing of the entire water column. In

fall, when the saline layer was diluted, vertical lake mixing was delayed, but eventually

the saline layer was eroded and the surface waters mixed with the benthic waters late

in November. At that time, DO was transport from the overlying water to the lake

sediment. Overall DO did not reach the lake bottom during the entire open-water

period from April to November (Figure 13 bottom)

Vertical dissolved oxygen profiles were very similar in late summer for the two simu-

lated scenarios, with and without a benthic saline layer, when temperature stratification

was at a maximum.

125D

etpt

h (m

)

6/1/08 8/1/08 10/1/08

0

2

4

6

8

10

12

14

Dissolved O

xygen (mg/L)

0

1

2

3

4

5

6

7

8

9

(a)

Dep

th (m

)

6/1/08 8/1/08 10/1/08

0

2

4

6

8

10

12

14

Dissolved O

xygen (mg/L)

0

1

2

3

4

5

6

7

8

9

(b)

Figure 5.14: Isopleths of simulated dissolved oxygen concentrations in a depth vs. timeplot without a saline layer (top) and with a saline layer (bottom) for the 2008 testscenario.

126

5.5 Discussion

5.5.1 Interpretation of Measurements (2007-2009) and Simulation Re-

sults (2007-2008)

Equations developed for the MINLAKE temperature model [133][120]were used to sim-

ulate temperature and salinity profiles in a stratified lake during the open-water season.

A conversion of salinity (specific conductance) to density and an effective hypolimnetic

diffusion coefficient linked to a Lake Number were introduced to accurately simulate

temperature and salinity profiles in Tanners Lake, a lake in the Twin Cities metropoli-

tan area of Minnesota. The dynamic lake model used daily weather parameters and

initial temperature and salinity profiles measured after ice-out as inputs. Daily sim-

ulated data and a few observed profiles for 2007 and 2008 and continuously recorded

profiles for 2008/2009 were compared. The interpretation of the three years of data and

two years of simulations focused on the saline layer.

In 2007 the saline layer eroded away a few weeks after ice-out resulting in an almost

completely mixed water column throughout the summer. In 2008 and 2009 this did

not occur; instead the saline benthic layer persisted throughout the summer. The main

cause for this significant and consequential difference appears to be a 9-day cooling

period between April 4 and April 12, 2007 right after ice-out where air temperatures

and dew point temperature were below 0 oC 5.3. The prolonged stratification instability

allowed for the effective hypolimnetic diffusion caused by wind mixing to erode away

the saline layer before temperature stratification was able to reduce the mixing between

the hypolimnion and epilimnion.

In 2008 and 2009 a steady warming of the surface waters followed ice-out. This warm-

ing quickly created a thermocline, which reduced the mixing between the hypolimnion

and the surface waters effectively limiting the erosion of the saline layer.

Convective mixing appeared to be a minimal component in the erosion of the saline

layer. Convective mixing alone was not strong enough to mix the surface waters with

the salinity layer in 2007, 2008 or 2009. In 2007 the density increase due to the heating

of the water to TMD (just below 4 oC) from 3.5 oC was only 0.002 kg/m3. At this same

time the density increase due to the change in salinity between the surface waters and

the hypolimnion was 0.42 kg/m3. In 2008 when the hypolimnetic water temperatures

127

were much cooler the difference in density caused by heating the water from 3 oC to TMD

amounted to 0.007 kg/m3 compared to the density difference of .47 kg/m3 between the

surface waters and the hypolimnion caused by salinity. The large differences between

the added density from salinity and the added density from heating the surface waters

to TMD eliminated the complete convective mixing of the water column. This means

that the major driving force for the erosion of the saline layer during the spring and fall

was wind energy.

The density stratification right after ice-out was dominated by salinity stratification.

Throughout the summer, however, when the temperature of the surface water heated

up, the density difference across the thermocline far outweighed the density gradients

caused by the chemocline. Consequently, it is the formation of the thermocline that

prevents the mixing of the saline layer with the surface waters during the summer. If

only the chemocline was present the density stratification caused by the salinity gradient

would not be sufficient to withstand wind mixing from top to bottom.

The data recorded continuously in 2009 at 2-minute intervals clearly showed the

accumulation of a saline water layer at the bottom of Tanners Lake. This layer grew

during the winter months, when melting events occurred, until ice-out (Figure 5.5).

The accumulation of salt water at the bottom of the lake suggests that the snowmelt

runoff plunged upon entering the lake to form a density current that flow to the lake

bottom. This flow pattern was documented using only temperature probes in Ryan

Lake in Minnesota [54].

Right after ice-out a final salinity increase was recorded in the deepest part of Tan-

ners Lake (Figures 5.5 and 5.66). At least two different processes could account for this:

(1) mixing between the sediment layer and the benthic water could have uprooted salt

stored in the sediments [138, 44, 71] or (2) arrival of a delayed snowmelt runoff traveling

through extended pathways.

Shortly after this final input of saline water, the erosion of the saline benthic layer

began. This erosion was not enough to completely mix the lake before a thermocline

formed in the lake reducing the vertical transport of mass, momentum and energy from

the lake surface to the lake bottom.

128

5.5.2 Effects of Benthic Saline Layer Formation on Lake Water Quality

The intermittent or persistent presence of a benthic saline layer at the bottom of an

urban lake can have a number of consequences for lake water quality. The saline layer

prevents natural convection and mixing of the surface waters with the benthic water.

This prevents oxygen from reaching the botom of the lake lengthening the anoxic periods

of the lake sediments [61]. This effect was clearly shown in the simulated DO profiles

(Figure 5.14 bottom). The saline layer reduced mixing from convection as well as

wind mixing of the hypolimnion, preventing oxygen from reaching the sediments in the

spring right after ice out. When the salt layer was removed oxygen was able to travel

throughout the water column due to convective and wind mixing (Figure 5.14 top).

DO remained in the hypolimnion until July when the oxygen demand of the sediments

finally reduced DO levels to those observed when a saline layer was present (Figure 5.14

bottom). The saline layer increased the anoxic period in the lower depths of the lake

by 3 months.

Biochemical (mostly microbial) DO uptake at the sediment water interface removes

DO from the water column, and diffusive transport from above usually replenishes it.

These processes were represented in the model. Lake bottom waters and lake sediments

become anaerobic when insufficient DO was supplied by convection or wind mixing from

the water above. Starting with zero DO at the lake bottom due to the presence of a

saline layer that prevents lake overturn, will cause continuing anoxia in summer on the

lake bed.

Under winter conditions, which were not modeled, there is no oxygen source in the

lake water (no surface aeration due to the ice cover, and no photosynthesis due to a

snow cover on the ice). Benthic DO continues, however, and in order to maintain aerobic

conditions near the lake, fall turnover and oxygen replenishment near the lake bed are

crucial.

A long anoxic period in the hypolimnion can facilitate the release of phosphorus and

metals from the sediments. Enhanced internal phosphorus release from the anaerobic

sediment [139, 140] increases cultural eutrophication. Increased chloride concentrations

have also been observed to increase the bioavailability of metals such as cadmium, lead,

chromium mercury among others [40, 37, 39, 4, 34]. By increasing the contact time

of the saline layer containing high concentrations of chloride with the sediments, the

129

release of metals from these sediments is increased.

Finally, the increased contact time of benthic organisms with elevated chloride con-

centrations can affect the biodiversity of the lake [59, 110]. Macro-invertebrates and

bottom feeding organisms would have to adjust to the increased length of the anoxic

period at the lake bed as well as increased chloride concentrations. All of these con-

sequences of the saline benthic layer formation are detrimental to water quality and

aquatic life in the lake.

5.6 Summary and Conclusions

Two years (2007, 2008) of intermittently measured temperature and specific conduc-

tance profiles and one year (2009) of continuously monitored data were used to show

the formation of a benthic saline layer in winter, and its effect on summer stratification

and mixing dynamic in Tanners Lake, Oakdale, Minnesota.

Erosion of the saline layer in the spring occurred in only one of the three years studied

(2007). In the other two years (2008 and 2009), the saline layer persisted throughout

the summer, and was destroyed only by fall turnover and mixing between the epilimnion

and hypolimnion when thermo stratification was at a minimum.

Simulations showed that from ice-out in April 2008 until November 2009 the saline

layer was able to prevent dissolved oxygen from reaching the lake sediments. Without

the saline layer the lake sediments would have been anoxic only from the beginning

of July until the end of October 2008. With the addition of a saline layer the anoxic

period experienced by the lake sediments persisted throughout the spring and summer.

Simulations also showed that in the fall turnover of the lake was delayed, when the

saline layer was present, until the end of November.

The results of this study provide information on the formation, the mixing and the

consequences of a benthic saline layer in a northern temperate urban lake that receives

snowmelt runoff from roads on which salt (NaCl) has been applied to increase driving

safety. Specific results are:

(1) The formation of the benthic saline layer has been documented in detail. The

record consists of specific conductance profiles recorded at 2-minute intervals from 28

Nov 2008 until 31 July 2009 in Tanners Lake in Oakdale, Minnesota. The formation of

130

the saline benthic layer is episodic, and follows the air temperature pattern.

(2) Natural convective mixing in spring or fall (spring and fall turnover) is not

intensive enough to remove the saline layer after ice out. Mixing of the hypolimnion by

wind energy applied at the water surface is needed to completely erode the saline layer.

(3) The formation of monomixis (one complete lake turnover per year) or meromixis

(no complete lake turnover per year) in a northern temperate lake due to road salt

application in the watershed appears to be contingent on both the strength (salt con-

centration) of the saline layer and the timing of the seasonal thermocline formation after

ice out.

(4) Formation of a seasonal thermocline effectively reduces the transport of wind

energy from the epilimnion to the hypolimnion, and hinders the erosion of the saline

layer. Lakes number was used in the model simulations to capture this effect.

Overall the presence of a saline benthic layer due to runoff containing road salt

(NaCl) was shown to disrupt the natural mixing mechanics of a dimictic lake. This

disruption has significant consequences for a lakes water quality and ecology.

Aknowledgements

We acknowledge the Minnesota Local Road Research Board (LRRB) and the University

of Minnesota Doctoral Dissertation Fellowship Program for providing support to com-

plete this research. We also thank Ben Erickson and Chris Ellis from the St. Anthony

Falls Laboratory for their assistance in designing and implementing the Buoy system.

References

[1] J. Marsalek. Road salts in urban stormwater: An emerging issue in stormwater

management in cold climates. Water Science and Technology, 48(9):61–70, 2003.

[2] United Stated Geological Survey. Salt statistics and information, 2007.

[3] R. B. Jackson and E. G. Jobbagy. From icy roads to salty streams. Proceedings of

the National Academy of Sciences, 102(41):14487–14488, October 11, 2005 2005.

[4] V. Novotny, D. W. Smith, D. A. Kuemmel, J. Mastriano, and Al Bartosova. Urban

and highway snowmelt: Minimizing the impact on receiving water. Technical

Report Pr. 94-IRM-2, Water Environment Research Foundation, Alexandria, VA,

1999.

[5] E. L Thunqvist. Regional increase of mean annual chloride concnetration in water

due to the application of deicing salt. Science of the Total Environment, 325:29–37,

2004.

[6] Environment Canada Health Canada. Priority substances list assessment report

- road salt. Tertiary environment protection act 1999., ECHC, Calgary, Ontario,

Canada, 2001.

[7] J. A. Richburg and W. A. P. I. Lowenstein. Effects of road salt and phragmites

australis on the vegetation of a western massachusetts calcareous lake basin fen.

Wetlands, 21(2):247–255, 2001.

[8] S. V. Panno, K. C. Hackley, H. H. Hwang, S. Greenberg, I. G. Krapac, S. Lands-

berger, and D. J. O’Kelly. Source identification of sodium and chloride contamina-

tion in natural waters: Preliminary results. In 12th Annual Research Conference

131

132

of the Illinois Groundwater Consortium. Research on Agrichemicals in Illionois.

Groundwater Status and Future Direction XII, Carbondale, Illinois, 2002.

[9] Domenico Sanzo and Stephen J. Hecnar. Effects of road de-icing salt (nacl) on

larval wood frogs (rana sylvatica). Environmental Pollution, 140(2):247–256, 3

2006.

[10] P. J. Talmage, K. E. Lee, R. M. Goldstein, J. P. Anderson, and J. D. Fallon. Water

quality, physical habitat, and fish-community composition in streams in the twin

cities metropolitan area, minnesota 1997-98. Technical report, 1999. ID: 58.

[11] B. J. Blasius and R. W. Merritt. Field and laboratory investigations on the ef-

fects of road salt (nacl) on stream macroinvertebrate communities. Environmental

Pollution, 120(-):219–231, 2002. ID: 7.

[12] E. Bendow and R. W. Merritt. Road-salt toxicity of select michigan wetland

macroinvertebrates under different testing conditions. Wetlands, 24(1):68–76,

March 2004 2004. ID: 32.

[13] J. M. Ramstack, S. C. Fritz, D. R. Engstrom, and S. A. Heiskary. The application

of a diatom-based trnasfer function to evaluate regional water-quality trends in

minnesota since 1970. Journal of Paleolimnology, 29:79–94, 2003.

[14] J. M. Ramstack, S. C. Fritz, and D. R. Engstrom. Twentieth century water quality

trends in minnesota lakes compared with presettlement variability. Canadian

Journal of Fisheries and Aquatic Sciences, 61:561–576, 2004.

[15] W. L. Flannery. Current status and knowledge of halophilic bacteria. Bacterial

Rev., 20(2):49–66, 1956.

[16] M. T. Madigan and J. M. Martinko. Brock Biology of Microorganisms. Pearson

Prentice Hall, Upper Saddle River, NJ, 2006.

[17] R. H. Vreeland and L. I. Hochstein. The Biology of Halophilic Bacteria. CRC

Press Inc., Boca Raton, FL, 1993.

[18] A. Oren. Halophilic Microorganisms and their Environment. Kluwer Academic

Publishers, Dordrecht, Netherlands, 2002.

133

[19] W. S. Scott. An analysis of factors influencing deicing salt levels in streams.

Journal of environmental management, 13:269–287, 1981.

[20] Minnesota Pollution Control Agenct. Draft mpca 2008 303(d) list. Technical

report, MPCA, 2008.

[21] Wenck Associates. Shingle creek chloride tmdl report. Technical report, Shin-

gle Creek Water Management Commission and the Minnesota Pollution Control

Agency, St Paul, MN, 2006.

[22] K. S. Godwin, S. D. Hafner, and M. F. Buff. Long-term trends in sodium and

chloride in the mohawk river, new york: The effect of fifty years of road-salt

application. Environmental Pollution, 124:273–281, 2003.

[23] S. S. Kaushal, P. M. Groffman, G. E. Likens, K. T. Belt, W. P. Stack, V. R.

Kelly, L. E. Band, and G. T. Fisher. Increased salinization of fresh water in the

northeastern united stated. Proceedings of the National Academy of Sciences,

102(38):13517–13520, September 20, 2005 2005.

[24] M. Backstrom, U. Nilsson, K. Hakansson, B. Allard, and S. Karlsson. Speciation

of heavy metals in road runoff and roadside total deposition. Water, air, and soil

pollution, 147(1-4):343–366, 2003.

[25] A. P. Davis, M. Shokouhian, and S. Ni. Loading estimates of lead, copper, cad-

mium, and zinc in urban runoff from specific sources. Chemosphere, 44(5):997–

1009, 2001. Compilation and indexing terms, Copyright 2007 Elsevier Inc. All

rights reserved.

[26] J. Marsalek, Q. Rochfort, B. Brownlee, T. Mayer, and M. Servos. Exploratory

study of urban runoff toxicity. Water Science and Technology, 39(12):33–39, 1999.

Compilation and indexing terms, Copyright 2007 Elsevier Inc. All rights reserved.

[27] D. K. Makepeace, D. W. Smith, and S. J. Stanley. Urban stormwater quality:

summary of contaminant data. Environmental Science and Technology, 25(2):93–

139, 1995.

134

[28] J. J. Sansalone, S. G. Buchberger, and S. R. Al-Abed. Fractionation of heavy

metals in pavement runoff. Science of the Total Environment, 189-190:371, 1996.

Compilation and indexing terms, Copyright 2007 Elsevier Inc. All rights reserved.

[29] P. Gobel, C. Dierkes, and W. G. Coldewey. Storm water runoff concentration

matrix for urban areas. Journal of contaminant hydrology, 91(1-2):26–42, 2007.

Compilation and indexing terms, Copyright 2007 Elsevier Inc. All rights reserved.

[30] P. L. Brezonik and T. H. Stadelmann. Analysis and predictive models of stormwa-

ter runoff volumes, loads, and pollutant concentrations from watersheds in the

twin cities metropolitan area, minnesota, usa. Water research, 36(7):1743–1757,

2002. Compilation and indexing terms, Copyright 2007 Elsevier Inc. All rights

reserved.

[31] G. B. Milton and G. A. Payne. Quality and quantity of runoff from selected

guttered and unguttered roadways in northeastern ramsey county, minnesota.

Technical Report U. S. Geological Survey Water- Resources Investigations Report

96-4284, 1996.

[32] Cam Westerlund, Maria Viklander, and Magnus Backstrom. Seasonal variations

in road runoff quality in lulea, sweden. Water Science and Technology, 48(9):93–

101, 2003. Compilation and indexing terms, Copyright 2007 Elsevier Inc. All

rights reserved.

[33] Jiri Marsalek, G. Oberts, K. Exall, and M. Viklander. Review of operation of

urban drainage systems in cold weather: Water quality considerations. Water

Science and Technology, 48(9):11–20, 2003. Compilation and indexing terms,

Copyright 2008 Elsevier Inc.

[34] L. A. Warren and A. P. Zimmerman. Influence of temperature and nacl on cad-

mium, copper and zinc partitioning among suspended particulate and dissolved

phases in an urban river. Water research, 28(9):1921–1931, 1994.

[35] V. Novotny, D. Muehring, D. H. Zitomer, D. W. Smith, and R. Facey. Cyanide

and metal pollution by urban snowmelt: impact of deicing compounds. Water

Science and Technology, 38(10):223–230, 1998.

135

[36] B. Bauske and D. Goetz. Effect of deicing salts on heavy metal mobility. Acta

Hydrochim. Hydrobiol, 21(1):38–42, 1993.

[37] M. Backstrom, S. Karlsson, L. Backman, L. Folkeson, and B. Lind. Mobilisation of

heavy metals by deicing salts in a roadside environment. Water research, 38:720–

732, 2004.

[38] S. Lofgren. The chemical effects of deicing salt on soil and stream water of five

catchments in southeast sweden. Water, air, and soil pollution, 130(1-4):863–868,

2001.

[39] A. C. Norrstrom. Metal mobility by de-icing salt from an infiltration trench for

highway runoff. Applied Geochemistry, 20(10):1907–1919, 2005.

[40] C. Amrhein, J. E. Strong, and P. A. Mosher. Effect of deicing salts on metal

and organic matter mobilization in roadside soils. Environmental Science and

Technology, 26(4):703–707, 1992.

[41] A. C. Norrstrom and E. Bergstedt. The impact of road de-icing salts (nacl) on

culloid dispersion and base cation pools in roadside soils. Water, air, and soil

pollution, 127(1-4):281–299, 2001. Compilation and indexing terms, Copyright

2007 Elsevier Inc. All rights reserved 0049-6979 01186500875 Colloid dispertions

Journal Article.

[42] Daniel Grolimund and Michal Borkovec. Colloid-facilitated transport of strongly

sorbing contaminants in natural porous media: Mathematical modeling and labo-

ratory column experiments. Environmental Science and Technology, 39(17):6378–

6386, 2005. Compilation and indexing terms, Copyright 2007 Elsevier Inc. All

rights reserved.

[43] A. C. Norrstrom and G. Jacks. Concentration and fractionation of heavy metals

in roadside soils receiving de-icing salts. Science of the Total Environment, 218(2-

3):161–174, 1998. Compilation and indexing terms, Copyright 2007 Elsevier Inc.

All rights reserved.

136

[44] T. Mayer, W. J. Snodgrass, and D. Morin. Spatial characterization of the occur-

rence of roads salts and their environmental concentrations as chlorides in cana-

dian surface waters and benthic sediments. Technical Report NWRI Contribution

No. 99-097, Environment Canada Health Canada, 1999.

[45] G. L. Oberts. Cold climate bmps: Solving the management puzzle. Water Science

and Technology, 48(9):21–32, 2003. Compilation and indexing terms, Copyright

2007 Elsevier Inc. All rights reserved.

[46] Maria Viklander. Dissolved and particle-bound substances in urban snow. Water

Science and Technology, 39(12):27–32, 1999. Compilation and indexing terms,

Copyright 2007 Elsevier Inc. All rights reserved.

[47] C. B. Amphlett. Inorganic Ion Exchange. Elsevier Publishing Company, Amster-

dam/London/New York, 1969. ID: 77.

[48] M. A. Tabatabai and D. L. Sparks. Chemical Processes in Soils. Soil Science

Society of America Inc, Madison, WI, 2005. ID: 78.

[49] J. B. Shanley. Effects of ion exchange on stream solute fluxes in a basin receiving

highway deicing salts. Journal of environmental quality, 23(-):977–986, 1994. ID:

28.

[50] C. F. Mason, S. A. Norton, I. J. Fernandez, and L. E. Katz. Deconstruction of the

chemical effects of road salt on stream water chemistry. Journal of environmental

quality, 28(-):82–91, 1999.

[51] D. O. Rosenberry, P. A. Bukaveckas, D. C. Buso, G. E. Likens, A. M. Shapiro,

and T. C. Winter. Movement of road salt to a small new hampshire lake. Water,

Air and Soil Pollution, 109:179–206, 1999.

[52] N. J. Warrence, K. E. Pearson, and J. W. Bauder. Basics of soil salinity and

sodicity effects on soil physical properties [online], 2003. ID: 65.

[53] K. B. Krauskopf and D. K. Bird. Introduction to geochemistry, volume 3rd ed;

3rd ed. McGraw-Hill, New York, 1995. ID: 67.

137

[54] C. R. Ellis, J. Champlin, and H. G. Stefan. Density current intrusions in an

ice-covered urban lake. Journal of the American Water Resources Association,

33(6):1363–1374, 1997. ID: 24.

[55] R. G. Wetzel. Limnology Lake and River Ecosystems. Academic Press, London,

United Kingdom, 3rd edition, 2001.

[56] W. S. Scott. Road de-icing salts in an urban stream and flood control reservoir.

Water Resources Bulletin, 15(-):1733–1742, 1979.

[57] B. M. Free and G. C. Mulamoottil. The limnology of lake wabukayne, a stormwater

impoundment. Water Resources Bulletin, 19(5):821–827, 1983.

[58] T. Mayer, J. Marasalek, and E. Delos Reyes. Nutrients and metal contaminants

status of urban stormwater detention ponds. Lake and Reserv. Management,

12(3):348–368, 1996.

[59] M. S. Evans and C. Frick. The effects of road salts on aquatic ecosystems. Tech-

nical report, Environment Canada Health Canada, 2001.

[60] A. Sander, E. V. Novotny, O. Mohseni, and H. G. Stefan. Inventory of road salt

use in the minneapolis/st. paul metropolitan area. Report Proj. Report No 503,

St. Anthony Falls Laboratory, University of Minnesota, 2007.

[61] D. M. Ramakrishna and T. Viraraghocan. Environmental impact of chemical

deicers - a review. Water, Air and Soil Pollution, 166:49–63, 2005.

