Can Tho City is experiencing water stress driven by rapid global changes. This study assesses the spatiotemporal variation in surface water quality (SWQ) through a multivariate statistical approach to provide evidence-based scientific information supporting sustainable water resource management and contributing to achieving the city’s sustainable development goals (SDGs). The complex SWQ dataset with 14 monthly-measured parameters at 73 sampling sites throughout the city was collected and analyzed. The obtained results indicated that average concentrations of biochemical oxygen demand, chemical oxygen demand (COD), dissolved oxygen (DO), total coliform, turbidity, total suspended solids, and phosphate (PO43−) exceeded the permissible national levels. Spatially, cluster analysis had divided the city’s river basin into three different zones (mixed urban-industrial, agricultural, and mixed urban–rural zones). The key sources of SWQ pollution in these three zones were individually identified by principal component/factor analysis (PCA/FA), which were mainly related to domestic wastewater, industrial effluents, farming runoff, soil erosion, upstream sediment flows, and severe droughts. Discriminant analysis also explored that COD, DO, turbidity, nitrate (NO3−), and PO43− were the key parameters discriminating SWQ in the city among seasons and land-use zones. The temporally analyzed results from weighted arithmetic water quality index (WAWQI) estimation revealed the deterioration of SWQ conditions, whereby the total polluted monitoring sites of the city increased from 29% in 2013 to 51% in 2019. The key drivers of this deterioration were the expansion in built-up and industrial land areas, farming runoff, and droughts.