Fecal bacteria source characterization and sensitivity analysis of SWAT 2005

2007 ASABE Annual International Meeting, Technical Papers

Volumn 6 BOOK, Issue , 2007, Pages

  Parajuli, Prem B ^a   Mankin, Kyle R ^a   Barnes, Philip L ^a   Green, Colleen H ^b  

^a Sunflower Networking Group   (United States)

^b U S DEPARTMENT OF AGRICULTURE   (United States)

Author keywords

Fecal coliform bacteria; Rainfall; Runoff; Sensitivity analysis; SWAT; Watershed

Indexed keywords

GEOMETRIC MEAN VALUE; INDEPENDENT PARAMETER PERTURBATION (IPP); LATIN HYPERCUBE SAMPLING (LHS);

MATHEMATICAL MODELS; RAIN; RUNOFF; SENSITIVITY ANALYSIS; WATERSHEDS;

COLIFORM BACTERIA;

EID: 35648936893     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (73)

1. ASAE Standards. 2000. D384.1: Manure production and characteristics. St. Joseph, MI: ASAE.
2. Arnold, J. G., R. Sinivasan, R. S. Muttiah, and J. R. Williams. 1998. Large area hydrologic modeling and assessment part I: model development. J. Am. Water Resour. Assoc. 34(1): 73-89.
3. Baffaut, C., and V. W., Benson. 2003. A bacterial TMDL for Shoal creek using SWAT modeling and DNA source tracking. Pp. 035-040 In Total Maximum Daily Load (TMDL) environmental regulations-II proceedings of the 8-12 November 2003 conference. ASAE Publication No. 701P1503. St. Joseph, MI: ASAE.
4. Barnes, E. M., and J. H. Young. 1994. Sensitivity analysis of the soil inputs for the growth model PEANUT. Trans. ASAE 37(5): 1691-1694.
5. Benaman, J., and C. A. Shoemaker. 2004. Methodology for analyzing ranges of uncertain model parameters and their impact on total maximum daily load process. J. Environ. Eng. 130(6): 648-656.
6. Boyer, W. Personal communication. 21 April 2005. Extension watershed specialist. Department of Agronomy, Kansas State University: Manhattan, KS.
7. Brunner, A. C., S. J. Park, G. R. Ruecker, R. Dikau, and P. L. G. Vlek. 2004. Catenary soil development influencing erosion susceptibility along a hillslope in Uganda. CATENA 58(1): 1-22.
8. Chang, S. S. 1999. Implementing probabilistic risk assessment in USEPA superfund program. Hum. Ecol. Risk Assess. 5(4): 737-754.
9. Clesceri, L., A. Greenberg, and A. Eaton. 1998. Standard methods for the examination of water and wastewater. Am. Public Health Assoc. Baltimore, MD: United Book Press, Inc.
10. Craun, G. F., and F. J. Frost. 2002. Possible information bias in a waterborne outbreak investigation. Int. J. Environ. Health Res. 12(1): 5-15.
11. Eckhardt, K., S. Haverkamp, N. Fohrer, and H. G. Frede. 2002. SWAT-G, a version of SWAT99.2 modified for application to low mountain range catchments. Phys. Chem. Earth 27: 641-644.
12. Ferreira, V. A., G. A. Weesies, D. C. Yoder, G. R. Foster, and K. G. Renard. 1995. The site and condition specific nature of sensitivity analysis. J. Soil Water Cons. 50(5): 493-497.
13. Feyereisen, G. W., T. C., Strickland, D. D. Bosch, and H. L. Batten. 2005. Evaluation of SWAT input parameter sensitivity for the Little River watershed. ASAE Paper No. 052167. St. Joseph, MI: ASAE.
14. Fontaine, D. D., P. L. Havens, G. E. Glau, and P. M. Tillotson. 1992. The role of sensitivity analysis in groundwater risk modeling for pesticides. Weed Tech. 6(3): 716-724.
15. Graff, C. D., A. M. Sadeghi, R. R. Lowrance, and R. G. Williams. 2005. Quantifying the sensitivity of the riparian ecosystem management model (REMM) to changes in climate and buffer characteristics common to conservation practices. Trans. ASAE 48(4): 1377-1387.
