Efficient irrigation management is critical for sustainable agriculture, particularly in water-scarce regions. Traditional methods for assessing irrigation impacts are often point-based and fail to capture spatial and temporal variability across large agricultural landscapes. This research presents an integrated framework combining remote sensing and hydrological modelling to comprehensively assess the impact of different irrigation practices on soil moisture dynamics and crop health. We utilized a time series of Sentinel-1 SAR and Sentinel-2 multispectral imagery to monitor surface soil moisture and vegetation indices (NDVI, NDWI) over an agricultural district employing diverse irrigation methods (drip, sprinkler, and flood irrigation). These remote sensing observations were integrated with the Soil Water Assessment Tool (SWAT) hydrological model, which was calibrated and validated using ground measurements. Our results demonstrated significant differences in soil moisture retention and distribution patterns among irrigation practices. Drip irrigation maintained more stable soil moisture levels with 25% less water consumption compared to flood irrigation, while sprinkler systems showed intermediate efficiency. Crop health indicators derived from Sentinel-2 revealed that fields under drip irrigation exhibited 15-20% higher NDVI values during critical growth stages and more uniform crop vigour. The coupled remote sensing-hydrological modelling approach successfully identified areas of water stress and waterlogging, with model validation showing strong agreement between simulated and observed soil moisture (R² = 0.89) and crop health parameters. Spatial analysis revealed that 35% of the flood-irrigated areas experienced either moisture stress or waterlogging, highlighting significant optimization potential. This research concludes that the integration of multi-sensor remote sensing with hydrological modelling provides a powerful, scalable approach for evaluating irrigation performance, identifying inefficiencies, and supporting precision water management decisions to enhance agricultural productivity and water sustainability.

irrigation, soil moisture, remote sensing, crop, hydrological modelling

agronomy

Presentation: poster