steven effler, susan o’donnell, david matthews, carol matthews, david o’donnell,

The Disconnection Between Limnological Information and the Phosphorus “Total

Maximum Daily Loads” (TMDL) Analysis for Onondaga Lake

Steven Effler, Susan O’Donnell,

David Matthews, Carol Matthews,

David O’Donnell,

Martin Auer, and

Emmet Owens

innovative

engineering &

t

echnology

Eutrophy at Onondaga Lake

– poor clarity– rapid hypolimnetic DO loss– fall DO depletion– fish exodus– high summer average

epilimnetic [TP] (> 50 µgP·L-1)

the central role of phosphorus (P) loading

oligo-mesotrophic before European settlement

cultural eutrophication has lead to– phytoplankton blooms– nuisance cyanobacteria

What are Loads?

lake

inflow outflow

load = inflow X concentration in the inflowmass/time volume/time mass/volume

load

represented as throughout talk

Types of Loads

point loads

non-point loads

rural

urban

What is a TMDL Analysis?

determine the loading rate that will help meet an established goal

current load(all sources)

[TP] >50 µgP·L-1

current in-lake

concentration

[TP] = 20 µgP·L-1

established goal

?

TotalTMDL

MaximumDaily Load

TP guidance value for mid-May to mid Sept.

a quantitative framework to guide

rehabilitation

TMDL Components[TP] = 20 µgP·L-1

guidance value

WLA = Waste Load Allocation = METROLA = allocation for non-point sources and

natural background =TribsMOS = margin of safety

WLA/METRO

LA/Tribs

TMDL = WLA + LA + MOS

Important Features of TMDL Analysis

accommodation of – important system specific characteristics– critical environmental conditions– recurring features of seasonality

consistency with format of standard– TP guidance value; summer average (mid-May to

mid-September) epilimnetic concentration of 20 µg·L-1 (upper bound mesotrophy)

model: quantitative linkage between external loads and lake concentrations

– synthesis of understanding of the system – behavior of phosphorus (P)

NYSDEC TMDL Analysis 1998

based on annual loads reported from Onondaga County monitoring program, 1990-1995

TMDL analysis calls for 50% reduction in Tribs 90% reduction in METRO

TMDL TP Load (2012)

METRO25%

Tribs65%

MOS 10%METRO Effluent

Tribs.32%

ME bypass

total METRO = 68%

prevailing TP (TMDL) loading

Model Framework Used in TMDL Analysis

TP loadingMETRO and tribs.

UML

LML

settlingmixing

UML = upper mixed layer, ~epilimnionLML = lower mixed layer, ~hypolimnion

outflow/Seneca River

settling sediment release

P TMDL/Management Plan/ACJphase I - composed of 3 stages (1998-2012)

– continuing in-lake discharge

Stage Starting Year METRO [TP] CSO’s Flow

– *METRO reductions have feasibility issues– also a LA (tributary) reductions of 50% during phase I

phase I I - update TMDL analysis in 2009

I 1998 550 µgP·L-1 62% reduction

II 2006 120 µgP·L-1 85% reduction

III 2012 20 µgP·L-1* no further reduction

Critical Evaluation of P TMDL for Onondaga Lake

Seneca River as source to the lake lake flushing “plunging inflows” contrasting bioavailability of particulate

phosphorus (PP) sources analytical problems loads/targets and feasibility synthesis of above effects to estimate effective

phosphorus loading

( )

previously presented information

presentation outline

issues addressed in this talk

Independent Long-Term Monitoring Program

R iver

O utle t

Lake

U

D

O no nd a g a La ke

Syra c use

O no nd a g a C re ek

U= up strea mD= d ownstrea m

D

U


the Seneca River as source to the lakelake flushing“plunging inflows”contrasting bioavailability of (PP) sourcesanalytical problemsloads/targets and feasibilitysynthesis of above effects to estimate

effective phosphorus loading



outlet - bi-directional flow

lakeriver

sediments

Stratified River Flow

bi-directional/stratified flow in outlet

outlet - normal

lake

sediments

O utle t

Lake

U

D

QI/S

salinity ~ 0.35 °/°°

salinity ~1.1 °/°°

man made causes– lowering lake water surface elevation to that of river– salinity pollution of lake

net river flow into lake called QI/S throughout talkwater quality concerns – P load to lake

