Bacteria Loadings Bacteria Loadings Watershed ModelWatershed Model

Copano Bay Copano Bay watershedwatershed

Copano Bay

Carrie GibsonCE 394K.2 Surface Water HydrologySpring Semester 2005University of Texas at AustinInstructor: David R. Maidment

BackgroundBackground

Section 303(d) of 1972 Clean Water Act Section 303(d) of 1972 Clean Water Act (CWA)(CWA)

Texas Surface Water Quality StandardsTexas Surface Water Quality Standards Fecal Coliform BacteriaFecal Coliform Bacteria EnterococciEnterococci

Aransas RiverAransas River Copano Copano BayBay

Mission RiverMission River

1.1. Identify major bacterial sources in Identify major bacterial sources in Copano Bay watershed.Copano Bay watershed.

2.2. Calculate total bacterial loadings, Total Calculate total bacterial loadings, Total Maximum Daily Loads (TMDLs), from Maximum Daily Loads (TMDLs), from bacterial sources.bacterial sources.

3.3. Determine amount of load reductions Determine amount of load reductions that is needed to meet water quality that is needed to meet water quality standards.standards.

Project OverviewProject Overview

Objective of Term ProjectObjective of Term Project

Model the accumulation and transport of Model the accumulation and transport of bacteria from upstream watersheds to bacteria from upstream watersheds to Copano Bay.Copano Bay.

Use Model Builder in Arc Toolbox of ArcGIS Use Model Builder in Arc Toolbox of ArcGIS 9.0.9.0.

Modify Schematic Processor.Modify Schematic Processor. Decays bacteria loads along streams segmentsDecays bacteria loads along streams segments Calculates increase in concentration in bay due to Calculates increase in concentration in bay due to

upstream bacteria loadings (CFSTR model)upstream bacteria loadings (CFSTR model)

GIS Data Preparation: Arc GIS Data Preparation: Arc HydroHydro

Terrain PreprocessingTerrain Preprocessing Watershed DelineationWatershed Delineation

Create Geometric NetworkCreate Geometric Network Use WRAP HydroUse WRAP Hydro

Legend

Value

High : 171.515244

Low : -2.198932

Legend

DescriptionBacteria Monitoring Stations

USGS Gauge Stations

Water Segment Endpoints

Watersheds

Basis of CalculationsBasis of Calculations

LoadLoad (cfu/year)(cfu/year) = = Flow Flow (m(m33/year)/year) * * Concentration Concentration (cfu/m(cfu/m33))

Runoff CalculationsRunoff Calculations

Ann Quenzer’s Thesis (based on land Ann Quenzer’s Thesis (based on land use)use) AgricultureAgriculture

QQ = 0.008312 * exp ( 0.011415 * = 0.008312 * exp ( 0.011415 * PP ) ) ForestForest

QQ = 0.0053 * exp ( 0.010993 * = 0.0053 * exp ( 0.010993 * PP ) ) UrbanUrban

QQ = 0.24 * = 0.24 * PP Open WaterOpen Water

QQ = 0 = 0

QQ = Runoff (mm/year) = Runoff (mm/year)PP = Precipitation (mm/year) – from PRISM = Precipitation (mm/year) – from PRISM

Runoff Calculations Runoff Calculations (continued)(continued)

Tools UsedTools Used Spatial Analyst Spatial Analyst

Analysis MaskAnalysis Mask Raster CalculatorRaster Calculator

Example: AgricultureExample: Agriculture

MosaicMosaic

Q = 0.008312 * exp ( 0.011415 * ) =

QAgriculture +Qtotal (mm/yr)

QOpenWater + QForest + QUrban

=

P Q

Runoff Calculations Runoff Calculations (continued)(continued)

Model Builder (Overview)

Agriculture

Forest

Urban

Open Water

Spatial Analyst/Raster CalculatorSpatial Analyst/Raster Calculator [mm/year]*(30m)*(30m)*(1m/1000mm) = [mm/year]*(30m)*(30m)*(1m/1000mm) =

[m[m33/yr]/yr]

0.9 * [mm/year] = [m0.9 * [mm/year] = [m33/year] /year] Zonal StatisticsZonal Statistics

