Evaluation of Pollution load and Factors on Water Quality based on Watershed Model in Okjeong Lake

This study aims to identify the factors influencing water quality in Okjeong Lake, which was formed by the construction of the Seomjin River Dam, and to analyze the non-point source pollution discharge characteristics of the upstream basin. Additionally, it seeks to propose priority management areas for pollution sources within this basin. For this purpose, data from the Ministry of Environment's measurement network was analyzed, and the HSPF model was developed to analyze the simulation results. The results of correlation analysis, multiple regression analysis, and factor analysis using hydrological and water quality data from Okjeong Lake and its upstream watersheds indicated that the water quality load from Seomjin River had a greater impact on the water quality of Okjeong Lake than the inflow from Churyeong-cheon. These statistical analyses highlight the importance of managing pollution sources in the upper watershed of Seomjin River for effective water quality management of Okjeong Lake. Simulation results from the HSPF model, which demonstrated reliable reproducibility, the analysis of water quality loads from the upper watershed of Seomjin River and Churyeong-cheon by rainfall events showed that the proportion of organic matter, T-N, and T-P loads was relatively higher in the 0~30 mm rainfall events compared to non-rainfall periods, indicating the importance of managing stormwater runoff. Additionally, the distribution of water quality loads on the Load Duration Curve (LDC) using the model simulation results showed that non-point pollution source management is crucial for both inflowing streams. However, in the upper watershed of Seomjin River, the frequency of T-P loads exceeding the LDC across all flow intervals was higher, indicating the need to manage both point and non-point pollution sources. These findings suggest that non-point pollution management in the upstream watersheds is essential for Okjeong Lake water quality management. Furthermore, the spatial distribution of the average delivery load index for each subbasin in the model was used to identify priority management areas for pollution sources and to provide essential information for establishing future pollution control strategies.