effects of the addition of multi-slip docks

8/7/2019 Effects of the Addition of Multi-Slip Docks

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e Journal of Transdisciplinary Environmental Studies vol. 9, no. 1, 2010

e Journal of Transdisciplinary Environmental Studies, ISSN 1602-2297http://www.journal-tes.dk/

Eects of the Addition of Multi-Slip DocksOn Reservoir Flushing and Water Quality:Hydrodynamic Modeling; Aquatic Impact;

Regulatory Limits

John E. Edinger, Consultant in Environmental Hydrology, 63 Crestline Rd., Wayne, PA 19087.

E-mail: [email protected] (Corresponding Author)

James L. Martin, Professor, Department of Civil and Environmental Engineering, Mississippi State Uni-versity, P.O. Box 9546, Mississippi State, MS 39762. E-mail: [email protected]

Abstract: Numerous multi-slip docking facilities are planned for placement along the shorelineof Tims Ford Reservoir located on the Elk River in south central Tennessee, USA. ese multi-slipdocking facilities will occupy dierent kinds of shoreline congurations including coves, mouths ofsmall tributaries, and other regions of limited ushing. Placement of the multi-slip docking facilitieswill limit the amount of local ushing that will take place in the vicinity of the multi-slip dockingstructures. Very few of the multi-slip docking facilities have been built to date, therefore comparativesimulations of ushing need to be performed for conditions without and with the proposed multi-slipdocking structures. is report describes the results of comparative simulations using computationalhydrodynamic and transport models. e analysis shows that there will be reduced ushing in over92% of the proposed multi-slip docking locations. e reduction in ushing will worsen waterquality conditions. e analysis and results of ushing estimates are compared to ushing guidelinesused by some US State regulatory agencies and international guidelines used by ANZECC (2000).

e comparative analysis of ushing allows evaluation of the changes in water quality includingcoliforms, dissolved oxygen, algal densities and sedimentation that will take place along the shorelineand in the vicinity of the multi-slip docking facilities. e magnitude of the probable changes dueto construction of the multi-slip docking facilities for coliforms, dissolved oxygen and algal densities

is greater than the seasonal changes in these water quality constituents as observed over the years inTims Ford Reservoir. In addition, ushing and the changes in algal densities could be compared tothe ANZECC (2000, Sec. 8.1.9.1) algal growth guideline. e change in water quality will notbe limited to the multi-slip docking areas alone. Many of the local changes that will take place atthe individual multi-slip docking facilities will aect water quality throughout 67% of the area ofthe reservoir. In particular the increased algal densities will generate seed for spores and cysts thatwill spread throughout the reservoir by attachment to sediment and decaying algae. e increasein benthic spores and cysts will increase the likelihood of the occurrence of algal blooms in the yearsfollowing construction of the multi-slip docking facilities.

Key Words:Water resources, marinas, mathematical models, sitting regulations, aquatic impacts,

environmental studies.


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Edinger and Martin: Eects of the Addition of Multi-Slip Docks On Reservoir Flushing.....

1. IntroductionTe construction of multi-slip docking facilitiestypically results in an increase of local ushing

time with consequent impacts on water qualityboth around the facility and potentially in adja-cent ambient waters. Te design of such facilitiesshould include minimization of pollution sourcesand maximization of ushing (Brown 1993). Anassessment the impacts of multi-slip docking facili-ties on ushing and water quality is often requiredprior to construction, such as to obtain state waterquality certication required by Section 401 ofthe US EPA Clean Water Act. A water qualitycertication is the mechanism by which the State

evaluates whether an activity may proceed andmeet water quality standards. For example, priorto Massachusetts Oce of Coastal Zone Manage-ment approval of marina projects under the law(Massachusetts OCZM 2001), it is expected thatdesign considerations include marina ushing,water quality, habitat, and shoreline stream bankstabilization. Te Delaware Department of NaturalResources and Environmental Control (DNREC2006) requires that applicants for new marinas orexpansions of existing marinas provide a

documented and valid assessment of the potentialwater quality impacts of the design, construction, andoperation of the proposed marina, specically, the as-sessment must explicitly address faecal coliform anddissolved oxygen surface water quality standards,

based on appropriate modelling, monitoring, anddata analysis. In Florida, the St. Johns River WaterManagement District (SJRWMD), in order to pro-vide reasonable assurance that water quality standardswill not be violated, requires data or hydrographic

studies to document the ushing time of the waterat the docking facility and generally requires a ush-ing time of less than or equal to four days. As anadditional water quality consideration for dockingfacilities (>10 slips), the SJRWMD guidance for as-sessment of ushing recommends reducing a test dyeconcentration to 10% of the initial value in 4 daysfor a dye test carried out at an individual marina. Al-though methodologies and specic regulations vary,the need to examine marina ushing has been therule, rather than the exception, in State water qual-ity regulations for over 20 years. Internationally, theANZECC (2000, Sec. 8.1.9.1) guideline specically

requires that ushing times be less than the doublingtime of algal densities.

