Geospatial analysis of soil moisture variability and its implications for irrigation management using GIS

Abstract

Soil moisture variability across space and time critically influences crop water availability, irrigation scheduling, and water-use efficiency, especially in regions with variable rainfall and heterogeneous soils. This review synthesises research on the use of geospatial tools—primarily Geographic Information Systems (GIS) and remote sensing—to quantify spatial and temporal patterns of soil moisture. We examine methods including interpolation of in situ measurements, satellite-derived microwave and multispectral data, and hybrid models combining soil, topographic, and climatic variables. We discuss the strengths and limitations of each approach, highlight recent advances in multi-sensor fusion and machine-learning estimation, and demonstrate how resulting soil moisture maps inform precision irrigation planning. Drawing on case studies from around the world and India, we outline how GIS-based soil-moisture analysis supports efficient water management, drought mitigation, and sustainable agriculture. The review concludes by identifying knowledge gaps and proposing directions for integrating soil moisture geospatial data into operational irrigation decision support systems.