The objective of this study was to analyze long-term temporal trends of water chemistry and spatial heterogeneity for 10 sampling sites of the Yeongsan River watershed using water quality dataset during 1995 to 2004 (obtained from the Ministry of Environment, Korea). The water quality, based on multi-parameters of biological oxygen demand (BOD), chemical oxygen demand (COD), conductivity, dissolved oxygen (Do), total phosphorus (TP), total nitrogen (TN) and total suspended solids (TSS), largely varied depending on the sampling sites, seasons and years. Largest seasonal variabilities in most parameters occurred during the two months of July to August and these were closely associated with large spate of summmer monsoon rain. Conductivity, used as a key indicator for a ionic dilution during rainy season, and nutrients of TN and TP had an inverse function of precipitation (absolute r values> 0.32, P< 0.01, n= 119), whereas BOD and COD had no significant relations(P> 0.05, n= 119) with rainfall. Minimum values in conductivity, TN, and TP were observed during the summer monsoon, indicating an ionic and nutrient dilution of river water by the rainwater. In contrast, major inputs of total suspended solids (TSS) occurred during the period of summer monsoon. BOD values varied with seasons and the values was closely associated (r=0.592: P< 0.01) with COD, while variations of TN were had high correlations (r=0.529 : P< 0.01) with TP. Seasonal fluctuations of DO showed that maximum values were in the cold winter season and minimum values were in the summer seasons, indicating an inverse relation with water temperature. The spatial trend analyses of TP, TN, BOD, COD and TSS, except for conductivity, showed that the values were greater in the mid-river reach than in the headwater and down-river reaches. Conductivity was greater in the down-river sites than any other sites. Overall data of BOD, COD, and nutrients (TN, TP) showed that water quality was worst in the Site 4, compared to those of others sites. This was due to continuous effluents from the wastewater treatment plants within the urban area of Gwangju city. Based on the overall dataset, efficient water quality management is required in the urban area for better water quality.