根据最新Sentinel-1雷达系统参数及研究区地表参数特点, 采用AIEM模型进行数值模拟分析, 建立稀疏植被覆被下地表微波散射特征数据库, 并在此基础上构建干旱区土壤水分模型.结果表明, 1)不同入射角和极化方式下, 后向散射系数对土壤含水量(Mv)、组合地表粗糙度(Zs)的响应分别呈明显对数相关, VV极化对土壤水分响应更敏感, 最优响应区间范围为Mv 0~30%、Zs 0~0.06 cm.2)初探Sentinel-1雷达数据预处理方法, GammaMAP滤波去噪最优, 模型用于土壤水分空间分布信息提取与研究区同期野外实况具有良好的一致性, 符合四月渭-库地区春旱期土壤水分时空分布特征.3)对于0-10 cm表层土壤水分, 模拟值同实测值相关系数达到0.76, 即该模型对于干旱区绿洲区域尺度表层土壤水分监测具有适用性.

According to the latest Sentinel-1 radar system parameters and the surface characteristic parameters of the study area, this paper established a database of surface microwave scattering characteristics under the sparse vegetation cover condition by AIEM model. On the basis of AIEM model numerical simulation analysis, soil moisture inversion model was constructed. The results showed that: 1) Under the different incident angles and polarization mode, the backscatter coefficient response of soil moisture (Mv) and the composite surface roughness (Zs) have obvious logarithmic correlation, respectively. Soil moisture response of VV polarization is sensitive, the optimal response range is for Mv 0~30%, Zs 0~0.06 cm. 2) GammaMAP filtering has good denoising effect in the sentinel-1 radar data preprocessing. The spatial distribution of soil moisture extracted from sentinel-1 images has good consistency with the actual situation in the same period field in the study area. In April, the soil moisture spatio-temporal distribution of Weigan-Kuqa river basin shows spring drought characteristics. 3) For 0~10 cm surface soil moisture, the correlation coefficient between the measured value and simulated value reaches 0.76, showing that this model is suitable for the extraction of soil moisture in the arid area of a certain regional scale.