다변량 통계분석 기반 저서성 대형무척추동물지수 등급체계 평가 (The Evaluation of Current Grade System for Benthic Macroinvertebrates Index Using Multivariate Statistical Analysis)

서지정보

· 발행기관 : 한국물환경학회
· 수록지 정보 : 한국물환경학회지 / 41권 / 1호 / 18 ~ 29페이지
· 저자명 : 이도건, 공동수, 박배경, 박성애, 차윤경

초록

The Benthic Macroinvertebrate Index (BMI) is used to assess water quality and the health of aquatic ecosystems in South Korea. In the current BMI grade system, the grades were classified based on the relationships between the BMI and three water quality variables (BOD5, TSS, and TP) using the past data. However, BMI values are also influenced by numerical environmental factors in addition to water quality, and the relationships between BMI and environmental factors may change in the long-term perspective. This study applied multivariate regression tree (MRT) analysis to classify BMI into five grades using a broader range of environmental variables, including hydrometeorological data and recent ecological information. The results of the MRT-based analysis, along with the relative importance of environmental variables, were compared w ith t he c urrent B MI g rade s ystem. Significant d ifferences w ere observed i n the split points derived from MRT analysis and the current system. Notably, flow velocity, a factor overlooked in thecurrent grading framework, emerged as a critical determinant, displaying clearer distinctions between grades. Additionally, predictions of BMI grades using random forest models based on MRT analysis showed slightly better performance than predictions using the current system. These findings highlight the need to incorporate a wider range of environmental factors into the BMI grading framework to improve its accuracy and adaptability for assessing water quality and aquatic ecosystem health, particularly in the context of long-term environmental changes.

영어초록

The Benthic Macroinvertebrate Index (BMI) is used to assess water quality and the health of aquatic ecosystems in South Korea. In the current BMI grade system, the grades were classified based on the relationships between the BMI and three water quality variables (BOD5, TSS, and TP) using the past data. However, BMI values are also influenced by numerical environmental factors in addition to water quality, and the relationships between BMI and environmental factors may change in the long-term perspective. This study applied multivariate regression tree (MRT) analysis to classify BMI into five grades using a broader range of environmental variables, including hydrometeorological data and recent ecological information. The results of the MRT-based analysis, along with the relative importance of environmental variables, were compared w ith t he c urrent B MI g rade s ystem. Significant d ifferences w ere observed i n the split points derived from MRT analysis and the current system. Notably, flow velocity, a factor overlooked in thecurrent grading framework, emerged as a critical determinant, displaying clearer distinctions between grades. Additionally, predictions of BMI grades using random forest models based on MRT analysis showed slightly better performance than predictions using the current system. These findings highlight the need to incorporate a wider range of environmental factors into the BMI grading framework to improve its accuracy and adaptability for assessing water quality and aquatic ecosystem health, particularly in the context of long-term environmental changes.

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