Evaluation of the ushing time and water qualityimpacts of docking facilities may be estimated usingdata and or models. Comparative model studies areperformed where there is little or no data availableto carry out fully parameterized water quality mod-elling, such as in the analysis of new or proposeddocking facilities. Generally, a comparative studyevaluates the eect of a perturbation by comparingthe results of model simulations with and withoutthe perturbation imposed. Comparative studiesmay form the basis for permit decisions and used

in litigation. For example, comparative analyseswere used in an arbitration case between a powerbuyer and supplier where power plant operationswere limited by water quality conditions (Edinger2004). Comparative analyses also were part of tworecent successful water quality issue proceedingsconcerning Gulf Island Reservoir and Dam onthe Androscoggin River in Maine (Edinger 2005,Edinger 2007).

In this paper a comparative study is presentedof the impacts of 41 multi-slip docking facilities

planned for placement along the shoreline of imsFord Reservoir located on the Elk River in southcentral ennessee shown on Map 1. Te proposedmulti-slip docking facilities are relatively evenlyspaced along the shoreline of the reservoir and willoccupy dierent kinds of shoreline congurationsincluding coves, mouths of small tributaries, andother regions of limited ushing. Te study com-pares the ushing rates from the overall ims Fordwater body and at individual shoreline locationsby running simulations using a three-dimensional

hydrodynamic and transport model without theshoreline multi-slip docking facilities, and compar-ing the results against simulations that included theshoreline multi-slip docking facilities. Methods forthe evaluation of ushing time and water qualityimpacts are presented.

2. Methods

2.1 Hydrodynamic Model

Te time-varying three-dimensional hydrodynamicand transport model applied in this study was


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Te Journal of ransdisciplinary Environmental Studies (ES)

GLLVH (the Generalized Longitudinal, Lateral,and Vertical Hydrodynamic and ransport model)as presented in Edinger (2002). Tis model wasoriginally developed by Edinger and Buchak (1980,1985). Details of the formulation of the GLLVH

model are given in Edinger and Buchak (1995).Te model includes horizontal and vertical mo-mentum, the barotropic and baroclinic componentsof the horizontal pressure gradient, vertical shear,constituent transport and an equation of state. Allof the dispersion coecients used in the model areinternally computed from known relationships.GLLVH is a nite dierence model that uses animplicit solution technique. Te implicit solutiontechnique allows large computational time stepson the order of minutes. Tis eciency permits thecomputations to be done on ordinary personal com-puters. Te application of GLLVH is described inEdinger (2002) and Martin et al. (2006). GLLVH

was applied using the bathymetry and inows toims Ford Reservoir.

2.1.1 Tims Ford Reservoir Model BathymetryTe bathymetry or water depths throughout ims

Ford Reservoir were evaluated by Gordon (1974).Using maps available at that time, the reservoir hyp-sographs were developed to give the planar area ofthe reservoir at each elevation from the lowest depthin the reservoir to the normal maximum operatingelevation of 888 feet above sea-level. Te surfacearea at the maximum normal operating surfaceelevation was found to be 10,600 acres. Te area-elevation was then integrated vertically to give thecumulative reservoir volume at each elevation fromthe lowest elevation point on the reservoir oor upto the maximum normal operating elevation. Tereservoir volume at the maximum normal operatingsurface was found to be 530,000 acre-feet.

Map 1. Tims Ford Reservoir conguration showing main inow and major tributary arms.


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Te three-dimensional bathymetric grid requiredby the hydrodynamic and transport model (Edinger2002) was derived from a number of sources. Te

shoreline of the reservoir at the maximum normaloperating elevation was developed from the mappresented in Gordon (1974) and the few elevationsgiven with it. Te rest of the model grid bathymetrywas developed from the ims Ford Lake Recreationand Fishing Guide with opography.

Te resulting three-dimensional bathymetric gridconsisted of 1,028 surface cells, and a total of 7,203volume cells. Te grid resolution was 200 by 200meters with two meter thick layers. Te model grid

hypsographs of planar elevation versus reservoirelevation and cumulative volume versus reservoirelevation are compared to the hypsographic datapresented in Gordon (1974) in Figure 1. It is seen

that the three-dimensional model grid hypsographsconform favorably to those presented in Gordon(1974).

2.1.2 Tims Ford Infow Ratesims Ford Reservoir was evaluated by Dycus andothers (1999) for aquatic health and water qualityconditions. For that study, the reservoir was evalu-ated at a surface area of 10,600 acres, a mean annualinow rate of 980 cubic feet per second (cfs) andan overall reservoir hydraulic residence time of 270days. Te mean annual inow and the hydraulicresidence time give a volume of 525,000 acre-feet.Te surface area and volume of the reservoir from

Dycus and others (1999) agree favourably with thoseprovided by Gordon (1974) and to those computedfrom the three-dimensional model grid. Gordon(1974) gives the total drainage area into ims FordReservoir of 529 square miles which gives an inowof 1.85 cfs/mi2for the mean annual ow.

