基于ERS散射计数据的土壤水分反演方法

The Improvement of Soil Moisture Estimation Using ERS Scatterometer Data

在全球能量与水循环研究中,地表土壤水分是非常关键的参数之一。ERS散射计因具有观测尺度大、重复周期短等优势而在地表土壤水分监测方面日益受到关注。采用目前最先进的理论模型AIEM(改进的积分方程模型),根据ERS散射计的参数设计模拟出一个涵盖较宽地表粗糙度和介电常数输入范围的数据库,利用这个数据库发展出一个参数化模型。该模型采用了一个综合均方根高度(RMS height)与相关长度(Correlation length)的粗糙度参数,该参数在每个入射角度下都可以用同一个函数来描述,解决了多角度数据情况下粗糙度参数的表达问题。应用新发展的参数化模型进行土壤水分的反演结果表明,该模型具有较高的精度。

ERS Wind Scatterometer provides capability of the multiple angles by three different look antennas. In this study, the authors have made an evaluation whether the multi - incidence angle observations can help improve surface soil moisture estimations or not. With the theoretical surface backscattering model, i. e. , the Advanced Integral Equation Model （AIEM）, the authors first simulated a surface backscattering database with a wide range of surface roughness and soil moisture properties at different incident angles. Then, a parametcrized surface backscattering model was developed using the simulated database. The newly developed simple model has the roughness function that can be described by a single combined roughness parameter from the commonly used surface roughness descriptors （RMS height and correlation length）. This makes it possible for the model to be used as an inversion model. The development of this simple model, its accuracy, and the inversion test can be demonstrated by using the ground measurements from the Intensive Observation Period （IOP98） field campaign in 1998 of the Global Energy and Water Experiment （GEWEX） Asian Monsoon Experiment Tibet （GAME/Tibet）.