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Exploiting soil moisture precipitation and streamflow observations to evaluate soil moisture/runoff coupling in land surface models

机译:利用土壤水分降水和水流观测值来评估土地表面模型中的土壤水分/径流耦合

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摘要

Accurate partitioning of precipitation into infiltration and runoff is a fundamental objective of land surface models tasked with characterizing the surface water and energy balance. Temporal variability in this partitioning is due, in part, to changes in pre-storm soil moisture, which determine soil infiltration capacity and unsaturated storage. Utilizing the NASA Soil Moisture Active Passive Level-4 soil moisture product in combination with streamflow and precipitation observations, we demonstrate that land surface models (LSMs) generally underestimate the strength of the positive rank correlation between pre-storm soil moisture and event runoff coefficients (i.e., the fraction of rainfall accumulation depth converted into stormflow runoff during a storm event). Underestimation is largest for LSMs employing an infiltration-excess approach for stormflow runoff generation. More accurate coupling strength is found in LSMs that explicitly represent sub-surface stormflow or saturation-excess runoff generation processes.
机译:将降水准确划分为入渗和径流是陆地表面模型的基本目标,该模型的任务是表征地表水和能量的平衡。这种划分的时间变化部分是由于暴风雨前土壤湿度的变化,这决定了土壤的入渗能力和非饱和储量。利用美国国家航空航天局土壤水分主动被动4级土壤水分产物与水流和降水观测结果相结合,我们证明了地表模型(LSM)通常低估了暴风前土壤水分与事件径流系数之间的正秩相关强度(也就是说,在暴风雨事件中,降雨积累深度的一部分转化为暴雨径流。对于采用暴雨径流生成的渗透过多方法的LSM,低估最大。在LSM中发现了更准确的耦合强度,这些LSM明确表示了地下风暴流或饱和度过多的径流生成过程。

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