  This study presents a comprehensive remote sensing analysis of rainfall
patterns and selected hydropower reservoir water extent in two tropical monsoon
countries, Vietnam and Sri Lanka. The aim is to understand the relationship
between remotely sensed rainfall data and the dynamic changes (monthly) in
reservoir water extent. The analysis utilizes high-resolution optical imagery
and Sentinel-1 Synthetic Aperture Radar (SAR) data to observe and monitor water
bodies during different weather conditions, especially during the monsoon
season. The average annual rainfall for both countries is determined, and
spatiotemporal variations in monthly average rainfall are examined at regional
and reservoir basin levels using the Climate Hazards Group InfraRed
Precipitation with Station (CHIRPS) dataset from 1981 to 2022. Water extents
are derived for selected reservoirs using Sentinel-1 SAR Ground Range Detected
(GRD) images in Vietnam and Sri Lanka from 2017 to 2022. The images are
pre-processed and corrected using terrain correction and refined Lee filter. An
automated thresholding algorithm, OTSU, distinguishes water and land, taking
advantage of both VV and VH polarization data. The connected pixel count
threshold is applied to enhance result accuracy. The results indicate a clear
relationship between rainfall patterns and reservoir water extent, with
increased precipitation during the monsoon season leading to higher water
extents in the later months. This study contributes to understanding how
rainfall variability impacts reservoir water resources in tropical monsoon
regions. The preliminary findings can inform water resource management
strategies and support these countries' decision-making processes related to
hydropower generation, flood management, and irrigation.
