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SWAT modeling with uncertainty and cluster analyses of tillage impacts on hydrological processes

机译:具有不确定性的SWAT建模和耕作对水文过程影响的聚类分析

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摘要

The impacts of tillage practices, majorly conventional tillage (CT) and no-till (NT), on soil hydraulic properties have been studied in recent decades. In this paper, we incorporated an auto-calibration algorithm into the Soil and Water Assessment Tool (SWAT) model and calibrated the model at eight field sites with soil water content (SWC) observations in the Pataha Creek Watershed, WA, USA. The Green-Ampt method in SWAT was chosen to determine infiltration and surface runoff. Parameter uncertainty was quantified by "relatively optimal" parameter sets filtered by a critical objective function value. Cluster analysis was adopted to obtain equal-sized parameter sets for each site and to compare parameter sets between tillage practices. The centers of these clusters were employed as a sample of parameter values. The clustered parameter sets were then used in scenario analysis to examine the impacts of cropland tillage practices on lateral flow, runoff and evapotranspiration (ET). The model parameters (e.g., soil hydraulic properties) were significantly different between CT and NT. In particular, higher bulk density, larger available water capacity, and higher effective hydraulic conductivity were found for NT than for CT. SWCs at three depths of the NT sites were significantly higher than those of CT sites, which could be attributed to tillage practices. However, higher available water capacity at NT sites indicated that the NT soil had a higher capacity to hold water. Thus the mean net changes in SWC during a year were not significantly different between CT and NT. The statistically different model parameters neither resulted in statistical differences in annual outputs (e.g., runoff and ET) nor substantial differences in monthly outputs. Our study indicates that the tillage impacts on hydrological processes are site-specific and scale-dependent.
机译:近几十年来,已经研究了耕作方式(主要是传统耕作(CT)和免耕种植(NT))对土壤水力特性的影响。在本文中,我们将自动校准算法整合到土壤和水评估工具(SWAT)模型中,并在美国华盛顿州Pataha Creek流域的八个野外站点对土壤水分含量(SWC)进行了观测,从而对该模型进行了校准。选择SWAT中的Green-Ampt方法来确定入渗和地表径流。参数不确定性通过“相对最佳”参数集进行量化,该参数集由关键目标函数值过滤。采用聚类分析来获得每个站点的大小相等的参数集,并比较耕作实践之间的参数集。这些聚类的中心被用作参数值的样本。然后将聚类的参数集用于情景分析,以检查耕作耕作方式对侧向流量,径流和蒸散量(ET)的影响。 CT和NT之间的模型参数(例如土壤水力特性)显着不同。特别是,与CT相比,NT的堆积密度更高,可用水容量更大,有效水力传导率更高。 NT站点三个深度的SWC显着高于CT站点,这可以归因于耕作实践。然而,北半球地点较高的可用水容量表明北半球土壤具有较高的持水能力。因此,CT和NT之间一年中SWC的平均净变化没有显着差异。统计上不同的模型参数既不会导致年度产出的统计差异(例如,径流和ET),也不会导致每月产出的实质性差异。我们的研究表明,耕作对水文过程的影响是针对特定地点和规模的。

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  • 作者单位

    Department of Biological Systems Engineering, Washington State University, Pullman, WA 99164-6120, USA,Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Bldg 2040, Room E272, MS-6301, Oak Ridge, TN 37831-6301, USA;

    State of Washington Water Research Center, Department of Civil and Environmental Engineering, Washington State University, Pullman, WA 99164, USA;

    Department of Biological Systems Engineering, Washington State University, Pullman, WA 99164-6120, USA;

    Department of Biological Systems Engineering, Puyallup Research & Extension Center, Washington State University, Puyallup, WA 98371-4998, USA;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Cluster analysis; Scenario analysis; SWAT; Tillage; Uncertainty;

    机译:聚类分析;情景分析;扑打;耕作;不确定;

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