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Near-surface soil moisture estimation using AMSR-E brightness temperature

机译:利用AMSR-E亮度温度估算近地表土壤湿度

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In situ measurement of soil moisture is difficu extensive and expensive observations are required for good estimation. This is the first study that uses rainfall and runoff data with the water balance equation to calibrate the roughness parameters (h and Q) and to validate satellite soil moisture data. The methodology used the Advanced Microwave Scanning Radiometer (AMSR-E) data and the first-order radiative transfer model in order to retrieve the volumetric soil moisture (vsm). The analysis of two years of data indicates that the estimated daily surface soil moisture is well correlated with the flow observations and a good correlation (R~2 = 0.74) is shown between the water storage change (△s) and the soil moisture change (△θ). The soil moisture estimated in this new approach would be more relevant to hydrological applications due to its linkage with the rainfall-runoff process.
机译:原地测量土壤水分很困难;为了进行良好的估算,需要进行广泛且昂贵的观察。这是第一项使用降雨和径流数据与水平衡方程式来校准粗糙度参数(h和Q)并验证卫星土壤湿度数据的研究。该方法使用了先进的微波扫描辐射计(AMSR-E)数据和一阶辐射传递模型,以获取土壤水分的体积(vsm)。对两年数据的分析表明,估计的每日表层土壤水分与流量观测值具有很好的相关性,并且储水量变化(△s)与土壤水分变化之间的相关性很好(R〜2 = 0.74)。 △θ)。由于这种新方法估算的土壤水分与降雨径流过程有关,因此与水文应用更为相关。

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