Inverse modeling with RZWQM2 to predict water quality

Methods of Introducing System Models into Agricultural Research

Volumn 2, Issue , 2015, Pages 327-363

  Nolan, Bernard T ^a   Malone, Robert W ^b   Ma, Liwang ^b   Green, Christopher T ^c   Fienen, Michael N ^d   Jaynes, Dan B ^b  

^a U S GEOLOGICAL SURVEY   (United States)

^b AGRICULTURAL RESEARCH SERVICE   (United States)

^c U S GEOLOGICAL SURVEY   (United States)

^d WISCONSIN WATER SCIENCE CENTER   (United States)

Author keywords

California; Inverse modeling; Inverse modeling theory; Iowa; PEST setup; Root zone water quality model; Water quality

Indexed keywords

EID: 85102465108     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.2134/advagricsystmodel2.c12     Document Type: Chapter

References (38)

1. Ahuja, L.R., K.W. Rojas, J.D. Hanson, M.J. Shaffer, and L. Ma. 2000. Root Zone Water Quality ModelModelling management effects on water quality and crop production. Water Resources Publ., Highlands Ranch, CO.
2. Allen, R. 1996. Assessing integrity of weather data for reference evapotranspiration estimation. J. Irrig. Drain. Eng. 122:97-106.
3. Cambardella, C.A., T.B. Moorman, D.B. Jaynes, J.L. Hatfield, T.B. Parkin, W.W. Simpkins, and D.L. Karlen. 1999. Water quality in Walnut Creek watershed: Nitrate-nitrogen in soils, subsurface drainage water, and shallow groundwater. J. Environ. Qual. 28:25-34.
4. Cameira, M.R., R.M. Fernando, L.R. Ahuja, and L. Ma. 2007. Using RZWQM to simulate the fate of nitrogen in field soil-crop environment in the Mediterranean region. Agric. Water Manage. 90:121-136.
5. Capel, P.D., K.A. McCarthy, and J.E. Barbash. 2008. National, holistic, watershed-scale approach to understand the sources, transport, and fate of agricultural chemicals. J. Environ. Qual. 37:983-993.
6. Close, M.E., R. Lee, G.N. Magesan, M.K. Stewart, G. Skuse, and G. Bekesi. 2005. Field study of pesti cide leaching in a Himatangi sand (Manawatu) and in a Kiripaka bouldery clay loam (Northland). 1. Results. Aust. J. Soil Res. 43:457-469.
7. Close, M.E., R. Lee, A.K. Sarmah, L. Pang, R. Dann, G.N. Magesan, J.P.C. Watt, and K.W. Vincent. 2008. Pesticide sorption and degradation characteristics in New Zealand soils-A synthesis from seven field trials. N.Z. J. Crop Hortic. Sci. 36:9-30.
8. Corwin, D.L., J. Hopmans, and G.H. De Rooij. 2006. From field- to landscape-scale vadose zone processes: Scale issues, modeling, and monitoring. Vadose Zone J. 5:129-139.
9. Doherty, J. 2008. PEST surface water utilities. Watermark Numerical Computing, Brisbane, Australia and University of Idaho, Idaho Falls.
10. Doherty, J. 2010. PEST-Model independent parameter estimation. Watermark Numerical Computing, Brisbane, Australia.
11. Doherty, J., and R.J. Hunt. 2009. Two statistics for evaluating parameter identifiability and error reduction. J. Hydrol. 366:119-127.
12. Doherty, J., and D. Welter. 2010. A short explanati on of structural noise. Water Resour. Res. 46:W05525, doi:10.1029/2009WR008377.
13. Domagalski, J.L., S.P. Phillips, E.R. Bayless, C. Zamora, C. Kendall, R.A. Wildman, and J.G. Hering. 2008. Influences of the unsaturated, saturated, and riparian zones on the transport of nitrate near the Merced River, California, USA. Hydrogeol. J. 16:675-690.
14. Fang, Q., T.R. Green, L. Ma, R.H. Erskine, R.W. Malone, and L.R. Ahuja. 2010. Optimizing soil hydraulic parameters in RZWQM2 under fallow conditions. Soil Sci. Soc. Am. J. 74:1897-1913.
15. Fisher, L.H., and R.W. Healy. 2008. Water movement within the unsaturated zone in four agricultural areas of the United States. J. Environ. Qual. 37:1051-1063.
16. Hanson, J., K. Rojas, and M. Shaffer. 1999. Calibrating the Root Zone Water Quality Model. Agron. J. 91:171-177.
17. Hatfield, J.L., J.H. Prueger, and D.W. Meek. 1999. Spatial variation of rainfall over a large watershed in central Iowa. Theor. Appl. Climatol. 64:49-60.
18. Hill, M.C., and O. Osterby. 2003. Determining extreme parameter correlation in ground water models. Ground Water 41:420-430.
