Assessing the Dynamic Evolution of Lake Victoria: a Remote Sensing Synthesis of Topo-Bathymetric Structure, Hydrological Storage, and Water Quality

Lake Victoria, Africa's largest freshwater lake and a critical ecological and hydrological resource, sustains the livelihoods of millions through fisheries, agriculture, hydropower, and tourism. However, increasing climatic variability, population pressure, and anthropogenic activities have intensified environmental stress on the lake, including fluctuations in water levels and declining water quality. In situ monitoring is limited across much of the basin, making satellite remote sensing indispensable for assessing the lake's long-term dynamics. This study presents a comprehensive remote sensing-based synthesis of the lake's long-term water quality, storage dynamics, and topo-bathymetry over the past four decades (1984–2024).First, we developed the lake's first publicly available seamless topo-bathymetric model by combining the Copernicus Digital Elevation Model with high-resolution bathymetric data (HRBS-GLWNB 2020). This enabled the derivation of hypsometric relationships linking water level, surface area, and storage volume, facilitating the reconstruction of long-term water storage records using Landsat imagery and radar altimetry. These records reveal substantial interannual to decadal hydrological variability.Second, we applied advanced time series methods, including the Bayesian Estimator of Abrupt Change, Seasonality, and Trend (BEAST) and TIMESAT, to detect regime shifts, trend changes, and seasonal dynamics in lake hydrology. Also, a correlation analysis was performed to investigate the relationship between fluctuations in Lake Victoria's water levels and regional precipitation patterns, with the aim of elucidating the climatic drivers of the lake's hydrological variability. Results reveal pronounced interannual to decadal variability, threshold-driven shifts in water levels, and complex seasonal cycles influenced by East African rainfall patterns, El Niño and La Niña–Southern Oscillation, and the Indian Ocean Dipole. This data offers insights into flood risk thresholds and stable versus unstable hydrological regimes.Third, we assessed lake water quality using MODIS-Aqua-derived chlorophyll-a and lake surface temperature data (2003–2024). Chlorophyll-a, a proxy for phytoplankton biomass, was analyzed using Carlson's Trophic State Index, Getis-Ord Gi* spatial clustering, and Rotated Empirical Orthogonal Function (REOF) analysis. These approaches revealed persistent eutrophic zones and coherent spatiotemporal patterns linked to watershed nutrient loading, agricultural runoff, and seasonal dynamics. Correlation analyses with hydrological and meteorological variables further clarified the drivers of eutrophication and algal bloom formation.Together, these findings provide a comprehensive understanding of Lake Victoria's hydro-ecological dynamics, offering critical insights for climate-resilient water management, ecological conservation, and policy development. The integration of satellite-based monitoring and data-driven analysis presents a scalable framework for managing large freshwater systems in data-scarce regions.