For three-dimensional modelling of ims Ford Res-ervoir, the total inow rate given in Dycus and others(1999) needed to be apportioned among its majorElk River inow and the major tributary arms ofthe reservoir. As shown by Gordon (1974) the ims

Ford Reservoir main inow is the Elk River belowWoods Reservoir which is at the northeastern cornerof Map 1. Te area drained via the Elk River intoims Ford Reservoir is 263 square miles. Tis leaves266 square miles of drainage area to be distributedamong the other reservoir tributaries. Te reservoirhas two large tributary arms: Lost Creek and Hur-ricane Creek. It has three smaller tributary arms ofinterest in the multi-slip docking facility study: Lit-tle Hurricane Creek, Winchester Creek and BoilingSprings Creek. From the map provided in Gordon

(1974) Lost Creek and Hurricane Creek each appearto occupy 25% of the remaining drainage area of 266square miles. Te three smaller tributary arms eachappear to occupy 16.6% of the remaining drainagearea. Te resulting drainage areas and mean annualinow rates for each of the inows to ims FordReservoir at 1.85 cfs/mi2are therefore apportioned asshown in able 1. Te totals in able 1 dier slightlyfrom those in the references due to rounding theproportion of drainage area to each of the inows.

Te three dimensional hydrodynamic and transportmodel (Edinger 2002) requires an initial tempera-ture prole to represent thermal stratication and

Elevation-Area Relation

0

2000

4000

6000

8000

10000

12000

760 780 800 820 840 860 880

Elevation, Ft.

Area,A

c-Ft

Model Area

Obs JG Area

Elevation-Volume Relation

0

100000

200000

300000

400000

500000

600000

760 780 800 820 840 860 880

Elevation, Ft.

Volume,Ac-Ft

Model Volume

Obs JG Volume

Figure 1. Comparison of Model Digital BathymetricHypsographs with TVA Data


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inow temperatures. Dycus and others (1999) givein their Appendix B diagrams of the seasonal tem-perature isopleths for the vertical distribution oftemperature at Elk River Dam shown on the south-ern edge of Map 1. It shows very little variation intemperature stratication from early June throughmid-September. Te three-dimensional model isinitialized for the temperature proles for ims

Ford given in Dycus et al. (1999). Te river inowtemperatures were set at the surface temperaturesin the model so that there will be little change intemperature over the sixty day simulation period.

2.1.3 Multi-Slip Docking Area RepresentationTe three dimensional model in Edinger (2002) wasapplied to simulate detailed reservoir ow patternsrst without representation of multi-slip dockingstructures and then with a representation of the mul-ti-slip docking structures and the shoreline region

encompassing them. Multi-slip docking structuresare represented in the model as extensions from theshorelines that behave as partial barriers to ow. Tevertical extent of the shoreline extension to representdock structures requires evaluation to determinetheir eects on ushing and water quality. Te USArmy Corps of Engineers report, Engineering andDesign - Environmental Engineering for Small BoatBasins (Brown 1993) presented an early evaluationof the processes involved. It outlined the factors af-fecting water quality that should be included whendeveloping permitting procedures for small boatdocks and basins. Te report shows that almost anysmall boat dock has related to it, or in eect creates,

some type of natural or man-made cove, basin orbackwater tributary.

Multi-slip dock structures were examined and mem-bers of the Coastal Modeling Experts list maintainedby the University of Delaware were asked to assessthe problem. Donohue (2007) stated based on hisexperience that:

Most multi-slip docking facility docks oat withless than 12 inches of draft. Tere are usually under-water structures like stiening truss work and fair-leads that may extend 6 to 8 feet below the waterline depending on the dock size. Te only other

environmental problems some attribute to docks isthe inhibition of wind driven surface ows and theushing of waters in a slough or cove. Te reality ofthe latter is more related to individual circumstancesthan some sort of general rule or certainty.

Te key elements here are that the eective hydraulicinterference of a multi-slip docking facility dependsupon: (1) the underwater structures beneath it; (2)the structures location in a slough or cove; and (3)individual site circumstances rather than a generalrule. Te use of the three-dimensional hydrody-

namic and transport modelling is designed to takecare of items (2) and (3), and as indicated there willbe interference with ow to more than just the draftof the oating dock.

Most of the 41 docks were at least the length of a200 meter grid cell and were spaced more than agrid cell apart along the shoreline on Map 1. Tethree-dimensional model vertical layer thicknesswas set at 2 meters and the shoreline extensionsrepresenting the multi-slip dock sides was also set

for a depth of 2 meters with a fraction of the surfacelayer ows toward or away from the shoreline exten-sions deected as allowed in the model formulation(Edinger 2002, Sec. 2.1.11).

2.2 Dye SimulationsEach volume cell in the three dimensional modelwas initialized with a virtual dye concentrationof 1,000 ppb. No dye was included in the inows;hence the dye concentration in each volume cellwill decrease over the simulation period due tothe un-dyed inows and the resulting circulationthrough the reservoir. Te output of the model wasset to obtain the dye concentration in each of the

Table 1 Tims Ford Inow Drainage Areas and Flows

Inow DA, Mi 2 Inow, cfs Inow

m3

/sElk River 263.0 486.6 13.8

Lost Cr. 66.5 123.0 3.5

Hurricane Cr. 66.5 123.0 3.5

Little Hurr. Cr. 44.2 81.8 2.3

Winchester Cr. 44.2 81.8 2.3

Boiling Spr. Cr. 44.2 81.8 2.3

otals 528.6 978.0 27.7


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cells where the multi-slip docking facilities will belocated. Te simulation was rst run without themulti-slip docks in place. A second simulation was

then conducted with the multi-slip docks in place.Both runs simulated a 60 day period of stratiedsummertime water conditions.

