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Simulation of water and nutrient processes can enhance intensive agriculture to help feed the world's population in a sustainable manner. Due to excessive N application, environmental protection and agricultural sustainability have become major issues in agriculture. In this study, we calibrated and tested the RZWQM model to assess N management in a double-cropping system comprised of winter wheat (Triticum aestivum L.) and corn (Zea mays L.) at Luancheng, in the North China Plain. Data, including biomass, grain yield, soil water, and soil and crop N, were used from 2001-2003 field trials applying 200 to 800 kg N ha 21 yr 21 for five cropping seasons. In general, soil water, biomass, and grain yields were predicted better than plant N uptake or soil residual N. Once it had been tested and used to improve the understanding of N processes in this cropping system, the model was further used to evaluate the effects of alternative water and N management scenarios on N leaching. Typical application rates of both water and N could be reduced by about half based on these results, which would have high economic, social, and environmental impacts in China. The results also demonstrate the potential of RZWQM for evaluating N and water management practices in other regions and climates of the world with intensive agriculture.

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Agricultural system models are tools to represent and understand major processes and their interactions in agricultural systems. We used the Root Zone Water Quality Model (RZWQM) with 26 years of data from a study near Nashua, IA to evaluate year to year crop yield, water, and N balances. The model was calibrated using data from one 0.4 ha plot and evaluated by comparing simulated values with data from 29 of the 36 plots at the same research site (six were excluded). The dataset contains measured tile flow that varied considerably from plot to plot so we calibrated total tile flow amount by adjusting a lateral hydraulic gradient term for subsurface lateral flow below tiles for each plot. Keeping all other soil and plant parameters constant, RZWQM correctly simulated year to year variations in tile flow (r 2 = 0.74) and N loading in tile flow (r 2 = 0.71). Yearly crop yield variation was simulated with less satisfaction (r 2 = 0.52 for corn and r 2 = 0.37 for soybean) although the average yields were reasonably simulated. Root mean square errors (RMSE) for simulated soil water storage, water table, and annual tile flow were 3.0, 22.1, and 5.6 cm, respectively. These values were close to the average RMSE for the measured data between replicates (3.0, 22.4, and 5.7 cm, respectively). RMSE values for simulated annual N loading and residual soil N were 16.8 and 47.0 kg N ha −1 , respectively, which were much higher than the average RMSE for measurements among replicates (7.8 and 38.8 kg N ha −1 , respectively). The high RMSE for N simulation might be caused by high simulation errors in plant N uptake. RightsWorks produced by employees of the U.S. Government as part of their official duties are not copyrighted within the U.S. The content of this document is not copyrighted. AbstractAgricultural system models are tools to represent and understand major processes and their interactions in agricultural systems. We used the Root Zone Water Quality Model (RZWQM) with 26 years of data from a study near Nashua, IA to evaluate year to year crop yield, water, and N balances. The model was calibrated using data from one 0.4 ha plot and evaluated by comparing simulated values with data from 29 of the 36 plots at the same research site (six were excluded). The dataset contains measured tile flow that varied considerably from plot to plot so we calibrated total tile flow amount by adjusting a lateral hydraulic gradient term for subsurface lateral flow below tiles for each plot. Keeping all other soil and plant parameters constant, RZWQM correctly simulated year to year variations in tile flow (r 2 = 0.74) and N loading in tile flow (r 2 = 0.71). Yearly crop yield variation was simulated with less satisfaction (r 2 = 0.52 for corn and r 2 = 0.37 for soybean) although the average yields were reasonably simulated. Root mean square errors (RMSE) for simulated soil water storage, water table, and annual tile flow were 3.0, 22.1, and 5.6 cm, respectively. These values were close to the average RMSE for the measured data betwee...

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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.

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