Satellite-enabled decision support for reservoir water availability, flood dynamics, and catchment stress in semi-arid regions
DOI:
https://doi.org/10.7494/jrme.2026.1.1.8604Keywords:
reservoir operation, water availability, flood risk management, catchment land-use change, decision-support systems, semi-arid water resourcesAbstract
The sustainable operation of inland reservoirs in semi-arid regions is increasingly challenged by intensified hydro-climatic variability and rapid catchment-scale land-use transformation, resulting in heightened flood risk and seasonal water stress. This study develops an operational, satellite-enabled decision-support framework for assessing reservoir water availability, flood dynamics, and catchment-induced hydrological stress, with direct relevance to reservoir operations and water resource management. Pakhal Lake, a historic inland reservoir in Telangana, India, is examined as a representative case study in semi-arid regions.
Temporally smoothed Sentinel-2-derived vegetation and water indices were used to characterise seasonal and interannual variability in reservoir-linked vegetation response and surface-water extent. At the same time, cloud-independent Sentinel-1 SAR imagery enabled reliable delineation of flood inundation during extreme monsoon conditions. Catchment land-use dynamics were quantified using machine-learning classifiers implemented within the Google Earth Engine platform to identify emerging anthropogenic pressures influencing reservoir inflows and storage behaviour.
The results reveal pronounced seasonal fluctuations in reservoir water extent and vegetation condition, with SAR analysis indicating flood-driven expansion of approximately 28% of the reservoir area during the extreme monsoon year of 2018. The rapid growth of built-up and bare land within the catchment highlights increasing hydrological stress, with implications for runoff generation, sediment delivery, and storage stability. The proposed framework provides actionable indicators to support reservoir operation, irrigation planning, and flood preparedness, offering a scalable and cost-effective monitoring approach for water resource management in data-scarce semi-arid regions.
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