<jats:title>Abstract</jats:title>
          <jats:p>Surface water pollution driven by land use practices and soil erosion remains a persistent challenge in tropical river basins of East Africa. Despite its socio-economic importance, the transboundary Sio Malaba Malakisi River Basin (SMMRB), shared by Kenya and Uganda, lacks comprehensive data on spatial and seasonal water quality dynamics. This study provides the first year-long baseline assessment of surface water quality in the SMMRB, using water samples collected from 12 monitoring sites across three distinct hydrological seasons: dry, short rainy, and long rainy. Twelve physicochemical parameters were analyzed following standardized protocols from the American Public Health Association (APHA), resulting in 854 data points. Multivariate statistical techniques: agglomerative hierarchical clustering, Wilk’s lambda analysis, and exploratory factor analysis (EFA), were used to identify patterns and key drivers of water quality variation. Three distinct spatial clusters, corresponding to the Sio, Malaba, and Malakisi sub-catchments, were identified, each exhibiting unique water quality profiles. Elevated concentrations of total phosphorus (TP), soluble reactive phosphorus (SRP), and total suspended solids (TSS) were observed, exceeding typical background levels for unpolluted rivers. Seasonal differences highlighted the role of sediment transport and dilution processes, particularly during the rainy seasons. These findings provide novel insights into nutrient transport and hydrogeomorphological influences in a tropical, data-scarce, transboundary basin. The results offer a scientific basis for setting up targeted monitoring stations and adaptive water management strategies. Future studies should assess long-term interactions between sediment and nutrients. Evaluating the effectiveness of soil and water conservation practices will also be important for improving water quality.</jats:p>

The spatiotemporal distribution of water quality characteristics of the tropical, transboundary Sio Malaba Malakisi River Basin using multivariate statistical techniques