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This study presents a comprehensive remote sensing analysis of rainfallpatterns and selected hydropower reservoir water extent in two tropical monsooncountries, Vietnam and Sri Lanka. The aim is to understand the relationshipbetween remotely sensed rainfall data and the dynamic changes (monthly) inreservoir water extent. The analysis utilizes high-resolution optical imageryand Sentinel-1 Synthetic Aperture Radar (SAR) data to observe and monitor waterbodies during different weather conditions, especially during the monsoonseason. The average annual rainfall for both countries is determined, andspatiotemporal variations in monthly average rainfall are examined at regionaland reservoir basin levels using the Climate Hazards Group InfraRedPrecipitation with Station (CHIRPS) dataset from 1981 to 2022. Water extentsare derived for selected reservoirs using Sentinel-1 SAR Ground Range Detected(GRD) images in Vietnam and Sri Lanka from 2017 to 2022. The images arepre-processed and corrected using terrain correction and refined Lee filter. Anautomated thresholding algorithm, OTSU, distinguishes water and land, takingadvantage of both VV and VH polarization data. The connected pixel countthreshold is applied to enhance result accuracy. The results indicate a clearrelationship between rainfall patterns and reservoir water extent, withincreased precipitation during the monsoon season leading to higher waterextents in the later months. This study contributes to understanding howrainfall variability impacts reservoir water resources in tropical monsoonregions. The preliminary findings can inform water resource managementstrategies and support these countries' decision-making processes related tohydropower generation, flood management, and irrigation.

Analysis of Rainfall Variability and Water Extent of Selected Hydropower  Reservoir Using Google Earth Engine (GEE): A Case Study from Two Tropical  Countries, Sri Lanka and Vietnam