Abstract The Huaihe River Basin (HRB) is an important water system in eastern China, and its water quality has received widespread attention. This study explored the latest spatial variation patterns of surface water quality in the HRB to cope with the increasingly severe challenges of water resource management. By integrating multidimensional water quality data from surface water monitoring stations, including dissolved oxygen (DO), chemical oxygen demand (CODMn and COD), biochemical oxygen demand (BOD5), ammonia nitrogen (NH3–N), total phosphorus (TP), and total nitrogen (TN), this study utilized a cluster analysis technique to categorize the water quality data and reveal changes in the geographic variability of water quality. Among the 382 monitoring stations in the HRB, 258 stations had TN content lower than Class V, which was the highest among all monitoring indicators. The entropy weight method used to assess the comprehensive water quality showed that there were 157 and 163 monitoring stations belonging to Class III and IV, respectively, and stations with poor water quality were distributed downstream in the river network and estuary area. Correlation and cluster analyses indicated that agricultural and organic matter pollution were the two main factors affecting water quality in the HRB, particularly in the downstream area, and the high loading of nutrient salts such as TP and NH3–N reflected the significant influence of agricultural activities. In addition, the study examined the potential driving role of factors such as topography, geomorphology, and human activities on water quality changes and visualized the relationship between water quality class and cluster categories through spatial distribution maps and Sankey diagrams to clarify the regional patterns of water quality problems.