This study analyzes the spatio-temporal variation of surface water quality (pre-monsoon, monsoon, and post-monsoon) within the lake water system of the Ernakulam District using GIS techniques. The selected physicochemical parameters were assessed from fifty sampling sites employed to analyze multivariate techniques like Pearson correlation, Principal Component Analysis (PCA), and Hierarchical Agglomerative Cluster Analysis (HACA). The WQI values ranged from 26 to 228, indicating water quality from excellent to unsuitable, with 27% of sites showing poor to unsuitable water quality and 45% classified as excellent to good, reflecting low pollution levels. Pearson correlation highlighted strong relationships among salinity, conductivity, temperature, and hardness, linked to tidal and evaporation effects. Principal Component Analysis (PCA) revealed three components: PC1 (35.23%), influenced by salinity and hardness due to tidal dynamics; PC2 (25.18%) reflecting organic pollution from NO2–N, NH4–N, and PO4–P; and PC3 (12%) associated with DO and SiO3, driven by river runoff. HACA analysis grouped parameters into tidal dynamics and anthropogenic pollution clusters. The findings emphasize the dual impact of natural processes and human activities on water quality, offering a baseline for effective management strategies in the study area.