인공증설 이후 하천 수질 변수 간 상관 구조의 계절별 변화 분석

초록

This study investigates the influence of wintertime artificial cloud seeding on the correlation structure among water quality parameters in a mountainous watershed. Two representative periods with contrasting hydrological and physicochemical conditions—March (immediately after seeding) and October (non-seeding season)—were compared. Using long-term monitoring data from the Odaecheon-1 site collected between 2013 and 2023, Pearson correlation coefficients were calculated for 18 water quality variables, and the inter-month differences (Δr) were used to assess seasonal structural changes. In March, strong positive correlations were observed among organic matter indicators, such as COD–TOC (r = 0.84) and BOD–TOC (r = 0.83), suggesting that snowmelt during the post-seeding period contributed to elevated organic loads. In contrast, October showed marked negative correlations between organic matter and nitrogen-related parameters, including COD–TN (r = –0.85) and COD–DTN (r = –0.86), which likely reflect the influence of nonpoint source pollution from decaying vegetation or agricultural runoff. The TP–NH4+-N pair showed higher correlation in March (Δr = 1.17), implying the simultaneous influx of ionic nutrients following seeding-induced snowfall and meltwater transport. On the other hand, DTP–Fecal Coliform (Δr = –0.73) and PO43--P–Fecal Coliform (Δr = –0.92) correlations were more pronounced in October, indicating the co-transport of pathogens and phosphate in non-seeding periods. This study quantitatively reveals that specific parameter pairs can reflect seasonal hydrological inputs and the potential influence of artificial precipitation experiments. Multivariate correlation analysis is shown to be a useful approach for evaluating the environmental impacts of cloud seeding operations.

키워드