GIS-based analysis for soil moisture estimation via kriging with external drift

Spatial distribution analysis of in-situ measurements within a study area using geostatistical approach is always a complex thing to perform. Present study deals with a geostatistical method to map the distribution of soil moisture and soil temperature throughout the study area using Hydra probe in-situ data. As soil moisture plays an important role in short- and long-term meteorological modelling and also is a vital component for sustaining life supporting systems at micro- and mega-scale, it is required to monitor its spatial and temporal variation with high precision. Presently, a multivariate geostatistical approach, i.e., Kriging with External Drift (KED), is used to improve the accuracy of spatial distribution mapping of soil moisture within the study area. Semi-variogram analysis is done to estimate the semi-variance in the model and the stability of the interpolated results. The correlation is established between the observed and predicted soil moisture that has shown R2 of 0.989 and Root Mean Square Error of 0.32, which shows that the model performed very well.