Abstract:
Climate change variations have significant adverse impacts on water resources, particularly in regions where the water supply is primarily dependent on reservoir systems. For efficient management of water resources, it is essential to comprehend the dynamics of reservoir water levels and climate-driven anomalies. Quantitatively appraising the water budget is crucial for enhancing socio-economic water and energy demands. Analyzing fluctuations in water levels and cyclic patterns of drought seasons due to climate change can significantly aid in the pre-planning and managing reservoir systems. This study aims to enhance water reservoir management by using satellite imagery to identify drought periods through surface water area analysis. With the fusion of Landsat 8 and Sentinel-1 data, this research focuses on mapping water surface changes at the Victoria Lake reservoir, Sri Lanka, using the Normalized Difference Water Index (NDWI) from 2018 to 2023. Both satellite data were acquired and subsequently processed on the Google Earth Engine platform (GEE). The resulting maps were created using ArcMap desktop software. The correlation coefficient observed between Landsat 8 and Sentinel-1 NDWI area measurements is 0.771, indicating a strong relationship between the two datasets. This high correlation underscores the reliability of using both sources to comprehensively analyze water surface area. Factors such as sensor calibration, atmospheric conditions, and data processing techniques can affect recorded values and correlations. Results revealed a cyclic pattern in water levels, with a notable trough in March 2019, followed by a significant drop lasting until March 2022, and another rapid decline observed within the subsequent year. Integrating satellite imagery in monitoring and decision-making processes offers a valuable tool for addressing the challenges of water and energy management under climate anomalies.
