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SWAT Model Application to Assess the Impact of Intensive Corn-farming on Runoff, Sediments and Phosphorous loss from an Agricultural Watershed in Wisconsin

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DOI: 10.4236/jwarp.2012.47049    5,101 Downloads   7,981 Views   Citations

ABSTRACT

The potential future increase in corn-based biofuel may be expected to have a negative impact on water quality in streams and lakes of the Midwestern US due to increased agricultural chemicals usage. This study used the SWAT model to assess the impact of continuous-corn farming on sediment and phosphorus loading in Upper Rock River watershed in Wisconsin. It was assumed that farmers in the area where corn was rotated with soybean would progressively skip soybean for continuous corn as corn became more profitable. Simulations using SWAT indicated that conversion of corn-soybean to corn-corn-soybean would cause 11% and 2% increase in sediment yield and TP loss, respectively. The conversion of corn-soybean to continuous corn caused 55% and 35% increase in sediment yield and TP loss, respectively. However, this increase could be mitigated by applying various BMPs and/or conservation practices such as conservation tillage, fertilizer management and vegetative buffer strips. The conversion to continuous corn tilled with conservation tillage reduced sediment yield by 2% and did not change TP loss. Increase in P fertilizer amount was roughly proportional to increase in TP loss and 11% more TP was lost when fertilizer was applied four months before planting. Vegetative buffer strips, 15 to 30 m wide, around corn farms reduced sediment yield by 51 to 70% and TP loss by 41 to 63%.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

E. Mbonimpa, Y. Yuan, M. Mehaffey and M. Jackson, "SWAT Model Application to Assess the Impact of Intensive Corn-farming on Runoff, Sediments and Phosphorous loss from an Agricultural Watershed in Wisconsin," Journal of Water Resource and Protection, Vol. 4 No. 7, 2012, pp. 423-431. doi: 10.4236/jwarp.2012.47049.

