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A universal agro-hydrological model for water and nitrogen cycles in the soil–crop system SMCR_N: critical update and further validation

机译:土壤-作物系统SMCR_N中水和氮循环的通用农业水文学模型:关键更新和进一步验证

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摘要

Agro-hydrological models have widely been used for optimizing resources use and minimizing environmental consequences in agriculture. SMCR_N is a recently developed sophisticated model which simulates crop response to nitrogen fertilizer for a wide range of crops, and the associated leaching of nitrate from arable soils. In this paper, we describe the improvements of this model by replacing the existing approximate hydrological cascade algorithm with a new simple and explicit algorithm for the basic soil water flow equation, which not only enhanced the model performance in hydrological simulation, but also was essential to extend the model application to the situations where the capillary flow is important. As a result, the updated SMCR_N model could be used for more accurate study of water dynamics in the soil–crop system. The success of the model update was demonstrated by the simulated results that the updated model consistently out-performed the original model in drainage simulations and in predicting time course soil water content in different layers in the soil–wheat system. Tests of the updated SMCR_N model against data from 4 field crop experiments showed that crop nitrogen offtakes and soil mineral nitrogen in the top 90 cm were in a good agreement with the measured values, indicating that the model could make more reliable predictions of nitrogen fate in the crop–soil system, and thus provides a useful platform to assess the impacts of nitrogen fertilizer on crop yield and nitrogen leaching from different production systems.
机译:农业水文模型已被广泛用于优化资源利用并最大程度地减少农业中的环境影响。 SMCR_N是最近开发的复杂模型,可以模拟作物对多种农作物对氮肥的响应,以及相关的可耕土壤中硝酸盐的淋溶。在本文中,我们用基本土壤水流方程的新的简单明了算法代替了现有的近似水文级联算法,描述了该模型的改进,这不仅增强了模型在水文模拟中的性能,而且对模型的必要性将模型应用程序扩展到毛细管流量很重要的情况。结果,更新后的SMCR_N模型可用于更精确地研究土壤-作物系统中的水动力学。仿真结果表明,模型更新的成功之处在于,在排水模拟和预测时程过程中,土壤-小麦系统中不同层的土壤含水量,更新后的模型始终优于原始模型。对更新的SMCR_N模型与来自4个田间作物实验的数据进行的测试表明,前90 cm处作物的氮素吸收量和土壤矿质氮与实测值高度吻合,表明该模型可以更可靠地预测作物氮素的命运。作物-土壤系统,因此提供了一个有用的平台来评估氮肥对不同生产系统中作物产量和氮素淋失的影响。

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