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Improving Distributed Runoff Prediction in Urbanized Catchments with Remote Sensing based Estimates of Impervious Surface Cover

机译:基于遥感的不透水地表覆盖估算,改善城市化集水区的径流分布预测

摘要

The amount and intensity of runoff on catchment scale are strongly determined by the presence of impervious land-cover types, which are the predominant cover types in urbanized areas. This paper examines the impact of different methods for estimating impervious surface cover on the prediction of peak discharges, as determined by a fully distributed rainfall-runoff model (WetSpa), for the upper part of the Woluwe River catchment in the southeastern part of Brussels. The study shows that detailed information on the spatial distribution of impervious surfaces, as obtained from remotely sensed data, produces substantially different estimates of peak discharges than traditional approaches based on expert judgment of average imperviousness for different types of urban land use. The study also demonstrates that sub-pixel estimation of imperviousness may be a useful alternative for more expensive high-resolution mapping for rainfall-runoff modelling at catchment scale.
机译:流域规模的径流数量和强度主要取决于不透水的土地覆盖类型,而这些类型是城市化地区的主要覆盖类型。本文考察了布鲁塞尔东南部沃卢威河集水区上部的各种方法(根据全分布的降雨径流模型(WetSpa)确定)估算不透水地表覆盖率对峰值流量预测的影响。研究表明,从遥感数据中获得的有关不透水表面空间分布的详细信息,与传统方法基于专家对不同类型城市土地利用的平均不透水性的判断相比,得出的峰值排放量估计值与传统方法大不相同。该研究还表明,对于流域尺度的降雨径流建模,较昂贵的高分辨率制图,子像素的不透性估计可能是有用的替代方法。

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