비점오염물질측정망 수질 측정 항목 및 강우사상 특성 인자간 상관관계 평가

초록

The emission load from non-point sources of pollution is continuously increasing and negatively impacting ecosystems in waterways. Therefore, the Ministry of Environment in Korea operates a network of non-point pollutant monitoring stations to collect data and predict future changes. However, the application of this data in waterway management policies remains limited due to the lack of accuracy. Recent advancements in big data analysis have enabled more accurate predictions of water quality changes using non-point source pollutant data. This study examined correlations among monitored data and water quality at the Samcheon station, representing a small water basin among the network. The correlation ranged from –0.769 to 0.695 for the entire study period. Specifically, correlations were –0.328 to 0.480 for the preceding dry period, –0.534 to 0.342 during rainfall events, and –0.477 to 0.274 for the days following rainfall. It was observed that the correlation widely varied depending on the weather conditions. Among them, those for entire period were the highest correlated, suggesting that it should be more agreeably used for future non-point water quality modelling.

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