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首页> 外文期刊>Transactions of the ASABE >Parameter sensitivity and uncertainty in SWAT: a comparison across five USDA-ARS watersheds. (Special Issue: Soil and water assessment tool (SWAT) modeling technology: current status.)
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Parameter sensitivity and uncertainty in SWAT: a comparison across five USDA-ARS watersheds. (Special Issue: Soil and water assessment tool (SWAT) modeling technology: current status.)

机译：SWAT中的参数敏感性和不确定性：五个USDA-ARS流域的比较。 （特刊：水土评估工具（SWAT）建模技术：当前状态。）

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摘要

The USDA-ARS Conservation Effects Assessment Project (CEAP) calls for improved understanding of the strengths and weaknesses of watershed-scale water quality models under a range of climatic, soil, topographic, and land use conditions. Assessing simulation model parameter sensitivity helps establish feasible parameter ranges, distinguish among parameters having regional versus universal interactions, and ensure that one model process does not compensate for another due to poor parameter settings. The Soil and Water Assessment Tool (SWAT) parameter sensitivity and autocalibration module was tested on two northern and three southern USDA-ARS experimental watersheds. These previously calibrated watersheds represent a range of climatic, physiographic, and land use conditions present in the U.S. Sixteen parameters that govern basin, snow accumulation/melt, surface, and subsurface response in the model were evaluated. Parameters governing surface runoff due to rainfall were found most sensitive overall, while parameters governing groundwater were the least sensitive. Surface runoff parameters were found most sensitive for areas with high evaporation rates and localized thunderstorms. Parameters from all categories were important in areas where precipitation includes both rainfall and snowfall. Differences in model performance were noticeable on a climatic basis; SWAT generally predicted streamflow with less uncertainty in humid climates than in arid or semi-arid climates. Study findings can be used to determine appropriate parameter ranges for ungauged watersheds of similar characteristics.
机译：USDA-ARS保护效果评估项目（CEAP）要求更好地了解在各种气候，土壤，地形和土地使用条件下的分水岭规模水质模型的优缺点。评估仿真模型参数的敏感性有助于建立可行的参数范围，区分具有区域性相互作用和普遍性相互作用的参数，并确保一个模型过程不会因参数设置不当而补偿另一个模型过程。土壤和水评估工具（SWAT）参数敏感性和自动校准模块在USDA-ARS的两个北部和南部的三个实验流域上进行了测试。这些先前已校准的流域代表了美国存在的一系列气候，地形和土地利用条件。评估了模型中控制盆地，积雪/融雪，地表和地下响应的16个参数。总的来说，控制降雨引起的地表径流参数最敏感，而控制地下水的参数最不敏感。发现地表径流参数对高蒸发率和局部雷暴地区最敏感。在降雨包括降雨和降雪的地区，所有类别的参数都很重要。在气候基础上，模型性能的差异非常明显;与干旱或半干旱气候相比，SWAT总体上预测在潮湿气候中的水流具有较小的不确定性。研究结果可用于确定具有相似特征的未赋水流域的适当参数范围。

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