Sensitivity of soil dielectric mixing models for SMOS soil moisture retrieval

Abstract

Soil moisture is a key variable behind many hydrologic phenomena and applications. Passive L-band microwave satellites such as SMOS or SMAP are promising for retrieval of soil moisture. However, accurate retrieval of soil moisture depends on applying the appropriate soil dielectric mixing model. In this study, three dielectric models are used in integration with single channel algorithm using H polarization for retrieval of soil moisture. Soil moisture deficit (SMD) derived from locally simulated hydrological model-PDM (Probability Distribution Model) is used as a benchmark for all the assessment. The statistical performance index such as R2 (square of correlation) indicates that the Mironov is performing better than Dobson and Wang & Schmugge models for SMOS soil moisture retrieval. © 2018 Proceedings - 39th Asian Conference on Remote Sensing: Remote Sensing Enabling Prosperity, ACRS 2018