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首页> 外文期刊>Hydrology and Earth System Sciences >Three perceptions of the evapotranspiration landscape: Comparing spatial patterns from a distributed hydrological model, remotely sensed surface temperatures, and sub-basin water balances
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Three perceptions of the evapotranspiration landscape: Comparing spatial patterns from a distributed hydrological model, remotely sensed surface temperatures, and sub-basin water balances

机译:对蒸散量景观的三种看法:比较分布式水文模型的空间格局,遥感地表温度和流域水平衡

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摘要

A problem encountered by many distributed hydrological modelling studies is high simulation errors at interior gauges when the model is only globally calibrated at the outlet. We simulated river runoff in the Elbe River basin in central Europe (148 268 km2) with the semi-distributed eco-hydrological model SWIM (Soil and Water Integrated Model). While global parameter optimisation led to Nash-Sutcliffe efficiencies of 0.9 at the main outlet gauge, comparisons with measured runoff series at interior points revealed large deviations. Therefore, we compared three different strategies for deriving sub-basin evapotranspiration: (1) modelled by SWIM without any spatial calibration, (2) derived from remotely sensed surface temperatures, and (3) calculated from long-term precipitation and discharge data. The results show certain consistencies between the modelled and the remote sensing based evapotranspiration rates, but there seems to be no correlation between remote sensing and water balance based estimations. Subsequent analyses for single sub-basins identify amongst others input weather data and systematic error amplification in inter-gauge discharge calculations as sources of uncertainty. The results encourage careful utilisation of different data sources for enhancements in distributed hydrological modelling.
机译:许多分布式水文建模研究遇到的一个问题是,当模型仅在出口处进行全局校准时,内部仪表的模拟误差很大。我们使用半分布式生态水文模型SWIM(水土流失综合模型)模拟了中欧易北河流域的河流径流(148 268 km2)。虽然全局参数优化导致主出口仪表的Nash-Sutcliffe效率为0.9,但与内部点测得的径流序列的比较显示出较大的偏差。因此,我们比较了三种不同的得出流域蒸散发量的策略:(1)通过SWIM建模,无需任何空间校准;(2)从遥感表面温度得出;(3)从长期降水和流量数据计算得出。结果表明,建模的蒸发量与基于遥感的蒸散量之间存在一定的一致性,但是基于遥感和水平衡的估计之间似乎没有相关性。随后对单个子流域的分析将输入的天气数据和量规间流量计算中的系统误差放大等确定为不确定性来源。结果鼓励谨慎使用不同的数据源,以增强分布式水文建模。

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