Factors determining spatio-temporal variations of soil moisture using microwave data

Soil moisture is seen as a key element in climate change studies and it is very important to apprehend the dynamics of changing soil moisture spatially and temporally in accordance with various factors. Soil, crop and meteorological parameters, local topography and land use land cover are the major factors which affect soil moisture locally and globally. A comprehensive understanding of the interrelationship between these factors and in conjunction with soil moisture conveys information, not only for agricultural applications as well as for meteorological processes. Active (ASCAT) and passive (AMSR-E) microwave remote sensing soil moisture data is used to derive a harmonised soil moisture product using an approach based on cumulative distribution frequency (CDF) matching. This technique couples the two datasets with accordance to a reference dataset. This technique is well suitable for time series analysis of data. Trend analysis is further performed to study the influence of various factors over soil moisture at different geographical locations. In this study, for the investigations on soil moisture assessment, the year 2009 is selected. Evaluation of the harmonised soil moisture product is done with available ground data to obtain the coefficient of determination as 0.64 and root mean square error (RMSE) of 0.142, which is much acceptable.