금강수계의 실시간자동측정 자료를 이용한 수질환경인자 간의 상관관계 분석
Analysis of Correlation between Water Quality Parameters using Data from Real-time Automatic Measurement
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In this study, correlations between seasons and parameters in the Geum River, South Korea, were examinedusing the hourly measurement data of water quality parameters by a real-time, automatic water-quality monitoringstation. Correlations between measures of water quality provided by this station exhibited the sametrends as those acquired by manual measurements; in both cases, water temperature showed high correlationswith DO and pH. Inflow-pollution-source items (TOC, TP) showed positive correlations with, and were muchinfluenced by, water temperature and precipitation. These two parameters had negative correlations with TN,which acts as a growth-limiting factor for algae. Linear regression analysis revealed that water temperaturecould be used to explain variations in DO (86.0%), pH (77.4%), TOC (51.7%), TN (39.6%), and TP (34.5%),at most. DO and TOC could explain variations in pH (90.8%) and TP (34.5%), respectively. The daily cyclesof change in water temperature, DO, and pH showed trends similar to that of air temperature. Generally, theywere highest from 13:00 to 16:00 hours, and lowest from 05:00 to 07:00 hours. The daily differences (largestin summer and smallest in winter) were most apparent in Bonghwangcheon, which is a tributary of the GeumRiver.
Abstract
In this study, correlations between seasons and parameters in the Geum River, South Korea, were examinedusing the hourly measurement data of water quality parameters by a real-time, automatic water-quality monitoringstation. Correlations between measures of water quality provided by this station exhibited the sametrends as those acquired by manual measurements; in both cases, water temperature showed high correlationswith DO and pH. Inflow-pollution-source items (TOC, TP) showed positive correlations with, and were muchinfluenced by, water temperature and precipitation. These two parameters had negative correlations with TN,which acts as a growth-limiting factor for algae. Linear regression analysis revealed that water temperaturecould be used to explain variations in DO (86.0%), pH (77.4%), TOC (51.7%), TN (39.6%), and TP (34.5%),at most. DO and TOC could explain variations in pH (90.8%) and TP (34.5%), respectively. The daily cyclesof change in water temperature, DO, and pH showed trends similar to that of air temperature. Generally, theywere highest from 13:00 to 16:00 hours, and lowest from 05:00 to 07:00 hours. The daily differences (largestin summer and smallest in winter) were most apparent in Bonghwangcheon, which is a tributary of the GeumRiver.
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