A satellite-driven approach to estimating delivered irrigation water via SM-based inversion algorithm: A case study of the Doroodzan irrigation district, Iran

In water-scarce semi-arid regions, efficient irrigation management is crucial for sustaining agricultural productivity and conserving freshwater resources. This study applies the SM-based inversion algorithm, utilizing 1 km Soil Moisture Active Passive (SMAP) soil moisture, ERA5 (ECMWF Reanalysis v5) precipitation, and GLEAM (Global Land Evaporation Amsterdam Model) evapotranspiration data, to estimate irrigation water use (IWU) across the Doroodzan irrigation network in Fars Province, Iran. Calibrated during non-irrigation periods, the SM-based inversion algorithm accurately captured seasonal and inter-annual IWU dynamics for 2018–2020, validated through time-series comparisons with canal release data and evapotranspiration trends. Results revealed significant conveyance and distribution inefficiencies, with satellite-based efficiencies of 26–37 % compared to 53 % reported by local authorities, indicating substantial water losses. These findings highlight the potential of the SM-based inversion algorithm for identifying spatial and temporal irrigation inefficiencies, supporting targeted interventions such as canal lining and real-time monitoring to enhance water-use efficiency in large-scale irrigation systems.