Agronomy Journal Journal of Natural Resources and Life Sciences Education
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Published in Agron. J. 95:1510-1524 (2003).
© American Society of Agronomy
677 S. Segoe Rd., Madison, WI 53711 USA

CROPPING SYSTEMS

Evaluation of GPFARM for Dryland Cropping Systems in Eastern Colorado

Allan A. Andalesa, Lajpat R. Ahuja*,a and Gary A. Petersonb

a USDA-ARS Great Plains Syst. Res. Unit, P.O. Box E, Fort Collins, CO 80522
b Dep. of Soil and Crop Sci., Colorado State Univ., Fort Collins, CO 80523

* Corresponding author (Laj.Ahuja{at}ars.usda.gov).

Received for publication August 29, 2002. GPFARM is an ARS decision support system for strategic (long-term) planning. This study evaluated its performance for comparing alternative dryland no-till cropping systems and established limits of accuracy for eastern Colorado, using data collected in 1987 through 1999 from an ongoing long-term experiment at three locations along a gradient of potential evapotranspiration (PET) (Sterling, low PET; Stratton, medium PET; and Walsh, high PET). The crop rotations, which included winter wheat (Triticum aestivum L.), corn (Zea mays L.), sorghum [Sorghum bicolor (L.) Moench], proso millet (Panicum miliaceum L.), and varying fallow periods, were wheat–fallow, wheat–corn–fallow, and wheat–corn–millet–fallow at Sterling and Stratton and wheat–fallow, wheat–sorghum–fallow, and wheat–sorghum–millet–fallow at Walsh. The ranges of relative error (RE) of simulated mean and root mean square error (RMSE) were total soil profile water content (RE: 0 to 23%; RMSE: 38 to 76 mm water), dry mass grain yield (RE: -27 to 84%; RMSE: 419 to 2567 kg ha-1), dry mass crop residue (RE: -5 to 42%; RMSE: 859 to 1845 kg ha-1), and total soil profile residual nitrate N (RE: -42 to 32%; RMSE: 26 to 78 kg ha-1). GPFARM simulations agreed with observed trends and showed that productivity and water use efficiency increased with cropping intensification and that Stratton was the most productive and Walsh the least. GPFARM (v. 2.01) was less suited for year-to-year grain yield prediction under dryland conditions but has potential as a tool for studying long-term interactions between environment and crop management system. Future development and applications of GPFARM must account for crop-specific responses to stress, detailed hydrology, better understanding of root uptake processes, and spatial variability to give more accurate grain yield predictions in water-stressed environments.

Abbreviations: CCC, Colorado Climate Center • CV, coefficient of variation • DSS, decision support system • ET, evapotranspiration • HI, harvest index • LAImax , maximum leaf area index • PET, potential evapotranspiration • RE, relative error of mean • RMSE, root mean square error • WCF, wheat–corn–fallow (rotation) • WCMF, wheat–corn–millet–fallow (rotation) • WC(S)F, wheat–corn (or sorghum)–fallow (rotation) • WC(S)MF, wheat–corn (or sorghum)–millet–fallow (rotation) • WF, wheat–fallow (rotation) • WSF, wheat–sorghum–fallow (rotation) • WSMF, wheat–sorghum–millet–fallow (rotation) • WUE, water use efficiency







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