Retrieval of soil moisture deficit through climate change initiative (CCI) soil moisture data and probability distributed model

Abstract

Soil moisture deficit (or SMD) is very important variable for many applications such as for flood and drought modelling, which is now possible to estimate using the remote sensing data. This study is an attempt to evaluate the climate change initiative (CCI) soil moisture data for SMD estimation at a catchment scale. The SMD (Soil Moisture Deficit) estimated from the Probability Distribution Model, by using the in situ station data was used as a benchmark for all the comparisons. Approaches based on generalized linear model and relevance vector machine are provided for the estimation of SMD. The overall analysis reveals that CCI soil moisture is of reasonable quality in estimating the soil moisture deficit at a catchment level. Therefore, this study provides first time comprehensive evaluation of CCI soil moisture in Indian condition and the result provides supportive evidence of the potential value of this product for meso-scale studies and hydrological applications. © 2017 Institute of Mechanics and Mechatronics, Faculty of Mechanical, TU Wien. All rights reserved.