16. Griensven, A. V. 2005. Sensitivity, auto-calibration, uncertainty and model evaluation in SWAT 2005. SWAT documentation 2005. Grassland, Soil & Water Research Laboratory, USDA-ARS. Temple, TX.
17. Gwo, J. P., L. E. Toran, M. D. Morris, and G. V. Wilson. 1996. Subsurface stormflow modeling with sensitivity analysis using a Latin-Hypercube sampling technique. Ground Water 34(5): 811-818.
18. Haan, C. T. 1989. Parametric uncertainty in hydrologic modeling. Trans. ASAE 32(1): 137-146.
19. Haan, C. T., and J. Zhang. 1996. Impact of uncertain knowledge of model parameters on estimated runoff and phosphorus loads in the Lake Okeechobee Basin. Trans. ASAE 39(2): 511-516.
20. Hession, W. C., D. E. Storm, C. T. Haan, S. L. Burks, and M. D. Matlock. 1996a. A watershed-level ecological risk assessment methodology. Water Resour. Bull. 32(5): 1039-1054.
21. Hession, W. C., D. E. Storm, and C. T. Haan. 1996b. Two-phase uncertainty analysis: An example using the universal soil loss equation. Trans. ASAE 39(4): 1309-1319.
22. Huisman, J. A., L. Breuer, and H. G. Frede. 2004. Sensitivity of simulated hydrological fluxes towards changes in soil properties in response to land use change. Phys. Chem. Earth 29: 749-758.
23. James, L. D. and S. J. Burges. 1982. Selection, Calibration, and Testing of Hydrologic Models. In: Hydrologic Modeling of Small Watersheds, Pp 437-472. C.T. Haan, H.P. Johnson, and D.L. Brakensiek (Eds). ASAE Monograph. St. Joseph, MI.
24. Jepson, M. 2005. Personal communication. Environmental scientist. Kansas Department of Health and Environment, Bureau of Water, Livestock Waste Management Section: Topeka, KS.
25. Jesiek, J. B. and M. L. Wolfe. 2005. Sensitivity Analysis of the Virginia Phosphorus Index management Tool. Trans. ASAE 48(5): 1773-1781.
26. Kansas Applied Remote Sensing (KARS) Program. 2001. GAP Analysis Program. Available at: http://www.kansasgis.org/catalog/catalog.cfm. Accessed on 29 March 2006.
27. Kansas Department of Agriculture. 2004a. Kansas Agricultural Statistics. Kansas Farm Facts 2004. Available at: http://www.nass.usda.gov/ks/ ffacts/2004/pdf/ffpdf.htm Accessed 30 May 2005.
28. Kansas Department of Agriculture. 2004b. Kansas Agricultural Statistics Services. Bluestem Pasture. Special Press Release. April 22, 2004. Topeka, KS.
29. Kansas Department of Health and Environment. 2000. Bureau of Water. Clean water needs survey. Kansas non-point source need inventory, methodology and assumptions. KDHE: Topeka, KS.
30. Kirsch, K., A. Kirsch, and J. G. Arnold. 2002. Predicting sediment and phosphorus loads in the Rock River basin using SWAT. Trans. ASAE 45(6): 1757-1769.
31. Larocque, M., and O. Banton. 1994. Determining parameter precision for modeling nitrate leaching: Inorganic fertilization in Nordic climates. Soil Sci. Soc. Am. J. 58(2): 396-400.
32. Lenhart, T., K. Eckhardt, N. Fohrer, and H. G. Frede. 2002. Comparison of two different approaches of sensitivity analysis. Phys. Chem. Earth 27: 645-654.
33. Lloyd, F. 2006. Personal communication. Big game coordinator, Kansas Department of Wildlife and Parks: Topeka, KS.
34. McFeters, G. A., and D. G. Stuart. 1972. Survival of coliform bacteria in natural waters: field and laboratory studies with membrane diffusion chambers. Appl. Environ. Microbiol. 24: 805-811
35. Mankin, K. R., S. H. Wang, J. K. Koelliker, D.G. Huggins, and F. deNoyelles. 2003. Watershed-lake water quality modeling: Verification and application. J. Soil Water Cons. 58(4): 188-197.
36. Mankin, K. R., and J. K. Koelliker. 2001. Clinton lake water quality assessment project - final report. KDHE contract number NPS 98-059. Kansas Department of Health and Environment, Bureau of Water: Topeka, KS.