[62] D. Bastviken, P. Sanden, T. Svensson, C. Stahlberg, M. Magounakis, and

G. Oberg. Chloride retention and release in a boreal forest soil: Effects of soil

water residence time and nitrogen and chloride loads. Environmental science and

technology, 40(9):2977–2982, 05/01 2006.

[63] T. Svensson, P. Sanden, D. Bastviken, and G. Oberg. Chlorine transport in a small

catchment in southeast sweden during two years. Biogeochemistry, 82:181–199,

2007.

[64] P. H. Jones and B. A. Jeffrey. Environmental impact of road salting. Chemical

Deicers and the Environment. Lewis Publishing, Boca Raton, FL, 1992.

138

[65] K. W. F. Howard and H. Maier. Road de-icing salt as a potential constraint

on urban growth in the greater toronto area, canada. Journal of contaminant

hydrology, 91(1-2):146–170, 2007.

[66] W. J. Andrews, A. L. Fong, L. Harrod, and M. E. Dittes. Water quality assessment

of part of the upper mississippi river basin, minnesota and wisconsin - ground

water quality in an urban part of the twin cities metropolitan area, minnesota,

1996. Technical Report Water-Resources Investigations Report 97-4248, United

State Geological Survey, Reston, VA, 1997.

[67] W. J. Andrews, J. R. Stark, A. L. Fong, and J. D. Fallon. Water quality assessment

of part of the upper mississippi river basin, minnesota and wisconsin - water

quality along a flow system in the twin cities metropolitan area, minnesota 1997-

98. Technical Report Water-Resources Investigations Report 2005-5120, United

State Geological Survey, Reston, VA, 2005.

[68] G. S. Bowen and M. J. Hinton. The temporal and spatial impacts of road salt

on streams draining the greater toronto area. pages 303–310. Canadian Water

Resources Association, December 2-4 1998 1998.

[69] A. Fong. Water-quality assessment of part of the upper mississippi river basin,

minnesota and wisconsin - ground-water quality in three different land-use ar-

eas 1996-1998. Technical Report Water-Resources Investigations Report 00-4131,

United State Geological Survey, Reston, VA, 2000.

[70] V. R. Kelly, G. M. Lovett, K. C. Weathers, S. E. G. Findlay, D. L. Strayer, D. J.

Burns, and G. E. Likens. Long-term sodium chloride retention in a rural water-

shed: Legacy effects of road salt on streamwater concentration. Environmental

Science and Technology, 42(2):410–415, 2008.

[71] E. V. Novotny, D. Murphy, and H. G. Stefan. Increase of urban lake salinity by

road deicing salt. Science of The Total Environment,, 406(1-2):131–144, 11/15

2008.

139

[72] R. C. Bubeck, W. H. Diment, B. L. Deck, A. L. Baldwin, and S. D. Lipton.

Runoff of deicing salt: Effect on irondequoit bay, rochester, new york. Science,

172(3988):1128–1132, Jun. 11 1971.

[73] K. W. F. Howard and P. J. Beck. Hydrogeochemical implications of groundwater

contamination by road de-icing chemicals. Journal of contaminant hydrology,

12:245–268, 1993.

[74] E. E. Huling and T. C. Hollocher. Groundwater contamination by road salt:

Steady-state concentrations in east central massachusetts. Science, 176(4032):288–

290, 1972.

[75] O. Ruth. The effects of de-icing in helsinki urban streams, southern finland. Water

Science and Technology, 48(9):33–43, 2003.

[76] G. M. Wulkowicz and Z. A. Saleem. Chloride balance of an urban basin in the

chicago area. Water Resources Research, 10(5):974–982, 1974.

[77] Metropolitan Council. Twin cities region population and households estimated

2007. Technical report, St. Paul, MN, 2007.

[78] Minnesota Climate Work Group. Minneapolis/st. paul metro area snow resources.

Technical report, St. Paul, MN, 2008.

[79] D. S. Kostick. Salt. Report, United States Geological Survey, 2004.

[80] National Atmospheric Deposition Program. Napd/ntn monitoring location mn01,

2008.

[81] Metropolitan Council. Estimate number of septic systems by community for 1997.

[82] R. J. Wilson. A chloride budget for olmsted county minnesota: A mass balance

approach in an environment dominated by anthropogenic sources, typical of the

temperate us midwest. Master’s thesis, Minnesota State University, 2007.

[83] G. Blomqvist and Eva-Lotta Johansson. Airborne spreading and deposition of de-

icing salt - a case study. The Science of The Total Environment, 235(1-3):161–168,

9/1 1999.

140

[84] D. Bastviken, F. Thomsen, T. Svensson, S. Karlsson, P. Sanden, G. Shaw,

M. Matucha, and G. Oberg. Chloride retention in forest soil by microbial up-

take and by natural chlorination of organic matter. Geochimica Cosmochimica

Acta, 71:3182:3192, 2007.

[85] M. L. Bester, E. O. Frind, J. W. Molson, and D. L. Rudolph. Numerical investi-

gation of road salt impact on an urban wellfield. Ground Water, 44(2):165–175,

2006.

[86] E. V. Novotny and H. G. Stefan. A 0-d modeling approach to study long-term

chloride concentration in lakes receiving runoff containing road salt. Water Air

Soil Pollution, In review, 2009.

[87] R. C. Bubeck and R. S. Burton. Changes in chloride concentrations, mixing

patterns, and stratification characteristics of irondequoit bay, monroe county, new

york, after decreased use of road-deicing salts, 1974-84. Technical report, 1989.

ID: 50.

[88] J. Judd. Lake stratification caused by runoff from street deicing. Water research,

4:521–532, 1970.

[89] E. B. Swain. The paucity of blue-green algae in meromictic Brownie lake: iron

limitation or heavy metal toxicity? PhD thesis, University of Minnesota - Twin

Cities, 1984.

[90] B. Tracey, N. Lee, and V. Card. Sediment indicators of meromixis: comparison of

laminations, diatoms, and sediment chemistry in brownie lake, minneapolis, usa.

Journal of Paleolimnology, 15:129–132, 1996.

[91] YSI. Model 63 Operations Manual, 1999.

[92] D. Murphy and H. G. Stefan. Seasonal salinity cycles in eight lakes of the min-

neapolis/st. paul metropolitan area. Technical report, St. Anthony Falls Labora-

tory, 2006.

141

[93] E. V. Novotny, D. Murphy, and H. G. Stefan. Salty lakes in minnesota. Tech-

nical Report Proj. Report No 505, St. Anthony Falls Laboratory, University of

Minnesota, Minneapolis, MN, 2007.

[94] E. Gorham, W. E. Dean, and J. E. Sanger. The chemical composition of lakes in

the north-central united states. Technical Report 82-149, United States Depart-

ment of the Interior, Washington, D.C., 1982.

[95] Minnesota Pollution Control Agenct. Minnesota lake water quality assessment

data 2004. Technical report, MPCA, St. Paul, MN, 2004.

[96] G. E. Hutchinson. A Treatise on Limnology - Chemistry of Lakes. John Wiley

and Sons, New York, NY, 1st edition, 1975.

[97] E. L Thunqvist. Increased chloride concentration in a lake due to deicing salt

application. Water Science and Technology, 48(9):51–59, 2003.

[98] E. Gorham and F. M. Boyce. Influence of lake surface area and depth upon

thermal stratification and the depth of the summer thermocline. Journal of Great

Lakes Research, 15(2):233–245, 1989.

[99] M. Hondzo and H. G. Stefan. Regional water temperature characteristics of lakes

subjected to climate change. Climatic Change, 24(3):187–211, 1993.

[100] H. G. Stefan and X. Fang. Model simulations of dissolved oxygen characteristics

of minnesota lakes: past and future. Environmental management, 18(1):73, 1994.

[101] R. W. Sadecki. Chloride lake study. Technical report, Minnesota Department of

Transportation, St. Paul, MN, 1989.

[102] I. T. Webster, S. J. Norquay, F. C. Ross, and R. A. Wooding. Solute exchange

by convection within estuarine sediments. Estuarine, Coastal and Shelf Science,

42(2):171–183, 2 1996.

[103] C. T. Simmons, T. R. Fenstemaker, and J. M. Sharp. Variable-density groundwa-

ter flow and solute transport in heterogeneous porous media: approaches, resolu-

tions and future challenges. Journal of Contaminant Hydrology, 52(1-4):245–275,

11 2001.

142

[104] C. T. Simmons, K. A. Narayan, and R. A. Wooding. On a test case for density-

dependent groundwater flow and solute transport models: The salt lake problem.

Water Resources Research, 35(12):3607–3620, 1999.

[105] C. T. Simmons and K. A. Narayan. Mixed convection processes below a saline

disposal basin. Journal of Hydrology, 194(1-4):263–285, 1997.

[106] R. A. Wooding, S. W. Tyler, and I. White. Convection in groundwater below an

evaporating salt lake: 1. onset of instability. Water Resources Research, 33:1199–

1217, 1997.

[107] J. D. Manous Jr, C. J. Gantzer, and H. G. Stefan. Spatial variation of sediment

sulfate reduction rates in a saline lake. Journal of Environmental Engineering,

133(12):1106–1116, 2007.

[108] S. S. Dixit, J. P. Smol, D. F. Charles, R. M. Hughes, S. G. Paulsen, and G. B.

ollins. Assessing water quality changes in the lakes of the northeastern united

states using sediment diatoms. Canadian Journal of Fisheries and Aquatic Sci-

ences, 56:131–152, 1999.

[109] T. B. Bridgeman, C. D. Wallace, G. S. Carter, R. Carvaial, L. C. Schiesari,

S. Aslam, E. Cloyd, E. Elder, A. Field, K. L. Schulz, P. M. Yurista, and G. W.

Kling. A limnological survey of third sister lake, michigan with historical compar-

isons. Journal of Lake and REservoir Management, 16:253–267, 2000.

[110] M. L. tuchman, E. F. Stoermer, and H. J. Carney. Effects of increased salinity on

the diatom assemblage in fonda lake, michigan. Hydrobiologia, 109:179–188, 1984.

ID: 43.

[111] W. J. Birge, J. A. Black, A. G. Westerman, T. M. Short, S. B. Taylor, D. M.

Bruser, and E. D. Wallingford. Recommendations on numerical values for regu-

lating iron and chloride concentrations for the purpose of protecting warm water

species of aquatic life in the commonwealth of kentucky. Technical Report Memo-

randum of Agreement No. 5429, Kentucky Natural Resources and Environmental

Protection Cabinet, 1985.

143

[112] E. V. Novotny, A. Sander, O. Mohseni, and H. G. Stefan. Chloride ion trans-

port and mass balance in a metropolitan area using road salt. Water Resources

Research, Under Review, 2009.

[113] S. Chapra. Total phosphorus model for the great lakes. Journal of Environmental

Engineering, 103:147–161, 1978.

[114] W. C. Songzogni, S. Chapra, D. E. Armstrong, and T. J. Logan. Bioavailability

of phosphorus inputs to lakes. Jounral Environmental Quality, 11:555–563, 1982.

[115] M. Seeley. Climate trends: what are some implications for minnesota’s air and

water resources? minnesota mpca presentation st. paul, mn. nov. 18, 2003.

[116] T. R. Karl and R. W. Knight. Secular trends of precipitation amount, frequency,

and intensity in the usa. Bulletin of the American Meteorological Society, 79:231–

241, 1998.

[117] Metropolitan Council.

[118] A. Lundmark. Predicting environmental impact of deicing salt - a modeling ap-

proach. Technical report, 2003. ID: 38.

[119] Dennis E. Ford and H. Stefan. Stratification variability in three morphomet-

rically different lakes under indentical meteorological forcing. Journal of the

American Water Resources Association, 16(2):243–247, 1980. 10.1111/j.1752-

1688.1980.tb02385.x.

[120] M. Hondzo and H. G. Stefan. Lake water temperature simulation model. Journal

of Hydraulic Engineering, 119(11):1251–1273, 1993.

[121] H. Stefan and D. E. Ford. Temperature dynamics in dimictic lakes. Journal of

Hydraulics Division, 101(1):97–114, January 1975 1975.

[122] Xing Fang and Heinz G. Stefan. Long-term lake water temperature and ice cover

simulations/measurements. Cold Regions Science and Technology, 24(3):289–304,

1996. Compilation and indexing terms, Copyright 2008 Elsevier Inc.

144

[123] J. Imberger and C. Patterson. Physical Limnology, pages 303–475. Advances in

Applied Mechanics. Acedemic Press, 1990.

[124] MDNR. Tanners lake information report. Technical report,

Minnesota Department of Natural Resources, St. Paul, MN.

http://www.dnr.state.mn.us/lakefind/showreport.html?downum=82011500.

June 25, 2009, 2009.

[125] R W Schmitt. Double diffusion in oceanography. Annual Review of Fluid Me-

chanics, 26(1):255–285, 11 2003.

[126] J. E. Edinger, D. K. Brady, and J. C. Geyer. Heat exchange and transport

in the environment. report no. 14. Technical Report NP-2900127; Other: ON:

DE82900127 United StatesOther: ON: DE82900127Thu Feb 07 04:39:53 EST

2008NTIS, PC A07/MF A01.TIC; ERA-07-019683; EDB-82-042345English, 1974.

[127] HG Stefan and JJ Cardoni. Model of light penetration in a turbid lake. Water

Resources Research, 19(1):109–120, February 1983 1974.

[128] J. M. K. Dake and D. R. F. Harleman. Thermal stratification in lakes:analysis

and laboratory studies. Water Resources Research, 5(2):404–495, 1969.

[129] D. M. Robertson and J. Imberger. Lake number, a quantitative indicator of mixing

used to estimate changes in dissolved oxygen. Internationale Revue der gesamten

Hydrobiologie und Hydrographie, 79:159–176, 1994.

[130] Jose R. Romero and John M. Melack. Sensitivity of vertical mixing in a large

saline lake to variations in runoff. Limnology and Oceanography, 41(5):955–965,

1996.

[131] J. Imberger and J. C. Patterson. Transport models for inland and coastal wa-

ters, chapter A Dynamic reservoir simulation model, DYRESM, pages 310–361.

Academic Press, 1981.

[132] A. E. Greenberg, L. S. Clesceri, and D. E. Eaton. Standard Methods: For the

Examination of Water and Wastewater. American Public Health Association,

145

American Water Works Association, Water Environment Ferderation, 18 edition,

1992.

[133] D. E. Ford and H. G. Stefan. Thermo prediction using integral energy model.

Journal of Hydraulics Division, 106(1):39–55, 1980.

[134] Xing Fang. Modeling of dissolved oxygen stratification dynamics in Minnesota

Lakes under different climate scenarios. Phd, University of Minnesota - Twin

Cities, Minneapolis, MN, May 1994.

[135] Xing Fang and Heinz G. Stefan. Interaction between oxygen transfer mechanisms

in lake models. Journal of Environmental Engineering, 121(6):447–454, 1995.

Compilation and indexing terms, Copyright 2008 Elsevier Inc.

[136] S. W. Zison, W. B. Mills, D. Diemer, and C. W. Chen. Rates, constants and

kinetic formulations in surface water quality modeling. Technical Report EPA-

600-3-78-105, Tetra Tech, Inc for U.S. Environmental Protection Agency, Athens,

Georgia, 1978.

[137] MCWG (Minnesota Climatology Working Group). Minnesota’s Lake Ice-Out Sta-

tus, May 19, 2009. Minnesota Climatology Working Group. St. Paul, MN., 2009.

[138] T. Mayer, Q. Rochfort, U. Borgmann, and W. Snodgrass. Geochemistry and

toxicity of sediment porewater in a salt-impacted urban stormwater detention

pond. Environmental Pollution, 156(1):143–151, 11 2008.

[139] C. H. Mortimer. The exchange of dissolved substances between mud and water

in lakes. J. Ecol., 29:280–329, 1941.

[140] C. H. Mortimer. Chemical exchanges between sediments and water in the great

lakes - speculation on probable regulatory mechanisms. Limnology and Oceanog-

raphy, 16:387–404, 1971.

Appendix A

Data Sets

146

Brownie LakeC = Measured Conductivity (υS/cm)T = Temperature (oC)SC = calculated specific conductance (υS/cm)Depth

(m) C T SC C T SC C T SC C T SC C T SC C T SC C T SC0 343 1.4 625 245.2 0 469 515 13.9 654 713 21.7 761 541 26.1 530 475 15.8 576 471 6.2 735

-0.5 250.7 0 480 514 14 651 705 21.3 759 537 25.9 528 475 15.8 576 471 6.2 735-1 380 3.9 637 265.8 0.2 505 514 14 651 701 21.1 757 535 25.7 528 474 15.7 576 471 6.1 737

-1.5 372.2 0.4 702 513 13.8 653 693 20.7 755 533 25.5 528 472 15.7 574 470 6.1 736-2 397 4.3 657 491.6 0.5 924 514 13.5 659 691 20.5 756 542 25.1 541 468 15.6 570 470 6.1 736

-2.5 447 4.5 734 638 1.4 1162 658 12.3 869 720 19.6 803 574 24.5 580 469 15.5 573 470 6.1 736-3 593 4.7 969 782 2.7 1362 967 9.6 1370 968 15.7 1177 604 23.4 623 470 15.5 574 469 6.1 734

-3.5 656 4.7 1071 861 3.9 1442 1145 7.5 1720 1293 10.8 1774 647 22.7 677 470 15.4 576 468 6 735-4 743 4.7 1214 946 4 1580 1200 6.3 1867 1316 9.4 1875 679 22.1 719 470 15.4 576 467 5.9 735

-4.5 830 4.7 1356 1048 4.1 1744 1241 5.6 1972 1336 7.3 2018 755 20.9 819 472 15.4 578 467 5.9 735-5 907 4.8 1477 1130 4.2 1875 1312 5.2 2110 1379 6.3 2145 923 18.2 1061 484 15.3 594 467 5.9 735

-5.5 970 4.8 1579 1200 4.3 1985 1346 5 2178 1428 6 2241 1271 14.1 1605 766 14.6 956 467 5.9 735-6 1080 4.9 1753 1300 4.3 2150 1424 5 2304 1482 5.7 2347 1500 10.7 2064 1546 12.1 2051 513 6 805

-6.5 1290 5.3 2068 1415 4.4 2333 1560 5.2 2509 1565 5.7 2479 1590 8.3 2335 1666 10.3 2316 1535 7.4 2312-7 1493 5.9 2350 1512 4.7 2469 1652 5.5 2632 1683 5.8 2658 1664 7.5 2499 1762 8.4 2580 1782 8.3 2617

-7.5 1646 6.7 2530 1650 5.2 2654 1727 5.6 2744 1773 6 2783 1738 6.9 2656 1832 7.5 2752 1872 8.1 2764-8 1805 7.2 2735 1783 5.8 2816 1796 5.8 2836 1855 6.2 2894 1817 6.8 2785 1900 7 2895 1947 8 2883

-8.5 1892 7.4 2850 1884 6.3 2931 1902 6.2 2968 1935 6.5 2992 1889 6.8 2896 1954 6.8 2995 2004 7.8 2984-9 1990 7.6 2981 1985 6.6 3061 1984 6.4 3077 2017 6.7 3101 1984 6.9 3032 2028 6.8 3109 2063 7.7 3081

-9.5 2050 7.8 3053 2065 6.9 3156 2044 6.6 3152 2081 6.9 3181 2056 7.1 3124 2099 6.9 3208 2124 7.7 3172-10 2118 8 3136 2132 7.1 3240 2123 6.8 3254 2152 7 3279 2130 7.4 3209 2156 7.1 3276 2162 7.8 3220

-10.5 2155 8.1 3182 2161 7.2 3274 2161 7 3293 2190 7.3 3309 2182 7.5 3278 2201 7.3 3325 2200 8 3258-11 2190 8.1 3234 2198 7.3 3321 2198 7.2 3330 2221 7.4 3346 2206 7.6 3304 2224 7.5 3341 2218 8.1 3275

-11.5 2202 8.2 3242 2223 7.4 3349 2227 7.3 3364 2239 7.6 3354 2229 7.8 3320 2236 7.6 3349 2230 8.2 3284-12 2225 8.3 3267 2243 7.4 3379 2244 7.4 3380 2250 7.7 3360 2230 7.9 3312 2253 7.6 3374 2247 8.3 3299

-12.5 2249 8.4 3293 2260 7.5 3395 2259 7.5 3393 2260 7.7 3375 2253 8 3336 2263 7.7 3380 2264 8.4 3315-13 2264 8.5 3306 2293 7.6 3434 2281 7.5 3426 2278 7.8 3393 2263 8 3351 2283 7.8 3400 2281 8.5 3331

-13.5 2273 8.6 3310 2281 7.7 3407 2285 7.6 3422 2270 7.8 3381 2269 8.1 3351 2296 7.9 3410 2309 8.6 3362-14 2300 8.7 3340 2285 7.6 3422 2191 7.7 3272 2238 8.1 3305 2306 8 3415 1922 8.8 2783

-14.5 2287 7.6 3425 1979 8.2 2914

11/6/069/24/061/14/06 2/25/06 5/6/06 6/13/06 8/8/06

C T SC C T SC C T SC C T SC C T SC C T SC C T SC C T400 0.9 741 380 9 547 640 21.1 692 505 18.1 582 376 6.4 583 282 0.1 538 195 0.2 370 435 10.9432 1.7 778 378 8.5 552 640 21.1 692 505 18.1 582 376 6.4 583 287 0.5 539 233 0.1 444 436 10.9449 2.9 777 373 8.5 545 621 19.8 689 505 18.1 582 375 6.3 583 321 1.7 578 422 2.1 750 457 10.4459 3.4 781 370 8.1 546 612 19.3 687 500 17.7 581 374 6.3 582 394 2.7 686 464 3 800 472 8.4471 4 786 414 8 613 612 18.4 700 495 17.3 580 374 6.3 582 402 3.1 691 533 3.4 907 666 7472 4 788 654 6.1 1023 647 15.9 783 494 17.2 580 374 6.2 584 438 3.4 746 649 3.4 1105 807 6.4544 4 908 829 5.8 1309 804 12.2 1064 494 17.2 580 374 6.2 584 511 3.5 867 720 3.4 1226 922 5.1614 4.5 1009 893 5.1 1441 926 9.4 1319 494 17.1 582 374 6.2 584 586 3.6 991 825 3.4 1404 986 4.5684 4.6 1121 940 5.1 1516 1009 7.4 1520 501 17 591 373 6.2 582 698 3.7 1177 891 3.4 1517 1048 4.1773 4.7 1263 983 5.1 1586 1038 6.8 1591 539 16.8 639 373 6.2 582 770 3.7 1298 956 3.4 1627 1120 4845 4.6 1384 1012 5.2 1627 1071 6.5 1656 1128 14.3 1418 373 6.2 582 853 3.7 1438 1036 3.5 1758 1226 4906 4.7 1480 1007 5.5 1605 1152 6.2 1797 1304 12.4 1717 373 6.2 582 950 3.8 1596 1127 3.7 1900 1276 4.1