19. Hill, M.C., and C.R. Tiedeman. 2007. Effective groundwater model calibration with analysis of data, sensitivities, predictions, and uncertainty. John Wiley and Sons, Hoboken, NJ.
20. Jaynes, D.B., D.L. Dinnes, D.W. Meek, D.L. Karlen, C.A. Cambardella, and T.S. Colvin. 2004. Using the late spring nitrate test to reduce nitrate loss within a watershed. J. Environ. Qual. 33:669-677.
21. Karlen, D.L., D.L. Dinnes, D.B. Jaynes, C.R. Hurburgh, C.A. Cambardella, T.S. Colvin, and G.R. Rippke. 2005. Corn response to late-spring nitrogen management in the Walnut Creek watershed. Agron. J. 97:1054-1061.
22. Legates, D.R., and G.J. McCabe. 1999. Evaluating the use of "goodness-of-fit" measures in hydrologic and hydroclimatic model evaluation. Water Resour. Res. 35:233-241.
23. Lin, Z., and D.E. Radcliffe. 2006. Automatic calibrate on and predicti ve uncertainty analysis of a semi-distributed watershed model. Vadose Zone J. 5:248-260.
24. Ma, L., L.R. Ahuja, S.A. Saseendran, R.W. Malone, T.R. Green, B.T. Nolan, P.N.S. Bartling, G.N. Flerch- inger, K.J. Boote, and G. Hoogenboom. 2011. A protocol for parameterization and calibration of RZWQM2 in field research. p. 1-64. In L.R. Ahuja and L. Ma (ed.) Methods of introducing system models into agricultural research. Advances in Agricultural Systems Modeling 2. ASA, CSSA, and SSSA, Madison, WI.
25. Ma, L., R.W. Malone, P. Heilman, D.L. Karlen, R.S. Kanwar, C.A. Cambardella, S.A. Saseendran, and L.R. Ahuja. 2007. RZWQM simulation of long-term crop production, water and nitrogen balances in Northeast Iowa. Geoderma 140:247-259.
26. Ma, L., R.W. Malone, D.B. Jaynes, K.R. Thorp, and L.R. Ahuja. 2008. Simulated effects of nitrogen management and soil microbes on soil nitrogen balance and crop production. Soil Sci. Soc. Am. J. 72:1594-1603.
27. Malone, R.W., D.B. Jaynes, L. Ma, B.T. Nolan, D.W. Meek, and D.L. Karlen. 2010. Soil-test N recommendations augmented with PEST-optimized RZWQM simulations. J. Environ. Qual. 39:1711-1723.
28. Malone, R.W., L. Ma, P. Heilman, D.L. Karlen, R.S. Kanwar, and J.L. Hatfield. 2007. Simulated N management effects on corn yield and tile-drainage nitrate loss. Geoderma 140:272-283.
29. Meyer, P.D., M.L. Rockhold, and G.W. Gee. 1997. Uncertainty analyses of infiltration and subsurface flow and transport for SDMP Sites. Report NUREG/CR-6565 PNNL-11705. U.S. Nuclear Regulatory Commission, Washington, DC.
30. Miller, C.T., G.A. Williams, C.T. Kelley, and M.D. Tocci. 1998. Robust solution of Richards' equation for nonuniform porous media. Water Resour. Res. 34:2599-2610.
31. Nolan, B.T., L.J. Puckett, L. Ma, C.T. Green, E.R. Bayless, and R.W. Malone. 2010. Predicting unsaturated zone nitrogen mass balances in agricultural settings of the United States. J. Environ. Qual. 39:1051-1065.
32. Poeter, E.P., and M.C. Hill. 1997. Inverse models: A necessary next step in ground-water modeling. Ground Water 35:250-260.
33. Poeter, E.P., M.C. Hill, E.R. Banta, S. Mehl, and S. Christensen. 2005. UCODE_2005 and six other computer codes for universal sensiti vity analysis, calibrate on, and uncertainty evaluation. USGS Techniques and Methods 6-A11. USGS, Reston, VA.
34. Schmied, B., K. Abbaspour, and R. Schulin. 2000. Inverse estimation of parameters in a nitrogen model using field data. Soil Sci. Soc. Am. J. 64:533-542.
35. Schwarz, G.E., A.B. Hoos, R.B. Alexander, and R.A. Smith. 2006. The SPARROW surface water- quality model: Theory, application, and user documentation. USGS Techniques and Methods Report, Book 6, Chapter B3. USGS, Reston, VA.
36. Thorp, K.R., R.W. Malone, and D.B. Jaynes. 2007. Simulating long-term effects of nitrogen fertilizer application rates on corn yield and nitrogen dynamics. Trans. ASABE 50:1287-1303.
37. USDA-NRCS. 2009. NSSH Part 618-Soil properties and qualities. Subpart B- Exhibits Available at http://soils.usda.gov/technical/handbook/contents/part618ex.html (accessed November 2009, verified 12 May 2011).
38. Vecchia, A.V., and R.L. Cooley. 1987. Simultaneous confidence and predicti on intervals for nonlinear regression models with application to a groundwater flow model. Water Resour. Res. 23:1237-1250.