37. Moore, J. A., J. D. Smyth, E. S. Baker, J. R. Miner, and D. C. Moffitt. 1989. Modeling bacteria movement in livestock manure systems. Trans. ASAE 32(3): 1049-1053.
38. Nash, J. E., and J. V. Sutcliffe. 1970. River flow forecasting through conceptual models: Part I. A discussion of principles. J. Hydrol. 10(3): 282-290.
39. Nearing, M. A., L. D. Ascough, and H. M. L. Chaves. 1989. WEPP model sensitivity analysis, Ch. 14. In USDA-Water Erosion Prediction Project: Hillslope Profile Model Documentation, L. J. Lane, and M. A. Nearing, eds. NSERL Report No. 2, 14.1-14.33. W. Lafayette, IN: USDA-ARS-NSERL.
40. Neitsch, S. L., J. G. Arnold, J. R. Kiniry, J. R. Williams, and K. W. King. 2002. Soil and water assessment tool theoretical documentation (Ver. 2000). Grassland, Soil and Water Research Laboratory, Agricultural Research Service: Temple, TX.
41. Neitsch, S. L., J. G. Arnold, J. R. Kiniry, J. R. Williams. 2005. Soil and Water Assessment Tool (SWAT), Theoretical Documentation. Blackland Research Center, Grassland, Soil and Water Research Laboratory, Agricultural Research Service. Temple, TX.
42. Overcash, M. R., and J. M. Davidson. 1980. Environmental impact of non-point source pollution. Ann Arbor, MI: Ann Arbor Science Publishers, Inc.
43. Parajuli, P., K. R. Mankin, and P. L. Barnes. 2006. Sensitivity analysis of SWAT/Microbial submodel for fecal bacteria prediction on a grazed watershed. Mid-Central ASABE Conference Paper No. MC06-4103. St. Joseph, MI.: ASABE.
44. Paul D., and S. L. Watson. 1994. Stocking rate and grazing management. MF-1118. Kansas State University Agricultural Experiment Station and Cooperative Extension Service: Manhattan, KS.
45. Peek, M. 2005. Personal communication. 16 February. Furbearer biologist, Kansas Department of Wildlife and Parks: Topeka, KS.
46. Pitman, J. 2006. Personal communication. 25 January. Small game coordinator, Kansas Department of Wildlife and Parks: Topeka, KS.
47. Sadeghi, A. M., and J. G., Arnold. 2002. A SWAT/Microbial Sub-Model for Predicting Pathogen Loadings in Surface and Groundwater at Watershed and Basin Scales. Pp. 56-63. Total Maximum Daily Load (TMDL) Environmental Regulations. ASAE Publication No. 701P0102. ASAE: St. Joseph, MI
48. Saleh A., J. G. Arnold, P. W. Gassman, L. M. Hauck, W. D. Rosenthal, J. R. Williams, and A. M. S. MacFarland. 1999. Application of SWAT for the Upper North Bosque River watershed. Trans. ASAE 43(5): 107-1087.
49. Sammons, N. 2007. Personal communications. Blackland Research Center, Grassland, Soil and Water Research Laboratory, Agricultural Research Service. Temple, TX.
50. Santhi, C., J. G. Arnold, J. R. Williams, L. M. Hauck, and W. A. Dugas. 2001. Application of a watershed model to evaluate management effects on point and non-point source pollution. Trans. ASAE 44(6): 1559-1570.
51. Shirmohammadi, A., I. Chaubey, R. D. Harmel, D. D. Bosch, R. Muñoz-Carpena, C. DharmaSi, A. Sexton, M. Arabi, M. L. Wolfe, J. Frakenberger, C. Graff, and T. M. Sohrabi. 2006. Uncertainty in TMDL Models. Trans ASABE 49(4): 1033-1049.
52. Silberbush, M., and S. A. Barber. 1983. Sensitivity analysis of parameters used in simulating K uptake with a mechanistic mathematical model. Agron. J. 75(6): 851-854.
53. Sohrabi, T. M., A. Shirmohammadi, T. W. Chu., H. Montas, and A. P. Nejadhashemi. 2002. Incorporating uncertainty analysis in SWAT2000 model predictions. ASAE Paper No. 022013. St. Joseph, MI: ASAE.