2.3 Estimation of Flushing RatesA theoretical estimation of reservoir ushing timecan be computed for comparison with model pre-dictions. Te ushing rate may be computed fromtime requirements to remove a dye from a speciedvolume of the reservoir. For a reservoir with a xedinow and outow rate, Q

r, and volume Vr, the

average rate of change in dye concentration (C) willbe:

1

from which it is expected that the decrease in averagedye concentration at the end of the simulation time

( si m) wouldbe:

2

where Co is the initial virtual dye concentration. Aushing rate can also be dened as Kr = Qr/Vr.

2.4 Individual Model Flushing Rates and TimesA ushing rate, Knd, can also be dened for indi-vidual cells within the reservoir where Cnd(sim) isthe dye concentration at the end of the simulationfor that individual cell. Here Knd is the ushing ratewith no model shoreline extensions representing

multi-slip docking fa-cilities. Te individual cell

flushing rate can becomputed as:

3

If Vdkis the volume of the model cell containing themulti-slip docking facility, a ow rate (Qnd) can beestimated for that model cell as:

Qnd

= Knd

Vdk

4

If shoreline extensions are placed around one or two

of the model cells containing the multi-slip dock-ing facility and its embayment and the dye simula-tion is re-run to obtain the

d y e concentration with themulti sl ip docking

f a - cilities at the end of simulation Cwd(sim), then similar relationshipsapply giving:

5

and for a ow rate with multi-slip docking facilities

(Qwd

):

Qwd

= Kwd

Vdk

6

2.5 Estimating Changes in Water QualityTe numerous sheries, biological and water qualitystudies carried out on ims Ford Reservoir, includ-ing Butkus (1990), Dycus, et al (1992), Dycusand Meinert (1992), Fehring (1993), Meinert andDycus (1993), Fehring and Meinert (1993), Sco,et al (1996), Dycus and Meinert (1998) and Dycus

(1999), were based on examining one or more ofthe following water quality parameters: coliform,dissolved oxygen, phytoplankton, and sediments.he effects of multi-slip docking facilities andchanges in local circulation on each of these waterquality parameters can be studied using the changesin ow rates and ushing through the multi-slipdocking regions. Te changes in water quality canbe determined from simple dierence computa-tions without running extensive simulations beyondthose performed for the ushing rates in the multi-

slip docking regions. Te water quality dierencecomputations without and with multi-slip dockingregions are based on the water quality models givenin Edinger (2002) that were derived from numerousother water quality studies.

2.5.1 Simple First Order Decay Relation orColiormsTe water quality change for a simple rst order de-cay relation, for example, coliforms, can be derivedfrom a constituent balance for a cell whose owswere determined from the dye simulation formula-tions used to derive Equation 4 and Equation 6respectively. Te constituent balance can be written

CQdt

dCV rr =

= sim

r

rsim T

V

Q-exp*Co)(TC

sim

o

simnd

nd

TC

)(TCLn

-K

=

sim

o

simwd

wd

T

C

)(TCLn

-K

=


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by determining the amount of material owing outof the cell from the amount owing into it minusthat lost by rst order decay. Te constituent bal-

ance with no multi-slip docking facilities would be:

Qnd

Cnd

= Qnd

Coo

RdV

dkC

nd7

where Cnd

is the constituent concentration withno multi-slip docking facilities ushing out of themodel cell, Coo would be the background of theconstituent concentration entering the multi-slipdocking facility area from o shore and Rd is theconstituent decay rate (colif-orm dye-o for example). Note

that when dividing through bythe volume, Vdk, the balance can be written moreconveniently as:

Knd

Cnd

= Knd

Coo

RdC

nd

8

giving:

9

S i m i -l a r l y ,

with multi-slip docking facilities, the constituentconcentration becomes:

10

and the dierence with docks in comparison towithout docks becomes:

11

Tis comparison conveniently eliminates the ar-bitrary Coo and for descriptive purposes can beexpressed as a percentage. First order decay rates formany water quality constituents including coliformsare given in Edinger (2002; able 10-1).

2.5.2 Eects on Dissolved OxygenTe change in dissolved oxygen without and withmulti-slip docking facilities can best be evaluatedusing the dissolved oxygen decit (DOD) which is

the depression of dissolved oxygen below saturationat a given water temperature. Its evaluation requires

rst formulating the

b i - ochemical demand(BOD) and then us-

ing that demand as one process in the dissolvedoxygen decit balance along with the ux of DODand its re-aeration from the surface (Edinger,2002;Ch. 12).

