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Using High-Resolution Data to Test Parameter Sensitivity of the Distributed Hydrological Model HydroGeoSphere

机译:使用高分辨率数据测试分布式水文模型HydroGeoSphere的参数敏感性

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Parameterization of physically based and distributed hydrological models for mesoscale catchments remains challenging because the commonly available data base is insufficient for calibration. In this paper, we parameterize a mesoscale catchment for the distributed model HydroGeoSphere by transferring evapotranspiration parameters calibrated at a highly-equipped headwater catchment in addition to literature data. Based on this parameterization, the sensitivity of the mesoscale catchment to spatial variability in land use, potential evapotranspiration and precipitation and of the headwater catchment to mesoscale soil and land use data was conducted. Simulations of the mesoscale catchment with transferred parameters reproduced daily discharge dynamics and monthly evapotranspiration of grassland, deciduous and coniferous vegetation in a satisfactory manner. Precipitation was the most sensitive input data with respect to total runoff and peak flow rates, while simulated evapotranspiration components and patterns were most sensitive to spatially distributed land use parameterization. At the headwater catchment, coarse soil data resulted in a change in runoff generating processes based on the interplay between higher wetness prior to a rainfall event, enhanced groundwater level rise and accordingly, lower transpiration rates. Our results indicate that the direct transfer of parameters is a promising method to benefit highly equipped simulations of the headwater catchments.
机译:对于中尺度流域,基于物理和分布式水文模型的参数化仍然具有挑战性,因为通常可用的数据库不足以进行校准。在本文中,除了文献数据外,我们还通过传递在高度装备的源头集水区校准的蒸发蒸腾参数,对分布式模型HydroGeoSphere中尺度集水区进行参数化。在此参数化的基础上,进行了中尺度集水区对土地利用,潜在蒸散量和降水以及源头集水区对中尺度土壤和土地利用数据的空间敏感性的敏感性。用转移参数模拟中尺度流域,以令人满意的方式再现了草地,落叶和针叶植被的日排放动态和月蒸散量。相对于总径流量和峰值流速,降水是最敏感的输入数据,而模拟的蒸散量和模式对空间分布的土地利用参数化最为敏感。在源头流域,由于降雨事件之前较高的湿度,增加的地下水位上升和较低的蒸腾速率之间的相互影响,粗土数据导致径流产生过程发生变化。我们的结果表明,参数的直接传递是有益于上游水源流域装备精良的模拟的有前途的方法。

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