Characterization of Soil Moisture Regime in the Kairouan Region, Tunisia

Abstract

Soil moisture (SM) is a major factor in agricultural practices and earth surface processes. Remote sensing has been widely applied to estimate the soil moisture. However, it is still a challenge to describe the horizontal and vertical availability and the redistribution of soil moisture in time. Therefore, it is necessary to develop a soil hydrological model capable of estimating soil moisture variation with high accuracy, which is important in planning and efficient use of land resources. Many methods based on optical or radar satellite data have already been developed to estimate SM under various climatic conditions and geographical distribution. In this study, the agricultural region of Kairouan in central Tunisia was chosen as a study area. To perform SM estimation, we analyzed the relation between the optical satellite data indices, such as the NDVI and the NDWI, and the radar data. In addition, we studied the correlation between the different backscatters (V, H), optical data, DEM and the environmental covariates in order to extract the highest correlation and the most informative data sources. These results will be the input of our model. The combination of remote sensing data, the environmental variables and the associate geospatial data can provide valuable information for soil moisture estimation; this has the potential to support decision making to optimize the land use structure and the water resources management, and for use in precision agricultural applications.