– QI/S has not been quantified– river rich in bioavailable P

Estimate(s) of Seneca River Inflow (QI/S)

conducted chloride mass balance around the lake/river system for 4 years

four year summer averagecompared to METRO

QI/S QMETRO

river summer avg [TP]>60 µgP·L-1

future METRO summer avg [TP]= 20 µgP·L-1

estimates of QI/S varied year to year and seasonallyfirst approximation of summer average QI/S

Interplay Between Lake Flushing Rate and Timing of the TP Guidance Value

flushing rate = inflow rate ÷ lake volume

high flushing rate – entering water remains in lake only a short time

inflow outflow

UMLLML

what is flushing rate?

Implications of Lake Flushing: Formation of a Lake Response Curve

response

tracer injected for one monthmodel run

repeated each month 30 year inflow record formation of lake “response

curve”

summer average (mid-May through mid-Sept.,timing of guidance value) epilimnetic concentration of tracer calculated from model output

Implications of Lake Flushing: Response Curve for METRO Loads

response curve driven by high flushing and timing of TP guidance value

effect ofinterannual

variation in runoff

critical loading interval April-August instead of annual loading ratesminor impact of loads received early fall through following spring time averaging interval of METRO permit (12 months) not protective interannual variations of Q are important

critical loading interval April-August instead of annual loading ratesminor impact of loads received early fall through following spring time averaging interval of METRO permit (12 months) not protective interannual variations of Q are important12 month averaging appropriate for lakes with low flushing rates

Implications of Lake Flushing: Response Curve for METRO Loads

response curve driven by high flushing and timing of TP guidance value

effect ofinterannual

variation in runoff

Effect of Seasonality of TDP Loading Rate

tributary loading rates are lower for April – August compared to annual loads

critical loading interval April-August instead of annual loading rates

Lake

more dense

Density and Plunging Inflows

Inflowless dense

Entry of Inflows

density () is a function of temperature (T) and salinity (S)depth inflow enters is a function of density difference

(T,S) between an inflow and the lake

plunging underflow


Lake

more dense

Inflowless dense

large density difference (T,S) leads to plunging inflows

Differences in Density

J F M A M J J A S O N D

T

/S

(kg·

m-3

)

-2

0

2

4 Onondaga Cr.

METRONinemile

Lake

more dense

Inflowless dense

Inflow Entry and Lake Stratification

UML

metalimnion

H

metalimnetic peak caused by

plunging inflow


stratification model

Stratification Model for Plunging Inflows

UML

LML

TMDL model

mixed (UML)

H

metalimnionplunging sub-model

Model Performance

Stratification Model Application


M ETR O

M etalim nion

O nondaga& N inem ile

Creeks

M eta lim nion

Bioassay Setup

Bioavailability

algal bioassay experiments to determine bioavailability of PP

Bioavailability of P According to Sources

dissolved P particulate P

TP

Bioavailability

Bioavailability of P According to Sources

all forms of P are not equally available to support algal growth

TP

highsettling

lowsettling

Particulate P

Bioavailability

organic P

P available for algal growth

dissolved P

inorganic P

Bioavailability: Contrasting Contributions of TDP to TP

total dissolved phosphorus (TDP) is bioavailable TDP/TP ratio as an indicator

BioavailabilitySite

OC-u OC-d NMC LC METRO SenRiv

Rat

io T

DP

/TP

0.0

0.2

0.4

0.6

0.8

tribs

SiteOC-u OC-d NMC METRO

Bio

avai

labl

e P

(µgP

·gT

SS

-1)

0

2000

4000

6000

8000

10000

12000

Contrasting Bioavailablity of PP

Bioavailability

consistent with literature

tribs

SiteOC-u OC-d NMC METRO

Rat

e(d

-1)

0.0

0.1

0.2

0.3

0.4

0.5

Contrasting Bioavailability Rates of PP

Bioavailability

consistent with literature

tribs

Contrasting Associations of Bioavailable PP and Settling

Site

Onon. Ck. upstream

Onon. Ck. downstream

Ninemile Ck.

