首页> 外文期刊>European Journal of Soil Science >Modelling intercrop management impact on runoff and erosion in a continuous maize cropping system: Part I. Model description, global sensitivity analysis and Bayesian estimation of parameter identifiability
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Modelling intercrop management impact on runoff and erosion in a continuous maize cropping system: Part I. Model description, global sensitivity analysis and Bayesian estimation of parameter identifiability

机译:间作管理对连续玉米种植系统中径流和侵蚀的影响建模:第一部分。模型描述,全局敏感性分析和参数可识别性的贝叶斯估计

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In order to evaluate the long-term impact of intercrop management on runoff and erosion in a continuous maize cropping system a new model was developed, based on the continuous plot-scale runoff model of Laloy & Bielders (2008) . This model is called the Continuous Runoff and Erosion Hillslope model with DYnamic soil Surface properties (CREHDYS). This paper details the erosion and crop growth and decay model components and presents a thorough global variance-based sensitivity analysis (GSA) with regard to the erosion prediction, followed by a Bayesian parameter identifiability assessment. As compared with the classical local univariate sensitivity analysis, a GSA is able to deal with the typical non-linearity of process-based hydrological and erosion models. The most influential parameters were the Manning's roughness coefficient followed by the saturated hydraulic conductivity of wheel track cells and the median particle size of the material. The soil aggregate stability and soil-cohesion parameters were found to be almost non-influential. Most of the results of the parameter identifiability procedure were in close agreement with the GSA. Indeed, the parameter uncertainty seemed to be proportional to the degree of influence, with Manning's coefficient being the most precisely identified, whereas soil and wheel track cohesion parameters showed the largest uncertainty. Exceptions were the soil aggregate stability and the Green-Ampt soil matric potential. The uncertainty associated with the former was surprisingly low given its low level of influence whereas the uncertainty associated with the latter is partially explained by its negative correlation with the soil saturated hydraulic conductivities of overland flow and wheel track cells.
机译:为了评估玉米间作管理对连续玉米种植系统中径流和侵蚀的长期影响,基于Laloy&Bielders(2008)的连续样地规模径流模型,开发了一个新模型。该模型称为具有动态土壤表面特性的连续径流和侵蚀坡度模型(CREHDYS)。本文详细介绍了侵蚀,作物生长和衰退模型的组成部分,并针对侵蚀预测提出了全面的基于全局方差的敏感性分析(GSA),然后进行了贝叶斯参数可识别性评估。与经典的局部单变量敏感性分析相比,GSA能够处理基于过程的水文和侵蚀模型的典型非线性。影响最大的参数是曼宁粗糙度系数,其次是轮距单元的饱和​​水力传导率和材料的中值粒径。发现土壤团聚体稳定性和土壤凝聚力参数几乎没有影响。参数可识别性程序的大多数结果与GSA紧密一致。实际上,参数不确定性似乎与影响程度成正比,其中最精确地确定了曼宁系数,而土壤和轮距内聚力参数显示出最大不确定性。土壤聚集体稳定性和绿安培土壤基质潜力除外。考虑到前者的影响程度低,与前者相关的不确定性低得令人惊讶,而与后者相关的不确定性部分地由其与陆上流动和轮迹单元的土壤饱和水导率的负相关性来解释。

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