Without multi-slip docking facilities in place, theBOD relationship would be:

Knd

BODnd

=Knd

BODoo

-Rbod

BODnd

12

w h e r eRb o d i sthe ra t eof BOD

decay and BODoo is the background BOD. Tisrelationship gives:

13

h eDOD relationship would be:

Knd

DODnd

=Knd

DODoo

+Rbod

BODnd

- RreDOD

nd14

w h e r eRre is thes u r f a c e

re-aeration rate. Te dissolved oxygen depression isin addition to any background dissolved oxygen de-pression below saturation that exists in the reservoir,and hence DODoo can be set to zero. Substitutingfrom Equation 14 for BODnd gives the relationship

for DODnd of:

15

Similarly, the relationship for DOD with docks canbe written as:

16

Each of these could be evaluated separately for aunit value of BODoo (ie, BODoo =1.0) to give thechange in DOD from the no dock case to the casewith multi-slip docking facilities as:

oo

dnd

ndnd C

RK

KC

+=

oo

dwd

wdwd C

RK

KC

+=

+

+

+=

dnd

nd

dnd

nd

dwd

wd

nd

ndwd

RK

K

RK

K

RK

K

C

)C-(C

( )bodndoo

ndndRK

BOD

KBOD +=

( )( )00

rendbodnd

ndbodnd BOD

RKRK

KRDOD

++=

( )( )00

rewdbodwd

wdbodd BOD

RKRK

KRDODw

++=

( )nd

ndwd

DOD

DOD-DOD=Fraction change in

Dissolved oxygen


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17

Note that if Equation 17 and Equation 16 wereplaced into Equation 15, the background BODoowould be eliminated.

2.5.3 Potential Aquatic Plant, Slime and AlgalDensity Change Due to Flushing RatesDock shading is known to aect shoreline plantgrowth (Sanger and Holland 2002). Tis becomesan important factor when trying to maintain existingshoreline grasses, or to build up valuable shorelinevegetation for erosion protection, sh spawning

habitat, and ascetic attraction. Te amount of shad-ing and a possible assessment of its eect on plantgrowth can be evaluated from the orientation ofthe dock facilities to the sun and the extent of theshading footprint.

Te underwater structural features of oating docksas well as boats kept within the water provide ex-tensive surface area for the growth of slimes andattached algae. Te seriousness of this problem canbe judged by how quickly a boat bottom will foul upbefore it requires vigorous cleaning, or the extent to

which complex docks with boat lifts are used. Tegrowth of slimes on underwater structural featuresof a dock and algal growths can be evaluated on acomparative basis from the fundamental relation-ships governing the growth of algae.

Algal densities along with their dissolved oxygenproduction and respiration vary hourly, daily andseasonally and are very dicult to characterize overa full summer season. A characterization of algal car-rying capacity of lakes and reservoirs was developed

by Reynolds and Marbely (2002). Teir evaluationrequires knowing the seasonal inow rate of nitrogenand phosphorous nutrients and the seasonal inowrate to the water body. It also allows examining theeects of varying mineral and light conditions. Teirevaluation applies to the whole reservoir and it isdoubtful that it could be used to determine the ef-

fects ofchang-e s i n

ushing rates through a volume of the reservoirsurrounding a docking facility. Additionally, thedetailed nutrient inow data required is often una-vailable.

Density dependent grazing is used in the evaluationof aquatic vegetation growth and decay (Gentleman

et al 2000). It is now being recognized that algalblooms and similar rapid growth of other aquaticbiota is more related to cysts and spores in sedimentsand attached to water contact surfaces (McGil-licuddy et al 2003). Te bloom mechanisms havebeen incorporated into combined hydrodynamicand water quality numerical modelling (Edinger etal, 2003).

It is possible to reduce the relationships given in Ed-i n g e r

e t a l(2003) describing the temporal variations in algaldensi-ties toa long

term steady-state estimate by examining the balance

between algal growth and zooplankton grazing usingthe time varying algal relationship of:

18

where Gp(N,P,I) = he phytoplankton growthrate as limited by concentrations of nitrogen andphosphorous constituents and by light, Dd = Tephytoplankton death rate, Dr = Te phytoplanktonrespiration rate, Kdg = zooplankton density depend-

ent grazing rate.

Te Gp(N,P,I) can be evaluated more simply by algalgrowth rates and death rates over a long period oftime as given in Edinger (2002; able 13-3). Letting

Kphy

=[Gp(N,P,I)-Dd-D

r] 19

then the algae transported through a multi-slip dock-ing location with no facility in place isdescribed as:

20

or

[ ] 2pdgprdpp

C*K-C*D-D-I)P,(N,Gdt

dC=

Knd*Cpnd = Knd* Cpoo + Kphy * Cpnd Kdg * Cpnd2

Kdg * Cpnd2 + (Knd - Kphy)*Cpnd - Knd* Cpoo = 0

Kdg * Cpwd2 + (Kwd - Kphy)*Cpwd Kwd* Cpoo = 0

( ) ( )( )[dg

poodgndphyndphy-ndpnd

K2

C*K*K42K-KKK-C

++


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21

a n d with multi-slip docking facilities:

22

In order to determine the dierence in algal densi-ties in the multi-slip docking areas, it is necessary tohave an estimate of background algal density Cpoothrough the season and rst evaluate Equation 21and Equation 22 separately for Cpnd and Cpwd. Teadvantage of this approach is that all the rate proc-esses of ushing, algal kinetics and density depend-ent grazing are included.

