SWAT model validation for point and non point source pollution

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This presentation is based on a project conducted in Texas, United States for establishing Best Management Practices in order to attain water quality standards under point and non point source pollutants.

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VALIDATION OF THE SWAT MODEL ON A LARGE RIVER BASIN WITH POINT AND NONPOINT SOURCES :

VALIDATION OF THE SWAT MODEL ON A LARGE RIVER BASIN WITH POINT AND NONPOINT SOURCES Citation: Santhi , C. , Arnold, J. G., Williams, J. R. , Dugas , W. A., Srinivasan , R., Hauck, L. M., 2001.Validation of the SWAT model on a large river basin with point and nonpoint sources. Journal of the American Water Resources Association 37(5): 1171-1188.

Contents:

Contents Introduction Purpose of the study Objective SWAT model description Study area Input data Performance indicators Model calibration Model validation Best Management Practices Results and discussion Summary and Conclusion Conclusions

Introduction:

Introduction United States Environmental Protection Agency ( USEPA, 1994 ) reported that nutrient enrichment is the major cause for impairment of water bodies. To restore the quality of these water bodies, the Total Maximum Daily Load ( TMDL ) was established by the Clean Water Act. A TMDL quantifies maximum allowable loads to the contributing point and nonpoint sources ( 1998 ). After establishment of TMDLs, control measures like Best Management Practices ( BMPs ) are implemented.

Introduction:

Introduction Texas Natural Resource Conservation Commission Texas State Soil and Water and Conservation Board Classified water bodies ……. : 386 Listed on the1998 303(d) list : 147 Bosque River watershed in North Central Texas: Phosphorus from confined animal-feeding operations Runoff from cropland and urban areas (nonpoint sources) Effluent from waste water treatment plants (point sources)

Purpose of the Study:

Purpose of the Study Assisting in TMDL development using water quality simulation models. Obtaining information for TMDL waste/load allocations and implementation strategies using models in combination with observational data.

Objective:

Objective To study the effect of different BMPs in reducing the pollution. To describe the calibration and validation of the SWAT model for flow, sediment, organic, and nutrients.

SWAT Model Description:

SWAT Model Description Hydrologic/ water quality model Developed by United States Department of Agriculture - Agricultural Research Service Continuous time model operates on a daily time step Predicts the impact of management on water, sediment, and agricultural chemical yields in large ungauged basins.

SWAT Model Description:

SWAT Model Description SWAT is physically based; uses readily available inputs; is computationally efficient to operate on large basins in a reasonable time; and is continuous in time and capable of simulating long periods for computing the effects of management changes.

SWAT Model Description:

SWAT Model Description

SWAT Model Description:

SWAT Model Description Output Parameter Method/ Approach Equation/ Function Sediment yield Modified Universal Soil Loss Equation Y = 11.8 ( Q s q p A area ) 0.56 K ⋅C⋅P⋅LS ⋅CFRG Channel sediment routing Bagnold's sediment transport equation CY U = SPCON×V SPEXP Plant Nitrogen use Williams et al., 1984 f(plant biomass, N concentration, N in soil ) Nitrate-N in ruoff , percolation, lateral flow f(nitrate in soil, volume of water ) Organic N transport McElroy et al.,1976 f(organic N in top soil, sediment yield, enrichment ratio )

SWAT Model Description:

Y : sediment yield on a given day ton Q s : surface runoff mm q p : peak runoff rate m 3 /s A area : Area km 2 K : soil erodibility factor C : cover and management factor P : support practice factor LS : topographic factor CFRG : coarse fragment factor CY U : sediment transport concentration capacity g/m 3 SPCON : concentration capacity at a velocity of 1 m/s g/m 3 V : flow velocity m/s SPEXP : constant in Bagnold's equation. SWAT Model Description

SWAT Model Description:

SWAT Model Description Output Parameter Method/ Approach Equation/ Function Plant Phosphorus use Williams et al., 1984 f(demand, supply) Soluble Phosphorus in runoff Leonard and Wauchope , 1980 f(P conc. in 10mm top soil, runoff volume, Partitioning factor ) Instream nutrient dynamics Brown and Barnwell, 1987 QUAL2E model kinetic routines Instream soluble P transformation First-order decay kinetics PC 0 = PC i ×e -a( chl /q) PC i or o : Soluble P inflow and outflow concentrations g/m 3 a : degradation coefficient chl : channel length km q : flow rate mm/day

Understanding Nitrogen:

Understanding Nitrogen Nitrogen Cycle source ( http://en.wikipedia.org/wiki/Nitrogen_cycle )

SWAT Model Description:

SWAT Model Description

SWAT Model Description:

SWAT Model Description

Study Area: Bosque River Watershed:

Study Area: Bosque River Watershed Area : 4277 km 2 Soil: HSG C,D sandy loam clay silty clay clay loamy Gravel 28% shallow soils

Study Area: Bosque River Watershed:

Study Area: Bosque River Watershed 100 dairies, 40,450 cows Pollution Sources: Dairy manure application over an area of about 9,450 ha Cropland & Urban runoff Waste Water Treatment Plants

Study Area: Bosque River Watershed:

Study Area: Bosque River Watershed Major crops under non waste application area: Corn, winter wheat, grain sorghum Percentage area under manure waste application: Summer pasture/ bermuda grass 40% Summer pasture grass with winter wheat in rotation 30% Sorghum hay 5% Sorghum hay with winter wheat in rotation 25%

Input Data:

Input Data Input files were developed using Geographic Resource Analysis Support System-Geographic Information System (GRASS-GIS)

Performance Indicators:

Performance Indicators Indicator Formula Characteristic Mean Standard Deviation Coefficient of Determination Indicates strength of relationship between the observed and simulated values Nash- suttcliffe Simulation Efficiency Indicates how well the plot of observed versus simulated value fits the 1:1 line Sorted Efficiency or Prediction Efficiency model's ability to describe the probability distribution of the observed results

Model Calibration:

Model Calibration Calibration period Streamflow : 1960 - 1997 Sediment & nutrient: Simulation: 1990 - 1998 Calibration: Hico:1993 -1997 Valley Mills:1996 -1997

Model Validation:

Model Validation Validation period: January to December 1998 Location: Hico Valley Mills

Best Management Practices:

Best Management Practices

Results and Discussion:

Results and Discussion

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Results and Discussion

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Results and Discussion

Summary and conclusion:

Summary and conclusion In general, simulated flow and nutrients were closer to the measured values during the validation. There was some underprediction of simulated sediment and organic nutrients in March1998 at Valley Mills. These underpredictions caused significant degradation in model prediction statistics in validation. SWAT predictions were acceptable, especially given the approximations and spatial variability involved in simulating a large complex system or watershed.

Summary and conclusion:

Summary and conclusion Scenario E, a scenario with added BMP conditions over the existing scenario, showed higher percentage reductions in mm loadings. The SWAT calibration and validation procedures presented in this paper are useful to researchers and engineers involved in studying water quality problems.

References:

References Williams, J. R., C. A. Jones, and P. A. Dyke, 1984. A Modeling Approach to Determine the Relationship Between Erosion and Soil Productivity. Transactions of ASAE 27:129-144. McElroy, A. D., S. Y. Chiu, J. W. Nebgen et al., 1976. Loading Functions for Assessment of Water Pollution from Nonpomt Sources. Environmental Protection Technical Services, EPA 600/2-76- 151. Leonard, R. A. and R. D. Wauchope , 1980. CREAMS: A Field-Scale Model for Chemicals, Runoff and Erosion from Agricultural Management Systems. In: The Pesticide Submodel , W. G. Kinsel , (Editor). USDA Conservation Research Report No. 2, Chapter 5. Brown, L. C. and T. 0. Barnwell, 1987. The Enhanced Water Quality Models: QUAL2E and QUAL2E-UNCAS Documentation and User Manual. EPA/600/3-87/007, USEPA. Athens, Georgia.

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