1070 4.9 1737 1143 5.8 1805 1233 6.3 1918 1408 9.7 1989 375 6.2 585 1074 4 1793 1174 3.8 1973 1383 4.31280 5.4 2046 1293 6.8 1982 1409 6.5 2179 1518 8.1 2242 1300 7.2 1970 1318 4.2 2187 1306 4 2181 1442 4.51595 5.8 2519 1500 7 2286 1566 6.8 2400 1626 7.2 2464 1616 8.1 2386 1502 5.1 2423 1514 4.8 2465 1536 4.71740 6.1 2723 1667 7.4 2511 1749 7.1 2658 1749 6.9 2673 1774 7.7 2649 1630 5.6 2590 1658 5.4 2650 1641 5.21872 6.5 2895 1775 7.6 2659 1860 7.4 2802 1844 6.8 2827 1854 7.4 2793 1820 6.4 2823 1819 5.9 2864 1845 5.81940 6.8 2974 1908 7.8 2841 1954 7.7 2918 1919 6.8 2942 1918 7.2 2906 1924 6.7 2958 1910 6.3 2971 1893 6.32052 7 3127 1986 8 2941 2034 8.2 2995 2004 6.9 3063 2009 7.1 3053 2030 7 3094 1992 6.6 3071 1986 6.62119 7.1 3220 2058 8.1 3039 2105 8.6 3065 2089 7 3183 2054 7.1 3121 2087 7.1 3171 2050 6.9 3133 2071 6.92158 7.2 3270 2120 8.3 3113 2138 8.8 3096 2131 7.1 3238 2130 7.2 3227 2138 7.2 3239 2122 7 3234 2124 7.12186 7.2 3312 2148 8.4 3145 2181 9.2 3124 2175 7.2 3295 2162 7.3 3266 2161 7.2 3274 2160 7.2 3273 2174 7.32210 7.3 3339 2178 8.5 3180 2210 9.4 3148 2189 7.3 3307 2178 7.3 3290 2188 7.3 3305 2184 7.3 3299 2198 7.42237 7.5 3360 2212 8.6 3221 2225 9.5 3161 2206 7.4 3323 2194 7.4 3305 2205 7.4 3322 2202 7.4 3317 2219 7.52258 7.4 3401 2227 8.5 3252 2235 9.7 3158 2220 7.5 3335 2200 7.4 3314 2219 7.4 3343 2216 7.4 3338 2239 7.62275 7.5 3417 2249 8.8 3257 2235 7.5 3357 2225 7.5 3342 2233 7.5 3354 2234 7.4 3365 2248 7.62300 7.6 3445 2271 8.8 3289 2241 7.5 3366 2235 7.5 3357 2255 7.6 3377 2241 7.5 3366 2251 7.72013 7.7 3006 2296 8.8 3325 2241 7.5 3366 2249 7.6 3368 2280 7.6 3415 2265 7.5 3402 2255 7.7

2200 8.8 3186 2253 7.6 3374 2269 7.7 3389 2295 7.7 3428 2207 7.7 3296 2262 7.72161 7.7 3227 1890 7.8 2815 1932 7.8

2/21/07 4/1/07 5/17/07 9/17/07 11/15/07 2/7/08 3/14/08 4/22/08

SC C T SC C T SC595 771 17.1 908 988 23.4 1019597 771 17.1 908 992 23.4 1023634 771 17.1 908 992 23.5 1021691 766 17 904 992 23.5 1021

1015 856 16.3 1027 989 23.4 10201252 1058 14.9 1311 1005 23 10451487 1074 11.3 1455 1060 22 11241621 1127 9 1623 1161 19.6 12951744 1159 6.4 1798 1274 15.8 15461870 1192 5.2 1917 1371 12.2 18152047 1230 4.8 2003 1430 9.3 20422124 1285 4.7 2099 1436 7.8 21392287 1658 4.7 2708 1478 6.6 22792370 1430 4.8 2328 1537 6.1 24052509 1537 5.1 2479 1667 6.1 26092639 1682 5.5 2680 1745 6.1 27312913 1809 5.9 2848 1839 6.2 28692945 1886 6.2 2943 1945 6.5 30083062 1985 6.5 3070 2011 6.6 31013165 2042 6.7 3139 2084 6.8 31943227 2084 6.9 3185 2132 7 32493284 2161 7.1 3284 2172 7.1 33003311 2180 7.2 3303 2197 7.3 33193333 2188 7.3 3305 2206 7.4 33233354 2199 7.3 3322 2216 7.4 33383367 2211 7.4 3331 2235 7.4 33673362 2215 7.4 3337 2245 7.5 33723368 2216 7.5 3329 2248 7.5 33773378 2215 7.5 3327 1979 7.6 29642877

4/22/08 5/30/08 8/15/08

Bryant LakeC = Measured Conductivity (υS/cm)T = Temperature (oC)SC = calculated specific conductance (υS/cm)Depth

(m) C T SC C T SC C T SC C T SC C T SC C T SC C T SC C T SC0 274 0.8 510 280 0.8 521 419 14 530 510 23 530 524 27.4 501 441 16.4 528 320 6.5 495 310 1 572

-0.5 289 2.3 510 298 1.1 548 419 14 530 510 23 530 526 27.3 504 441 16.3 529 322 6.3 501 329 1.7 593-1 292 2.7 509 310 3 535 418 13.9 530 509 22.9 530 526 27.2 505 441 16.3 529 324 6.2 506 345 2.9 597

-1.5 293 3 505 313 3.2 536 418 13.9 530 508 22.8 530 525 27.1 505 441 16.3 529 324 6.1 507 348 3.3 594-2 294 3.1 505 313 3.3 535 418 13.9 530 507 22.7 530 524 27 505 440 16.2 529 330 6.1 516 348 3.3 594

-2.5 294 3.1 505 313 3.4 533 418 13.8 532 501 22 531 523 27 504 440 16.2 529 331 6 520 349 3.4 594-3 294 3.1 505 314 3.5 533 418 13.8 532 497 21.6 532 523 27 504 439 16.2 528 331 6 520 349 3.4 594

-3.5 296 3.2 507 315 3.5 534 417 13.8 530 497 21.4 534 523 26.7 507 440 16.1 530 331 6 520 349 3.5 592-4 296 3.2 507 315 3.7 531 417 13.7 532 497 21.3 535 522 26.3 509 440 16.2 529 332 6 521 349 3.5 592

-4.5 299 3.3 511 319 3.7 538 417 13.8 530 495 21.1 535 532 25 532 439 16.2 528 333 5.9 524 351 3.6 594-5 303 3.4 516 322 3.8 541 416 13.7 530 492 20.6 537 540 23.8 553 439 16.1 529 335 5.9 527 356 3.9 596

-5.5 305 3.4 519 326 3.8 548 414 13.2 534 465 16.5 555 537 22.3 566 438 16.1 528 335 5.9 527 357 4 596-6 307 3.4 523 330 3.8 555 412 13 535 445 15 550 511 19.8 567 438 16 529 334 5.8 527 360 4.1 599

-6.5 310 3.4 528 335 3.9 561 413 12.8 538 440 14 557 501 16.4 599 436 15.9 528 334 5.8 527 360 4.1 599-7 314 3.4 535 347 3.9 581 406 10.5 562 437 13.1 566 492 15.3 604 436 15.8 529 335 5.8 529 363 4.1 604

-7.5 317 3.4 540 347 3.9 581 397 9.3 567 427 11.1 581 479 13.1 620 436 15.8 529 334 5.7 529 364 4.1 606-8 322 3.5 546 354 3.9 593 394 9 567 433 10.7 596 485 11.7 650 436 15.8 529 334 5.7 529 365 4.2 606

-8.5 327 3.5 555 361 3.8 607 387 8 573 442 9.8 623 494 10.8 678 441 15.5 539 335 5.6 532 368 4.2 611-9 334 3.5 567 370 3.8 622 454 9 654 495 9.8 697 491 14.2 619 335 5.6 532 374 4.2 621

-9.5 341 3.6 577 379 3.8 637 457 8.3 671 497 9.3 710 536 11 732 334 5.5 532 380 4.2 630-10 344 3.6 582 405 3.8 681 469 7.6 702 502 8.7 729 532 10 746 333 5.4 532 388 4.2 644

-10.5 360 3.7 607 427 3.9 715 478 7.3 722 515 7.9 765 537 9.5 763 333 5.4 532 400 4.2 664-11 378 3.7 637 453 4 756 481 7 733 522 7.8 777 537 9.2 769 333 5.4 532 409 4.3 676

-11.5 378 3.9 633 458 4.3 757 502 6.8 769 540 8.9 780 334 5.4 534 428 4.3 708-12 587 8.6 855 335 5.4 535 440 4.3 728

-12.5 335 5.5 534 440 4.4 725-13 426 6 669 465 4.5 764

11/8/06 2/21/079/24/061/21/06 2/26/06 5/5/06 6/14/06 8/8/06

C T SC C T SC C T SC C T SC C T SC C T SC C T SC C T SC366 7.4 551 519 18.9 587 584 25.1 583 487 18.5 556 362 5.8 572 253 0 484 288 0.7 537 386 7.4 581363 7.3 548 518 18.8 588 584 25.1 583 487 18.3 558 362 5.8 572 257 0.3 487 322 0.7 601 386 7.4 581363 7.2 550 518 18.7 589 584 25.1 583 487 18.3 558 361 5.8 570 280 1 517 361 1.4 657 385 7.3 582361 7.1 549 516 18.6 588 583 25 583 487 18.3 558 361 5.8 570 339 1.8 609 365 2 651 384 7.2 582361 7 550 515 18.6 587 582 25 582 487 18.3 558 361 5.8 570 352 1.8 632 368 2.2 652 384 7.1 583360 6.8 552 508 18 586 582 25 582 486 18.2 559 361 5.8 570 354 1.8 636 368 2.3 650 384 7.1 583357 6.6 550 505 17.7 587 577 24.5 583 486 18.1 560 361 5.8 570 355 1.9 635 368 2.3 650 384 7.1 583357 6.6 550 505 17.6 588 575 24.4 582 485 18.1 559 361 5.8 570 355 1.9 635 368 2.4 647 384 7.1 583359 6.5 555 504 17.6 587 573 24.2 582 485 18 560 361 5.8 570 357 2 637 369 2.5 647 384 7.1 583357 6.6 550 503 17.5 587 575 24.1 585 485 18 560 361 5.8 570 358 2.2 634 370 2.6 647 384 7 585357 6.6 550 499 17.1 588 573 24.1 583 485 18 560 361 5.8 570 358 2.4 630 374 2.7 651 384 7 585357 6.6 550 488 16 589 570 23.6 586 484 17.9 560 361 5.8 570 364 2.4 640 377 2.8 655 384 7 585357 6.5 552 476 15.2 586 557 21.2 601 483 17.9 559 361 5.8 570 366 2.6 640 380 2.9 658 384 7 585357 6.5 552 459 13.5 588 535 18.5 611 483 17.8 560 361 5.8 570 366 2.6 640 381 3 657 385 7 587357 6.6 550 444 12.3 586 497 15.5 607 482 17.7 560 361 5.8 570 368 2.7 641 383 3 661 385 7 587357 6.5 552 424 10.6 585 479 14.2 603 482 17.5 563 361 5.8 570 371 2.8 644 387 3.1 665 432 5.2 695358 6.5 554 406 9.3 580 461 12.4 607 482 17.4 564 361 5.8 570 373 2.8 648 389 3.1 669 435 4.9 706359 6.5 555 397 8.2 585 440 10.5 609 490 16.2 589 361 5.8 570 376 2.9 651 392 3.1 674 442 4.6 724362 6.2 565 392 7.8 584 426 9.5 605 510 14.2 643 361 5.8 570 378 3 652 394 3.2 675 465 4.4 767363 6.4 563 387 7.4 583 418 9 602 482 11.2 655 361 5.8 570 380 3 655 396 3.2 679 494 4.2 820387 6.1 606 384 7.2 582 413 8.5 603 473 10.3 658 361 5.8 570 383 3 661 402 3.2 689 521 3.8 876412 5.6 655 383 7.1 582 410 7.9 609 465 9.5 661 361 5.8 570 387 3.1 665 410 3.3 700 580 3.8 975446 5.1 719 381 6.9 582 408 7.7 609 463 9 667 361 5.7 572 391 3.2 670 418 3.3 714 595 3.8 1000497 4.7 812 380 6.7 584 410 7.4 618 461 8.7 669 361 5.7 572 398 3.2 682 429 3.4 730 607 3.8 1020554 4.7 905 382 6.6 589 416 7.2 630 462 8.5 675 361 5.7 572 407 3.3 695 439 3.4 747 622 3.8 1045592 4.6 970 383 6.6 591 419 7.2 635 462 8.4 676 361 5.7 572 417 3.3 712 453 3.5 769 635 3.9 1064622 4.7 1016 403 6.6 621 483 7.1 734 516 8.1 762 408 6 640 457 3.3 780 474 3.6 802 640 4 1069

4/1/07 5/17/07 7/13/07 9/17/07 11/15/07 2/7/08 3/14/08 4/22/08

C T SC C T SC521 16.8 618 606 24.6 611521 16.8 618 606 24.6 611521 16.8 618 606 24.6 611520 16.8 617 605 24.6 610520 16.8 617 605 24.6 610520 16.8 617 606 24.6 611519 16.7 617 606 24.5 612519 16.7 617 606 24.5 612518 16.6 617 606 24.2 615517 16.5 617 605 24.1 616515 16.3 618 603 24 615514 16.2 618 601 23.7 616504 15 623 596 22.2 630484 13 628 591 20.7 644476 12 633 576 17.6 671468 11.3 634 557 15.7 677463 10.5 640 542 13.9 688460 9.7 650 537 12.5 705466 9.2 667 533 11.1 726463 8.7 672 529 10.3 736462 8.6 673 529 10 741474 8.1 700 533 9.5 757524 7.3 792 542 9 781552 6.9 844 544 8.7 790556 6.8 852 548 8.5 800560 6.7 861 560 8.4 820595 6.5 920 580 8.3 852

8/15/085/30/08

Cedar LakeC = Measured Conductivity (υS/cm)T = Temperature (oC)SC = calculated specific conductance (υS/cm)Depth

(m) C T SC C T SC C T SC C T SC C T SC C T SC C T SC C T SC0 307 1.1 564 249 0 477 442 13.6 565 550 21.7 587 506 26.5 492 423 15.9 512 347 6.3 540 317 0 607

-0.5 266 0 509 550 21.6 588 506 26.5 492 429 15.8 520 347 6.2 541 335 0.2 636-1 325 3.1 558 300 0.4 566 447 13.6 571 548 21.6 586 506 26.5 492 429 15.8 520 362 6.1 567 360 0.6 674

-1.5 326 3.3 557 332 0.9 615 547 21.5 586 504 26.4 491 429 15.8 520 363 6.1 568 364 3 628-2 326 3.3 557 338 1.1 622 448 13.5 574 546 21.5 585 504 26.3 492 429 15.8 520 363 6.1 568 365 3.1 627

-2.5 326 3.2 559 339 1.4 617 546 21.4 586 507 26.3 495 428 15.8 519 363 6.1 568 365 3.1 627-3 326 3.3 557 341 1.8 612 448 13.5 574 545 21.4 585 508 26.2 497 427 15.7 519 363 6.1 568 365 3.1 627

-3.5 326 3.3 557 342 2.1 608 449 13.5 575 544 21.3 585 504 26.1 494 427 15.7 519 363 6.1 568 365 3.1 627-4 327 3.4 556 344 2.1 611 449 13.4 577 528 19.5 590 510 26 500 427 15.7 519 363 6.1 568 365 3.2 625

-4.5 328 3.4 558 345 2.3 609 450 13.5 577 519 18.4 594 548 24.3 555 427 15.5 522 363 6 570 366 3.2 627-5 331 3.5 561 349 2.6 610 450 13.4 578 486 15 601 556 21.5 596 428 15.5 523 363 6 570 366 3.2 627

-5.5 331 3.5 562 350 2.8 608 432 10.8 593 474 13.6 606 540 18.9 611 428 15.4 524 363 6 570 366 3.2 627-6 332 3.6 562 356 2.9 616 414 9 596 457 12.1 606 508 16.3 609 428 15.4 524 363 6 570 366 3.2 627

-6.5 334 3.6 564 363 3 626 399 7.6 598 446 10.6 615 490 13.7 625 430 15.2 529 363 6 570 366 3.3 625-7 335 3.8 563 364 3 628 398 7.3 601 440 9.6 623 470 12 625 461 14.3 579 363 6 570 367 3.3 627

-7.5 336 3.8 565 369 3 636 395 6.9 604 426 8.6 620 458 11.1 624 478 11.4 646 368 6 578 368 3.3 628-8 338 3.8 568 375 3.1 645 395 6.6 609 418 7.5 628 441 9.4 628 456 9.7 644 370 6 581 369 3.4 628

-8.5 340 3.8 572 382 3 659 395 6.2 616 412 7.2 624 434 8.7 630 445 8.6 648 369 6 579 370 3.4 630-9 342 3.8 575 385 3.1 662 394 6 618 404 6.6 623 428 7.8 637 447 7.9 664 369 6 579 371 3.5 630

-9.5 343 3.9 575 390 3 673 393 5.8 621 407 6.3 633 421 7.3 636 447 7.5 671 368 5.9 579 374 3.6 633-10 346 3.9 579 391 3 674 402 5.6 639 406 6.1 635 419 7 639 444 7.3 671 368 5.9 579 374 3.6 633

-10.5 347 4 579 393 3 678 404 6 634 422 6.8 647 445 7 678 368 5.9 579 374 3.6 633-11 350 4.1 583 394 3.1 677 407 5.9 641 424 6.7 652 448 6.8 687 412 6.1 645 374 3.7 631

-11.5 355 4.4 585 428 5.9 674 433 6.5 670 465 6.7 715 414 6.1 648 374 3.7 631-12 355 4.5 583 446 6.5 690 375 3.7 632

-12.5 385 3.8 647-13 392 3.8 659

-13.5-14

-14.515

-15.5-16

11/6/06 2/21/079/24/061/14/06 2/25/06 5/6/06 6/13/06 8/8/06

C T SC C T SC C T SC C T SC C T SC C T SC C T SC C T SC C T SC388 8.6 565 525 18.7 597 489 18.6 557 362 7 552 318 0.2 604 316 1 583 355 7.2 538 490 17 578 555 24.3 563378 7.6 566 525 18.6 598 489 18.6 557 361 6.9 552 325 0.4 613 325 1 600 355 7.1 539 490 17 578 555 24.3 563377 7.4 568 525 18.9 594 489 18.6 557 361 6.9 552 329 1.3 601 338 1.6 611 355 7.1 539 490 16.9 580 558 24.3 566372 7 567 525 18.9 594 489 18.6 557 361 6.9 552 334 1.4 608 344 2.2 609 355 7.1 539 490 16.9 580 558 24.3 566371 6.9 567 524 18.8 594 489 18.6 557 361 6.8 553 335 2.1 595 346 2.4 609 355 7 541 490 16.9 580 558 24.3 566370 6.8 567 523 18.8 593 489 18.6 557 361 6.8 553 335 2.1 595 346 2.5 607 355 6.8 544 490 16.9 580 558 24.3 566370 6.7 569 522 18.7 593 489 18.6 557 361 6.8 553 336 2.1 597 347 2.6 606 354 6.7 544 490 16.8 581 559 24.3 567369 6.7 567 517 18.5 590 489 18.6 557 361 6.8 553 336 2.2 595 347 2.6 606 354 6.6 546 489 16.8 580 559 24.3 567369 6.6 569 512 18 591 489 18.6 557 361 6.8 553 336 2.3 593 347 2.6 606 356 6.5 551 488 16.6 581 558 24.2 567368 6.6 567 508 17.6 592 487 18.4 557 361 6.8 553 337 2.4 593 347 2.7 604 358 6.4 555 483 16.2 581 559 23.4 577368 6.6 567 489 16 591 487 18.3 558 361 6.8 553 337 2.4 593 348 2.8 604 378 5.2 608 454 13 589 561 22.3 592368 6.5 569 466 13.9 591 486 18.3 557 361 6.8 553 338 2.6 591 349 3 602 384 4.5 631 439 11.4 593 538 18.3 617369 6.4 572 440 11 601 487 18.3 558 361 6.8 553 339 2.7 591 350 3.1 602 386 4.3 638 427 10.4 592 513 15.5 627372 6.3 579 420 9.3 600 486 18.2 559 361 6.8 553 343 2.8 596 352 3.2 603 389 4.1 647 419 9.2 600 488 13.4 627380 5.8 600 408 8.2 601 485 17.9 561 361 6.8 553 343 2.8 596 354 3.2 607 389 4 650 415 8.7 603 466 11.4 630385 5.8 608 402 7.5 604 487 17.1 574 362 6.8 555 345 2.9 597 357 3.2 612 390 3.9 653 411 8.1 607 451 10.3 627386 5.6 613 397 7.2 601 493 13.7 629 361 6.8 553 349 3 602 359 3.3 613 392 3.9 657 409 7.6 613 443 9.3 633397 4.8 646 394 6.9 602 463 10.5 640 361 6.8 553 350 3.1 602 360 3.4 613 393 3.8 660 409 7 623 437 8.3 642414 4.4 683 393 6.7 604 450 9.5 639 362 6.8 555 356 3.1 612 362 3.4 616 396 3.7 668 408 6.8 625 434 7.7 648426 3.9 714 390 6.6 601 437 8.7 635 362 6.8 555 353 3.2 605 364 3.5 618 398 3.6 673 409 6.7 629 432 7.5 649429 3.8 721 389 6.4 603 434 8 643 362 6.7 557 355 3.3 606 367 3.5 623 406 3.6 687 410 6.3 638 431 6.8 661435 3.8 731 389 6.4 603 428 7.5 643 362 6.7 557 356 3.3 608 368 3.5 624 412 3.5 699 414 5.8 654 429 6.5 663433 3.7 730 389 6.4 603 424 7.2 642 362 6.7 557 357 3.3 610 370 3.5 628 419 3.5 711 416 5.6 661 428 6.3 666436 3.7 735 388 6.3 604 422 7.1 641 362 6.7 557 360 3.4 613 372 3.5 631 425 3.5 721 416 5.4 665 429 6.2 669437 3.7 737 388 6.3 604 421 6.8 645 362 6.7 557 352 3.4 599 374 3.5 635 429 3.5 728 417 5.2 671 429 6 673436 3.7 735 389 6.3 605 422 6.6 651 362 6.7 557 364 3.4 620 377 3.6 638 429 3.4 730 418 5.1 674 430 5.8 679440 3.7 742 389 6.3 605 422 6.5 653 362 6.7 557 367 3.4 625 381 3.6 644 441 3.4 751 420 4.9 682 432 5.7 684442 3.7 745 389 6.3 605 425 6.3 661 362 6.7 557 371 3.5 630 384 3.6 649 455 3.4 775 421 4.8 685 433 5.7 686443 3.7 747 389 6.3 605 426 6.2 665 362 6.7 557 377 3.5 640 388 3.7 654 457 3.4 778 422 4.8 687 435 5.6 691443 3.6 749 389 6.3 605 428 6.2 668 361 6.7 555 381 3.6 644 395 3.7 666 464 3.4 790 423 4.7 691 435 5.5 693444 3.6 751 389 6.3 605 430 6.1 673 361 6.7 555 395 3.8 664 409 3.9 685 465 3.4 792 423 4.7 691 436 5.5 695444 3.6 751 436 6.3 678 431 6.1 674 437 6.7 672 454 3.7 765 409 4 683 455 3.6 770 425 4.6 696 463 5.4 740455 3.6 770 457 6 717 424 4 708 441 4.5 725

4/1/07 5/17/07 9/17/07 11/15/07 2/7/08 3/13/08 4/22/08 5/30/08 8/15/08

Lake GervaisC = Measured Conductivity (υS/cm)T = Temperature (oC)SC = calculated specific conductance (υS/cm)Depth

(m) C T SC C T SC C T SC C T SC C T SC C T SC C T SC C T SC0 700 26.4 682 539 16.4 645 451 8.8 653 390 0.2 741 405 1.1 745 432 5.9 680 625 17.1 736 747 24.1 742