Te solution to the quadratic Equations 21 and 22 is:

23

and a similar solution can be written for Cpwd.

Te Cpoo, or background algal density at a locationwithout docks can be considered a carrying capac-ity value based on the algal density rate processessimilar to the phytoplankton carrying capacity de-veloped by Reynolds and Marbely (2002) based on

nutrient loadings for the whole lake or reservoir. Agood denition would be the Cpoo resulting fromthe algal rate parameters alone with no ushing asbackground. From Equation 22 or Equation 23 withKnd or Kwd set to zero, it would be evaluated fromeither Cpwd or Cpnd as:

24

whichis the Cpoo that results from the balance between algalgrowth and zooplankton grazing. It is sucient toallow determining the change in algal density withoutand with multi-slip docking facilities as (Cpwd Cpnd)/Cpnd similar to that used in the other water qualityrelationships. Almost any algal like slime that attachesto multi-slip docking understructure will be limitedby a balance between growth rate and grazing. It is

when this balance is upset that additional seed forspores and cysts get spread throughout the reservoir

and trapped into the sediment to become the sourcefor vegetative cellular material which generates algalblooms (McGillicuddy et al. 2003, Edinger et al.

2003).

2.5.4 Application to Changes in SedimentationTe simple rst order decay can be used to approxi-mate the change in bottom sediment concentrationunder a multi-slip docking facility by dening therst order decay rate as Rv= Vs/Ddkwhere Vs is thesettling rate for the chosen sediment size and Ddkis the water depth at the multi-slip docking facilitylocation. Te sediment analysis can be performedover a range of expected sediment sizes using Stokes

law to determine settling velocity. Te change inthe amount settled for each sediment size will varydepending on the ushing rates without and withthe docks.

From the simple rst order relation for coliforms,the dierence in sediment concentrations within the

multi-slip docking regions would be:

25

Te Csoo for reservoir suspended and settling sedi-ment typically is of the order of magnitude of 1.5kg/m3 and using this as a background value, the dif-ference in sedimentation rates through the multi-slipdocking regions with and without the facilities canbe estimated as:

26

dg

phypoo

K

KC =

( )soo

vnd

nd

vwd

wdsndswd C

)R(K

K

RK

KC-C

+

+

=

Diff. in settling rate (kg/m2/yr)=(Cswd-Csnd)*Vs(m/yr)

Dye Ratio vs Flushing Time

-60

-40

-20

0

2040

60

0 0.5 1 1.5 2

Dye Ratio

IncreaseinFlush

ing

Time,Days

Days

upper limb

lower limb

Linear (upper limb)

Linear (lower limb)

Figure 2. Relationships between Cwd/Cnd Ratio andChange in Flushing Time with Two Limbs


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3. Results and Discussion

3.1 Hydrodynamic Simulation

Te dye ushing results determined with the hy-drodynamic simulations are that the nal dye con-centrations with the multi-slip docking facility ishigher than without them at 38 of the 41 proposedmulti-slip docking facility locations included in themodel. Te ratio of the nal dye concentration in thesimulations with docks to that without docks (Cwd/

Cnd

) quanties the degree to which a particular dockstructure alters the circulation. When this ratio isgreater than unity there will probably be a decreasein water quality at the multi-slip docking facilitylocation due to reduced ushing around the docks,and the greater the ratio the greater the potentialwater quality problems. Figure 2 shows values ofthe Cwd/Cnd ratio are greater than one (i.e., ushingis reduced by docks) for over 92% of the plannedmulti-slip docking facility locations.

Changes in water quality in the multi-slip docking

regions would also aect water quality through-out the remainder of the lake. Te relationshipbetween the dye ratio, Cwd/Cnd,and the increased flushing timeg i v e n in Figure 2 shows theflushing time bifurcates into twobranches when Cwd/Cnd> 1 indicat-ing that for certain locations the increased residencetime is higher than at other locations for a givenvalue of the ratio. Figure 2 demonstrates that theincreased residence time is as much a function of

location and shoreline within the reservoir where themulti-slip docking facility is located on the lake asit is a function of the facility being in that location.3.2 Estimating Reservoir Flushing RatesFor the overall lake, Kr has the value of 1/270 perday. Using Equation 2 starting with the initial dyeconcentration of Co = 1,000 ppb over the 60 daysimulation time, the theoretical dye concentrationthroughout the lake with no multi-slip dockingshould be 800 ppb. Te average dye concentrationover the 41 shoreline multi-slip docking sites fromthe model simulation was 683 +/- 323 ppb com-puted from only 41 shoreline multi-slip dockingsites out of a total of 7,023 model cells. Te model

simulation value is within less than one standarddeviation dierence of the theoretical value indi-cating that the model simulation results are quite

reasonable.

3.3 Individual Model Flushing Rates and Timeshe multi-slip docking volume flow rate andushing rate at each of the locations were usedin estimating the changes in water quality withinthe multi-slip docking facility volumes, where theincrease or decrease in local ushing time with themulti-slip docking facilities was derived from theabove ushing rates. Te increase in time is denedas the time it would take for Cwd to reduce to the

concentration with no docks, Cnd, at a rate of Kwd.Tis increase in time is derived from Equation 5where Cwd is substituted for Co as:

27

All but three, or 85%, of the 41 multi-slip dockingfacilities show increases in ushing times rangingfrom an average of 17 days up to a maximum of52 days.

