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潜在蒸散发数据对网格hbv模型降雨径流模拟的影响分析
首发时间：2017-05-04
摘要：遥感数据是作为缺资料或少资料地区构建水文模型的重要输入数据来源。利用以遥感数据为主的多源数据，构建了雅砻江流域雅江以上集水区的网格hbv模型，较好的模拟了雅江站2008年至2013年的降雨径流。利用美国全球陆面数据同化系统提供的气象数据产品与fao56 penman公式与修正的hargreaves公式分别计算了潜在蒸散发数据，从数值与时间尺度分析了二者与modis/mod16潜在蒸散发数据产品分别作为网格hbv模型的驱动数据对模型降雨径流模拟结果的影响，结果表明，由于参数的调整与网格hbv模型的自身结构使的模型对潜在蒸散发输入数据并不敏感。
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effect of pet data on rainfall-runoff simulation of grid-based hbv model
abstract：remote sensing data is an important input data source for building hydrological model in those lacking or having no data catchments. the grid-based hbv model was established in the catchment above yajiang station in yalong river basin with multi-source data, which can simulate the streamflow of yajiang station from 2008 to 2013 well. potential evapotranspiration was calculated using the meteorological data products provided by the us global land data assimilation system with the fao56 penman formula and the modified hargreaves formula, respectively. the influence of magnitude and time scale of the two calculated potential evapotranspiration data and modis mod16 potential evapotranspiration products on the rainfall runoff simulation results was analyzed. the results show that the model is not sensitive to the potential evapotranspiration input due to the adjustment of the model parameters and the structure of the grid-based hbv model.
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