-0.5 700 26.5 681 537 16.4 643 443 8.2 652 406 0.3 769 411 1.3 751 431 5.8 681 625 17.1 736 746 24.1 742-1 701 26.5 681 537 16.4 643 441 8 653 414 0.6 775 422 2.3 745 432 5.8 682 625 17.1 736 745 23.9 742

-1.5 700 26.5 681 537 16.5 641 440 8 652 422 1.2 774 426 2.7 742 432 5.8 682 623 17.1 734 747 23.8 742-2 701 26.5 681 537 16.5 641 440 7.9 653 416 2.4 732 427 2.9 739 431 5.8 681 622 16.9 736 747 23.8 742

-2.5 701 26.4 683 538 16.5 642 439 7.9 652 417 3 719 427 2.9 739 432 5.7 684 621 16.9 735 746 23.8 742-3 701 26.4 683 537 16.5 641 439 8 650 419 3.3 716 427 2.9 739 431 5.8 681 621 16.9 735 746 23.7 742

-3.5 700 26.4 682 537 16.5 641 438 8 649 420 3.4 715 428 2.9 741 431 5.8 681 620 16.9 733 747 23.7 742-4 699 26.2 683 538 16.5 642 438 8 649 421 3.4 717 428 2.9 741 431 5.8 681 620 16.8 735 747 23.7 742

-4.5 694 26.1 680 538 16.5 642 438 8 649 422 3.3 721 428 3 738 431 5.7 683 618 16.7 734 747 23.6 742-5 687 25.7 678 538 16.4 644 438 8.1 647 423 3.4 720 428 3.1 736 431 5.6 685 606 15.7 737 740 22.9 742

-5.5 699 24.3 708 537 16.3 644 438 8.2 645 425 3.5 721 429 3.2 735 431 5.6 685 591 14.9 732 750 20.7 742-6 680 20.6 742 534 16.2 642 438 8.2 645 426 3.4 725 432 3.3 738 431 5.6 685 569 13.1 736 748 18.5 742

-6.5 654 17.3 767 531 16.1 640 438 8.3 643 429 3.4 730 435 3.4 741 447 5 723 542 11.2 736 623 16.6 742-7 633 14.4 794 531 16.1 640 437 8.4 640 431 3.5 731 438 3.4 746 470 4.6 770 522 9.8 736 599 14.8 744

-7.5 616 12.4 811 532 16 642 436 8.4 638 435 3.5 738 441 3.4 751 473 4.4 780 510 8.7 741 579 13.3 746-8 609 10.8 836 655 13.3 843 435 8.4 637 441 3.5 748 446 3.4 759 480 4.3 794 503 8.3 739 561 11.9 748

-8.5 606 10.3 843 632 11.6 849 435 8.4 637 443 3.5 752 449 3.4 764 498 4.1 829 501 8.1 740 550 11.1 749-9 600 9.8 845 621 11 848 434 8.6 632 444 3.8 746 451 3.6 763 500 8 740 543 10.2 757

-9.5 594 9.5 844 613 10.2 855 434 8.8 628 449 3.9 752 454 3.6 768 498 7.9 740 526 9.5 747-10 593 9 854 608 9.8 857 434 8.9 627 447 4 746 457 3.6 773 495 7.7 739 521 8.8 754

-10.5 589 8.5 860 606 9.4 863 434 9 625 450 4.1 749 457 3.6 773 494 7.5 742 518 8.6 754-11 589 8.4 862 625 9.1 898 434 9 625 456 4.2 757 460 3.6 778 493 7.4 743 517 8.2 761

-11.5 590 8.2 869 629 9.2 901 434 9 625 457 4.2 758 467 3.7 787 493 7.3 745 517 8.1 763-12 587 8.1 867 433 9.1 622 460 4.4 758 472 3.8 793 492 7.3 743 515 8 763

-12.5 587 8 869 434 9.2 622 468 4.5 769 476 3.8 800 492 7.3 743 516 7.8 768-13 589 7.8 877 434 9.2 622 469 4.6 768 486 4 811 495 7.2 750 535 7.6 801

-13.5 597 7.8 889 480 9.2 687 477 4.6 782 486 4.1 809 600 4.2 995-14 497 9.1 714 584 4.3 966

5/17/07 7/13/074/1/078/9/06 9/25/06 11/8/06 1/24/07 2/21/07

C T SC C T SC C T SC C T SC C T SC C T SC C T SC660 20.2 727 398 6.7 612 360 1.1 662 390 1.9 698 457 7.6 684 668 17.5 780 822 26.7 796662 20.3 727 398 6.7 612 366 1.3 669 390 1.9 698 455 7.5 683 668 17.5 780 803 25.8 791661 20.3 726 397 6.6 612 367 1.5 666 390 1.9 698 454 7.3 686 664 17.1 782 799 25.3 794662 20.4 726 397 6.6 612 378 1.8 679 393 2.2 696 452 7.2 685 664 17 784 794 25.1 792663 20.4 727 397 6.5 614 378 1.9 676 394 2.3 696 452 7.2 685 662 16.9 783 791 25.1 789662 20.4 726 396 6 622 378 2 674 394 2.3 696 446 6.7 686 661 16.8 784 790 24.7 795663 20.4 727 396 6.5 612 378 2.1 672 394 2.3 696 445 6.5 688 660 16.6 786 787 24.5 795663 20.4 727 396 6.5 612 378 2.1 672 394 2.3 696 441 6.1 690 660 16.5 788 788 24.4 797662 20.4 726 396 6.5 612 378 2.2 670 395 2.3 697 440 6 691 659 16.4 789 784 24.1 798662 20.4 726 396 6.5 612 379 2.4 667 396 2.4 697 440 5.9 693 656 16.2 789 782 24 797662 20.4 726 396 6.5 612 379 2.5 665 396 2.5 694 442 5.9 696 646 15.4 791 781 23.9 798662 20.4 726 396 6.5 612 379 2.6 662 398 2.6 696 448 5.4 716 634 14.1 801 774 23.3 800660 20.3 725 396 6.5 612 383 2.9 663 398 2.8 691 486 4.6 796 611 12.8 797 748 20.7 815658 20 727 396 6.5 612 390 3 673 403 3 695 487 4.3 805 599 11.6 805 711 18.5 812659 19.5 736 396 6.4 614 391 3.2 670 406 3.1 698 508 4.2 843 581 10.4 806 694 17 819646 16.3 775 396 6.4 614 392 3.5 665 410 3.2 703 529 3.9 886 580 9.8 817 684 14.2 862615 14.5 769 395 6.4 613 394 3.6 666 413 3.3 705 555 3.7 936 579 9.4 825 669 13.1 866603 13.4 775 395 6.4 613 399 3.9 668 422 3.4 718 606 3.4 1032 579 8.9 836 656 12.3 866689 12.1 914 395 6.4 613 405 3.9 678 428 3.4 729 649 3.1 1116 579 8.6 843 642 11.2 872677 11.5 912 395 6.4 613 407 3.9 682 433 3.3 740 660 3 1138 580 8.3 852 637 10.6 879563 10.6 777 395 6.4 613 409 4.1 681 439 3.3 750 674 2.9 1166 584 7.9 867 636 10 891555 9.9 780 395 6.4 613 411 4.3 680 443 3.4 754 685 2.9 1185 605 7.3 914 637 9.5 905549 9.4 782 395 6.4 613 416 4.6 682 451 3.5 765 698 2.8 1212 623 6.8 955 637 9.2 912548 9.3 783 395 6.4 613 420 4.8 684 462 3.6 781 705 2.9 1220 635 6.5 982 636 9.1 913547 9.2 783 395 6.4 613 425 4.8 692 485 3.6 820 720 2.9 1246 643 6.2 1003 635 8.7 922547 9.2 783 395 6.5 611 433 4.9 703 507 3.6 857 729 3 1257 653 6 1025 636 8.7 924547 9.1 786 482 6.6 743 450 5.2 724 541 3.6 915 730 3 1259 658 5.8 1039 643 8.7 934558 8.9 806 550 3.8 924 650 5.8 1026

9/12/07 11/16/07 2/8/08 3/14/08 4/22/08 5/30/08 8/15/08

Lake McCarronC = Measured Conductivity (υS/cm)T = Temperature (oC)SC = calculated specific conductance (υS/cm)Depth

(m) C T SC C T SC C T SC C T SC C T SC C T SC0 357 2.8 619 328 0.6 614 500 16 604 587 24.5 593 589 26.6 572 481 16.7 572

-0.5 366 1.1 673 498 15.7 606 586 24.4 593 590 26.7 571 481 16.8 570-1 371 3.7 626 384 2.8 667 498 15.6 607 584 24.2 593 590 26.7 571 477 16.6 568

-1.5 371 3.8 624 388 3.4 660 497 15.6 606 581 23.8 595 590 26.8 570 476 16.5 568-2 372 3.8 625 388 3.4 660 496 15.5 606 576 23.5 593 590 26.7 571 476 16.5 568

-2.5 373 3.8 627 388 3.5 658 485 14.9 601 565 22.8 590 590 26.8 570 475 16.5 567-3 374 3.8 628 389 3.5 660 479 14.2 603 560 22.2 592 589 26.8 569 475 16.5 567

-3.5 374 3.8 628 389 3.5 660 477 13.9 605 556 21.9 591 588 26.8 568 474 16.5 566-4 374 3.8 629 389 3.5 660 475 13.8 604 552 21.5 592 588 26.8 568 474 16.5 566

-4.5 376 3.8 632 390 3.6 660 474 13.5 607 539 20.7 587 589 26.8 569 475 16.5 567-5 376 3.8 632 391 3.7 659 471 13.2 608 511 18.1 589 595 24.5 601 475 16.5 567

-5.5 378 3.8 634 392 3.7 661 465 12.9 605 486 14.8 604 583 21.6 623 475 16.5 567-6 378 3.8 635 392 3.6 663 460 11.5 620 480 13.7 612 563 19.1 635 475 16.4 568

-6.5 379 3.8 637 394 3.7 664 439 7.8 654 479 11.8 640 537 16.3 644 476 16.4 570-7 381 3.8 640 396 3.7 668 431 5.7 683 473 10.6 652 522 13.9 662 474 16.3 568

-7.5 382 3.8 642 398 3.7 671 423 5.1 682 467 9.7 660 514 11.6 691 535 14.7 666-8 382 3.8 643 399 3.7 673 422 4.9 685 463 7.6 693 506 10 709 537 16.5 641

-8.5 383 3.8 644 401 3.7 676 428 4.5 703 460 6.8 705 494 9.2 708 526 12 700-9 385 3.8 647 403 3.7 679 428 4.3 708 457 6.2 713 487 7.6 729 511 9.7 722

-9.5 385 3.8 647 406 3.7 684 430 4.2 713 456 5.7 722 485 7.2 735 507 8.5 740-10 386 3.8 649 409 3.6 692 434 4.1 722 458 5.2 737 490 6.3 762 508 7.5 763

-10.5 389 3.8 654 412 3.7 695 443 4 740 466 5 754 492 6 772 511 6.5 790-11 390 3.8 656 418 3.7 705 462 3.9 774 480 4.8 782 494 5.8 780 513 6 805

-11.5 394 3.8 662 426 3.7 718 474 3.9 794 485 4.7 792 503 5.4 804 511 5.8 807-12 396 3.9 664 435 3.7 733 487 3.9 816 498 4.6 816 509 5.2 819 513 5.7 813

-12.5 400 4 668 449 3.7 757 510 3.8 857 509 4.5 837 514 5.1 829 518 5.5 825-13 407 4 680 474 3.7 799 527 3.8 886 515 4.5 846 518 5.1 836 525 5.4 839

-13.5 418 4.1 696 512 3.7 863 531 3.8 892 522 4.5 858 520 5.2 836 535 5.4 855-14 430 4.1 715 575 3.9 963 532 3.8 894 527 4.5 866 526 5.2 846 539 5.4 862

-14.5 481 4.2 798 570 3.9 955 533 3.8 896 561 4.6 919 567 5.3 909 622 5.4 994-15 563 4 940 535 3.8 899

-15.5 558 3.8 938-16 580 3.9 972

9/25/061/14/06 2/26/06 5/6/06 6/14/06 8/9/06

C T SC C T SC C T SC C T SC C T SC C T SC434 9.7 613 376 0.9 697 419 6.3 652 583 17.6 679 656 24.1 667 571 20.5 625434 9.7 613 386 1.7 696 415 6.3 646 583 17.6 679 656 24.1 667 571 20.5 625431 9.3 616 405 3.3 692 415 6.2 648 578 17.3 678 655 24 668 571 20.5 625429 9.2 614 406 3.3 693 414 6.1 648 578 17.3 678 653 23.9 667 571 20.5 625428 9.1 615 407 3.4 693 414 6.2 646 577 17.3 676 652 23.8 667 571 20.5 625427 9.2 612 407 3.4 693 413 6.2 644 577 17.2 678 652 23.8 667 571 20.5 625425 9 612 408 3.5 692 413 6.2 644 577 17.2 678 652 23.8 667 571 20.5 625424 9 611 408 3.5 692 414 6.1 648 575 17.1 677 651 23.8 666 571 20.5 625423 8.9 611 408 3.5 692 414 6.1 648 564 16.1 680 651 23.7 668 571 20.5 625422 8.8 611 407 3.5 691 414 6.1 648 543 14.7 676 650 23.6 668 571 20.5 625421 8.8 610 408 3.5 692 414 6.2 646 522 13 677 648 23.5 667 570 20.5 624420 8.7 610 408 3.6 690 414 6.1 648 497 10.8 682 588 17.7 683 570 20.4 625418 8.7 607 410 3.7 691 413 6.1 646 466 8.3 684 537 13.5 688 570 19.8 633417 8.7 606 410 3.7 691 413 6.1 646 447 7.2 677 502 11.4 678 573 18.1 660416 8.7 604 411 3.7 693 414 6 650 435 6.4 675 493 10.4 684 545 14.1 688416 8.8 602 413 3.8 694 415 5.8 655 427 5.8 674 470 9.1 675 515 11.9 687416 8.7 604 414 3.8 696 415 5.8 655 428 5.6 680 457 8 677 497 10.2 693416 8.7 604 415 3.8 697 415 5.8 655 424 5.4 678 454 7.3 686 480 8.9 693415 8.7 603 416 3.8 699 416 5.8 657 424 5.4 678 445 6.8 682 466 8.2 686415 8.9 599 417 3.8 701 417 5.6 662 423 5.3 678 441 6.1 690 461 7.5 692415 8.8 601 418 3.8 702 419 5.5 668 423 5.3 678 438 5.7 694 452 6.6 697415 8.9 599 420 3.8 706 420 5.4 671 425 5.3 681 437 5.5 696 453 6.1 709415 8.9 599 421 3.8 707 428 4.6 701 425 5.2 683 437 5.3 701 541 5.7 857415 9.1 596 424 3.7 715 451 4.5 741 426 5.3 683 444 5.2 714 453 5.5 722416 9.1 597 427 3.7 720 479 4.6 785 429 5.3 688 447 5.1 721 457 5.2 735416 9.2 596 432 3.7 728 498 4.7 813 433 5.3 694 452 5.1 729 459 5.1 740417 9.2 597 445 3.7 750 520 4.7 849 442 5.3 709 458 5 741 463 5 749419 9.4 597 459 3.7 774 552 4.8 899 458 5.6 728 461 5 746 468 4.9 760553 9 796 498 3.8 837 566 4.8 922 474 5.6 753 468 4.7 764 472 4.9 766601 9.4 856 546 3.8 918 584 4.9 948 490 5.6 778 472 4.7 771 474 4.9 769

610 3.8 1025 596 3.9 998 519 5.6 825 473 4.7 773 478 4.8 778613 3.9 1027 567 5.1 915 538 5.4 860 481 4.7 786 479 4.8 780

524 4.7 856 605 4.8 985

11/8/06 2/21/07 4/1/07 5/17/07 7/13/07 9/12/07

C T SC C T SC C T SC C T SC C T SC C T SC413 6.8 633 330 0 632 343 1.7 618 404 8.4 592 539 17.2 633 642 26.7 622412 6.8 632 373 0.3 706 343 1.7 618 403 8.3 592 539 17.1 635 642 26.7 622412 6.8 632 386 1.8 693 343 1.7 618 403 8.3 592 528 17 623 641 26.4 624412 6.8 632 390 2.2 691 401 2.7 699 402 8.2 592 536 16.9 634 637 26.2 623412 6.7 633 390 2.3 689 402 2.8 698 402 8.1 594 535 16.9 633 632 25.8 622412 6.7 633 391 2.4 688 402 2.8 698 400 8 592 534 16.8 633 633 25.6 626412 6.7 633 391 2.4 688 402 2.8 698 400 8 592 534 16.7 635 631 25.3 627412 6.7 633 391 2.4 688 402 2.8 698 400 7.9 594 534 16.6 636 630 25 630412 6.7 633 391 2.4 688 402 2.8 698 396 7.7 591 533 16.6 635 627 24.6 632412 6.5 637 391 2.4 688 402 2.8 698 400 6.8 613 533 16.6 635 626 24.4 633412 6.5 637 391 2.4 688 402 2.8 698 435 5.8 687 527 13.6 674 622 23.5 640412 6.5 637 391 2.5 686 402 2.8 698 435 5.1 702 484 11.5 652 603 20.6 658412 6.5 637 392 2.5 687 402 2.8 698 435 4.8 708 459 10.4 636 567 16.2 682412 6.5 637 394 2.6 689 404 2.8 701 433 4.6 709 454 9.5 645 554 15.1 683412 6.5 637 395 2.6 690 405 2.8 703 431 4.2 715 452 8.7 656 543 13.6 694412 6.5 637 397 2.6 694 407 2.8 707 433 4.1 721 449 8.1 663 529 12.7 691412 6.5 637 398 2.6 696 408 2.9 706 433 3.7 730 450 7.4 678 523 11.7 701412 6.5 637 398 2.6 696 412 2.9 713 435 3.7 733 453 6.8 694 508 9.9 714412 6.5 637 400 2.6 699 141 2.9 244 444 3.3 758 454 6.2 708 505 8 748412 6.5 637 401 2.7 699 416 2.9 720 447 3.3 763 456 5.4 729 505 6.8 774412 6.5 637 404 2.7 704 421 2.9 729 452 3.3 772 462 4.6 757 512 5.9 806412 6.5 637 407 2.7 709 424 2.9 734 456 3.2 781 471 4.3 779 514 5.4 822412 6.5 637 409 2.7 712 428 2.9 741 457 3.2 783 478 3.8 803 514 5.1 829412 6.5 637 412 2.7 718 435 2.9 753 464 3.1 798 491 3.6 830 515 4.8 839412 6.5 637 412 2.8 715 443 2.9 767 472 3.1 811 496 3.6 839 515 4.8 839412 6.5 637 420 2.9 727 457 2.9 791 496 3.1 853 502 3.5 852 516 4.5 848412 6.5 637 422 3 728 474 2.9 820 522 3.1 897 505 3.5 857 516 4.4 851412 6.5 637 432 3 745 492 2.9 851 534 3.1 918 508 3.4 865 520 4.3 860412 6.5 637 463 3 799 523 2.9 905 564 3.2 966 508 3.4 865 520 4.3 860412 6.5 637 487 3.1 837 592 3.1 1018 581 3.3 992 511 3.4 870 521 4.2 864412 6.4 639 551 3.3 941 625 3.3 1067 592 3.2 1014 514 3.4 875 523 4.2 868412 6.4 639 593 3.5 1006 656 3.5 1113 489 3.5 830 596 3.5 1011 525 4.1 874511 6.1 800 610 3.6 1032 649 3.6 1098 515 4.1 857

8/15/0811/15/07 2/8/08 3/14/08 4/22/08 5//30/2008

Parkers LakeC = Measured Conductivity (υS/cm)T = Temperature (oC)SC = calculated specific conductance (υS/cm)

depth(m) C T SC C T SC C T SC C T SC C T SC C T SC C T SC0 602 15.1 742 610 22.2 644 641 27.6 611 16.1 602 449 6.4 696 419 0.6 785 440 7.3 665

-0.5 601 15.1 741 610 22.1 646 640 27.6 610 16 601 447 6.3 695 434 1.5 787 438 7.2 664-1 601 15 743 625 22.1 662 648 27.5 618 16 604 446 6.3 694 448 2.8 778 438 7.1 666

-1.5 599 14.9 742 623 22.1 660 642 27.5 613 16 602 445 6.2 694 461 3.6 780 435 6.9 665-2 596 14.7 742 623 22.1 660 640 27.5 611 16 602 444 6.1 695 462 3.6 781 434 6.8 665

-2.5 594 14.6 741 611 21.3 657 640 27.4 612 15.9 603 443 6.1 693 463 3.7 781 434 6.7 667-3 594 14.6 741 606 21 656 636 27.1 611 15.9 603 443 6 695 464 3.8 780 432 6.7 664

-3.5 592 14.5 741 610 20.6 666 631 26.8 610 15.9 603 443 6 695 467 4.1 777 432 6.6 666-4 589 14.1 744 616 19.8 684 631 26.5 613 15.9 603 443 6 695 475 4.2 788 432 6.6 666

-4.5 587 14 743 614 18.4 703 660 24.7 664 15.9 603 443 6.1 693 478 4.3 791 431 6.6 665-5 581 13.5 745 597 17 705 684 22.6 717 15.9 602 443 6.1 693 486 4.3 804 431 6.4 668

-5.5 580 12.7 758 581 15.1 716 690 20.4 756 15.9 602 443 6.1 693 490 4.2 813 585 5.4 935-6 614 9.8 865 638 12.8 832 696 17.7 809 15.9 602 442 6.1 692 502 4.2 833 626 4.5 1029

-6.5 711 7.3 1074 785 10.9 1074 770 15 952 15.4 630 442 6.1 692 514 4.2 853 648 4.4 1068-7 773 5.9 1217 873 9.1 1254 888 12.4 1169 15.2 641 441 6.1 690 541 4.3 895 667 4.3 1103

-7.5 855 5 1383 906 7.7 1353 965 10.4 1338 13 1276 441 6.1 690 576 4.3 953 714 4.3 1181-8 916 4.6 1501 954 6.3 1484 1004 9.1 1442 10.9 1410 441 6.1 690 640 4.3 1058 764 4.3 1264

-8.5 955 4.5 1570 970 5.8 1532 1012 8 1499 9.3 1489 440 6.1 689 705 4.4 1162 868 4.4 1431-9 976 4.4 1609 988 5.4 1579 1021 7.4 1538 8.4 1530 439 6 689 781 4.4 1288 911 4.3 1507

-9.5 988 4.4 1629 993 5.2 1597 1020 7 1554 8.1 1541 438 6 687 864 4.5 1420 1024 4.3 1694-10 984 4.5 1617 996 5 1612 1023 6.5 1582 7.8 1555 438 6 687 870 4.6 1425 1117 4.3 1847

-10.5 995 4.9 1615 1021 6.4 1584 7.6 1564 437 6.1 684 922 4.6 1511 1213 4.3 2006-11 990 4.9 1607 1022 6.3 1590 7.4 1575 737 6.2 1150 933 4.7 1524 1254 4.4 2067