3.4 Estimating Changes in Water Quality

3.4.1 Simple rst order decay relation orColiormsTe results for coliforms without and with themulti-slip docking facilities were computed from

wd

wd

nd

K

C

CLn

t

=

Dye Ratio vs Pct Coliform

Change

-15

-10

-5

0

5

10

0 0.5 1 1.5 2

Dye Ratio

ColiformChange,

Pct

E-Coli

Figure 3. Relationships between Cwd/Cnd Ratio andChange in Coliforms


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Equation 11 and compared to results for coliformmean, maximum and minimum values in ims FordReservoir as sampled through the year in 1998. Temagnitudes of the increases in coliforms with themulti-slip docking can be compared with the datausing the statistical normalized range of results de-ned as (Max Min)/Mean as a basis for judgingthe severity of the multi-slip docking additions. Tenormalized range statistic is used for comparisonbecause most of the available water quality data are

summarized using the mean, maximum, and mini-mum values. Te normalized range for coliformswith the multi-slip docking in place will be aboutve times as great as that recently observed in imsFord Reservoir.

Te relationship between the change in coliformswithout and with the docks, and the dye ratio, Cwd/Cnd, is given in Figure 3. It shows that the changein coliform density will be almost proportional tothe increased dye ratio.

3.4.2 Dissolved OxygenTe results for DOD, changes in dissolved oxygenwithout and with docks and a comparison to ob-served results showed that the depression in dissolved

oxygen with the multi-slip docking facilities in placewould be up to 5 times the seasonal normalizedchange in dissolved oxygen presently observed inthe reservoir. Figure 4 gives the relationship betweenthe Cwd/Cnd ratio and the change in DOD. Figure 4indicates that the change in DOD is almost directlyproportional to the increase in the dye ratio.

3.4.3 Potential Aquatic Plant, Slime and AlgalDensity Change Due to Flushing RatesChanges in algal densities without and with docks

were compared to observed data results. Mean,maximum, and minimum algal densities among thedocks as computed were about the same magnitudeof the mean, maximum, and minimum algal densi-ties computed from observed data over a year indi-cating that the simulations are producing realisticalgal densities using algal model default parametersgiven in Edinger (2002, able 10-1). Te range ofalgal densities with the docks in place was estimatedto be 2 to 3 times the range of algal densities pres-ently observed throughout a year and with the docksit is expected that the algal problems will get worse.

Figure 5 shows the relationship between the Cwd/Cnd

Figure 4. Relationships between Cwd/Cnd Ratio andChange in DOD

Dye Ratio vs DOD Change

-3

-2

-1

0

1

2

0 0.5 1 1.5 2

Dye Ratio

DODChange,mg/l

DOD

Figure 5. Relationships between Cwd/Cnd Ratio andChange in Phytoplankton

Dye Ratio vs Chla Change

-50

-40

-30

-20

-10

0

10

20

3040

50

0 0.5 1 1.5 2

Dye Ratio

ChlaChange,ug/l

Chla

Figure 6. Relationships between Flushing Time and Change

in Phytoplankton.

Flushing Time Change vs Chla

Change

-60

-40

-20

0

20

40

60

-50 -25 0 25 50 75

Flushing Time Change, Days

ChlaChange,ug/l

Chla


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12


ratio and change in algal densities with the additionof the docks. Like Figure 2, the change in algal densi-ties is bifurcated indicating that some of the changeis due to the addition of the docks themselves, andsome of the change is due to the location of thedocks within the reservoir. Figure 6 shows that thechange in algal densities is more directly related tothe increased ushing time which, similar to Figure2, is related to location throughout the reservoir.

3.4.4 Application to Changes in SedimentationNot all the sediment will be lost within a multi-slipdocking region, but some will be carried out intothe remainder of the lake transporting with it theseeds from the phytoplankton and attached aquaticsthat settle to the bottom of the reservoir and growto the spores and cysts that release vegetative cellularmaterial that results in algal blooms (McGillicuddyet al. 2003, Edinger et al. 2003).

Analysis of the increase in sedimentation rateswithout and with docks showed that the sedimen-tation rate will increase with a variance (StandardDeviation/Mean) by about a factor of 5. hevariance for the dye tracer ratio for comparison isabout 0.2, indicating that there is a wider variationin the increase in sedimentation rates at dierentlocations throughout the reservoir. Figure 7 showsthat the increase in sedimentation is proportionalto the Cwd/Cnd dye ratio.

3.4.5 Application o Dierent Dock FlushingCriteria to Proposed Tims Ford DocksTe State of Florida has a specic guideline for

ushing at individual multi-slip docking facilities(SJRWMD 2005). Te guideline is to reduce thetest dye concentration to 10% of the initial value

in 4 days for a dye test carried out at an individualmarina. Tis test is dierent from the change inthe concentration of dye of the whole lake usedpreviously, where the latter can be replenished as itis ushed away from a marina location. It providesan independent analysis of the marinas relative toan independent criterion that is used elsewhere todetermine if there will be water quality problems atthe multi-slip docking facility.

