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Impacts of input parameter spatial aggregation on an agricultural nonpoint source pollution model

机译:输入参数空间聚集对农业面源污染模型的影响

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The accuracy of agricultural nonpoint source pollution models depends in part on how well model input parameters describe the relevant characteristics of the watershed. The spatial extent of input parameter aggregation has previously been shown to have a substantial impact on model output. This study investigates this problem using the Soil and Water Assessment Tool (SWAT), a distributed-parameter agricultural nonpoint source pollution model. The primary question addressed here is: how does the size or number of subwatersheds used to partition the watershed affect model output, and what are the processes responsible for model behavior? SWAT was run on the Pheasant Branch watershed in Dane County, WI, using eight watershed delineations, each with a different number of subwatersheds. Model runs were conducted for the period 1990-1996. Streamflow and outlet sediment predictions were not seriously affected by changes in subwatershed size. The lack of change in outlet sediment is due to the transport-limited nature of the Pheasant Branch watershed and the stable transport capacity of the lower part of the channel network. This research identifies the importance of channel parameters in determining the behavior of SWAT's outlet sediment predictions. Sediment generation estimates do change substantially, dropping by 44% between the coarsest and the finest watershed delineations. This change is primarily due to the sensitivity of the runoff term in the Modified Universal Soil Loss Equation to the area of hydrologic response units (HRUs). This sensitivity likely occurs because SWAT was implemented in this study with a very detailed set of HRUs. In order to provide some insight on the scaling behavior of the model two indexes were derived using the mathematics of the model. The indexes predicted SWAT scaling behavior from the data inputs without a need for running the model. Such indexes could be useful for model users by providing a direct way to evaluate alternative models directly within a geographic information systems framework. (C) 2000 Elsevier Science B.V. All rights reserved. [References: 27]
机译:农业面源污染模型的准确性部分取决于模型输入参数描述流域相关特征的能力。输入参数聚合的空间范围先前已显示出对模型输出具有重大影响。本研究使用土壤和水评估工具(SWAT)来调查此问题,该工具是一种分布式参数农业面源污染模型。这里解决的主要问题是:用于划分集水区的子集水区的大小或数量如何影响模型输出,以及负责模型行为的过程是什么? SWAT是在威斯康星州Dane县的野鸡分支分水岭上运行的,使用了8个分水岭划界,每个划界具有不同数量的子分水岭。对1990-1996年进行了模型运行。流域和出口沉积物的预测并没有受到小流域规模变化的严重影响。出口沉积物缺乏变化的原因是the鸡流域的运输受到限制,并且河道下部的运输能力稳定。这项研究确定了通道参数对于确定SWAT出口沉积物预测行为的重要性。泥沙产生的估算值确实发生了很大变化,在最粗和最细的流域划分之间下降了44%。这种变化主要是由于修正的通用土壤流失方程中径流项对水文响应单位(HRU)面积的敏感性。之所以会出现这种敏感性,是因为在这项研究中使用了非常详细的HRU集实施了SWAT。为了对模型的缩放行为提供一些见识,使用模型的数学方法得出了两个指标。索引可以从数据输入中预测SWAT缩放行为,而无需运行模型。通过提供直接在地理信息系统框架内评估替代模型的直接方法,此类索引对模型用户可能有用。 (C)2000 Elsevier Science B.V.保留所有权利。 [参考:27]

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