From Water Deficits to Storage Solutions: A Remote Sensing–Based Water Balance Framework

Agriculture is the largest consumer of freshwater globally, yet reliable estimates of irrigation water requirements and withdrawals remain scarce, particularly in data-poor and rainfed-dominated regions. In sub-Saharan Africa, increasing climate variability and growing food demand are intensifying seasonal water stress and highlighting the need for improved water management and irrigation planning tools.

We present the Securing Water in Agriculture (SWAG) tool, an agro-hydrological framework that integrates remote sensing–derived evapotranspiration with land-use and crop data to quantify spatially and temporally explicit crop water demand, deficits, and irrigation surpluses. Beyond these, SWAG evaluates management interventions, including small-scale storage and water reallocation within irrigation schemes.

The framework was applied across Kenya’s central highlands from 2019 to 2023. Results indicate monthly deficit volumes are largest in the dry season from June to September, with particularly severe conditions in 2021 and 2022, when monthly deficits exceeded 150 million m³. Surplus volumes are present but generally smaller, typically remaining below 100 million m³. On a monthly basis, cropland deficit areas range from approximately 18,000 ha during wet months to up to 450,000 ha at the height of the dry season, whereas surplus areas in a given month are consistently smaller, varying between approximately 17,000 and 98,000 ha per month.

To support irrigation management and to meet the deficits, SWAG evaluates the spatial feasibility and seasonal performance of small-scale storage (e.g. 1,000 m³ farm ponds) through pond-scale water balance simulations. Results indicate that storage potential is highest in small headwater catchments, where potential pond densities locally exceed 25 ponds km⁻², while most catchments accommodate fewer than 10 ponds km⁻². On average, runoff volumes exceed 2,000 million m³ during the rainy season months (April–May and October–November), and pond water levels remain high during subsequent deficit periods, indicating that additional storage can generally offset deficits.

By coupling spatially and temporally explicit water demand analytics with storage and reallocation options, the SWAG framework helps close the agricultural water budget in data-scarce basins and provides a practical decision-support tool for improving irrigation management, water use efficiency, and climate resilience in vulnerable farming systems.