Te application of the Florida guideline requires

dying each individual multi-slip docking facilityalone and comparing the dye concentration withinthe facility to the initial dye concentration at theend of four days. Each individual multi-slip dockingfacility was initialized with a dye concentration of1,000 ug/l and the remaining dye concentration atthe end of 4 days was determined. Te multi-slipdocking facilities dye concentration at the end offour days showed that only 9 of the facilities ex-amined, or less than 20%, might have satised theFlorida individual marina facility ushing criteriaof having a dye concentration of 100 ug/l or less at

the end of 4 days. Most of the 9 multi-slip dockingfacilities that would satisfy the Florida marina ush-ing criteria are located along the eastern shorelineof Map 1 where the original channel of the maininowing Elk River is located.

State of Florida ocials point out that the ush-ing guideline is only one criterion for marina anddockage facility siting (Lazar, 2005) and other localconditions need to be considered. However, even bythis simple criterion close to 80% of the proposed

multi-slip docking facilities for ims Ford reser-voir will have water quality problems due to poorushing. Te international ANZECC (2000, Sec.8.1.9.1) guideline for ushing required to minimizealgal densities can be applied using Figure 6. Figure6 shows that doubling the ushing times more thandoubles the change in algal densities at most of theindividual docks.

4. SummaryAnalyses of the potential water quality impact ofmarinas are usually required prior to construction,such as for determining whether violations of statewater quality standards would occur prior to the

Figure 7. Relationships between Cwd/Cnd Ratio and

Change in Settling Rate

Dye Ratio vs Sedimentation

RateChange

-50

-40

-30

-20

-10

0

10

20

0 0.5 1 1.5 2

Dye Ratio

SedRateChange,

kg/m^2/year

Sed Rate


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13


issuance of state certications under section 401 ofthe Clean Water Act. Since the facilities do not yetexist, a comparative analysis can be used whereby

conditions are compared with and without the fa-cility in place. In this paper, a comparative analysiswas demonstrated for a set of 41 multi-slip dockingfacilities planned for placement along the shorelineof ims Ford Reservoir, located on the Elk Riverin south central ennessee. Te comparative studywas based on the application of the publicly avail-able three-dimensional Generalized Longitudinal,Lateral, and Vertical Hydrodynamic and ransport(GLLVH) model given in Edinger (2002) basedon earlier formulations of GLLVH by Edinger

and Buchak (1980, 1985, 1995). Te comparativeanalysis of ushing based on the hydrodynamicmodel application allowed evaluation of the changesin water quality including coliforms, dissolved oxy-gen, algal densities and sedimentation that will takeplace along the shoreline and in the vicinity of themulti-slip docking facilities.

Te comparative analysis showed that there willbe reduced ushing in over 92% of the proposedmulti-slip docking locations and that the increasedushing time will worsen water quality conditions

as indicated by comparison to US State of FloridaGuidelines and international ANZECC Guidelines.Te analysis suggested that the change in waterquality will not be limited to the multi-slip dockingareas alone, and that local changes will ultimatelyaect water quality throughout 67% of the area ofthe reservoir. In particular the increased algal densi-ties will generate seed for spores and cysts that willspread throughout the reservoir by attachment tosediment and decaying algae. Te increase in benthicspores and cysts will increase the likelihood of the

occurrence of algal blooms following constructionof the multi-slip docking facilities.

Te reports on data for coliforms, dissolved oxygenand algal densities given in Dycus and others (1992,1999) indicate that water quality in ims FordReservoir is generally unacceptable for recreationaluse of the reservoir. Te model simulation resultsshowed that the magnitude of the probable changesin these water quality parameters with the docks inplace was greater than the observed seasonal changesin these water quality constituents over a year ofavailable data by factors of 3 to 5 mostly due to

reduced ushing or increased ushing time furtherindicating that the docks would have a signicantimpact on the reservoir.

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Notation

Te following symbols are used in this paper:nd = subscript to indicate condition no dockingfacilities in place,wd = subscript to indicate condition with dockingfacilities in place,oo = subscript to indicate background conditions,BOD = Biochemical oxygen demand,C = Concentration,Co = Initial concentration,Cp = Phytoplankton concentration,Cs = Sediment concentration,C(sim) = Individual cell dye concentration at the

end of the simulation (sim),Dd = Phytoplankton death rate,DOD = Dissolved oxygen decit,Dr = Phytoplankton respiration rate,Gp = Phytoplankton growth rate as limited by con-centrations of nitrogen (N),phosphorous (I), and light (I),K = First order decay rate,Kdg = Zooplankton density dependent grazing rate,Kphy= Phytoplankton net growth rate,Kr = Reservoir ushing rate,

Q = Flow rate,Qr = Outow rate,Rbod = Rate of BOD decay,Rd = Constituent decay rate (coliform dye-o forexample),Rre = Surface reaeration rate,sim = Simulation time,Vdk= Volume of the model cell containing the multi-slip docking facility,Vr = Reservoir volume,Vs = Settling velocity.

effects of the addition of multi-slip docks

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