-11.25 976 5 1579 974 6.3 1515 7.3 1522 1266 4.8 2061

5/7/06 6/14/06 8/8/06 9/24/06 11/8/06 2/22/07 4/1/07

C T SC C T SC C T SC C T SC C T SC C T SC C T SC C T SC694 18.9 786 730 24.7 734 652 18.5 744 471 5.1 760 476 0.1 908 198 0.2 376 751 8.9 751 750 16.9 887692 18.5 790 730 24.6 736 652 18.4 746 471 5.1 760 477 0.4 900 261 0.2 496 754 8.7 754 750 16.9 887692 18.4 792 728 24.7 732 650 18.3 745 470 5.1 758 488 1.3 892 457 0.3 865 760 8.4 760 750 16.9 887692 18.3 794 726 24.6 732 648 18.2 745 470 5.1 758 497 1.8 892 531 2.6 928 764 8.1 764 750 16.9 887691 18.3 792 719 24.1 732 647 18.1 745 470 5 761 501 1.9 897 537 3 926 774 7.7 774 750 16.9 887690 18.2 793 714 23.8 731 642 17.5 749 470 5 761 503 2 897 537 3 926 794 7.6 794 750 16.9 887689 18.1 794 712 23.7 730 643 17.4 752 470 5 761 506 2.1 899 535 3 923 544 7.6 815 749 16.9 886681 17.8 790 708 23.6 727 635 17.1 748 470 5 761 507 2.1 901 531 2.9 919 607 6.7 933 750 16.9 887678 17.5 791 706 23.4 728 633 17.1 745 470 5 761 510 2.2 903 547 2.7 953 678 4.8 1104 749 16.9 886678 17.4 793 707 21.2 762 633 17 747 470 5 761 513 2.3 906 570 2.7 993 714 4.1 1188 745 16.3 893667 15.3 819 682 18.9 772 633 16.9 749 470 5 761 517 2.4 910 590 2.8 1024 720 3.9 1206 708 14.4 888652 14.4 818 661 15.8 802 633 16.9 749 470 5 761 521 2.4 917 613 2.8 1064 774 3.7 1305 676 11.6 909659 10.7 907 647 14.5 809 633 16.8 751 470 5 761 530 2.4 933 643 2.8 1116 789 3.6 1334 658 10.3 915572 9 824 638 12.5 838 634 16.5 757 470 5 761 559 2.5 980 672 2.8 1167 797 3.4 1357 728 8.1 1075558 8.1 824 600 11.2 815 654 14.4 820 470 5 761 570 2.6 996 713 2.8 1238 884 3.4 1505 844 7.2 1279548 7.5 823 585 9.9 822 627 12.1 832 470 5 761 600 2.6 1049 719 2.9 1244 920 3.4 1566 1002 5.4 1602544 7.1 827 570 8.8 825 616 10.8 845 470 5 761 640 2.6 1119 745 2.9 1289 956 3.4 1627 1062 4.8 1729532 6.6 820 567 8.1 837 609 10.2 849 469 4.9 761 664 2.7 1157 782 2.9 1353 992 3.4 1689 1106 4.5 1818531 6.3 826 564 7.6 845 599 9.2 858 469 4.9 761 696 2.8 1208 843 2.9 1459 1036 3.5 1758 1119 4.4 1845532 6 835 563 7.4 848 593 8.7 861 468 4.8 762 729 3 1257 935 3 1613 1126 3.6 1904 1129 4.3 1867533 5.7 844 564 7.2 855 595 8.3 874 468 4.8 762 772 3 1331 976 3 1683 1204 3.6 2036 1149 4.2 1906536 5.7 849 563 7.1 855 598 8.1 883 468 4.8 762 880 3 1518 1100 3.1 1891 1270 3.6 2148 1161 4.2 1926538 5.6 855 672 7.2 1018 601 8 890 468 4.8 762 829 3.2 1420 1066 3.1 1833 1307 3.7 2203 1150 4.1 1914770 5.5 1227 688 7.1 1045 688 7.9 1022 527 5.5 840 1100 3.7 1854

5/17/07 7/13/07 9/17/07 11/16/07 2/8/08 3/14/08 4/22/08 5/30/08

C T SC752 24.7 756751 24.7 755749 24.6 755744 24.5 751744 24.4 753743 24.3 753742 24.3 752741 24.2 752732 23.9 748714 23.3 738766 21.3 824776 18.3 890806 15.1 994869 11.9 1159985 9.9 1384

1046 8.9 15101124 7.6 16831154 7 17591165 6.5 18021174 6.3 18261178 6.1 18431182 5.8 18661145 5.8 1808

8/15/08

Ryan LakeC = Measured Conductivity (υS/cm)T = Temperature (oC)SC = calculated specific conductance (υS/cm)Depth

(m) C T SC C T SC C T SC C T SC C T SC C T SC C T SC0 289 2.1 513 307.2 0.5 577 386.5 16.8 458 432 22.5 454 469 28.3 441 16.3 468 380 8 563

-0.5 309.1 1.1 569 386.7 16.7 460 431 22.5 453 469 28.4 440 16.2 469 381 7.9 566-1 295 2.7 514 314.7 2.1 559 385.6 16.6 459 429 22 455 460 27.4 440 16.2 468 379 7.7 566

-1.5 296 2.8 513 314.2 2.7 547 376.7 15.7 458 420 21.1 454 451 26.6 438 16.1 469 379 7.7 566-2 296 2.9 512 314.7 2.8 546 374.1 15.1 461 416 20.6 454 452 26.2 442 16 468 378 7.6 566

-2.5 296 2.9 513 315.4 2.8 548 362.5 14.5 453 411 19.8 456 456 24.7 459 15.2 466 369 6.8 566-3 298 2.8 517 316.7 2.8 550 355.9 13.2 459 403 18.3 462 454 22.5 477 14.7 468 366 6.6 564

-3.5 298 2.8 517 315.5 2.9 546 342.4 12 456 386 15 477 429 18.4 491 14.6 467 364 6.5 563-4 300 2.8 520 316.4 3 546 324 8.6 472 369 12.6 484 416 16.1 501 14.4 468 363 6.4 563

-4.5 303 2.8 526 318.4 3 549 314.9 7.1 478 353 10.6 487 386 12.1 512 14.1 475 361 6.4 560-5 305 2.9 528 322.2 3 556 314.9 6.9 481 340 8.4 498 370 9.7 523 13.2 501 360 6.3 560

-5.5 309 2.9 535 325.4 3 561 320.4 5.3 514 340 7.2 515 374 8.1 552 11.4 550 359 6.2 560-6 311 3 536 331.4 2.9 573 326.6 4.8 532 349 5.8 551 392 6.6 604 8.2 607 358 6.1 560

-6.5 313 3 539 337.9 3 583 332.8 4.5 547 368 5.1 594 414 5.8 654 7.1 653 357 6.1 559-7 319 3.1 549 348.3 3 601 347.1 4.3 574 394 4.6 646 441 5.3 707 6.5 701 357 6.1 559

-7.5 322 3.1 554 362.7 3 626 367 4 613 422 4.5 694 473 5 765 6.1 745 357 6.1 559-8 336 3.1 577 391.3 3 675 419.2 3.8 704 471 4.2 781 507 4.8 825 5.9 785 356 6 559

-8.5 368 3.2 631 434.8 3 750 488 3.6 825 504 4.1 839 533 4.7 871 5.7 833 355 6 557-9 408 3.2 698 483 3 833 539 3.5 915 531 4.1 884 546 4.6 895 5.5 861 355 6.3 552

-9.5 456 3.2 781 540 3.1 928 557 3.5 945 544 4 908 554 4.6 908 5.6 869 356 6.4 552-10 511 3.3 873 571 3.2 978 565 3.5 959 553 4.1 920 562 4.6 921 5.6 892 357 6.6 550

-10.5 599 3.5 1016 640 3.4 1089 574 3.6 971 560 4.1 932 582 4.7 951 5.6 907 544 6.7 836-11 600 3.6 1015 604 4.2 1002 5.6 1042

11/08//20069/25/061/14/06 2/25/06 5/6/06 6/14/06 8/8/06

C T SC C T SC C T SC C T SC C T SC C T SC C T SC C T SC343 0.5 645 338 8.5 494 482 18.7 548 499 24.1 508 457 19.6 510 323 4.9 524 317 0.1 604 216 0.2 410356 1.9 637 338 8.5 494 482 17.7 560 499 24.1 508 457 19.5 511 323 4.9 524 322 0.5 605 293 0.8 545367 2.3 648 337 8.3 495 480 18.5 548 499 24.1 508 443 18 511 323 4.8 526 330 1.3 603 337 1.6 609367 2.4 646 337 8.3 495 478 18.3 548 493 23.5 508 436 17.5 509 323 4.8 526 333 1.9 596 340 2 606368 2.4 647 337 8.2 496 474 18 547 491 23.3 507 430 17 508 323 4.8 526 335 2 597 341 2.2 604367 2.4 646 338 8.2 498 472 17.8 547 490 22.7 513 428 16.7 509 323 4.7 528 336 2.1 597 343 2.3 606367 2.4 646 338 8.1 499 456 15.5 557 503 20.8 547 428 16.4 512 323 4.7 528 336 2.2 595 344 2.6 601367 2.4 646 341 7.8 508 411 10.6 567 488 17.8 566 427 16.1 514 323 4.7 528 337 2.3 595 344 2.7 599367 2.4 646 347 7.5 521 396 9.1 569 468 15.4 573 431 15.6 525 323 4.7 528 337 2.4 593 345 2.8 599367 2.4 646 356 6.7 547 378 7.7 565 424 11.1 577 444 14.8 551 324 4.7 529 338 2.7 589 348 2.8 604367 2.4 646 360 5.9 567 366 6.8 561 405 9.1 582 441 12.7 576 324 4.7 529 338 2.8 587 354 2.9 613366 2.4 644 370 4.8 602 360 6.2 562 382 7.3 577 424 9.9 596 324 4.7 529 344 2.9 595 361 3 623366 2.3 646 375 4.5 616 359 5.8 567 376 6.8 576 413 8.3 606 324 4.7 529 346 3 597 370 3 638367 2.3 648 380 4.2 630 362 5.6 575 373 5.9 587 402 7.1 611 324 4.7 529 350 3.1 602 378 3 652366 2.3 646 388 4.1 646 363 5.5 578 375 5.7 594 404 6.6 623 324 4.7 529 357 3.1 614 389 3 671368 2.3 650 400 3.9 670 362 5.5 577 381 5.5 607 404 6.1 632 324 4.7 529 362 3.2 620 402 3 693405 2.4 713 426 3.9 714 362 5.5 577 390 5.4 623 417 5.8 658 324 4.7 529 373 3.4 635 433 3 747445 2.5 780 460 3.9 771 361 5.4 577 402 5.3 645 428 5.6 680 324 4.7 529 384 3.6 649 492 3 849494 2.7 861 482 4 805 362 5.4 579 422 5.2 679 438 5.5 698 324 4.7 529 404 3.7 681 553 3 954546 3.2 936 517 4.3 855 372 5.2 598 437 5.2 703 444 5.4 710 324 4.7 529 457 3.8 768 633 3 1092586 3.4 998 556 4.4 917 391 5.2 629 440 5.2 708 447 5.4 714 324 4.7 529 567 3.8 953 715 3 1233646 3.6 1093 582 4.7 951 424 4.9 688 511 5.2 822 588 5.4 940 354 4.8 576 597 3.5 1013 727 3.2 1246

593 4.8 966 432 4.6 708

2/22/07 4/1/07 5/17/07 7/13/07 9/17/07 11/15/07 2/8/08 3/14/08

C T SC C T SC C T SC345 13.1 446 443 17 523 485 25.7 479345 13 448 443 17 523 482 25.4 478345 12.7 451 443 17 523 477 24.8 479343 12.6 449 442 17 522 475 24.4 481330 11 450 442 16.9 523 476 24.3 482313 7.7 467 442 16.9 523 478 23.9 488313 7 477 414 15.1 511 484 22.6 507313 6.7 481 337 13.2 435 458 19 517313 6.6 483 354 10.7 487 424 15 524314 6.3 488 345 9.3 493 409 12.5 537319 6.1 499 337 8.4 493 390 10.3 542350 4.8 570 330 7 503 409 8.9 591378 4.5 621 367 6 576 449 7.3 678406 3.6 687 425 5.2 683 499 6.6 769430 3.4 732 462 4.6 757 544 5.8 859462 3.3 789 500 4.2 830 573 5.3 919494 3.3 844 535 3.9 896 616 4.9 1000600 3.3 1025 570 3.9 955 635 5 1028644 3.3 1100 617 3.7 1040 648 4.7 1058654 3.3 1117 629 3.7 1060 654 4.8 1065690 3.3 1178 635 3.6 1074 664 4.5 1091733 3.3 1252 639 3.7 1077 670 4.7 1094754 3.4 1284 647 3.7 1091

8/15/084/22/08 5/30/08

Sweeney LakeC = Measured Conductivity (υS/cm)T = Temperature (oC)SC = calculated specific conductance (υS/cm)Depth

(m) C T SC C T SC C T SC C T SC C T SC C T SC C T SC0 923 29.2 854 724 18.1 834 641 8.9 926 660 2.3 1165 670 8.4 981 1015 19.5 1134 1113 25.5 1102

-0.5 920 29 855 724 18 836 640 8.8 927 702 2.7 1223 671 8.3 985 1014 19.4 1135 1112 25.5 1101-1 918 28 868 724 18 836 638 8.7 926 705 2.7 1228 669 8.1 988 1010 19.2 1136 1109 25.3 1103

-1.5 915 28.4 859 720 17.8 835 634 8.3 931 706 2.6 1234 668 8 989 1003 18.9 1135 1107 25.2 1103-2 916 28.3 862 718 17.6 836 633 8.3 929 705 2.6 1232 668 7.9 992 998 18.7 1135 1101 24.7 1107

-2.5 914 28.2 861 717 17.5 837 632 8.3 928 705 2.6 1232 670 7.8 998 996 18.7 1132 1100 24.5 1111-3 910 27.9 862 716 17.4 838 630 8.2 928 706 2.5 1238 694 7.6 1039 994 18.6 1132 1093 24.4 1106

-3.5 900 27.3 862 715 17.4 836 628 8.2 925 706 2.5 1238 742 7.4 1118 990 18 1143 1092 24.3 1107-4 900 27.1 865 715 17.4 836 628 8.2 925 706 2.5 1238 780 6.5 1206 954 16 1152 1089 23.7 1117

-4.5 900 27 867 714 17.4 835 628 8.2 925 706 2.5 1238 807 5.7 1278 923 14 1169 1064 21.4 1143-5 900 27 867 714 17.4 835 628 8.3 922 707 2.5 1240 835 4.8 1360 863 10.9 1181 997 16.5 1190

-5.5 900 27 867 714 17.4 835 628 8.3 922 718 2.6 1255 854 4.3 1412 833 9.2 1193 944 13.5 1210-6 900 26.9 868 714 17.5 833 624 8.4 914 727 2.6 1271 879 3.7 1482 815 8.3 1197 914 12 1216

-6.5 899 26.8 869 714 17.4 835 621 8.5 907 727 2.7 1266 907 3.7 1529 810 8 1199 892 11 1218-7 899 26.8 869 713 17.5 832 723 2.9 1251 948 3.7 1598 809 7.7 1208 887 10.4 1230

-7.5 959 26.6 931 714 17.5 833 710 2.9 1229 939 3.7 1583 880 10.3 1224-8 722 17.6 841

7/13/075/17/078/8/06 9/24/06 11/8/06 2/22/07 4/2/07

C T SC C T SC C T SC C T SC C T SC C T SC C T SC827 20.8 899 540 5.9 850 451 0.1 860 605 0.4 1141 1087 12.5 1428 994 17.3 1165 1105 25.1 1103822 20.3 903 540 5.9 850 520 1.7 937 681 0.9 1262 1046 10.7 1439 994 17.3 1165 1164 25.1 1162819 20.1 904 540 5.9 850 572 1.9 1024 768 1.9 1374 1040 10.5 1438 994 17.3 1165 1095 24.8 1099817 19.9 905 540 5.9 850 700 2.2 1240 774 2 1380 1036 10.4 1437 993 17.3 1164 1089 24.5 1100815 19.8 905 540 5.9 850 702 2.3 1239 774 2 1380 1018 9.7 1438 993 17.3 1164 1087 24.3 1102810 19.5 905 540 5.9 850 702 2.3 1239 777 2 1386 1008 9.3 1440 990 17.1 1166 1086 24.1 1105810 19.5 905 540 5.9 850 703 2.3 1241 785 2 1400 991 8.3 1455 985 16.9 1165 1084 24.1 1103809 19.5 904 540 5.9 850 705 2.3 1245 793 2 1414 968 7.4 1458 972 15.4 1190 1083 23.9 1106800 18.9 905 540 5.9 850 707 2.3 1248 810 2 1445 962 7.1 1462 950 12.8 1239 1084 23.7 1112796 18.6 907 540 5.9 850 710 2.3 1253 823 2 1468 959 6.7 1474 963 10 1350 1128 22.9 1175795 18.5 908 540 5.9 850 712 2.3 1257 845 2 1507 959 6.3 1492 978 8.4 1432 1142 20.7 1244799 18.4 914 541 5.9 852 721 2.3 1273 858 2 1530 959 5.9 1510 988 8 1463 1142 15.7 1389803 18.3 921 541 5.9 852 726 2.3 1282 902 2 1609 962 5.7 1524 990 7.5 1487 1137 13.5 1457812 18 937 545 5.9 858 740 2.3 1306 935 2.1 1662 981 5.2 1578 987 7.1 1500 1111 11.7 1489940 16.4 1125 553 6.1 865 751 2.3 1326 998 2.1 1774 1002 4.8 1631 986 7.1 1498 1098 10.8 1507995 15.4 1218 553 6.1 865 770 2.4 1355 1014 2.1 1802 1006 4.6 1648 988 6.9 1510 1083 10.2 1510989 14.9 1225 563 6.8 863 765 2.7 1333 981 2.2 1738 1005 4.6 1647 971 6.8 1488 1068 10.3 1485

9/17/07 11/16/07 2/8/08 3/14/08 4/22/08 5/30/08 8/15/08

Tanners LakeC = Measured Conductivity (υS/cm)T = Temperature (oC)SC = calculated specific conductance (υS/cm)Depth

(m) C T SC C T SC C T SC C T SC C T SC C T SC C T SC0 680 25.8 670 521 15.9 631 502 7.7 750 425 1.5 771 441 1.6 797 466 5.8 736 629 17.2 739

-0.5 681 25.9 669 521 15.9 631 501 7.6 750 440 2 785 450 2 803 465 5.7 736 627 17 740-1 681 25.9 669 531 15.9 643 500 7.4 753 450 3.1 774 465 2.3 821 464 5.6 737 630 16.9 745

-1.5 680 25.9 669 535 15.9 648 498 7.3 752 453 3.3 774 476 3.1 818 464 5.6 737 631 16.9 746-2 680 25.9 669 537 15.8 651 498 7.2 755 455 3.3 777 477 3.2 817 464 5.6 737 633 16.9 749

-2.5 680 25.9 669 537 15.8 651 496 7.2 751 455 3.3 777 477 3.2 817 464 5.6 737 635 16.8 753-3 679 25.9 668 537 15.8 651 496 7.2 751 456 3.3 779 478 3.2 819 464 5.6 737 637 16.8 755

-3.5 673 25.7 664 537 15.8 651 495 7.2 750 456 3.3 779 478 3.2 819 464 5.6 737 639 16.8 758-4 640 24.9 641 537 15.8 651 494 7.1 751 457 3.3 780 478 3.2 819 464 5.6 737 639 16.8 758

-4.5 647 23.2 670 537 15.7 653 492 7 750 458 3.2 785 479 3.2 821 464 5.6 737 626 15.7 761-5 653 21.8 696 534 15.6 651 491 6.9 750 459 3.2 786 479 3.2 821 466 5.5 743 593 13.3 764

-5.5 623 18.2 716 533 15.5 651 490 6.9 749 461 3.2 790 479 3.2 821 469 5.3 752 575 11.9 767-6 598 15.5 731 528 15.3 648 489 6.9 747 463 3.1 796 480 3.2 822 478 5.1 771 555 10.4 770

-6.5 570 13.8 725 526 15 650 489 6.9 747 465 3 802 482 3.3 823 484 4.8 788 533 9 768-7 569 11.1 775 592 12.8 772 488 6.9 746 467 3 805 484 3.3 827 495 4.5 814 523 8.2 770

-7.5 580 9.7 819 606 10.3 843 487 6.9 744 469 2.9 812 488 3.3 833 508 3.9 851 507 7 773-8 617 7.6 924 636 8.8 921 486 6.9 743 473 2.9 818 493 3.2 845 524 3.8 881 499 6.5 772

-8.5 665 7.1 1010 703 7.6 1053 485 6.9 741 478 3 824 496 3.2 850 536 3.6 907 497 6.1 778-9 738 6.2 1151 763 6.8 1170 485 6.9 741 485 3 836 504 3.1 866 555 3.6 939 493 5.8 778

-9.5 773 5.8 1221 785 6.4 1218 485 6.9 741 494 3 852 519 3.1 892 580 3.5 984 493 5.7 781-10 791 5.5 1260 804 6.1 1258 485 7 739 506 3 873 530 3.1 911 621 3.5 1054 491 5.6 780

-10.5 818 5.2 1315 815 5.9 1283 485 7.1 737 513 3 885 539 3.1 927 679 3.5 1152 490 5.5 781-11 851 5.1 1373 844 5.7 1337 485 7.3 733 537 3 926 550 3.1 945 704 3.5 1195 492 5.4 786

-11.5 878 5 1421 858 5.6 1363 485 7.4 731 551 3 950 555 3.2 951 730 3.4 1243 495 5.3 794-12 899 4.9 1459 896 5.4 1432 485 7.6 726 575 3 992 575 3.1 988 764 3.5 1296 498 5.2 801

-12.5 913 4.9 1482 912 5.4 1458 486 7.7 726 610 3 1052 612 3.1 1052 819 3.5 1390 500 5.2 804-13 927 4.9 1505 915 5.4 1463 532 7.9 790 652 3.1 1121 673 3.2 1153 931 3.5 1580 502 5.2 807

-13.5 931 4.9 1511 916 5.4 1464 888 8.1 1311 756 3.2 1295 796 3.3 1359 967 3.5 1641 503 5.2 809-14 935 4.9 1518 916 5.4 1464 908 8.1 1341 913 3.3 1559 983 3.4 1673 978 3.6 1654 503 5.2 809

-14.5 878 5 1421 866 5.5 1380 847 8.2 1247 873 3.5 1481 954 3.5 1619 992 3.6 1678 704 5.1 1136