Sum of runoff in Sum of runoff in delineated watershedsdelineated watersheds

Runoff Calculations Runoff Calculations (continued)(continued)

Model Builder (Overview)

Legend

350068 - 7314390

7314391 - 19471190

19471191 - 37897196

37897197 - 76952504

76952505 - 140070144

Runoff per Watershed (m3/year)

Event Mean Concentrations Event Mean Concentrations (EMCs)(EMCs)

From Reem Jihan From Reem Jihan Zoun’s thesis, Zoun’s thesis, Estimation of Fecal Estimation of Fecal Coliform Loadings Coliform Loadings to Galveston Bayto Galveston Bay

Join EMC table to Join EMC table to Land Use polygon Land Use polygon feature classfeature class

Land Land Use Use

CodeCodeCategoryCategory Fecal Fecal

Colonies Colonies per 100 mLper 100 mL

1111 Open WaterOpen Water 00

2121 Low Intensity ResidentialLow Intensity Residential 22,00022,000

2222 High Intensity ResidentialHigh Intensity Residential 22,00022,000

23 23 Commercial/Industrial/Commercial/Industrial/TransportationTransportation

22,00022,000

3131 Bare Rock/Sand/ClayBare Rock/Sand/Clay 00

3232 Quarries/Strip Mines/Gravel Quarries/Strip Mines/Gravel PitsPits

00

4141 Deciduous ForestDeciduous Forest 1,0001,000

4242 Evergreen ForestEvergreen Forest 1,0001,000

4343 Mixed ForestMixed Forest 1,0001,000

5151 ShrublandShrubland 2,5002,500

6161 Orchards/Vineyards/OtherOrchards/Vineyards/Other 2,5002,500

7171 Grasslands/HerbaceousGrasslands/Herbaceous 2,5002,500

8181 Pasture/HayPasture/Hay 2,5002,500

8282 Row CropsRow Crops 2,5002,500

8383 Small CropsSmall Crops 2,5002,500

8585 Urban/Recreational GrassesUrban/Recreational Grasses 22,00022,000

9191 Woody WetlandsWoody Wetlands 200200

9292 Emergent Herbaceous Emergent Herbaceous WetlandsWetlands

200200

Event Mean Concentrations Event Mean Concentrations (continued)(continued)

Model Builder (Overview) cfu/m3

Event Mean Concentrations Event Mean Concentrations (continued)(continued)

*

[C (cfu/m3)] [Q (m3/yr)]

Sums grid cell values for each watershed

=

[(cfu/yr)]

Annual Bacterial

Loading per grid cell

Model Builder (Overview)

Bacterial Loading (cfu/year)Bacterial Loading (cfu/year)

Legend

Watersheds

BacteriaLoadings_Q

7.826016E+12

1.814594E+13

5.753609E+13

7.43162E+13

1.385689E+14

1.885352E+14

2.168401E+14

2.631193E+14

3.652496E+14

4.272617E+14

4.508016E+14

4.525783E+14

4.924875E+14

5.693007E+14

5.86366E+14

7.790088E+14

9.367532E+14

1.071634E+15

1.802483E+15

2.147E+15

2.308304E+15

3.307898E+15

Bacterial Loadings per Watershed

Model Builder: SummaryModel Builder: Summary

Runoff (m3/yr)

Concentration (cfu/m3)

Load (cfu/year)

Cumulative Loading per Watershed

Cumulative Runoff per Watershed

Schematic Processor

Schematic ProcessorSchematic Processor

Schematic NetworkSchematic Network Feature ClassesFeature Classes

SchemaNode (watershed or junction in stream network)SchemaNode (watershed or junction in stream network) SchemaLink (straight lines that connect Schematic nodes)SchemaLink (straight lines that connect Schematic nodes)

Legend

SchemaNode

1

2

3

SchemaLink

1

2

3

WatershedDrainage JunctionBay

Watershed to JunctionJunction to JunctionJunction to Bay

Schematic Processor Schematic Processor (continued)(continued)

Implemented using dynamic linked libraries, Implemented using dynamic linked libraries, DLLsDLLs clsDecay.dllclsDecay.dll

