퍼지로직 기반의 HMU 분류를 이용한 Meso-scale 하천 서식처 적합성 평가

Abstract

The need for precise methodologies to assess the health of river ecosystems has grown, leading to the development of Meso-scale habitat evaluation as an important approach. The objectives of this study were to improve fuzzy logic for a Hydromorphological Unit (HMU) classification method considering multiple physical habitat variables, and to analyze meso-scale stream habitat suitability under varying streamflow conditions using the developed Fuzzy logic. The study was conducted on the Bokha River, where a HEC-RAS 2D model was used to simulate depth and velocity, and habitat suitability indices were derived based on fuzzy logic using depth and velocity data from simulations. A modified Fuzzy Logic algorithm was employed to flexibly and precisely account for the interactions between hydrological characteristics and environmental variables in Meso-scale habitat evaluation. The Fuzzy Logic-based Meso-scale river habitat evaluation model successfully distinguished habitat types based on velocity and depth data and visualized habitat changes under different flow conditions. The evaluation using the Centroid method highlighted the potential to integrate ecological factors and physical environmental conditions into habitat assessment, offering practical insights for river ecosystem restoration and management. This study is expected to contribute foundational data for future river ecosystem management and restoration efforts.