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ORIGINAL RESEARCH

Evaluating Nitrogen and Water Management in a Double-Cropping System Using RZWQM

^a Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences
^b USDA-ARS Great Plains Systems Research Unit, Fort Collins, CO 80526
^* Corresponding author (tim.green{at}ars.usda.gov)

Received 11 January 2005.

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^–1 yr^–1 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.

Abbreviations: MRE, mean relative error • NCP, North China Plain • NUE, nitrogen use efficiency • OM, organic matter • RE, relative error • RMSE, root mean squared error • SD, standard deviation

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