The spatiotemporal changes of lake water resources objectively reflect not only the process of the water resources balance, but also the ecological environment changes in the lake area. In recent decades, climate changes and human activities have caused great impacts on the spatial distribution of the earth’s water resources and the spatiotemporal process of the surface water cycle, which has caused a series of ecological crises and environmental problems, such as the drying-up of inland lakes, the disappearance of the oasis, water shortage or flooding and water pollution. Therefore, monitoring and fully understanding the dynamic changes of lakes is of great scientific significance for grasping regional water balance, water resources management, and sustainable development of the ecological environment. In this study, we focus on using multi-source satellite data on the estimation of water volume and multi-timescale variations analysis for large scale lakes. This study combines the problems in the practical application of “African Water Action”, taking the largest lake in Africa, Lake Victoria, as the study area, and utilizes long-term serial multi-source satellite data of the past 15 years (2003–2017), including Moderate-resolution Imaging Spectroradiometer (MODIS), Jason-1/-2/-3 and Gravity Recovery and Climate Experiment (GRACE) to perform the comprehensive analysis on the water volume change estimation. Firstly, the satellite altimetry data of Jason-1/-2/-3 and MODIS imagery was used to calculate series of water level, and to extract series of water surface area, respectively. On this basis, a more accurate regression model between the area and water level variation ($\Delta H$) was constructed. Then, the model between water volume variation ($\Delta V$) and $\Delta H$, derived from area-$\Delta H$ model, was applied to calculate the relative water volume of Lake Victoria. Meanwhile, terrestrial water storage (TWS) changes between 2003 and 2016, derived from GRACE data, were also used for a comparative verification of the $\Delta V$ results. The results show the long-term series change trends of $\Delta V$ and the TWS are the same. Finally, the multi-timescale analysis of water volume changes was carried out on different time scales, such as the inter-annual, inter-monthly, and variation period.

Lakes are important components of the Earth's surface water bodies, and their fluctuating water levels and changing water volumes can have an important impact on ecological processes and landscape patterns within a watershed. Climate change and human activities are the main drivers of water volume changes in lakes. We applied a long time series analysis approach using classical statistics and geographic information system (GIS) technics to quantitatively attribute water volume variations in Lake Victoria from 2000 to 2019. We examined several drivers of lake water volume variations: meteorological factors including regional climate change (precipitation, evaporation) and global climate change (El Niño/Southern Oscillation events), and anthropogenic factors including socio-economic development and land use/cover change. The results show that regional climate change has a greater impact on lake water volume variations than global climate change; among them, the correlation coefficient between precipitation and lake water volume variations is the largest (0.410), with an impact lag of 1 month. For anthropogenic factors, variations in lake water volume are more pronounced in areas with rapid economic development and high population growth, with correlation coefficients greater than 0.440. Different types of land use/cover have varying impacts on Lake Victoria's water volume variations. Overall, the influence of anthropogenic factors is greater than that of meteorological factors. This study results not only provides a scientific basis for exploring the hydrological changes and their drivers in the world's large transboundary lakes, but also be great scientific significance to rational use of water resources and sustainable regional development.

Water purification capacity (WPC), a crucial regulator of aquatic ecosystem services, plays an important role in mitigating non-point source pollution and ensuring water quality in a basin. In this study, the long-term water purification capacity of the three countries surrounding Lake Victoria (Kenya, Tanzania and Uganda) was investigated using multi-source remote sensing data. and furthermore, the relationship between water purification and phytoplankton blooms, as well as anthropogenic activities, was exlored. By applying InVEST model, nitrogen and phosphorus (N/P) retention and output were derived, which were utilized to quantitatively assess reginal WPC. High resolution, long-term (2000–2021) spatial distribution of water purification capacity index (WPI) were then generated. The results reveal significant spatiotemporal changes of WPI, with a general trend of initial decline followed by subsequent increase being observed. Notably, comparatively lower WPI was exhibited by Uganda than by Tanzania and Kenya. Among the anthropogenic factors, the frequency of phytoplankton blooms was identified as serving as a spatial validation of WPI. While a significant negative correlation between WPI and GDP was demonstrated, its correlation with population was found to be considerably weaker. These findings contribute significantly to transboundary water resources management and sustainable development, and provide information support for the maintenance of regional ecological health.