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Application of SWAT for Water Quality Modeling of the Caddo Lake Watershed, TXKendra Riebschleager, M.S., E.I.T.August 5, 2009
Espey Consultants, Inc.3809 S. 2nd Street, B-300Austin, TX 78704512.326.5659
2
Outline Description of Study Area Scope of Work Methodology
Project Setup/Watershed Delineation Edit Inputs Initial Results Calibration Procedures
Manual Sensitivity Analysis Auto-Calibration
Next Steps Coordinate with Lake Model Alternatives Analysis
3
Description of Study Area
4
Description of Study Area Population ~570,000 (10 counties, 1 parish) Employment – Services, wholesale/retail, and
manufacturing Agriculture – Livestock 64%, crop sales
22.5% Natural Resources – oil and gas industry,
lignite
5
Description of Study Area Topography
Gently rolling to hilly dissected by flat floodplains and terraces
Avg. Elevation 200 to 500 ft msl
Major Drainages Big Cypress Creek Little Cypress Creek Black Cypress Bayou James Bayou Frazier Creek
Soils Bowie-Cuthbert-Kirvin
Associations gently sloping to steep, well
drained to moderately well drained, loamy and gravelly
Darco Association gently sloping to
moderately steep, well drained, sandy soils
Cuthbert-Redsprings Association Strongly sloping to steep,
well drained, gravelly soils.
6
Description of Study Area Vegetative Cover
Pine and mixed Pine-hardwood Forests Cultivated or Pasture land Bottomland hardwood forest and Cypress Swamp
Climatology Avg. Annual Air Temperature 64-67ºF Precipitation
Storm events 60 days/yr ~33 inches
Evaporation Monthly Range ~10” in summer, 3” in winter
7
Description of Study Area
Photo: Bruce Moring, USGS
8
Scope of Work Model the watershed influences on Caddo Lake
Extent of Study: Cypress Basin downstream of Lake O’Pines
Parameters of Interest: Nutrients, DO, Bacteria
Develop hydrodynamic and water quality model for Caddo Lake
Perform Alternatives Analysis in support of WPP
Watershed ModelingMethodology
10
Watershed Modeling Cypress Creek Basin encompasses 110 mi2
over two-thirds rural significant amount of agricultural lands
SWAT provides a wide variety of agricultural surface treatments enabling simulation of structural and non-structural BMP's for evaluation of alternative strategies for runoff control from agricultural areas.
Currently not including bacteria in SWAT model SELECT approach Load Duration Curves
11
Watershed - SWAT Model Setup Watershed Delineation Hydrologic Response Unit (HRU) Definition
Unique areas with similar hydrologic characteristics to “lump” model runs
Input Data Files Weather data (precip, temp) PS and NPS Pollutant Loadings
Permitted Discharges Fertilizer/Pesticide Applications
Land Practices Ponds and Reservoirs
12
SWAT - WatershedDelineation Digital Elevation Model
NED 30-m NHD Plus Streams
Define Points of Interest
13
SWAT – Watershed Delineation Things to Consider
Calibration data Water Quality Station Locations USGS Flow Gage Locations
Point Sources Direct discharges from WWTP Expected Loading from CAFOs
Reservoirs and Large Ponds Lake O’Pines controlled discharge National Inventory of Dams (storage > 15,000 ac-ft)
Lake Gilmer 2001
14
SWAT – Delineated Watersheds
Lake O’ Pines Watershed
15
SWAT - HRU Definition Inputs Include: Land use
NLCD 2001 verified by aerial photography Soils
NRCS SSURGO Slope
SWAT derives from the DEM Four Classes
0-1%, 1-3%, 3-9%, >9%
16
SWAT – Edit Input Data Files Weather data (precip, temp, etc.)