METRO

P Associations

inorganic

organic/inorganic

inorganic

organic

Bioavailability

widely different deposition rates of bioavailable PP

Settling

fast

medium

fast

slow

Analytical Issue TP Issuefailure to correct for turbidity during the TP analysis leads to false high TP loads

no turbidityspectrophotometer

cuvette

high turbidity

Analytical Issue: Effect on TP Loads

failure to correct for turbidity during the TP analysis leads to false high TP loads

Annual Load Estimates for 2000

Tributary TP Loads: Prevailing versus Literature

UAL = unit area loads, kgP·km-2·yr-1

Sites Literature

lake tributaries are not rich targets 50% reduction goal ?

common literature

rangesrural

urban

What is Effective P Loading?

Synthesis

effective P loading is that portion of the total loading that will support algae growth in the lake

M eta lim nion

“e ffective”tp load

apparent TP load algal

growth

Effective TDP Loading: Prevailing (kg·d-1)

Synthesis

annual

productiveseason

to productivelayers

effective load

apparent loadMETRO Tributaries

Effective PP Loading: Prevailing (kg·d-1)

unblanked

annual

Synthesis

METRO

productiveseason

bioavailable

notdeposited

to productivelayers

effective load

apparent load Tributaries

TMDL TP Contributions

METRO68%

tribs.32%

NYSDEC prevailing TP (TMDL) loading

realistic prevailing loading conditions

Synthesis

Effective P Loading Contributions

tribs.14%

METRO86%

without river

METRO80%

tribs.13%

Sen. Riv.7%

with river

bypass

METROtribs.

Sen. Riv.

Futuristic Partitioning “Effective” P Loading Contributions

stage III: METRO limit (20 µgP·L-1), other prevailing

manageable

target richness

Synthesis

only fraction of trib. load subject to management

ConclusionsNYSDEC TMDL Analysis is fatally flawed in the following

ways...

R iver

O utle t

Lake

TMDL Analysis Did Not Include

1. Seneca River load

QI/S

conclusions

outlet - bi-directional flow

lakeriver

sedimentsoutlet - bi-directional flow

lakeriver

sediments

2. implications of rapid lake flushing

inflow outflow

UMLLML

conclusions

12 month averaging for METRO effluent is not protective of the lake

TMDL Analysis Did Not Consider

3. implications of the plunging inflows phenomenon

Lake

more dense

Inflowless dense

UML

metalimnion

H

conclusions

model applied was an inappropriate framework


4. contrasting bioavailability and settling characteristics of PP for different sources

conclusions


highsettlinghighsettling

lowsettlinglowsettling

Particulate P

organic P

dissolved P

inorganic Pmodel applied was an inappropriate

framework

4. TP tributary concentrations of Onondaga County monitoring program are false high

no turbidity high turbidity

conclusions

TMDL Analysis Did Not Recognize

5. target richness and feasibility of non-point load reduction goals

conclusions

50% non-point loading reduction goals are not feasible

rural

urban

TMDL Analysis Did Not Fully Consider

METRO

6. apparent verses effective loads

conclusions


effective load

apparent load

short-comings caused understatement of METRO’s role and overstatement of

tributaries role

METRO Tributaries

Important Features of TMDL Analysis

accommodation of – important system specific characteristics– critical environmental conditions– recurring features of seasonality

model – quantitative linkage between external loads and lake concentrations– synthesis of understanding of the system – behavior of phosphorus (P)

Conclusionsexisting P TMDL analysis developed by the NYSDEC

cannot be considered a reliable basis to guide rehabilitation of the lake’s related problems

conduct a valid P TMDL analysis for Onondaga Lake now (don’t wait until 2009)

develop a plan to eliminate the Seneca River inflowreconsider management strategies

Recommendations

steven effler, susan o’donnell, david matthews, carol matthews, david o’donnell,

Documents

update tmdl analysis

onondaga lakeseneca

onondaga lakethe seneca

onondaga lakesteven

yearsriver summer avg

external loads

lake discharge

annual loads