5/17/074/1/078/8/06 9/25/06 11/8/06 1/24/07 2/21/07

C T SC C T SC C T SC C T SC C T SC C T SC C T SC C T SC762 23.7 781 661 19.9 732 454 7.5 682 407 0.1 776 440 2.1 782 434 7.9 645 621 16.6 740 741 25.4 735762 23.7 781 663 19.9 735 454 7.4 684 410 0.3 776 440 2.1 782 434 7.9 645 621 16.6 740 737 25.1 736761 23.7 780 663 19.9 735 454 7.4 684 421 1.4 767 440 2.1 782 435 7.8 648 620 16.5 740 731 24.7 735761 23.7 780 663 19.9 735 454 7.4 684 425 1.8 763 444 2.2 787 435 7.8 648 619 16.5 739 728 24.5 735761 23.7 780 662 19.9 733 454 7.4 684 425 1.9 761 446 2.5 782 434 7.7 648 619 16.4 741 726 24.4 734761 23.7 780 662 19.9 733 454 7.4 684 425 2 758 446 2.5 782 434 7.6 650 618 16.4 739 725 24.3 735761 23.7 780 662 19.9 733 454 7.4 684 425 2 758 446 2.5 782 434 7.6 650 618 16.4 739 724 24.2 735761 23.7 780 663 19.9 735 454 7.4 684 426 2 760 446 2.5 782 434 7.5 652 618 16.3 741 724 24 738760 23.7 779 662 20 732 454 7.4 684 425 2 758 446 2.5 782 459 5.7 727 617 16.3 740 722 23.8 739750 22.7 784 662 20 732 454 7.3 686 425 2 758 446 2.5 782 477 5.3 765 583 14.3 733 714 23.1 741690 18.6 786 662 19.9 733 454 7.3 686 425 2.1 755 446 2.5 782 488 4.6 800 565 12.7 738 702 21.6 751666 16 804 666 19.4 746 454 7.3 686 426 2.2 755 446 2.6 780 495 4.2 821 536 10.8 735 652 17.5 761630 13.2 813 678 18 783 454 7.3 686 428 2.3 756 448 2.6 783 496 4 828 524 9.7 740 616 14.7 767591 10.9 809 656 14.7 817 454 7.3 686 432 2.3 763 451 2.6 788 500 3.7 843 513 8.6 747 593 12.7 775572 9.6 810 635 12.6 832 454 7.3 686 438 2.3 773 454 2.6 793 502 3.7 846 513 7.7 766 585 10.7 805558 8.8 808 600 10.5 830 454 7.3 686 443 2.4 779 459 2.7 800 512 3.4 872 525 6.8 805 596 9.3 851549 7.7 820 582 9.4 829 454 7.3 686 444 2.4 781 466 2.7 812 528 3.4 899 544 6.4 844 619 8.4 906540 7.1 821 569 8.6 829 454 7.3 686 450 2.4 792 475 2.7 827 541 3 933 569 6.1 890 643 7.6 963532 6.8 815 561 7.7 838 454 7.3 686 459 2.6 802 488 2.7 850 559 2.9 967 603 5.3 967 656 6.8 1006527 6.1 825 554 7.1 842 454 7.3 686 473 2.6 827 504 2.8 875 571 2.9 988 650 4.8 1058 662 6.5 1024523 6 821 551 6.9 842 454 7.3 686 485 2.7 845 532 2.8 924 666 2.9 1152 660 4.6 1081 667 6.2 1041521 5.9 820 549 6.7 844 454 7.3 686 499 2.7 869 565 2.8 981 700 2.9 1211 685 4.3 1133 669 6.1 1047520 5.6 826 547 6.5 846 454 7.3 686 519 2.7 904 605 2.9 1047 722 3 1245 690 4.2 1145 678 5.9 1067520 5.5 829 546 6.3 849 454 7.3 686 534 2.7 930 644 2.9 1114 755 3 1302 698 4.1 1162 682 5.8 1077525 5.4 839 546 6.2 852 454 7.3 686 588 2.7 1024 681 2.9 1178 818 3.1 1406 705 4.1 1173 687 5.6 1091529 5.4 846 546 6.2 852 454 7.3 686 633 2.8 1099 730 3 1259 847 3.1 1456 726 3.9 1216 691 5.6 1098529 5.4 846 546 6.1 854 454 7.3 686 672 2.9 1163 787 3 1357 865 3.1 1487 751 3.8 1262 692 5.6 1099534 5.3 856 546 6 857 454 7.3 686 778 2.9 1346 860 3.1 1478 878 3.1 1509 751 3.7 1266 692 5.5 1103531 5.3 851 546 6 857 454 7.3 686 745 3 1285 908 3.1 1561 924 3.2 1583 751 3.7 1266 692 5.5 1103581 5.3 931 621 5.9 978 537 7.1 816 808 3.2 1384 992 3.1 1705 830 3.4 1413 747 3.7 1259 703 5.6 1117

7/13/07 9/12/07 11/16/07 2/8/08 3/13/08 4/22/08 5/30/08 8/15/08

Lake Area Vs Depth profilesTanners Lake Lake McCarronmeters hectare meters hectare

0.00 30.61 0 27.03783.05 21.63 3.048 20.14474.57 18.28 4.572 17.410956.10 15.18 6.096 14.924259.14 7.51 9.144 11.54655

12.19 1.38 12.192 7.6261513.72 0.06 15.24 3.34125

17.3736 0.081Sweeney Lakemeters hectare Lake Gervais

0.00 25.08 meters hectare1.52 17.91 0 93.153.05 14.69 1.524 70.66444.57 11.44 3.048 61.77876.10 5.66 4.572 53.196757.62 0.46 6.096 42.4035

7.62 25.25589.144 10.0683

Parkers Lake 10.668 4.70205meters hectare 12.192 1.38915

0 40.7025 13.716 0.29971.524 32.08005 14.9352 0.02433.048 16.07854.572 10.2627 Cedar Lake6.096 6.9255 meters hectare7.62 4.45095 0 72.07785

9.144 2.16675 3.048 50.8396510.668 0.5589 4.572 44.85375

11.2776 0.02835 6.096 36.50679.144 15.8274

12.192 5.5485Ryan Lake 15.24 0.0729meters hectare

0.00 6.99 Bryant Lake1.52 4.39 meters hectare3.05 3.83 0 66.0154.57 3.27 1.524 51.4356.10 2.46 3.048 43.92637.62 1.43 4.572 34.177959.14 0.60 6.096 24.04485

10.06 0.02 9.144 5.9251512.192 1.555213.716 0.08505

ANION CHROMATOGRAPHY RESULTSSAMPLES TAKEN 11/15/07CUSTOMER: ERIC NOVOTNY - CIVIL ENGINEERING - AREA LAKESDATE: 03 - 06 - 2008ANALYST: RICK KNURRSYSTEM: DIONEX ICS-2000 Chromatograph - AS20 (4mm) - AMMS III (4mm) SuppressorCONDITIONS: NaOH gradient - 1ml/min - Suppression w/ 25 mN Sulfuric Acid - 50 ul loop

All concentrations are in ppm (ug/g)

SAMPLE DESCRIPTION Fluoride Chloride Nitrite-N Bromide Nitrate-N Sulfate Phosphate-P

Detection Limits <0.005 <0.005 <0.002 <0.005 <0.001 <0.010 <0.002BROWNIE 1 M 0.101 134.4 <0.002 0.032 0.687 4.691 0.005BROWNIE 13 M <0.005 703.7 <0.002 0.256 0.006 0.212 0.004

BRYANT 1 M 0.167 83.68 <0.002 0.034 0.953 8.701 0.052BRYANT 12 M 0.168 84.01 <0.002 0.034 0.922 8.744 0.045

CEDAR 1 M 0.100 96.44 0.002 0.028 0.585 9.915 0.013CEDAR 13.5 M 0.100 95.99 0.002 0.028 0.451 9.881 0.008

GERVAIS 1 M 0.104 109.4 0.002 0.031 0.761 12.95 0.046GERVAIS 12 M 0.104 108.6 <0.002 0.033 0.758 12.88 0.047

MCCARRON 1 M 0.075 102.3 0.022 0.057 0.302 30.05 0.011MCCARRON 15 M 0.076 102.8 0.001 0.053 0.858 30.19 <0.002

PARKERS 1 M 0.202 146.2 0.001 0.044 0.369 13.53 0.019PARKERS 10 M 0.202 146.0 <0.002 0.043 0.315 13.53 0.009

RYAN 1 M 0.089 82.29 0.001 0.019 1.683 5.731 0.083RYAN 10 M 0.091 83.01 0.005 0.019 1.697 5.787 0.107

SWEENY 1 M 0.109 125.6 0.001 0.112 0.522 36.00 <0.002SWEENY 7 M 0.110 127.7 0.001 0.116 0.507 36.71 <0.002

TANNERS 1 M 0.093 132.0 0.015 0.025 0.648 15.35 0.095TANNERS 12.5 M 0.092 131.5 0.004 0.026 0.493 15.38 0.080

CATION CHROMATOGRAPHY RESULTSSAMPLES TAKEN 11/15/07CUSTOMER: ERIC NOVOTNY - CIVIL ENGINEERING - AREA LAKESDATE: 03 - 06 - 2008ANALYST: RICK KNURRSYSTEM: DIONEX ICS-2000 Chromatograph - CS16 (4mm) - CSRS Ultra II (4mm) Suppressor CONDITIONS: 25 mM Methane sulfonic acid eluent - 1ml/min - AutoSuppression - 100 ul loop

All concentrations are in ppm (ug/g)

SAMPLE DESCRIPTION Lithium Sodium Ammonium Potassium Magnesium Calcium Strontium

Detection Limits <0.0001 <0.002 <0.005 <0.002 <0.005 <0.005 <0.005BROWNIE 1 M 0.0070 84.55 0.117 2.345 3.946 19.14 0.023BROWNIE 13 M 0.0223 419.8 55.38 12.46 12.87 60.22 0.128

BRYANT 1 M 0.0043 48.18 0.377 2.974 15.31 41.16 0.048BRYANT 12 M 0.0041 47.22 0.127 2.992 15.44 41.40 0.054

CEDAR 1 M 0.0163 58.88 0.133 3.102 8.911 36.25 0.044CEDAR 13.5 M 0.0164 58.78 0.116 3.829 8.716 37.14 0.044

GERVAIS 1 M 0.0041 58.53 0.128 2.767 11.86 41.80 0.043GERVAIS 12 M 0.0044 59.44 0.116 2.872 12.09 42.49 0.038

MCCARRON 1 M 0.0036 53.64 1.389 3.273 15.62 46.23 0.051MCCARRON 15 M 0.0039 53.05 0.958 3.304 15.52 45.84 0.058

PARKERS 1 M 0.0094 91.33 0.117 2.400 14.83 36.30 0.057PARKERS 10 M 0.0097 92.04 0.107 2.371 14.94 36.44 0.046

RYAN 1 M 0.0026 51.47 0.135 3.116 6.282 42.59 0.027RYAN 10 M 0.0023 51.46 0.123 3.100 6.246 42.78 0.024

SWEENY 1 M 0.1281 55.56 0.129 3.454 24.72 75.13 0.073SWEENY 7 M 0.1342 56.49 0.112 3.483 25.41 77.92 0.067

TANNERS 1 M 0.0027 68.88 0.114 3.173 13.95 44.46 0.049TANNERS 12.5 M 0.0028 69.23 0.117 3.143 13.94 44.23 0.045

ANION CHROMATOGRAPHY RESULTSSAMPLES TAKEN 2/22/2007CUSTOMER: ERIC NOVOTNY - CIVIL ENGINEERINGDATE: 03 - 22 - 2007ANALYST: RICK KNURRSYSTEM: DIONEX ICS-2000 Chromatograph - AS20 (4mm) - Atlas Anion ES (4mm) CONDITIONS: KOH gradient - 1ml/min - External Water Mode - 50 ul loop

All concentrations are in ppm (ug/g)

SAMPLE DESCRIPTION Fluoride Chloride Nitrite-N Bromide Nitrate-N Sulfate Phosphate-P

Detection Limits <0.005 <0.005 <0.002 <0.005 <0.001 <0.010 <0.002PARKERS 1 M 0.221 144.7 0.004 0.041 0.08 14.10 0.008PARKERS 10 M 0.239 307.4 0.014 0.061 0.19 19.48 0.038MCCARRONS 1 M 0.065 105.3 0.008 0.055 0.05 38.60 0.006MCCARRONS 14 M 0.067 140.9 0.006 0.072 0.02 36.35 0.004SWEENY 1 M 0.119 189.8 0.006 0.153 0.17 55.51 0.004SWEENY 6.5 M 0.117 194.2 0.008 0.157 0.17 56.73 0.005TANNERS 1 M 0.081 140.8 0.007 0.034 0.34 15.17 0.039TANNERS 12 M 0.089 195.7 0.008 0.045 0.43 15.68 0.045GERVAIS 1 M 0.104 132.0 0.021 0.042 0.09 13.50 0.028GERVAIS 12.5 M 0.103 135.1 0.010 0.047 0.03 15.96 0.074BROWNIE 1 M 0.090 185.8 0.009 0.042 0.30 5.680 0.012BROWNIE 12.5 M 0.112 614.8 0.005 0.192 0.01 1.717 0.005BRYANT 1 M 0.167 79.48 0.021 0.039 0.22 7.798 0.003BRYANT 12 M 0.177 101.4 0.004 0.045 0.04 10.07 0.002RYAN 1 M 0.087 99.39 0.014 0.019 0.31 5.574 0.066RYAN 10 M 0.089 186.0 0.037 0.041 0.10 4.047 0.312CEDAR 1 M 0.093 104.8 0.051 0.036 0.27 10.73 0.025CEDAR 12 M 0.094 103.5 0.014 0.038 0.09 10.78 0.033

Sediment core samples (depth in cm)MCCARRONS 0 - 4 0.092 118.6 <0.010 0.117 0.162 77.76 0.014MCCARRONS 28 - 32 0.104 69.60 <0.010 0.096 0.077 17.09 0.007MCCARRONS 60 - 64 0.087 57.58 <0.010 0.172 0.076 3.553 0.009MCCARRONS 92 - 96 0.057 41.92 <0.010 0.166 0.067 1.899 <0.010MCCARRONS 116 - 120 0.063 34.15 <0.010 0.179 0.104 3.044 <0.010

Sediment core samples (depth in cm)TANNERS 0 - 4 0.167 409.4 0.014 0.106 0.220 35.91 0.044TANNERS 28 - 32 0.151 217.3 <0.010 0.127 0.069 4.637 0.012TANNERS 60 - 64 0.103 146.1 <0.010 0.116 0.112 1.525 0.008TANNERS 92 - 96 0.079 88.02 <0.010 0.115 0.077 0.929 <0.010TANNERS 116 - 120 0.078 77.73 <0.010 0.108 0.063 3.380 <0.010

CATION CHROMATOGRAPHY RESULTSSAMPLES TAKEN 2/22/2007CUSTOMER: ERIC NOVOTNY - CIVIL ENGINEERINGDATE: 03 - 22 - 2007ANALYST: RICK KNURRSYSTEM: DIONEX ICS-2000 Chromatograph - CS16 (4mm) - Atlas Cation ES (4mm) CONDITIONS: 25 mM Methane sulfonic acid - 1ml/min - External Water Mode - 25 ul loop

All concentrations are in ppm (ug/g)

SAMPLE DESCRIPTION Lithium Sodium Ammonium Potassium Magnesium Calcium

Detection Limits <0.0001 <0.002 <0.005 <0.002 <0.005 <0.005PARKERS 1 M 0.0079 96.56 0.263 2.629 17.33 33.87PARKERS 10 M 0.0074 203.8 0.829 2.853 20.67 50.90MCCARRONS 1 M 0.0020 53.11 0.999 3.403 16.73 47.62MCCARRONS 14 M 0.0031 75.93 2.061 3.490 18.65 58.27SWEENY 1 M 0.1550 86.88 0.731 4.194 37.58 108.8SWEENY 6.5 M 0.1464 123.5 0.748 4.312 37.38 107.3TANNERS 1 M <0.0005 85.77 0.526 3.542 16.91 51.52TANNERS 12 M <0.0005 104.8 0.400 3.434 16.42 51.41GERVAIS 1 M <0.0005 73.14 0.786 3.122 15.34 48.50GERVAIS 12.5 M <0.0005 71.06 1.975 3.243 18.51 57.60BROWNIE 1 M 0.0041 113.3 0.793 2.883 4.690 20.61BROWNIE 12.5 M 0.0143 366.9 36.22 9.988 10.61 48.71BRYANT 1 M 0.0033 48.82 0.676 3.234 18.07 43.39BRYANT 12 M 0.0039 55.70 2.148 3.226 17.57 45.44RYAN 1 M <0.0005 63.35 4.120 4.038 7.661 50.60RYAN 10 M <0.0005 122.7 7.184 4.409 7.775 50.69CEDAR 1 M 0.0142 66.58 1.839 3.772 10.01 40.90CEDAR 12 M 0.0142 60.41 1.267 3.416 9.490 38.92

Sediment core samples (depth in cm)MCCARRONS 0 - 4 <0.0005 69.81 39.84 6.393 26.45 103.2MCCARRONS 28 - 32 <0.0005 36.07 42.79 5.724 17.88 62.05MCCARRONS 60 - 64 <0.0005 31.79 52.79 5.582 27.20 84.51MCCARRONS 92 - 96 <0.0005 19.53 51.85 4.652 19.83 62.76MCCARRONS 116 - 120 <0.0005 13.54 49.74 4.105 13.38 47.15

Sediment core samples (depth in cm)TANNERS 0 - 4 <0.0005 247.4 18.66 6.690 20.35 73.96TANNERS 28 - 32 <0.0005 128.8 38.33 6.918 17.21 66.66TANNERS 60 - 64 <0.0005 71.44 37.76 5.122 14.21 62.01TANNERS 92 - 96 <0.0005 47.59 43.13 5.323 14.26 72.27TANNERS 116 - 120 <0.0005 36.07 42.67 5.190 13.54 63.68

Waster water treatmentplant effluent data

Date LocationsChloride (mg/L)

Sodium (mg/L)

6/20/07 BLUE_LAKE 401 2857/3/07 BLUE_LAKE 418 2927/25/07 BLUE_LAKE 396 2748/1/07 BLUE_LAKE 400 2878/8/07 BLUE_LAKE 386 2908/22/07 BLUE_LAKE 308 2499/5/07 BLUE_LAKE 366 2839/19/07 BLUE_LAKE 403 29610/3/07 BLUE_LAKE 368 27210/17/07 BLUE_LAKE 381 26310/31/07 BLUE_LAKE 370 27511/14/07 BLUE_LAKE 365 27611/28/07 BLUE_LAKE 397 27612/12/07 BLUE_LAKE 414 30112/26/07 BLUE_LAKE 426 3181/9/08 BLUE_LAKE 410 2841/23/08 BLUE_LAKE 369 2862/6/08 BLUE_LAKE 389 2852/20/08 BLUE_LAKE 364 3193/5/08 BLUE_LAKE 395 2963/19/08 BLUE_LAKE 412 2874/2/08 BLUE_LAKE 393 2714/16/08 BLUE_LAKE 360 2424/30/08 BLUE_LAKE 344 2235/14/08 BLUE_LAKE 374 2435/28/08 BLUE_LAKE 408 2616/11/08 BLUE_LAKE 2496/25/08 BLUE_LAKE 384 2437/9/08 BLUE_LAKE 390 2487/23/08 BLUE_LAKE 392 62.68/6/08 BLUE_LAKE 385 2918/20/08 BLUE_LAKE 382 2429/3/08 BLUE_LAKE 435 2779/17/08 BLUE_LAKE 418 27810/1/08 BLUE_LAKE 377 28410/15/08 BLUE_LAKE 416 30810/29/08 BLUE_LAKE 410 30911/12/08 BLUE_LAKE 430 3026/20/07 COTTAGE_GR 353 2567/3/07 COTTAGE_GR 340 2517/25/07 COTTAGE_GR 342 2518/1/07 COTTAGE_GR 337 2618/8/07 COTTAGE_GR 347 2638/22/07 COTTAGE_GR 307 237

9/5/07 COTTAGE_GR 315 2379/19/07 COTTAGE_GR 365 26610/3/07 COTTAGE_GR 343 25710/17/07 COTTAGE_GR 343 26210/31/07 COTTAGE_GR 348 26311/14/07 COTTAGE_GR 330 26311/28/07 COTTAGE_GR 368 26312/12/07 COTTAGE_GR 389 28112/26/07 COTTAGE_GR 376 2761/9/08 COTTAGE_GR 376 2551/23/08 COTTAGE_GR 335 2472/6/08 COTTAGE_GR 351 2722/20/08 COTTAGE_GR 327 2653/5/08 COTTAGE_GR 322 2503/19/08 COTTAGE_GR 372 2654/2/08 COTTAGE_GR 372 2634/16/08 COTTAGE_GR 350 2474/30/08 COTTAGE_GR 336 2515/14/08 COTTAGE_GR 330 2385/28/08 COTTAGE_GR 336 2456/11/08 COTTAGE_GR 302 2166/25/08 COTTAGE_GR 356 2277/9/08 COTTAGE_GR 356 2187/23/08 COTTAGE_GR 337 54.68/6/08 COTTAGE_GR 334 2458/20/08 COTTAGE_GR 376 2459/3/08 COTTAGE_GR 342 2419/17/08 COTTAGE_GR 387 25910/1/08 COTTAGE_GR 388 26910/15/08 COTTAGE_GR 366 26210/29/08 COTTAGE_GR 336 24111/12/08 COTTAGE_GR 370 2676/20/07 METRO 246 1897/3/07 METRO 209 1667/11/07 METRO 248 1877/24/07 METRO 223 1737/25/07 METRO 232 1807/26/07 METRO 238 1877/27/07 METRO 234 1967/30/07 METRO 217 1877/31/07 METRO 218 1858/1/07 METRO 232 1958/2/07 METRO 239 2028/3/07 METRO 234 1968/6/07 METRO 206 1708/7/07 METRO 220 1718/8/07 METRO 228 1888/22/07 METRO 211 1809/5/07 METRO 200 180

9/19/07 METRO 223 19410/3/07 METRO 226 18310/17/07 METRO 225 17510/31/07 METRO 251 19411/14/07 METRO 232 19211/28/07 METRO 255 18712/12/07 METRO 268 20512/26/07 METRO 260 1961/9/08 METRO 266 2071/23/08 METRO 270 1702/6/08 METRO 268 2072/20/08 METRO 248 1983/5/08 METRO 272 1893/19/08 METRO 278 1944/2/08 METRO 297 2244/16/08 METRO 248 1844/30/08 METRO 248 1745/14/08 METRO 263 1725/28/08 METRO 232 1586/11/08 METRO 240 1756/25/08 METRO 244 1747/9/08 METRO 240 6337/23/08 METRO 242 1678/6/08 METRO 248 1838/20/08 METRO 258 1869/3/08 METRO 208 1629/17/08 METRO 270 18710/1/08 METRO 269 20010/15/08 METRO 230 18610/29/08 METRO 232 19611/12/08 METRO 244 1996/20/07 SENECA 298 4507/3/07 SENECA 274 3907/25/07 SENECA 274 4208/1/07 SENECA 273 4248/8/07 SENECA 296 4828/22/07 SENECA 235 3989/5/07 SENECA 249 3749/19/07 SENECA 291 46210/3/07 SENECA 263 39310/17/07 SENECA 265 48610/31/07 SENECA 257 39211/14/07 SENECA 278 34811/28/07 SENECA 278 44112/12/07 SENECA 294 39212/26/07 SENECA 312 4631/9/08 SENECA 292 3851/23/08 SENECA 276 4252/6/08 SENECA 294 452

2/20/08 SENECA 274 4133/5/08 SENECA 271 3363/19/08 SENECA 305 3614/2/08 SENECA 308 4434/16/08 SENECA 282 3904/30/08 SENECA 276 3425/14/08 SENECA 291 4215/28/08 SENECA 276 2806/11/08 SENECA 274 3316/25/08 SENECA 285 3187/9/08 SENECA 258 3787/23/08 SENECA 288 94.78/6/08 SENECA 291 4728/20/08 SENECA 293 4599/3/08 SENECA 293 3419/17/08 SENECA 296 46610/1/08 SENECA 305 45710/15/08 SENECA 294 49210/29/08 SENECA 240 48811/12/08 SENECA 284 547