Is data sufficient to spatially and temporally describe watershed? SWAT assigns weather data from nearest station location to sub-watershed
How can we improve the data? Interpolation Techniques
Point Source and Non-Point Source Pollutant Loadings Permitted Discharges Fertilizer Applications Livestock Grazing Septic Systems
Land Practices Pond data
storage > 15,000 ac-ft Along stream network
Reservoir data Volume Construction date
17
Run the SWAT Model Route watershed surface pollutants through
catchments Rainfall/Runoff Mechanisms
Simulated Weather Events SCS Curve Number Method
Growth and Decay Plant Uptake
Route pollutants from catchments to streams Incorporates QUAL-2E model for routing and predicting
stream concentrations
18
SWAT – Initial RunAverage Monthly Flow at USGS 07346045 Black Cypress Bayou
SWAT Subbasin 89
0
10
20
30
40
50
60
70
80
3/1997 7/1998 12/1999 4/2001 9/2002 1/2004 5/2005 10/2006 2/2008 7/2009
Date
Flow
(cm
s)
SWAT FlowUSGS Gauge Flow
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SWAT Calibration Process1. Hydrology
Daily Predicted vs. Measured at gauged locations2. Sediments
Total amounts (tons/acre) TSS concentrations
LOADEST for monthly load predictions3. Water Quality
Depends on reliable hydrology/sediment predictions Available SWQM data
Nitrogen (Total N, TKN, NH4, NO3, NO2) Phosphorus (Total P, Ortho-P)
20
SWAT - Model Calibration Sensitivity Analysis Determine which input parameters have greatest
influence on model results Use both measured and literature values for
fine tuning model inputs Incorporate Stakeholder Suggestions based on
their knowledge of the watershed
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SWAT Calibration - Hydrology Key Considerations
Water Balance Overall Amount Distribution among hydrologic components
Storm Sequence Time lag or shifts
Time of concentration, travel time Shape of Hydrograph
Peak Recession Consider antecedent conditions
22
SWAT Calibration - Hydrology Initial Run
Graphically compare prediction to flow data at gauged locations Manual Calibration
Adjust model parameters to more appropriately describe watershed Primarily Graphical Exercise
Sensitivity Analysis Which parameters have the greatest influence on the model
predictions? Auto-Calibration
Based on manual adjustment and modifying most sensitive parameters to meet model objectives
Saves time, increases efficiency Statistical Optimization Techniques
23
SWAT – Initial RunAverage Monthly Flow at USGS 07346045 Black Cypress Bayou
SWAT Subbasin 89
0
10
20
30
40
50
60
70
80
3/1997 7/1998 12/1999 4/2001 9/2002 1/2004 5/2005 10/2006 2/2008 7/2009
Date
Flow
(cm
s)
SWAT FlowUSGS Gauge Flow
24
Manual Calibration Procedure Peak Flows CN, canopy cover, soil available water capacity,
soil evaporation Groundwater (baseflows) Minimum flow, revap => Increase Deep Aquifer
Recharge Time of Peak Overland and Channel Roughness (n values) Surface lag coefficient
25
Manual CalibrationDaily Flow at USGS 07346045 / Subbasin 89 Black Cypress Bayou
0
100
200
300
400
500
600
1/1/2000 2/20/2000 4/10/2000 5/30/2000 7/19/2000 9/7/2000 10/27/2000 12/16/2000
Date
Flow
(cm
s)
0.0
20.0
40.0
60.0
80.0
100.0
120.0
140.0
160.0
180.0
200.0
USGS Gauge FlowSWAT Daily Flow Sim 16SWAT Daily Flow Sim 1Precip at Jefferson
26
Manual Calibration
Flow Duration Curve
0
20
40
60
80
100
120
140
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Percent Exceedance
Flow
(cm
s)
SWAT Sim 16Black Cypress Bayou Gauge
27
Sensitivity Analysis Estimate the rate of change in the output of a model
with respect to changes in model inputs Parameters important to have more accurate values Understand the behavior of the system being modeled Evaluate applicability of the model
Rank Name Description Location
1 ESCO Soil evaporation compensation factor *.hru
2 ALPHA_BF Baseflow alpha factor [days] *.gw
3 GWQMN Threshold water depth in the shallow aquifer for flow (mm) *.gw
4 CN2 Initial SCS CNII value *.mgt
5 CH_N2 Manning’s n value for main channel *.rte
6 CH_K2 Channel effective hydraulic conductivity [mm/hr] *.rte
7 SURLAG Surface runoff lag time [days] *.bsn
8 SOL_AWC Available soil water capacity [mm H2O/mm soil] *.sol
9 CANMX Maximum canopy storage [mm] *.hru
28
Auto-Calibration – In Progress Automation of calibration requires the formulation of
“closeness” measures (objective functions) Automatic Optimization
Algorithms that optimize an objective function by systematically searching the parameter space according to a fixed set of rules
Simplified by Sensitivity Analysis – determine parameters to optimize Manual Calibration – narrow optimization space for parameters
SWAT-CUP SUFI-2
Local Optimization Nash-Sutcliffe Objective Function
Next Steps
30
Calibration Re-run model with calibrated hydrology
parameters Begin Sediment Calibration Nutrient Calibration
31
Lake Modeling Watershed model output (SWAT results) will be
input to the lake model Pollutant loadings reaching the lake based on watershed
characteristics and practices Special Considerations for Caddo Lake
Lack of temperature stratification Off-channel wetland areas Shallow depths Invasive Species (Macrophytes)
Giant Salvinia Hyacinth
32
Lake Modeling EC Determined the Appropriate Model based
on Caddo Lake’s Unique Environment WASP7 (Water Quality Analysis Simulation
Program) Determine through scenario analysis the
impact of watershed NPS load Percent Reduction Goal Relative to other sources of pollutants
(resuspension, lake discharges, etc.)
33
SWAT - Alternatives Analysis Modify Watershed Practices Fertilizer Application CAFO waste management Structural BMPs Wastewater Treatment Options
Consolidate or Replace septic systems Additional Regionalized Collection Systems
Resultant Change in Pollutant Loadings Feed to lake model
34Espey Consultants, Inc.3809 S. 2nd Street, B-300Austin, TX 78704
Questions or Comments Phone 512-326-5659 Kendra Riebschleager
[email protected] David Harkins [email protected] Tim Osting [email protected] Ernest To [email protected]
35
Extra Slides
36
SELECT – Potential Bacteria Loading Spatially Explicit Load Enrichment Calculation Tool
Distributes Sources of Bacteria Livestock, Wildlife, Septic Systems, WWTPs
Within the appropriate habitat Livestock in pastures/grassland Wildlife in forested and non-developed lands Septic Systems in residential areas without municipal services
Considering other factors Magnitude of fecal production and bacteria concentration Soil type Distance to streams and waterbodies
37
Lake Modeling - WASP