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United States Department of Agriculture

Agricultural Research Service

Research Project: ENHANCED SYSTEM MODELS AND DECISION SUPPORT TOOLS TO OPTIMIZE WATER LIMITED AGRICULTURE Title: Evaluating GPFARM Crop Growth, Soil Water, and Soil Nitrogen Components for Colorado Dryland Locations

Author
item Ascough, James

Submitted to: Natural Resources Research Update (NRRU)
Publication Type: Research Technical Update
Publication Acceptance Date: March 30, 2009
Publication Date: March 30, 2009
Repository URL: http://ars.usda.gov/Research/docs.htm?docid=15371
Citation: Ascough II, J.C. 2009. Evaluating GPFARM Crop Growth, Soil Water, and Soil Nitrogen Components for Colorado Dryland Locations. Natural Resources Research Update (NRRU). Update #238985.

Technical Abstract: GPFARM is a farm/ranch decision support system (DSS) designed to assist in strategic management planning for land units from the field to the whole-farm level. This study evaluated the regional applicability and efficacy of GPFARM based on simulation model performance for dry mass grain yield, total soil profile water content, crop residue, and total soil profile residual NO3-N across a range of dryland no-till experimental sites in eastern Colorado. Field data were collected from 1987 through 1999 from an on-going, long-term experiment at three locations in eastern Colorado along a gradient of low (Sterling), medium (Stratton), and high (Walsh) potential evapotranspiration. Simulated crop alternatives were winter wheat (Triticum aestivum L.), corn (Zea mays L.), sorghum (Sorghum bicolor L.), proso millet (Panicum miliaceum L.), and fallow. Relative error (RE) of simulated mean, root mean square error (RMSE), and index of agreement (d) model evaluation statistics were calculated to compare modeled results to measured data. A one-way, fixed-effect ANOVA was also performed to determine differences among experimental locations. GPFARM simulated versus observed REs ranged from -3% to 35% for crop yield, 6% to 8% for total soil profile water content, -4% to 32% for crop residue, and -7% to -25% for total soil profile residual NO3-N. For trend analysis (magnitudes and location differences), GPFARM simulations generally agreed with observed trends and showed that the model was able to simulate location differences for the majority of model output responses. GPFARM appears to be adequate for use in strategic planning of alternative cropping systems across eastern Colorado dryland locations; however, further improvements in the crop growth and environmental components of the simulation model (including improved parameterization) would improve its applicability for short-term (tactical) planning scenarios. Publications contributing to the NRRU Release as shown above: Ascough II, J. C., G. S. McMaster, A. A. Andales, N. C. Hansen, and L. A. Sherrod. 2007. Evaluating GPFARM crop growth, soil water, and nitrogen component for Colorado dryland locations. Transactions of the ASABE 50(5): 1565-1578. Ascough II, J. C., M. J. Shaffer, D. L. Hoag, G. S. McMaster, G. H. Dunn, L. R. Ahuja, and M. A. Weltz. 2002. GPFARM: An integrated decision support system for sustainable Great Plains agriculture. In Sustaining the Global Farm - Local Action for Land Leadership: Selected Papers from the 10th Intl. Soil Conservation Organization (ISCO) Conference, 951-960. D. E. Stott, R. H. Mohtar, and G. C. Steinhardt, eds. West Lafayette, Ind.: Purdue University, USDA-ARS and the International Soil Conservation Organization. McMaster, G. S., J. C. Ascough II, G. H. Dunn, M. A. Weltz, M. J. Shaffer, D. Palic, B. C. Vandenberg, P. N. S. Bartling, D. Edmunds, D. L. Hoag, and L. R. Ahuja. 2002. Application and testing of GPFARM: A farm and ranch decision support system for evaluating economic and environmental sustainability of agricultural enterprises. Acta Horticulturae 593: 171-177. McMaster, G. S., J. C. Ascough II, M. J. Shaffer, L. A. Deer-Ascough, P. F. Byrne, D. C. Nielsen, S. D. Haley, A. A. Andales, and G. H. Dunn. 2003. GPFARM plant model parameters: Complications of varieties and the genotype x environment interaction in wheat. Trans. ASAE 46(5): 1337-1346. Peterson, G. A., D. G. Westfall, and C. V. Cole. 1993. Agroecosystem approach to soil and crop management research. SSSA J. 57(5): 1354-1360. Peterson, G. A., D. G. Westfall, F. B. Peairs, L. Sherrod, D. Poss, W. Gangloff, K. Larson, D. L. Thompson, L. R. Ahuja, M. D. Koch, and C. B. Walker. 2000. Sustainable dryland agroecosystem management. Tech. Bulletin No. TB00-3. Fort Collins, Colo.: Colorado State University Agricultural Experiment Station. Shaffer, M. J., P. N. S. Bartling, and J. C. Ascough II. 2000. Object-oriented simulation of integrated whole farms: GPFARM framework. Comp. Elect. Agric. 28(1): 29-49. Shaffer, M. J., P. N. S. Bartling, and G. S. McMaster. 2004. GPFARM modeling of corn yield and residual soil nitrate-N. Comp. Elect. Agric. 43(2): 87-107. Sherrod, L. A., G. A. Peterson, D. G. Westfall, and L. R. Ahuja. 2005. Soil organic pools after 12 years in no-till dryland agroecosystems. SSSA J. 69(5): 1600-1608.

Last Modified: 10/22/2014
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