Grab sample Sodium and chloride concentrations from the Metropolitan council

DateChloride, Filtered

Sodium, Filtered Date

Chloride, Filtered

Sodium, Filtered Date

Chloride, Filtered

Sodium, Filtered

2/8/08 43.5 2/4/08 14.4 2/6/08 40.71/10/08 38 35.8 1/7/08 15 12.3 1/9/08 43 32.811/30/07 36 28.4 11/26/07 15 11.8 11/29/07 35 26.111/2/07 24 19.6 10/29/07 13 9.63 10/31/07 21 16.510/5/07 18 12.3 10/1/07 18 15.2 10/3/07 42 32.79/27/07 35 29.7 9/24/07 18 14.2 9/26/07 45 33.29/20/07 35 30.3 9/17/07 16.8 9/18/07 56 43.39/7/07 28 24.7 9/4/07 22 17.1 9/5/07 38 30.38/23/07 16 13.9 8/20/07 21 16.4 8/22/07 52 41.78/9/07 40 42.9 8/6/07 16 14.2 8/8/07 55 47.27/27/07 35 39.5 7/23/07 19 14.6 7/25/07 43 40.77/13/07 27 34.2 7/9/07 12 7/10/07 33 31.26/29/07 22 26.3 6/25/07 11 9.42 6/27/07 29 23.46/14/07 22 23.7 6/11/07 8 7.64 6/13/07 22 20.16/8/07 23 22.3 6/4/07 11 8.77 6/6/07 23 195/18/07 24 25.3 5/14/07 15 9 5/16/07 25 21.15/4/07 24 25.4 4/30/07 12 7.8 5/2/07 22 17.34/20/07 21 18.9 4/16/07 16 9.02 4/18/07 23 174/6/07 20 12.8 4/2/07 13 7.4 4/4/07 20 11.93/23/07 13 6.96 3/19/07 11.9 3/21/07 11.23/9/07 56 50.1 3/5/07 25 21.1 3/6/07 79 56.22/16/07 52 50.9 2/12/07 36 25 2/14/07 60 492/7/07 50 44.5 1/29/07 19 15.7 2/1/07 60 44.31/5/07 45 42.4 1/4/07 24 17.5 1/2/07 55 4312/1/06 48 47 11/27/06 18.8 11/29/06 51 41.911/6/06 54 55.8 10/30/06 19 14.1 11/1/06 50 39.910/20/06 45 45.2 10/3/06 21 15.1 10/18/06 53 39.310/4/06 50 51.1 9/18/06 24 17.4 10/3/06 51 39.79/29/06 48 45.9 9/6/06 15.8 9/19/06 60 43.69/22/06 47 46.8 7/31/06 16.5 9/15/06 57 43.99/5/06 45.6 7/17/06 19 14.5 9/15/06 58 447/31/06 38.9 7/5/06 16 12 9/8/06 52 38.97/21/06 34 32.5 6/12/06 15 9.78 9/8/06 51 38.97/12/06 32 27.8 5/31/06 19 10.6 9/1/06 51 40.87/7/06 28 24.6 5/16/06 14 8.41 9/1/06 51 416/28/06 26 19 5/2/06 18 9.45 8/25/06 57 42.16/20/06 20 12.8 4/17/06 16 8.63 8/25/06 55 42.46/14/06 22 17.6 4/4/06 7.2 8/18/06 52 39.76/9/06 28 24.4 3/15/06 8/18/06 52 40.96/2/06 26 24.5 2/27/06 18 12.3 8/11/06 51 41.15/25/06 25 22.1 2/13/06 21 12.4 8/11/06 51 40.7

Minnesota River at Jordan (Minnesota river mile 39.6)

Mississippi River at anoka (Upper Mississippi River mile

871.6)

Mississippi River at Hastings (Upper Mississippi River mile

815.6)

5/19/06 20 22.3 1/30/06 33 19.4 8/4/06 49 39.95/12/06 22 20.4 1/19/06 18 11.4 8/4/06 49 39.45/5/06 22 13.7 1/5/06 20 10.8 7/28/06 51 39.84/27/06 22 20.3 12/20/05 21 12.4 7/28/06 51 404/19/06 21 18.6 12/6/05 22 12 7/19/06 44 36.54/14/06 20 14.5 11/17/05 22 13.8 7/5/06 32 254/7/06 21 11.5 11/3/05 21 11.5 6/14/06 27 22.23/31/06 23 15.6 10/17/05 17 8.9 5/30/06 22 17.73/24/06 26 21.3 10/3/05 20 10.8 5/17/06 20 16.23/17/06 9/13/05 18 11.5 5/3/06 23 17.13/10/06 29 23.7 8/29/05 20 14.3 4/19/06 20 15.63/3/06 33 26.3 8/16/05 14 10.8 4/5/06 20 12.62/16/06 30 23.1 8/2/05 16 11.6 3/15/062/3/06 27 16.2 7/20/05 17 11.8 3/1/06 34 25.41/20/06 31 25.3 7/7/05 9.07 2/21/06 36 27.81/6/06 32 23 6/14/05 12 6.55 2/1/06 34 23.8

12/16/05 33 26.9 6/1/05 14 8.62 1/18/06 30 21.312/2/05 33 22.2 5/16/05 18 10.1 1/4/06 34 22.411/18/05 33 27.5 5/4/05 9.32 12/14/05 31 19.811/4/05 30 24.4 4/20/05 16 7.01 11/30/05 37 22.210/27/05 28 21.1 4/4/05 12 6.32 11/16/05 32 23.210/20/05 25 18.8 3/21/05 20 12 11/2/05 27 18.710/6/05 19 10.8 3/7/05 22 14.3 10/19/05 21 13.79/21/05 27 22.9 2/14/05 18 12.6 10/5/05 21 13.19/16/05 29 27 2/3/05 16 12.2 9/14/05 35 27.19/9/05 28 28.8 1/5/05 14 11 8/31/05 33 26.49/2/05 31 31.5 12/14/04 13 9.38 8/17/05 35 27.98/25/05 23 19.4 12/1/04 15 9.29 8/3/05 30 25.38/17/05 36 35.7 11/15/04 15 9.88 7/20/05 26 22.48/12/05 33 33.5 11/1/04 14 8.56 7/6/05 21 158/4/05 26 28.9 10/20/04 12 9.03 6/15/05 17 11.47/29/05 27 29.7 10/5/04 12 8.89 6/1/05 20 12.77/22/05 24 29.1 9/13/04 14 9.8 5/18/05 22 12.57/15/05 24 26.3 8/30/04 19 13.5 5/4/05 23 14.67/8/05 24 21.2 8/16/04 18 11.6 4/20/05 20 11.16/29/05 25 20.2 8/2/04 17 11.4 4/6/05 17 9.686/23/05 25 18.4 7/19/04 17 9.86 3/23/05 51 36.16/17/05 25 17.2 7/6/04 18 10.5 3/9/05 43 29.66/9/05 26 15.7 6/14/04 14 6.65 2/16/05 45 31.46/3/05 27 18.2 6/1/04 16 8.53 2/8/05 58 41.25/26/05 24 16 5/17/04 13 8.98 1/20/05 42 31.25/20/05 23 13.3 5/3/04 12 8.72 1/6/05 46 34.75/12/05 27 16.9 4/13/04 11 8.28 12/15/04 32 22.75/6/05 30 21.7 3/29/04 15 10.3 12/6/04 31 22.74/29/05 26 18.3 3/15/04 23 16.5 11/17/04 26 19.74/22/05 25 15.8 3/1/04 20 14.7 11/3/04 25 17.34/15/05 25 13.1 2/17/04 17 13.4 10/20/04 28 19.54/8/05 23 14.9 2/3/04 14 11.2 10/4/04 22 14.93/31/05 21 13.1 1/20/04 15 11.9 9/15/04 34 23.4

3/25/05 33 27.9 1/5/04 16 11.4 9/1/04 42 29.53/17/05 48 38.5 12/15/03 18 13.4 8/18/04 36 24.13/11/05 31 25.5 12/1/03 18 13.2 8/4/04 36 25.13/3/05 37 28.9 11/3/03 19 14 7/21/04 28 16.72/17/05 45 30.5 9/29/03 17 12.6 7/9/04 31 19.22/8/05 47 39.8 9/16/03 18 12 6/16/04 19 10.91/25/05 47 39.6 9/2/03 18 12.6 6/3/04 23 13.31/11/05 44 39.4 8/4/03 15 9.75 5/19/04 40 27.212/22/04 41 32.5 6/30/03 9 4.89 5/5/04 31 2212/8/04 35 27.4 6/3/03 18 8.7 4/14/04 25 18.311/22/04 36 31.6 5/27/03 17 8.48 3/31/04 29 20.211/9/04 30 22.6 5/5/03 19 8.39 3/17/04 47 32.510/21/04 29 20.9 2/18/03 16 10.4 3/3/04 70 48.810/8/04 26 17.3 2/4/03 18 13.3 2/19/04 63 46.29/16/04 33 28.5 12/2/02 18 10.4 2/5/04 59 449/2/04 33 26.9 11/18/02 19 11.2 1/26/04 55 40.18/19/04 28 20.8 11/4/02 16 9.33 1/8/04 49 35.18/12/04 10/15/02 17 12/17/03 61 46.98/5/04 27 19 9/30/02 17 9.58 12/3/03 64 43.97/22/04 26 16.4 9/16/02 16 8.69 11/19/03 50 36.77/8/04 24 15.3 9/3/02 15 7.83 11/5/03 48 36.86/17/04 18 9.82 8/19/02 13 10/15/03 51 37.76/10/04 24 8/5/02 12 7.05 10/1/03 46 33.36/4/04 16 8.72 7/1/02 10 5.34 9/17/03 42 30.25/27/04 26 14.9 6/10/02 18 10.5 9/4/03 47 35.25/20/04 48 35.7 6/3/02 16 9.88 8/20/03 35 24.45/13/04 52 39.4 4/29/02 13 8.06 8/6/03 28 20.75/7/04 48 40.6 2/19/02 14 11.6 7/16/03 18 12.14/30/04 48 43.9 2/4/02 11 10.8 7/2/03 17 10.44/22/04 44 39.8 1/22/02 10 9.84 6/18/03 26 174/15/04 38 35.4 11/14/01 9 8.77 6/5/03 28 17.54/1/04 31 27.5 11/1/01 4 4.37 5/29/03 24 15.83/18/04 31 25.2 7/30/01 10 8.46 5/21/03 23 14.33/8/04 45 39 5/7/01 11 5.88 5/7/03 28 17.42/25/04 79 70 4/30/01 9 4.98 4/16/03 33 23.42/20/04 65 59.4 2/20/01 10 4/2/03 31 20.12/13/04 70 66.7 2/9/01 13 10.9 3/19/03 85 60.22/6/04 70 65.6 1/16/01 9.96 3/5/03 51 32.31/30/04 70 64.6 11/17/00 9 7.4 2/20/03 51 29.51/23/04 73 65.7 9/18/00 11 9.09 2/6/03 61 43.41/16/04 71 66.4 7/31/00 14 9.4 1/23/03 40 29.91/9/04 70 65.3 5/1/00 17 11.7 1/8/03 32 25.1

12/30/03 63 59.2 2/9/00 13 11.6 12/18/02 36 25.712/23/03 66 62.4 12/4/02 34 2212/11/03 69 67.7 11/20/02 28 19.612/5/03 70 65.1 11/12/02 28 19.511/25/03 63 62.6 10/16/02 22 13.211/21/03 59 59.5 10/2/02 31 20.711/13/03 60 59 9/18/02 23 14.4

11/7/03 63 61.6 9/5/02 22 13.510/30/03 60 53.2 8/21/02 21 14.710/17/03 58 52.8 8/7/02 18 1210/3/03 57 55.5 7/17/02 16 11.59/19/03 45 39.3 7/2/02 17 129/5/03 41 41.2 6/26/02 20 12.48/22/03 36 31.5 6/12/02 27 18.58/7/03 30 28.1 6/5/02 28 19.67/18/03 25 18.8 5/15/02 22 15.67/3/03 25 16.3 5/1/02 22 16.36/20/03 28 4/17/02 16 12.76/6/03 29 21.1 4/3/02 30 21.15/30/03 29 20.9 3/20/02 61 48.15/23/03 26 3/6/02 38 29.15/9/03 28 20.6 2/21/02 34 26.54/18/03 33 2/6/02 40 31.84/3/03 26 19.3 1/24/02 32 26.83/20/03 28 1/9/02 33 24.73/7/03 12/19/01 30 22.82/21/03 61 12/5/01 33 27.12/7/03 61 53.5 11/19/01 29 23.4

12/20/02 39 34.3 11/8/01 28 22.612/6/02 48 38.5 10/17/01 36 28.711/14/02 36 30.8 10/3/01 37 29.110/18/02 27 9/19/01 38 25.910/4/02 40 34.5 9/6/01 32 259/19/02 35 30.8 8/15/01 27 21.79/6/02 27 22.5 8/1/01 22 17.48/23/02 23 7/18/01 23 18.48/8/02 18 17.9 7/5/01 17 14.28/2/01 20 18.6 6/20/01 11 7.837/6/01 18 6/6/01 16 12.46/6/01 19 5/23/01 16 13.15/10/01 15 12.6 5/9/01 13 9.75/4/01 12 10.9 4/4/01 30 23.14/5/01 9 3/19/01 53 39.53/9/01 3/6/01 51 40.52/23/01 54 2/21/01 40 342/13/01 53.7 2/8/01 43 32.91/9/01 1/17/01 42 31.512/8/00 1/5/01 33 23.911/22/00 54 46.6 12/19/00 41 31.511/7/00 60 54.1 12/6/00 26 22.210/6/00 11/20/00 24 19.29/21/00 63 49.7 11/2/00 36 26.49/8/00 48 10/17/00 45 31.88/4/00 35 30.4 10/3/00 46 34.85/8/00 37 36.9 9/19/00 45 314/7/00 33 9/6/00 37 25.4

3/3/00 32 8/15/00 40 29.48/1/00 30 21.77/21/00 22 157/6/00 24 16.96/16/00 27 18.76/2/00 26 175/17/00 21 17.35/2/00 30 23.74/18/00 24 19.84/4/00 28 21.13/14/00 24 17.82/29/00 49 40.62/15/00 39 31.52/3/00 36 281/27/00 34 26.41/4/00 39 29.9

Chloride data (mg/L) from 10 streams located in the TCMA

DateBasset Creek Date

Battle Creek Date

Bluff Creek Date

Carver Creek Date

Credit River Date

Fish Creek Date

Minnehaha Creek Date

Nine Mile Date

Riley Creek Date

Shingle Creek

1/24/01 186 9/18/01 108 1/6/00 55 1/4/00 24 7/7/00 36 7/22/01 67 1/12/01 105 1/6/00 133 1/12/01 471/29/01 1031 4/12/02 177 2/2/00 49 2/2/00 24 7/12/00 30 9/18/01 106 1/30/01 192 2/25/00 122 1/29/01 44 3/7/01 8043/30/01 148 5/5/02 139 2/28/00 71 2/25/00 35 10/4/00 36 12/6/01 125 3/6/01 1166 2/26/00 182 1/30/01 148 4/3/01 161

4/3/01 140 6/3/02 101 5/9/00 61 2/28/00 38 11/8/00 60 4/12/02 121 3/20/01 169 4/12/00 132 3/30/01 55 5/2/01 884/6/01 108 6/7/02 94 6/4/00 51 3/6/00 47 11/29/00 53 5/9/02 170 3/30/01 181 4/19/00 60 4/2/01 69 6/26/01 1174/9/01 99 6/18/02 139 6/20/00 58 5/18/00 43 1/9/01 72 6/7/02 120 4/3/01 201 5/8/00 101 4/3/01 71 7/23/01 64

4/12/01 96 6/19/02 106 7/5/00 63 5/31/00 59 2/22/01 52 6/18/02 134 4/5/01 167 5/17/00 41 4/6/01 58 8/6/01 1054/16/01 105 6/21/02 95 7/9/00 38 6/4/00 68 3/6/01 113 6/21/02 59 4/9/01 148 5/18/00 103 4/11/01 51 9/27/01 804/21/01 83 7/3/02 83 10/6/00 58 8/1/00 26 3/14/01 147 7/10/02 56 4/12/01 137 5/30/00 68 5/24/01 66 10/17/01 1454/24/01 91 7/6/02 61 11/15/00 72 8/23/00 43 3/21/01 119 7/18/02 62 4/21/01 108 6/4/00 27 6/1/01 68 11/27/01 1035/25/01 76 7/10/02 43 1/3/01 59 10/6/00 23 3/27/01 69 7/24/02 59 4/23/01 91 6/15/00 37 6/11/01 50 12/19/01 1696/13/01 68 7/16/02 95 2/26/01 61 11/13/00 55 3/29/01 55 7/26/02 85 4/25/01 92 6/20/00 65 6/13/01 31 1/23/02 351

7/3/01 102 7/20/02 71 3/28/01 113 1/3/01 38 4/2/01 47 8/3/02 45 4/27/01 95 6/21/00 13 6/22/01 66 2/14/02 2987/17/01 75 7/24/02 59 4/4/01 71 3/9/01 25 4/4/01 39 8/13/02 79 5/1/01 112 7/6/00 67 7/5/01 61 3/8/02 5157/23/01 74 7/27/02 64 4/11/01 58 3/27/01 52 4/6/01 39 8/16/02 43 5/5/01 73 7/7/00 18 8/6/01 37 3/11/02 1690

8/1/01 86 8/3/02 41 4/12/01 61 4/2/01 65 4/9/01 34 8/20/02 42 5/9/01 64 7/9/00 19 8/18/01 29 3/11/02 20208/14/01 92 8/13/02 100 11/13/01 58 4/6/01 46 4/13/01 30 9/5/02 33 5/17/01 57 7/9/00 36 9/6/01 38 3/12/02 13908/29/01 90 8/13/02 100 12/3/01 91 4/6/01 54 4/16/01 30 10/2/02 82 5/20/01 50 7/13/00 36 9/7/01 17 4/16/02 131

9/4/01 104 8/20/02 39 12/19/01 59 4/9/01 52 4/19/01 37 11/8/02 97 5/23/01 51 7/25/00 13 9/20/01 34 5/8/02 629/7/01 49 8/27/02 76 1/16/02 58 4/9/01 52 4/23/01 30 12/18/02 117 5/29/01 59 7/26/00 43 9/22/01 22 6/13/02 82

9/19/01 92 8/29/02 47 2/6/02 55 4/13/01 43 4/26/01 30 2/27/03 116 6/4/01 55 8/8/00 10 10/2/01 40 7/22/02 1039/22/01 53 10/2/02 92 3/5/02 58 4/17/01 43 5/1/01 35 3/27/03 88 6/5/01 54 8/21/00 49 11/2/01 37 9/11/02 7410/1/01 93 11/8/02 105 3/13/02 235 4/17/01 43 5/6/01 42 4/16/03 96 6/11/01 52 9/5/00 48 12/11/01 45 10/9/02 5711/2/01 116 12/18/02 176 3/29/02 103 4/19/01 40 5/8/01 42 5/4/03 127 6/18/01 56 9/21/00 70 1/22/02 38 11/14/02 161

11/26/01 106 2/27/03 542 3/29/02 84 4/23/01 35 5/18/01 43 5/9/03 114 7/3/01 53 11/6/00 31 2/15/02 41 12/30/02 19111/26/01 199 3/27/03 167 4/4/02 120 4/26/01 33 5/20/01 41 6/12/03 113 7/22/01 48 11/8/00 59 3/11/02 54 1/13/03 22812/3/01 139 5/22/03 108 4/11/02 111 5/1/01 33 5/26/01 34 6/25/03 77 8/13/01 52 11/29/00 102 3/19/02 66 2/11/03 325

1/2/02 152 6/5/03 91 4/17/02 94 5/3/01 32 6/1/01 43 7/18/03 94 8/18/01 49 1/10/01 227 3/27/02 49 4/10/03 1562/1/02 178 6/12/03 137 4/28/02 125 5/8/01 32 6/11/01 47 8/15/03 115 8/29/01 51 3/6/01 339 3/29/02 64 5/8/03 1503/1/02 232 6/17/03 129 5/8/02 92 5/14/01 34 6/13/01 23 8/20/03 81 9/4/01 54 3/14/01 544 4/6/02 58 6/18/03 152

3/12/02 660 6/24/03 53 5/9/02 93 5/25/01 36 6/13/01 23 9/10/03 118 9/7/01 51 3/29/01 171 4/17/02 66 7/23/03 1333/13/02 522 7/16/03 105 5/22/02 73 5/25/01 37 6/15/01 26 9/11/03 21 9/22/01 50 4/2/01 168 4/26/02 65 8/5/03 169

4/9/02 161 7/18/03 117 6/5/02 95 6/13/01 31 6/20/01 29 9/18/03 46 10/2/01 63 4/4/01 148 5/8/02 61 9/23/03 1545/21/02 118 8/15/03 120 6/21/02 22 6/13/01 27 7/10/01 40 10/12/03 78 11/1/01 70 4/7/01 98 5/30/02 65 10/28/03 1735/21/02 118 8/20/03 102 6/22/02 39 6/15/01 33 7/25/01 44 10/30/03 111 11/24/01 61 4/13/01 97 6/4/02 49 11/13/03 1656/11/02 67 9/10/03 122 6/25/02 44 6/18/01 33 8/16/01 48 11/21/03 114 11/26/01 85 4/22/01 70 6/19/02 66 12/15/03 4526/17/02 115 9/11/03 69 7/10/02 43 6/28/01 33 9/6/01 43 12/10/03 127 12/3/01 115 4/24/01 71 6/24/02 63 1/20/04 3596/19/02 82 9/18/03 65 7/11/02 52 7/10/01 33 10/2/01 44 1/13/04 121 1/2/02 192 5/6/01 32 7/3/02 58 2/24/04 13206/21/02 64 10/11/03 125 8/3/02 24 7/25/01 31 10/22/01 42 3/12/04 126 2/1/02 166 5/7/01 84 7/5/02 72 4/14/04 2136/24/02 79 10/28/03 103 8/4/02 44 8/14/01 28 11/16/01 38 3/17/04 108 3/1/02 193 5/23/01 74 7/10/02 41 5/17/04 586/26/02 86 10/30/03 113 8/16/02 25 9/5/01 25 11/21/01 39 4/15/04 134 3/12/02 231 6/11/01 33 8/19/02 60 6/2/04 737/10/02 46 11/21/03 121 8/18/02 37 10/2/01 26 12/19/01 43 4/18/04 155 3/27/02 272 6/13/01 38 9/5/02 68 7/12/04 497/16/02 94 12/10/03 659 8/22/02 28 10/22/01 23 1/15/02 77 4/21/04 135 4/9/02 261 6/13/01 32 10/4/02 31 8/25/04 1477/20/02 88 1/13/04 512 9/6/02 16 11/13/01 22 2/6/02 56 5/20/04 135 4/10/02 218 6/20/01 45 10/24/02 61 9/28/04 1017/24/02 49 2/19/04 1285 9/18/02 60 12/19/01 40 3/6/02 52 5/20/04 99 4/27/02 238 7/11/01 101 11/25/02 40 11/16/04 1357/28/02 56 3/12/04 242 10/4/02 41 1/16/02 30 3/13/02 220 5/27/04 126 5/5/02 190 8/16/01 98 12/30/02 39 1/25/05 663

8/8/02 85 3/17/04 287 10/7/02 46 2/6/02 25 3/29/02 39 5/29/04 112 5/8/02 150 8/29/01 8 1/30/03 38 3/15/05 3378/16/02 56 3/25/04 142 10/10/02 50 3/5/02 43 4/4/02 47 6/5/04 119 5/11/02 135 9/6/01 80 3/5/03 38 5/11/05 1448/20/02 40 4/6/04 218 11/19/02 66 3/29/02 41 4/17/02 50 6/9/04 95 5/21/02 143 9/7/01 24 3/15/03 71 7/15/05 163

