为实现土壤湿度连续准确的时空刻画,在不同气候条件下进行多源遥感土壤湿度产品(SMOS、ASCAT、ESA CCI、SMAP)与分布式降雨径流模型模拟土壤湿度时空对比研究。考虑到遥感数据与模型模拟数据时空匹配度上的差异性,将遥感原始表层土壤湿度(Surface Soil Moisture, SSM)和预处理后的剖面土壤湿度(Profile Soil Moisture, PSM)与分布式水文模型模拟的PSM分别进行对比。对比所用时间尺度为日尺度,空间尺度为流域尺度和栅格尺度。研究区域为湿润气候条件下的渠江流域和半干旱气候条件下的伊洛河流域。结果表明,在同一流域内当分布式水文模型土壤湿度模拟能力较高时,SMAP反演PSM与模型模拟值一致性较高,相关系数达到0.8,相对其他遥感产品其准确度较高。研究成果对获取高准确度土壤湿度时空信息具有一定的指导意义和实践价值。
To acquire accurate soil moisture information in time and space, soil moisture information (surface soil moisture SSM and profile soil moisture PSM) from multiple satellites (SMOS, ASCAT, ESA CCI and SMAP) is compared with PSM simulations from a distributed hydrological model. The comparison is developed at daily scale and catchment/grid scale in a humid catchment (Qujiang catchment) and a semiarid catchment (Yiluohe catchment) in China. Results indicate that SMAP PSM show higher consistency with simulated PSM when the performance of simulated PSM is high in a catchment, with the correlation coefficient reaching 0.8. Thus, the accuracy of SMAP is regarded to be relatively higher compared to other satellite products. The research offers guidance and practical values for acquiring accurate soil moisture information in time and space.
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