5 th International SWAT Conference Development of a tool to estimate Best Management Practices (BMP) efficiency using SWAT Maringanti C., I. Chaubey, B. Engel Purdue University, West Lafayette, IN M. Arabi Colorado State University, Fort Collins, CO
Outline Introduction Objectives Methodology Case study watershed Results and discussion Conclusions Future work 2
NPS pollution Nitrogen Phosphorus Sediment Pesticides Source: Alexander et al., 2008 Source: N.Rabalais, Louisiana Universities Marine Consortium Hypoxia in the Gulf of Mexico: Area ~ 16,700 km 2 3
BMPs to reduce NPS pollution Best management practices (BMPs) a viable solution to reduce NPS pollutant loads Buffer filter strips Parallel terraces Grade stabilization structures Grassed waterways Residue management Strip cropping Contour cropping Farm bill 2007 provides $7.8 b for conservation practices Terrace Strip cropping Source: NEWQD, Purdue University 4
BMP selection problem BMP selection and placement in a watershed is a daunting task Example: 10 BMPs to be selected in 100 farms will have 10 100 combinations Optimization algorithms required to search the solution space to find best possible ecologically effective and environmentally feasible solution(s) Genetic algorithm 5
Goals and objectives Overall Goal Develop an easy to use interface to perform BMP optimization to achieve maximum pollution reduction with minimum BMP implementation costs in the watershed Objectives 1)Develop an interface to estimate the BMP pollution effectiveness 2)Develop an interface for optimal selection and placement of BMPs in a watershed for NPS pollution control 6
Combination of BMPs A set created with different combinations of BMPs for implementation based on land use, soil, and slope constraints All the possible combination of BMPs are evaluated using the SWAT model e.g. if corn field can take 3 BMPs and soybean can take 9 different BMPs; 27 different combinations to estimate the pollution reduction efficiencies 7
BMP SIMulator (BSIM) tool Pollution reduction efficiencies of BMPs estimated using the BSIM tool Implements a combination of BMPs possible at a HRU/subbasin or basin level in the watershed Simulates the SWAT model to estimate the pollutant loads with the presence of BMPs Estimate the pollution reduction efficiency by comparing the reduced load with the baseline (with the current scenario) 8
BSIM Tool developed in Matlab TM GUIDE tool in Matlab to create the interface BMP details input through the interface BMP represented at a HRU/subbasin or basin level in SWAT Some BMPs directly represented in the SWAT model (e.g. filter strips, tillage practices, residue management) Other BMPs representation from previous studies (Arabi et al. 2008 1 ) Modify the input files based on the BMP selected Similar to the swatedit developed by Dr. Yang and Dr. Abbaspour 2 at EAWAG but more focused on BMP implementation and an easy to use interface 1 Arabi, M., J. R. Frankenberger, B. A. Engel, and J. Arnold (2008). Representation of agricultural conservation practices with SWAT, Hydrological Processes. 2 http://www.eawag.ch/organisation/abteilungen/siam/software/swat/index_en 9
BSIM interface 10
Study watershed Wildcat Creek Watershed USGS 8 digit HUC 05120107 Area: 1956 km 2 74% row crops (38% corn, 34% soybean) Pesticide is an important pollutant of concern in the watershed NPS pollution reduction projects through USEPA 319 USGS Station ID 03335000 Calibration gauge IDEM Station ID 03911 IDEM Station ID 03910 USGS Station ID 03337000 USGS Station ID 03333450 11
Results SWAT model setup 30 m DEM from USGS 52 subbasins STATSGO soils and NASS 2007 land use 509 HRUs 12
Calibration for stream flow 300 250 Simulated Observed R 2 = 0.80 2 R NS = 0.58 Stream flow (m 3 /s) 200 150 100 50 0 01-Jan-2000 30-Apr-2000 28-Aug-2000 26-Dec-2000 25-Apr-2001 23-Aug-2001 21-Dec-2001 20-Apr-2002 18-Aug-2002 16-Dec-2002 15-Apr-2003 13-Aug-2003 11-Dec-2003 09-Apr-2004 07-Aug-2004 05-Dec-2004 13
Calibration for sediment 20 Monthly Sediment Load (1000tons) 15 10 5 Observed (Loadest) Simulated (SWAT) R 2 = 0.88 2 R NS = 0.62 0 0 10 20 30 40 50 60 Month 14
Representation of BMPs in SWAT SWAT parameters Updated value SWAT input file extension CH_N2 (Manning s roughness) CH_COV (Channel cover) CH_EROD (Chanel erodibility) Grass Waterways 0.25.rte 0.001.rte 0.001.rte Grass Waterways Filter Strips Filter Strips FILTERW (Filter strip width) 10 (m).mgt Source: NEWQD, Purdue University 15
BMP reduction efficiencies BMP Scenario Total Sediment Load (t/ha) % Sediment Reduction Baseline 6.38 Grassed Waterways 6.18 3 Parallel Terrace 1.063 83 Contour 4.4 31 Filter Strip 10 m 1.8 71 16
Conclusions BMP SIMulator (BSIM) tool can be used to represent several agricultural BMPs at a watershed level to obtain BMP pollution reduction efficiencies Tool was developed using Matlab Matlab license not necessary to run the tool Tool tested for application of BMPs in Wildcat Creek Watershed in Indiana 17
Future work Incorporate the BMP optimization tool into a common framework to obtain optimal selection and placement of BMPs in a watershed Expand the number of BMPs to be simulated using the tool Test the model for application of BMPs in watersheds of varied climate and land use 18
Thanks for your attention Questions? 19