References

[1] R. B. Alexander, R. Smith, G. Schwarz, E. Boyer, J. N lan and J. Brakebill, “Differences in Phosphorus and Nitrogen Delivery to the Gulf of Mexico from the Mississippi River Basin,” Environmental Science & Technology, Vol. 42, No. 3, 2008, pp. 822-830. doi:10.1021/es0716103
[2] USEPA, “National Water Quality Inventory,” Report to Congress, 2004 Reporting Cycle.
[3] T. W. Simpson, R. W. Howarth, H. W. Paerl, A. Sharpley and K. Mankin, “The New Gold Rush: Fueling Ethanol Production While Protecting Water Quality,” Journal of Environmental Quality, Vol. 37, No. 2, 2008, pp. 318-324. doi:10.2134/jeq2007.0599
[4] D. A. Landis, M. M. Gardiner, W. Van der Werf and S. Swinton, “Increasing Corn for Biofuel Production Reduces Biocontrol Services in Agricultural Landscapes,” Proceedings of the National Academy of Sciences of the United States of America, Vol. 105, No. 51, 2008, pp. 20552-20557. doi:10.1073/pnas.0804951106
[5] The CADMUS group, Inc., “Total Maximum Daily Loading (TMDL) for Total Phosphorus and Total Suspended Solids in the Rock River Basin,” July 2011 Final Report.
[6] A. N. Sharpley, B. Foy and P. Withers, “Practical and Innovative Measures for Control of Agricultural Phosphorus Losses to Water: An Overview,” Journal of Environmental Quality, Vol. 29, No. 1, 2000, pp. 1-9. doi:10.2134/jeq2000.00472425002900010001x
[7] M. W. Gitau, W. J. Gburek and A. R. Jarrett, “A Tool for Estimating BMP Effectiveness for Phosphorus Pollution Control,” Journal of Soil and Water Conservation, Vol. 60, No. 1, 2005, pp. 1-10.
[8] A. N. Sharpley, and H. Tunney, “Phosphorous Research Strategies to Meet Agricultural and Environmental Challenges of the 21st Century,” Journal of environmental quality, Vol. 29, No. 1, 2000, pp. 176-181. doi:10.2134/jeq2000.00472425002900010022x
[9] Y. Yuan, R. L. Bingner and R. A. Rebich, “Evaluation of AnnAGNPS on Mississippi Delta MSEA Watersheds,” Transactions of the ASAE, Vol. 44, No. 5, 2001, pp. 1183-1190.
[10] L. Heathwaite, A. Sharpley and W. Gburek, “A Conceptual Approach for Integrating Phosphorus and Nitrogen Management at Watershed Scales,” Journal of Environmental Quality, Vol. 29, No. 1, 2000, pp. 158-166. doi:10.2134/jeq2000.00472425002900010020x
[11] I. Chaubey, L. Chiang, M. W. Gitau and S. Mohamed, “Effectiveness of Best Management Practices in Improving Water Quality in Pasture-Dominated Watershed,” Journal of Soil And Water Conservation, Vol. 65, No. 6, 2010, pp. 424-437. doi:10.2489/jswc.65.6.424
[12] Y. Yuan, R. L. Bingner and M. A. Locke, “A Review of Effectiveness of Vegetative Buffers on Sediment Trapping in Agricultural Areas,” Ecohydrology, Vol. 2, 2009, pp. 321-336. doi:10.1002/eco.82
[13] Y. Yuan, M. H. Mehaffey, R. D. Lopez, R. L. Bingner, R. Bruins, C. Erickson and M. A. Jackson, “AnnAGNPS Model Application for Nitrogen Loading Assessment for the Future Midwest Landscape Study,” Water, Vol. 3, 2011, pp. 196-216. doi:10.3390/w3010196
[14] G. W. Roth, “Crop Rotations and Conservation Tillage,” Conservation Tillage Series (1), College of Agricultural Sciences Cooperative Extension Penn State University, 1996.
[15] W. Rawls and H. H. Richardson, “Runoff Curve Numbers for Conservation Tillage,” Journal of soil and water conservation, Vo. 38, No. 6, 1983, pp. 494-496.
[16] J. Dejong-Hughes and J. Vetsch, “On-Farm Comparison of Conservation Tillage Systems for Corn Following Soybeans,” University of Minnesota Extension, 2007.
[17] J. G. Arnold, R. Srinivasan, R. S. Muttiah and J. R. Williams, “Large Area Hydrologic Modeling and Assessment, Part I: Model Development,” Journal of American Water Resources Association, Vol. 34, No. l, 1998, pp. 73-89. doi:10.1111/j.1752-1688.1998.tb05961.x
[18] S. L. Neitch, J. G. Arnold, J. R. Kiniry and J. R. Williams, “Soil and Water Assessment tool theoretical documentation,” Blackland Research Center, Temple, Texas, 2005.
[19] B. Schmalz and N. Fohrer, “Comparing Model Sensitivities of Different Landscapes Using the Ecohydrological SWAT Model,” Advances in Geosciences, Vol. 21, 2009, pp. 91-98. doi:10.5194/adgeo-21-91-2009
[20] M. W. Gitau, L. Chiang, M. Sayeed and I. Chaubey, “Watershed Modeling Using Large-Scale Distributed Computing in Condor and SWAT,” Simulation, Vol. 88, No. 3, 2012, pp. 365-380. doi:10.1177/0037549711402524
[21] M. Mehaffey, R. Van Remortel, E. Smith and R. Bruins, “Developing a Dataset to Assess Ecosystem Services in the Midwest United States,” International Journal of Geographic Information Services, Vol. 25, 2011, pp. 681-685. doi:10.1080/13658816.2010.497148
[22] D. N. Moriasi, J. G. Arnold, M. W. Van Liew, R. L. Bingner, R. D. Harmel and T. L. Veith, “Model Evaluation Guidelines for Systematic Quantification of Accuracy in Watershed Simulations,” Transactions of the ASABE, Vol. 50, No. 3, 2007, pp. 885-900.
[23] K. L. White and I. Chaubey, “Sensitivity Analysis, Calibration, and Validation for a Multisite and Multivariable SWAT Model,” Journal of the American Water Resources Association, Vol. 41, No. 5, 2005, pp. 1077-1089. doi:10.1111/j.1752-1688.2005.tb03786.x
[24] P. W. Gassman, M. R. Reyes, C. H. Green and J. G. Arnold, “The Soil and Water Assessment Tool: Historical Development, Application and Future Research Directions,” Transactions of ASABE, Vol. 50, No. 4, 2007, pp. 1211-1250.
[25] A. Van Griensven, T. Meixner, S. Grunwald, T. Bishop, M. Di Luzio and R. A. Srinivasan, “Global Sensitivity Analysis Method for the Parameters of Multi-Variable Watershed Models,” Journal of Hydrology, Vol. 324, No. 1-4, 2006, pp. 10-23. doi:10.1016/j.jhydrol.2005.09.008
[26] USDA-NRCS, “Rusle 2 and Crop Management Zones,” 2011. http://fargo.nserl.purdue.edu/rusle2_dataweb/RUSLE2_Index.htm
[27] S. L. Neitch, J. G. Arnold, J. R. Kiniry and J. R. Williams, “Soil and Water Assessment Tool Input/Output File Documentation,” Blackland Research Center, Temple, Texas, 2005.
[28] J. B. Peters, C. A. M. Laboski and L. G. Bundy, “Sampling Soils for Testing,” University of Wisconsin-Extension Publication A2100, 2007.

  
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