54. Soupir, M. L., H. E. Saied Mostaghimi, and E. F. Alphin. 2006. Partitioning of E. coli and Enterococci between plantonic and sorbed phases in surface runoff from pasturelands. ASAE Paper No. 062197. St. Joseph, MI: ASAE.
55. Soutter M., and A. Musy. 1999. Global sensitivity analysis of three pesticide leaching models using a Monte Carlo approach. J. Environ. Qual. 28(4): 1290-1297.
56. Spruill, C. A., S. R. Workman, and J. L. Taraba. 2000. Simulation of daily and monthly stream discharge from small watersheds using the SWAT model. Trans. ASAE 43(6): 1431-1439.
57. State of Kansas/Sanborn. 2002. Digital Orthophoto Quarter Quadrangles. Available at: http://www.kansasgis.org. Accessed 29 May 2006.
58. Suter, G. W. II, L. W. Barthouse, and R. V. O'Neil. 1987. Treatment of risk in environment impact assessment. Environ. Manag. 11(3): 295-303.
59. Timm, R. M., G. R. Pisani, N. A. Slade, J. R. Choate, G. A. Kaufman, and D. W. Kaufman. 2007. Mammals of Kansas. Available at: http://www.kS.ku.edu/ libres/Mammals_of_Kansas. Accessed 17 February 2007.
60. Tiscareno-Lopez, M., V. L. Lopes, J. J. Stone, and L. J. Lane. 1993. Sensitivity analysis of the WEPP watershed model for rangeland applications. I. Hillslope processes. Trans. ASAE 36(6): 1659-1672.
61. Tiscareno-Lopez, M., V. L. Lopes, J. J. Stone, and L. J. Lane. 1994. Sensitivity analysis of the WEPP watershed model for rangeland applications. II. Channel processes. Trans. ASAE 37(1): 151-158.
62. US, EPA. 2001. Protocol for developing pathogen TMDLs. EPA 841-R-00-002.
63. US, Department of Agriculture. 2006. Agriculture Census of the United States. National Atlas of the United States. Available at: http://www. nationalatlas.gov/atlasftp.html. Accessed 29 May 2006.
64. United States Department of Agriculture, Natural Resources Conservation Service. 2005. Soil Data Mart. Available at: http://soildatamart.nrcs.usda. gov/Default.aspx. Accessed 29 May 2006.
65. US, EPA. 1997. Policy for use of probabilistic analysis in risk assessment at the US, EPA. Science Policy Council. Washington, DC. Available at: http://www.epa.gov/osa/spc/2probana.htm. Accessed 18 March 2006.
66. US, Geological Survey. 1999. National Elevation Dataset. Available at: http://www.kansasgis.org/catalog/catalog.cfm. Accessed on 29 March 2006.
67. Walker, S. E., J. K. Mitchell, M. C. Hirschi, and K. E. Johnsen. 2000. Sensitivity analysis of the root zone water quality model. Trans. ASAE 43(4): 841-846.
68. Walker, S. E., S. Mostaghimi, T. A. Dillaha, and F. E. Woeste. 1990. Modeling animal waste management practices: impacts on bacteria levels in runoff from agricultural lands. Trans. ASAE 33(3): 807-817.
69. Wang, X., M. A. Youssef, R. W. Skaggs, J. D. Atwood, and J. R. Frankenberger. 2005. Sensitivity Analysis of the Nitrogen Simulation Model, DRAINMOD-N II. Trans. ASAE 48(6): 2205-2212.
70. Ward, A. D., and W. J. Elliot. 1995. Environmental Hydrology. New York, NY: Lewis Publishers.
71. White, K. L. and I. Chaubey. 2005. Sensitivity Analysis, Calibration, and Validations for a Multisite and Multivariable SWAT Model. J. Am. Water Resour. Assoc. 41(5): 1077-1089.
72. Zeckoski, R. W., B. L. Benham, S. B. Shah, M. L. Wolfe, K. M. Brannan, M. Al-Smadi, T. A. Dillaha, S. Mostaghimi, and C. D. Heatwole. 2005. BSLC: A tool for bacteria source characterization for watershed management. Trans. ASAE 21(5): 879-889.
73. Zerihun, D., Z. Wang, S. Rimai, J. Feyen, and J. M. Reddy. 1996. Analysis of surface irrigation performance terms and indices. Agri. Water Manag. 34(1): 25-46.