9/5/02 85 4/15/04 216 12/5/02 63 4/3/02 51 5/8/02 64 6/11/04 97 5/21/02 143 9/7/01 9 3/27/03 60 9/9/05 569/25/02 72 4/18/04 145 12/18/02 62 4/17/02 65 5/21/02 57 6/29/04 118 5/28/02 82 9/10/01 61 4/10/03 62 10/13/05 8910/2/02 83 4/20/04 163 1/7/03 58 5/9/02 72 6/4/02 40 7/11/04 89 6/4/02 74 9/22/01 14 4/15/03 71 11/7/05 15910/4/02 52 4/25/04 166 2/13/03 58 5/11/02 70 6/21/02 26 7/30/04 117 6/6/02 67 9/24/01 61 5/5/03 62 12/22/05 283

10/10/02 66 5/9/04 115 3/17/03 133 5/22/02 69 6/22/02 27 9/5/04 41 6/10/02 61 10/4/01 65 5/9/03 51 1/12/06 38711/12/02 100 5/12/04 143 4/2/03 88 6/21/02 32 6/24/02 29 10/24/04 112 6/17/02 72 10/10/01 43 5/10/03 46 2/23/06 27812/2/02 122 5/21/04 161 4/18/03 99 6/22/02 49 7/11/02 33 10/28/04 52 6/19/02 68 10/22/01 84 5/19/03 54 3/23/06 5041/10/03 135 5/26/04 127 5/1/03 80 6/25/02 41 7/29/02 32 10/29/04 91 6/21/02 49 11/16/01 92 6/6/03 52 4/6/06 1433/11/03 265 5/29/04 112 5/11/03 51 6/28/02 35 8/4/02 18 11/19/04 110 6/21/02 51 11/24/01 15 6/13/03 64 4/20/06 1553/17/03 187 6/5/04 88 5/12/03 60 7/10/02 29 8/6/02 22 11/23/04 129 6/24/02 45 12/5/01 88 6/25/03 27 5/1/06 87

4/2/03 142 6/8/04 70 6/27/03 56 7/11/02 31 8/9/02 24 12/17/04 145 7/10/02 48 12/17/01 124 7/3/03 38 5/4/06 1124/16/03 135 6/11/04 103 7/15/03 42 7/19/02 28 8/21/02 14 3/30/05 111 7/15/02 57 1/15/02 150 7/14/03 22 5/12/06 74

5/2/03 115 6/11/04 64 7/21/03 58 7/28/02 20 8/22/02 20 4/12/05 130 7/20/02 54 2/7/02 188 7/29/03 60 5/18/06 1155/9/03 95 6/23/04 99 8/5/03 59 8/3/02 14 9/9/02 26 4/25/05 155 7/24/02 51 3/6/02 208 8/26/03 37 6/14/06 216

5/19/03 54 6/29/04 141 9/10/03 57 8/4/02 26 9/18/02 39 5/12/05 123 7/28/02 45 3/29/02 278 9/12/03 24 6/28/06 1396/3/03 103 7/3/04 110 10/29/03 59 8/6/02 22 9/26/02 33 5/18/05 117 8/8/02 53 4/11/02 101 10/3/03 38 7/17/06 2236/6/03 94 7/6/04 89 11/25/03 59 8/8/02 23 10/4/02 18 5/31/05 154 8/16/02 46 4/12/02 158 10/11/03 40 7/19/06 187

6/25/03 30 7/11/04 53 12/17/03 61 8/16/02 20 10/4/02 24 6/5/05 148 8/20/02 39 4/12/02 188 10/31/03 39 7/26/06 1686/27/03 72 7/21/04 130 1/13/04 57 8/18/02 22 10/8/02 24 6/8/05 101 9/5/02 52 5/5/02 87 12/3/03 41 8/2/06 867/14/03 91 7/28/04 137 2/12/04 57 8/21/02 18 10/14/02 29 6/13/05 116 9/5/02 43 5/8/02 40 1/6/04 41 8/14/06 90

8/5/03 54 7/30/04 132 3/2/04 95 8/22/02 19 11/15/02 40 6/20/05 131 9/6/02 43 5/8/02 113 2/3/04 38 8/17/06 1449/5/03 129 7/30/04 145 3/10/04 96 8/28/02 21 12/5/02 50 6/27/05 84 9/13/02 53 5/8/02 111 2/26/04 57 8/23/06 100

9/12/03 76 8/7/04 151 3/18/04 94 9/18/02 26 12/18/02 55 6/29/05 98 10/2/02 48 5/21/02 129 3/1/04 63 9/7/06 7710/2/03 98 8/16/04 107 3/28/04 97 10/5/02 29 1/7/03 49 7/23/05 72 10/4/02 42 5/22/02 36 3/25/04 52 9/8/06 8011/6/03 149 8/22/04 103 4/19/04 118 10/7/02 31 2/6/03 61 7/25/05 75 10/10/02 47 5/28/02 14 4/1/04 52 9/22/06 11812/8/03 239 8/29/04 64 4/21/04 107 10/14/02 33 3/17/03 59 7/29/05 122 11/12/02 47 6/2/02 29 4/18/04 50

1/9/04 218 8/31/04 107 5/6/04 64 11/19/02 35 4/2/03 45 8/4/05 77 12/2/02 48 6/3/02 60 4/21/04 572/19/04 481 9/5/04 38 5/17/04 34 12/5/02 39 4/9/03 49 8/9/05 69 1/10/03 88 6/4/02 40 5/4/04 52

3/1/04 255 9/13/04 89 5/23/04 58 12/18/02 40 4/17/03 67 8/26/05 62 3/11/03 110 6/6/02 57 5/9/04 473/5/04 293 9/23/04 100 5/27/04 49 1/7/03 40 4/22/03 43 8/31/05 91 3/18/03 284 6/11/02 31 5/17/04 33

3/19/04 227 9/30/04 123 5/29/04 42 2/13/03 36 5/5/03 50 9/3/05 76 4/2/03 202 6/19/02 23 5/22/04 593/26/04 145 10/1/04 112 5/30/04 34 3/17/03 51 5/11/03 36 9/12/05 75 4/16/03 186 6/21/02 33 5/23/04 44

4/5/04 211 10/7/04 107 6/2/04 61 4/16/03 44 5/13/03 29 9/21/05 71 5/2/03 165 6/22/02 57 5/31/04 664/18/04 145 10/14/04 149 6/9/04 44 4/21/03 46 5/21/03 36 9/30/05 93 5/8/03 88 6/24/02 51 6/3/04 70

5/9/04 134 10/23/04 123 6/10/04 42 4/24/03 46 6/6/03 33 10/28/05 83 5/19/03 66 7/3/02 24 6/30/04 605/17/04 108 10/28/04 65 6/12/04 30 5/1/03 46 6/24/03 35 11/30/05 98 6/3/03 54 7/10/02 47 7/30/04 585/24/04 114 10/29/04 58 7/9/04 69 5/6/03 45 7/3/03 32 12/30/05 104 6/4/03 50 7/13/02 57 9/1/04 415/26/04 135 11/19/04 89 7/11/04 35 5/11/03 43 7/3/03 31 1/31/06 89 6/6/03 47 7/20/02 13 9/5/04 175/27/04 91 11/23/04 116 8/2/04 63 5/13/03 44 7/15/03 45 2/28/06 130 6/25/03 32 7/25/02 43 9/14/04 14

6/2/04 98 11/27/04 235 8/25/04 65 5/15/03 45 7/15/03 42 3/29/06 113 6/27/03 42 7/28/02 16 9/30/04 426/12/04 76 12/17/04 219 9/15/04 48 5/19/03 43 7/25/03 47 4/27/06 160 7/14/03 58 8/3/02 29 11/3/04 426/18/04 98 1/31/05 1184 9/16/04 51 5/22/03 40 8/6/03 46 5/3/06 152 8/5/03 60 8/13/02 50 11/30/04 45

7/2/04 117 2/28/05 523 10/14/04 64 5/27/03 39 8/14/03 46 5/8/06 114 8/29/03 66 8/16/02 16 12/30/04 1437/6/04 87 3/30/05 178 10/27/04 63 10/13/03 22 9/5/03 46 5/12/06 124 9/5/03 70 8/18/02 38 1/28/05 55

7/28/04 100 4/11/05 185 12/6/04 72 10/29/03 23 9/12/03 32 5/24/06 146 9/12/03 63 8/20/02 21 2/25/05 478/10/04 127 4/16/05 122 1/20/05 62 11/12/03 23 10/21/03 45 6/5/06 81 10/2/03 65 9/5/02 10 5/4/05 619/14/04 64 4/25/05 190 2/15/05 135 11/25/03 29 11/18/03 38 6/28/06 124 11/21/03 70 9/6/02 12 6/20/05 529/20/04 110 5/6/05 199 3/1/05 61 12/11/03 30 12/15/03 55 7/16/06 104 12/8/03 79 9/7/02 35 8/23/05 39

10/22/04 120 5/12/05 117 3/7/05 96 12/22/03 26 1/12/04 46 7/19/06 40 2/27/04 123 9/19/02 57 11/2/05 5810/28/04 63 5/16/05 143 3/22/05 145 1/8/04 27 2/9/04 60 7/24/06 137 3/2/04 124 10/4/02 37 1/20/06 60

11/8/04 98 5/31/05 179 3/30/05 103 1/22/04 26 3/2/04 83 7/28/06 143 3/10/04 185 10/4/02 27 5/2/06 3912/2/04 119 6/13/05 100 3/31/05 102 2/4/04 25 3/15/04 54 8/1/06 62 3/19/04 259 10/23/02 66 5/24/06 631/11/05 188 6/20/05 91 4/12/05 125 2/24/04 26 3/25/04 48 8/21/06 120 3/25/04 190 11/15/02 89 6/5/06 43

2/8/05 285 6/27/05 72 4/16/05 105 3/9/04 49 3/27/04 49 8/23/06 95 4/5/04 250 11/27/02 98 6/16/06 233/8/05 198 6/29/05 84 4/18/05 99 3/24/04 48 4/19/04 59 9/3/06 76 4/18/04 185 12/11/02 107 9/22/06 32

3/24/05 197 7/17/05 136 5/4/05 78 4/5/04 53 5/3/04 57 9/13/06 121 5/9/04 160 1/2/03 126 9/28/06 423/30/05 161 7/20/05 98 5/13/05 99 4/20/04 61 5/9/04 52 9/22/06 84 5/17/04 133 2/6/03 240 12/12/06 43

4/8/05 156 7/23/05 67 5/19/05 81 5/4/04 61 5/17/04 49 10/30/06 136 5/26/04 120 3/4/03 220 1/9/07 474/16/05 128 7/25/05 43 5/19/05 41 5/19/04 70 5/23/04 47 11/17/06 146 5/27/04 107 3/14/03 554 3/14/07 59

5/3/05 136 7/29/05 132 6/8/05 40 5/24/04 66 5/27/04 41 12/28/06 158 5/29/04 99 3/16/03 273 3/27/07 485/9/05 129 8/4/05 73 6/9/05 54 5/28/04 61 5/30/04 38 1/31/07 169 6/9/04 72 4/9/03 169 3/28/07 55

5/12/05 125 8/8/05 81 6/14/05 51 6/2/04 47 5/30/04 42 3/29/07 135 6/18/04 54 4/17/03 158 3/31/07 675/16/05 109 8/9/05 41 6/21/05 57 6/17/04 31 6/1/04 36 4/27/07 136 7/6/04 47 5/5/03 104 4/20/07 73

6/2/05 126 8/16/05 78 6/21/05 60 6/30/04 30 6/9/04 36 5/22/07 152 7/16/04 50 5/10/03 50 4/23/07 696/7/05 103 8/26/05 30 7/11/05 68 7/22/04 30 6/12/04 33 5/22/07 111 7/28/04 47 5/11/03 80 6/14/07 446/8/05 91 8/31/05 99 8/16/05 65 8/4/04 30 7/1/04 45 5/30/07 102 8/10/04 51 5/14/03 39 8/10/07 39

6/20/05 81 9/2/05 88 8/26/05 43 8/20/04 30 7/11/04 28 6/2/07 118 9/5/04 52 5/19/03 69 8/18/07 287/12/05 121 9/12/05 67 9/4/05 12 8/31/04 28 8/2/04 51 6/13/07 151 9/14/04 46 5/29/03 86 9/6/07 148/23/05 137 9/19/05 103 9/5/05 23 9/13/04 29 8/17/04 47 6/18/07 122 9/20/04 55 6/6/03 68 9/18/07 188/26/05 77 9/21/05 39 9/6/05 21 9/22/04 31 8/30/04 50 7/8/07 90 10/22/04 67 6/24/03 81 10/5/07 16

9/3/05 47 9/24/05 56 9/8/05 42 10/5/04 33 9/16/04 33 7/18/07 64 10/28/04 61 6/25/03 50 10/18/07 499/7/05 6 9/28/05 76 9/13/05 49 10/20/04 31 10/13/04 47 7/25/07 133 11/8/04 74 6/28/03 30 11/14/07 47

9/12/05 70 9/30/05 95 9/25/05 49 11/1/04 37 10/26/04 52 7/26/07 123 11/19/04 77 7/3/03 14 2/8/08 459/21/05 89 10/4/05 51 10/4/05 12 11/17/04 39 12/1/04 50 8/11/07 60 12/2/04 89 7/4/03 4410/4/05 25 10/28/05 92 10/6/05 22 11/30/04 44 12/27/04 51 8/13/07 60 2/8/05 120 7/14/03 1110/7/05 80 11/30/05 574 11/3/05 66 12/7/04 45 1/24/05 54 8/17/07 86 3/8/05 243 7/25/03 71

10/11/05 92 12/30/05 480 11/28/05 95 12/21/04 53 2/24/05 70 8/20/07 124 3/25/05 269 8/6/03 8211/4/05 96 1/31/06 980 12/22/05 63 1/7/05 38 3/7/05 84 8/23/07 94 3/28/05 216 8/14/03 9212/9/05 142 2/28/06 304 1/18/06 95 1/20/05 32 3/26/05 50 8/27/07 65 4/8/05 203 8/20/03 121/10/06 180 3/29/06 233 2/2/06 118 2/2/05 40 3/30/05 47 8/31/07 113 4/16/05 165 9/5/03 89

2/8/06 231 4/27/06 214 3/21/06 133 2/15/05 47 3/31/05 38 9/13/07 115 5/3/05 180 9/12/03 83/10/06 254 5/3/06 166 4/2/06 88 3/1/05 60 4/16/05 59 9/18/07 74 5/12/05 147 10/21/03 973/29/06 167 5/8/06 82 4/6/06 76 3/16/05 54 5/5/05 54 9/20/07 77 5/16/05 121 11/14/03 98

4/3/06 158 5/12/06 130 5/1/06 70 3/28/05 54 5/13/05 54 9/24/07 86 6/8/05 62 12/3/03 1074/11/06 150 5/24/06 187 5/24/06 72 3/31/05 38 5/24/05 52 9/30/07 81 6/8/05 59 1/12/04 1165/19/06 106 5/25/06 128 6/22/06 75 4/14/05 53 6/6/05 55 10/5/07 91 6/20/05 52 2/18/04 4696/13/06 156 5/29/06 159 7/14/06 70 4/15/05 52 6/8/05 53 10/16/07 78 7/8/05 52 3/3/04 2506/16/06 57 6/5/06 79 8/17/06 67 4/18/05 49 6/20/05 41 10/18/07 71 8/23/05 55 3/16/04 2257/10/06 146 6/16/06 114 9/3/06 51 5/4/05 45 6/29/05 44 10/29/07 104 8/26/05 47 3/25/04 99

8/1/06 51 6/24/06 171 9/18/06 71 5/19/05 48 6/30/05 33 11/9/07 121 9/3/05 49 3/26/04 1358/16/06 96 6/26/06 144 10/26/06 70 5/20/05 48 7/5/05 47 12/20/07 130 9/7/05 57 4/14/04 1668/23/06 88 6/28/06 141 11/16/06 69 5/24/05 43 7/18/05 72 9/12/05 59 4/18/04 67

9/3/06 77 6/28/06 137 11/29/06 98 6/6/05 47 8/3/05 61 9/21/05 60 4/19/04 1429/14/06 124 7/16/06 189 12/11/06 67 6/8/05 41 8/4/05 45 10/4/05 31 4/20/04 13210/5/06 124 7/19/06 157 12/31/06 58 6/9/05 43 8/17/05 53 10/11/05 54 4/29/04 13211/2/06 143 7/24/06 114 1/25/07 68 6/13/05 41 8/23/05 53 11/4/05 51 5/9/04 2112/5/06 152 7/28/06 134 2/20/07 70 6/15/05 40 9/4/05 30 12/9/05 68 5/13/04 491/11/07 148 8/1/06 92 3/12/07 114 6/20/05 39 9/6/05 35 1/10/06 210 5/17/04 242/16/07 184 8/21/06 161 3/13/07 99 6/22/05 38 9/7/05 22 2/8/06 264 5/19/04 42

3/6/07 375 8/23/06 77 3/13/07 170 7/6/05 39 9/9/05 23 3/10/06 260 5/23/04 323/14/07 137 9/1/06 96 3/30/07 76 7/18/05 36 9/13/05 26 3/30/06 239 5/25/04 833/28/07 111 9/13/06 146 4/17/07 105 8/1/05 35 9/21/05 37 4/11/06 173 5/27/04 293/30/07 108 9/16/06 138 4/23/07 131 8/16/05 33 9/25/05 32 5/12/06 68 5/29/04 594/16/07 138 9/18/06 99 5/17/07 73 8/23/05 33 10/4/05 18 5/19/06 58 5/30/04 664/23/07 153 9/27/06 135 6/19/07 68 9/12/05 33 10/6/05 17 6/13/06 51 6/1/04 535/14/07 141 10/11/06 152 7/18/07 64 9/26/05 38 10/10/05 27 6/16/06 43 6/5/04 436/12/07 147 10/30/06 176 8/28/07 48 9/27/05 37 11/3/05 45 7/10/06 70 6/9/04 34

7/6/07 179 11/11/06 191 9/19/07 76 10/4/05 19 11/21/05 48 7/19/06 60 6/11/04 547/8/07 83 11/17/06 180 9/26/07 79 10/5/05 31 11/29/05 68 8/1/06 44 6/12/04 548/1/07 148 12/28/06 334 10/5/07 65 10/6/05 32 12/13/05 58 8/10/06 64 7/1/04 94

8/11/07 91 1/31/07 294 10/5/07 65 10/11/05 32 12/28/05 66 8/16/06 62 7/11/04 268/20/07 88 2/27/07 902 10/8/07 56 10/14/05 33 1/10/06 72 8/23/06 58 7/12/04 608/28/07 49 3/29/07 160 10/16/07 71 10/25/05 35 1/17/06 369 8/24/06 47 8/3/04 80

9/4/07 106 4/27/07 217 10/18/07 49 11/3/05 32 2/14/06 64 9/3/06 67 8/17/04 909/18/07 51 4/30/07 202 12/19/07 68 11/21/05 37 2/22/06 73 9/14/06 77 9/7/04 8610/7/07 73 5/5/07 188 1/16/08 64 11/30/05 42 3/8/06 146 9/22/06 72 9/14/04 12

10/25/07 100 5/8/07 107 2/26/08 63 12/13/05 46 3/23/06 81 10/5/06 74 9/15/04 4811/5/07 114 5/22/07 190 12/28/05 45 3/29/06 52 11/2/06 87 10/13/04 8612/4/07 148 5/24/07 91 1/10/06 43 3/31/06 41 12/5/06 89 10/26/04 88

1/7/08 195 5/29/07 209 1/24/06 49 4/6/06 40 1/11/07 182 10/28/04 172/22/08 200 5/30/07 129 2/15/06 54 4/18/06 51 3/15/07 220 12/1/04 88

6/1/07 136 2/22/06 54 4/26/06 53 3/28/07 165 12/27/04 976/4/07 163 3/8/06 52 4/29/06 64 3/30/07 128 1/19/05 97

6/13/07 191 3/22/06 49 5/1/06 48 4/16/07 150 2/24/05 2636/18/07 138 3/29/06 41 5/4/06 43 4/23/07 160 3/7/05 239

6/21/07 124 4/3/06 38 5/17/06 49 5/14/07 71 4/16/05 377/3/07 162 4/10/06 35 6/15/06 62 5/30/07 68 4/19/05 1217/8/07 79 4/11/06 35 6/21/06 63 6/12/07 70 5/5/05 169

7/18/07 55 4/13/06 35 7/12/06 62 6/22/07 57 5/13/05 1117/25/07 156 4/18/06 35 7/27/06 65 7/6/07 57 5/24/05 97/26/07 114 4/29/06 35 8/2/06 46 7/8/07 46 6/6/05 121

8/4/07 127 5/4/06 35 8/9/06 49 8/1/07 55 6/8/05 318/11/07 96 5/18/06 35 8/24/06 47 8/11/07 40 6/13/05 358/13/07 74 6/8/06 35 8/31/06 62 8/18/07 42 6/20/05 188/18/07 78 6/20/06 33 9/3/06 27 8/21/07 48 6/27/05 208/20/07 98 6/21/06 33 9/3/06 43 9/4/07 83 6/29/05 768/23/07 108 7/11/06 36 9/7/06 43 9/18/07 61 6/29/05 288/27/07 89 7/27/06 35 9/28/06 62 10/7/07 65 7/5/05 918/28/07 61 8/8/06 37 10/23/06 61 10/25/07 59 7/18/05 928/31/07 146 8/24/06 35 11/15/06 56 11/5/07 53 7/23/05 14

9/6/07 87 9/7/06 39 12/13/06 58 12/4/07 79 7/25/05 239/13/07 138 9/28/06 36 12/31/06 29 1/7/08 106 8/3/05 819/18/07 82 10/26/06 25 1/12/07 66 8/4/05 99/20/07 43 11/21/06 29 2/21/07 92 8/17/05 829/26/07 97 11/28/06 23 3/12/07 142 8/23/05 829/30/07 84 12/11/06 39 3/12/07 145 8/26/05 710/2/07 93 12/31/06 55 3/13/07 58 9/5/05 3410/5/07 79 1/10/07 51 3/15/07 39 9/6/05 3210/7/07 62 2/20/07 31 3/29/07 53 9/21/05 56

10/17/07 81 3/12/07 56 4/30/07 63 9/24/05 1010/29/07 94 3/14/07 26 5/10/07 61 9/28/05 32

11/9/07 134 3/19/07 35 6/21/07 81 10/4/05 1012/20/07 207 3/20/07 38 7/19/07 59 10/4/05 111/29/08 876 3/23/07 40 8/11/07 30 10/5/05 232/28/08 647 3/26/07 39 8/11/07 35 10/7/05 24

3/30/07 38 8/14/07 40 10/25/05 694/2/07 38 8/18/07 36 11/3/05 78

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7/18/07 31 10/24/07 62 1/25/06 2308/20/07 41 11/19/07 60 2/14/06 3249/26/07 42 12/11/07 70 2/22/06 30610/5/07 45 1/9/08 78 3/8/06 325

10/18/07 46 2/25/08 97 3/23/06 33810/31/07 47 4/4/06 18911/13/07 48 4/7/06 15412/12/07 49 4/7/06 1611/16/08 50 4/18/06 1682/26/08 33 4/29/06 108

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