Simulates decay of bacteria along stream segmentsSimulates decay of bacteria along stream segments loadloadpassedpassed = load = loadreceivedreceived * e * e-kt-kt

k = first-order decay coefficient (dayk = first-order decay coefficient (day-1-1) - stored as attribute in ) - stored as attribute in SchemaLinkSchemaLink

t = travel time along streams, t (days) - stored as attribute in t = travel time along streams, t (days) - stored as attribute in SchemaLinkSchemaLink

Decay

Schematic Processor Schematic Processor (continued)(continued)

clsCFSTR.dllclsCFSTR.dll Calculates the increase in concentration of a bay due to Calculates the increase in concentration of a bay due to

bacteria loadings.bacteria loadings. AssumptionsAssumptions

Bay is completely mixed and acts as Continuous Flow, Bay is completely mixed and acts as Continuous Flow, Stirred Tank Reactor (CFSTR)Stirred Tank Reactor (CFSTR)

Inflow = OutflowInflow = Outflow c = L/(Q+kV)c = L/(Q+kV)

c = concentration in bay (cfu/mc = concentration in bay (cfu/m33))

L = bacteria load entering bay (cfu/yr)L = bacteria load entering bay (cfu/yr)

Q = total flow (mQ = total flow (m33/yr) – stored as attribute in SchemaNode/yr) – stored as attribute in SchemaNode

k = first-order decay coefficient (dayk = first-order decay coefficient (day-1-1) - stored as attribute ) - stored as attribute in SchemaNodein SchemaNode

V = volume of bay (mV = volume of bay (m33) – stored as attribute in SchemaNode) – stored as attribute in SchemaNode

Parameters (Inputs)Parameters (Inputs) SchemaLink (SrcTypes 1 and 2)SchemaLink (SrcTypes 1 and 2)

Travel TimeTravel Time (t in days), (t in days), Decay CoefficientDecay Coefficient (k in day (k in day-1-1)) SchemaNode SchemaNode

SrcType 3 – Copano BaySrcType 3 – Copano Bay VolumeVolume (V in m (V in m33), ), Decay CoefficientDecay Coefficient (k in day (k in day-1-1)) Cumulative RunoffCumulative Runoff (Q in m (Q in m33/year) /year)

SrcType 1 – WatershedsSrcType 1 – Watersheds Bacterial Loading per WatershedBacterial Loading per Watershed (L in cfu/year) (L in cfu/year)

Schematic Processor: Schematic Processor: SummarySummary

Determined by UserDetermined by UserCalculated from Previous Steps in Model Calculated from Previous Steps in Model BuilderBuilder

Results: Cumulative Runoff Results: Cumulative Runoff (m(m33/yr)/yr)

Legend

CumRunoff_m3_yr

5324348 - 5453502

5453503 - 25230928

25230929 - 67500777

67500778 - 134301478

134301479 - 624956736

Results: Bacterial Loading Results: Bacterial Loading (cfu/yr)(cfu/yr)

Legend

PassedVal

7315246902771.310000 - 1.326444e+014

1.326444e+014 - 3.652496e+014

3.652496e+014 - 5.861752e+014

5.861752e+014 - 1.071634e+015

1.071634e+015 - 3.307898e+015

Results: Concentration Results: Concentration (cfu/100mL)(cfu/100mL)

Legend

Concentration_cfu_100mL

1.583800 - 42.812500

42.812501 - 162.007900

162.007901 - 390.243300

390.243301 - 732.386900

732.386901 - 2845.973800

Tasks to be CompletedTasks to be Completed

Determine Determine travel timestravel times of river segments of river segments and and decay coefficientsdecay coefficients of bacteria. of bacteria.

Incorporate point source bacteria loadings Incorporate point source bacteria loadings into non-point source bacteria loading into non-point source bacteria loading model.model. Determine locations and bacteria loadings Determine locations and bacteria loadings

from horses, cattle, waterbirds (probable from horses, cattle, waterbirds (probable candidates), WWTPscandidates), WWTPs

Compare model loads and concentrations Compare model loads and concentrations to existing monitoring data. to existing monitoring data.