S. A. Saseendran

Modeling nitrogen and water management effects in a wheat-maize double-cropping system

Excessive N and water use in agriculture causes environmental degradation and can potentially jeopardize the sustainability of the system. A field study was conducted from 2000 to 2002 to study the effects of four N treatments (0, 100, 200, and 300 kg N ha(-1) per crop) on a wheat (Triticum aestivum L.) and maize (Zea mays L.) double cropping system under 70 +/- 15% field capacity in the North China Plain (NCP). The root zone water quality model (RZWQM), with the crop estimation through resource and environment synthesis (CERES) plant growth modules incorporated, was evaluated for its simulation of crop production, soil water, and N leaching in the double cropping system. Soil water content, biomass, and grain yield were better simulated with normalized root mean square errors (NRMSE, RMSE divided by mean observed value) from 0.11 to 0.15 than soil NO(3)-N and plant N uptake that had NRMSE from 0.19 to 0.43 across these treatments. The long-term simulation with historical weather data showed that, at 200 kg N ha(-1) per crop application rate, auto-irrigation triggered at 50% of the field capacity and recharged to 60% field capacity in the 0- to 50-cm soil profile were adequate for obtaining acceptable yield levels in this intensified double cropping system. Results also showed potential savings of more than 30% of the current N application rates per crop from 300 to 200 kg N ha(-1), which could reduce about 60% of the N leaching without compromising crop yields.

EVALUATION OF RZWQM UNDER VARYING IRRIGATION LEVELS IN EASTERN COLORADO

The ability to predict and manage crop growth under varying available water conditions is of vital importance to the agricultural community since water is the most important limiting factor for agricultural productivity, especially in semi–arid regions. This study evaluated an agricultural system model, the USDA–ARS Root Zone Water Quality Model (RZWQM), for its ability to simulate the responses of corn (Zea mays L.) growth and yield to various levels of water stress. Data sets collected in 1984, 1985, and 1986 in northeastern Colorado were used for model evaluation. Three irrigation levels were imposed in 1984 and four levels in 1985 and 1986. Measurements included soil water content in 1985, leaf area index (LAI) and aboveground biomass in 1984 and 1985, and corn yield and plant height in 1984, 1985, and 1986. The RZWQM was calibrated for the lowest (driest) irrigation treatment in 1985 and then used to predict soil water and agronomic attributes for other irrigation treatments in all three years. Overall, the model responded well to irrigation treatments and weather conditions. Prediction of plant height was adequate in 1985 and 1986. Although biomass was reasonably predicted in early and late growing seasons, it was over–predicted during the middle growing season in both 1984 and 1985. Maximum LAI and plant height were over–predicted in 1984, however. Total soil water storage was well predicted in 1985, and so was evapotranspiration (ET) during the crop growing season. Yield predictions were within 1% to 35% of measured values for all the three years. Even with a low prediction of yield in 1986, the model correctly simulated the relative increase of yield with irrigation amount. Therefore, once RZWQM is calibrated for a location, it can be used as a tool to simulate relative differences in crop production under different irrigation levels and as a guide to optimize water management.

Winter Cover Crop Effects on Nitrate Leaching in Subsurface Drainage as Simulated by RZWQM-DSSAT

Planting winter cover crops such as winter rye (Secale cereale L.) after corn and soybean harvest is one of the more promising practices to reduce nitrate loss to streams from tile drainage systems without negatively affecting production. Because availability of replicated tile-drained field data is limited and because use of cover crops to reduce nitrate loss has only been tested over a few years with limited environmental and management conditions, estimating the impacts of cover crops under the range of expected conditions is difficult. If properly tested against observed data, models can objectively estimate the relative effects of different weather conditions and agronomic practices (e.g., various N fertilizer application rates in conjunction with winter cover crops). In this study, an optimized winter wheat cover crop growth component was integrated into the calibrated RZWQM-DSSAT hybrid model, and then we compared the observed and simulated effects of a winter cover crop on nitrate leaching losses in subsurface drainage water for a corn-soybean rotation with N fertilizer application rates over 225 kg N ha-1 in corn years. Annual observed and simulated flow-weighted average nitrate concentration (FWANC) in drainage from 2002 to 2005 for the cover crop treatments (CC) were 8.7 and 9.3 mg L-1 compared to 21.3 and 18.2 mg L-1 for no cover crop (CON). The resulting observed and simulated FWANC reductions due to CC were 59% and 49%. Simulations with the optimized model at various N fertilizer rates resulted in average annual drainage N loss differences between CC and CON increasing exponentially from 12 to 34 kg N ha-1 for rates of 11 to 261 kg N ha-1, but the percent difference remained relatively constant (65% to 70%). The results suggest that RZWQM-DSSAT is a promising tool to estimate the relative effects of a winter crop under different conditions on nitrate loss in tile drains, and that a winter cover crop can effectively reduce nitrate losses over a range of N fertilizer levels.