Due to the continued increase in land use changes and changing climatic patterns in the Lake Victoria basin, understanding the impacts of these changes on the water quality of Lake Victoria is imperative for safeguarding the integrity of the freshwater ecosystem. Thus, we analyzed spatial and temporal patterns of land cover, precipitation, and water quality changes in the Lake Victoria basin between 2000 and 2022 using global satellite products. Focusing on chlorophyll-a (Chl-a) and turbidity (TUR) in Lake Victoria, we used statistical metrics (correlation coefficient, trend analysis, change budget, and intensity analysis) to understand the relationship between land use and precipitation changes in the basin with changes in Chl-a and TUR at two major pollution hotspots on the lake, i.e., Winam Gulf and Inner Murchison Bay (IMB). Results show that the Chl-a and TUR concentrations in the Winam gulf increase with increases in precipitation. Through increases in precipitation, the erosion risks are increased and transport of nutrients from land to the lake system, promoting algal growth and turbidity. In the IMB, Chl-a and TUR concentrations decrease with an increase in precipitation, possibly due to dilution, but peak during moderate rainfall. Interestingly, changes in land use and land cover (LULC) at 5-year intervals showed no substantial correlation with water quality changes at selected hotspots even though a broader LULC change analysis over the past two decades indicated a notable 300% increase in built-up areas across the Lake Victoria basin. These findings underscore the dominant influence of precipitation changes over LULC changes on the water quality of Lake Victoria for the selected hotspot areas.

The increase of human interventions and developments are modifying the land use/land cover (LULC) of the global landscape, thus severely affecting the water quality of rivers and lakes. Appropriate management and effective policy developments are required to deal with the problems of surface water contamination around the globe. However, spatiotemporal variations of water quality and its complex relation with land cover (LC) changes, challenge adequate water resources management. In this study, we explored the use of remote sensing to relate LC change in the Katari River Basin (KRB) located in the Bolivian Andes and water quality on the shores of Lake Titicaca, in order to support water management. An unsupervised classification of Landsat 7 satellite images and trajectory analysis was applied to understand the modifications of LC through time. In addition, water-quality indicators at the outlet of the basin were retrieved from remote-sensing images and its temporal behavior was analyzed. The results show that the expansion of urban areas is the predominant environmental driver in the KRB, which has great impact on the water quality of Lake Titicaca. We conclude that there is a strong link between the rapid growth of urban and industrial areas with the detriment of river and lake water quality. This case study shows how remote sensing can help understand driver–impact relations.

Lake Chinchaycocha, Peru’s second-largest high-altitude lake and a Ramsar-designated wetland of international importance, is increasingly threatened by anthropogenic pollution and hydroclimatic shifts. This study integrates Sentinel-2 multispectral imagery with in situ water quality data from Peru’s National Water Observatory to assess spatiotemporal dynamics in 31 physicochemical parameters between 2018 and 2024. We evaluated 40 empirical algorithms developed globally for Sentinel-2 and tested their transferability to this ultraoligotrophic Andean system. The results revealed limited predictive accuracy, underscoring the need for localized calibration. Subsequently, we developed and validated site-specific models for ammoniacal nitrogen, electrical conductivity, major ions, and trace metals, achieving high predictive performance during the rainy season (R² up to 0.95). Notably, the study identifies consistent seasonal correlations—such as between total copper and ammoniacal nitrogen—and strong spectral responses in Band 1, linked to runoff dynamics. These findings highlight the potential of combining public monitoring data with remote sensing to enable scalable, cost-effective assessment of water quality in optically complex, high-Andean lakes. The study provides a replicable framework for integrating national datasets into operational monitoring and environmental policy.

Understanding the current water quality dynamics is necessary to ensure that ecological and sociocultural services are provided to the population and the natural environment. Water quality monitoring of lakes is usually performed with in situ measurements; however, these are costly, time consuming, laborious, and can have limited spatial coverage. Nowadays, remote sensing offers an alternative source of data to be used in water quality monitoring; by applying appropriate algorithms to satellite imagery, it is possible to retrieve water quality parameters. The use of global remote sensing water quality products increased in the last decade, and there are a multitude of products available from various databases. However, in Latin America, studies on the inter-comparison of the applicability of these products for water quality monitoring is rather scarce. Therefore, in this study, global remote sensing products estimating various water quality parameters were explored on Lake Titicaca and compared with each other and sources of data. Two products, the Copernicus Global Land Service (CGLS) and the European Space Agency Lakes Climate Change Initiative (ESA-CCI), were evaluated through a comparison with in situ measurements and with each other for analysis of the spatiotemporal variability of lake surface water temperature (LSWT), turbidity, and chlorophyll-a. The results of this study showed that the two products had limited accuracy when compared to in situ data; however, remarkable performance was observed in terms of exhibiting spatiotemporal variability of the WQ parameters. The ESA-CCI LSWT product performed better than the CGLS product in estimating LSWT, while the two products were on par with each other in terms of demonstrating the spatiotemporal patterns of the WQ parameters. Overall, these two global remote sensing water quality products can be used to monitor Lake Titicaca, currently with limited accuracy, but they can be improved with precise pixel identification, accurate optical water type definition, and better algorithms for atmospheric correction and retrieval. This highlights the need for the improvement of global WQ products to fit local conditions and make the products more useful for decision-making at the appropriate scale.

The increase of human interventions and developments is modifying the land use/land cover (LULC) of the global landscape, thus affecting the water quality of rivers and lakes severely. Lake Titicaca and Lake Nicaragua (also known as Lake Cocibolca) are the largest lakes in Latin America. Despite Bolivia and Nicaragua being countries with a vast richness of natural resources, they face unsustainable practices ranging from over-exploitation of resources to drastic LULC changes that have created environmental problems that consequently affect human well-being and health. Additionally, climate change (CC) is exacerbating these problems and causing new ones. Therefore, it is also necessary to consider the effects that it will have on water quality, either by changes in temperature or by changes in precipitation (floods or droughts) that affect river flows and sediment transport.Environmental sustainability means securing adequate management of natural resources in all human productive and livelihood activities. Monitoring and assessing the quality of surface waters are fundamental for managing and ensuring the improvement of its state. A good understanding of the LULC change and CC dynamics is crucial to develop efficient strategy assessment, pollution management, and land use planning for the promotion of sustainable development. For these case studies, the integrated use of remote sensing products; especially considering the scarcity of data, enables a comprehensive understanding of the cause-effect relations in the water system, which assists policymakers in developing management plans for a variety of natural resource management applications.