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Some Challenges in Hydrologic Model Calibration for Large-Scale Studies: A Case Study of SWAT Model Application to Mississippi-Atchafalaya River Basin

机译:大规模研究中水文模型标定中的一些挑战:以SWAT模型在密西西比-阿查法拉雅河流域的应用为例

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This study is a part of the Conservation Effects Assessment Project (CEAP) aimed to quantify the environmental and economic benefits of conservation practices implemented in the cultivated cropland throughout the United States. The Soil and Water Assessment Tool (SWAT) model under the Hydrologic United Modeling of the United States (HUMUS) framework was used in the study. An automated flow calibration procedure was developed and used to calibrate runoff for each 8-digit watershed (within 20% of calibration target) and the partitioning of runoff into surface and sub-surface flow components (within 10% of calibration target). Streamflow was validated at selected gauging stations along major rivers within the river basin with a target R 2 of 0.6 and Nash and Sutcliffe Efficiency of 0.5. The study area covered the entire Mississippi and Atchafalaya River Basin (MARB). Based on the results obtained, our analysis pointed out multiple challenges to calibration such as: (1) availability of good quality data, (2) accounting for multiple reservoirs within a sub-watershed, (3) inadequate accounting of elevation and slopes in mountainous regions, (4) poor representation of carrying capacity of channels, (5) inadequate capturing of the irrigation return flows, (6) inadequate representation of vegetative cover, and (7) poor representation of water abstractions (both surface and groundwater). Additional outstanding challenges to large-scale hydrologic model calibration were the coarse spatial scale of soils, land cover, and topography.
机译:这项研究是保护效果评估项目(CEAP)的一部分,该项目旨在量化全美国耕地中实施的保护措施的环境和经济利益。本研究使用了美国水文联合建模(HUMUS)框架下的土壤和水评估工具(SWAT)模型。开发了一种自动流量校准程序,用于校准每个8位流域的径流(在标定目标的20%之内),并将径流划分为地表和地下水流分量(在标定目标的10%之内)。在沿流域内主要河流的选定测量站对流量进行了验证,目标R 2大于0.6,纳什和苏克利夫效率大于0.5。研究区域覆盖了整个密西西比河和阿查法拉亚河流域(MARB)。根据获得的结果,我们的分析指出了标定的多个挑战,例如:(1)高质量数据的可用性;(2)考虑一个小流域内的多个水库;(3)山区海拔和坡度的计算不充分地区,(4)渠道的承载能力代表不佳,(5)灌溉回流的捕获不充分,(6)营养覆盖物代表不充分,(7)取水量(地表水和地下水)均不佳。大规模水文模型校准的其他突出挑战是土壤,土地覆盖物和地形的粗糙空间规模。

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