AHP-Entropy 기법을 활용한 홍수 예⋅경보 체계 구축 대상농업용저수지 우선순위 평가
Priority Assessment of Agricultural Reservoirs for Flood Forecasting and Warning Systems Using the AHP-Entropy Method
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This study aims to establish a scientific and objective framework for prioritizing agricultural reservoirs for flood warning system implementation inresponse to increasing flood risks from climate change and aging infrastructure. Out of 3,426 reservoirs nationwide, 1,211 were selected through filteringcriteria including safety inspection reports, emergency action plans, reservoir specifications, and flood vulnerability grades. The evaluation frameworkcombines the AHP (analytic hierarchy process) and Entropy weight method, using nine standardized indicators grouped into four categories: watershedcharacteristics, structural characteristics, vulnerability indicators, and downstream risk. Based on weighted composite scores, reservoirs were classifiedinto four risk levels. The results identified 303 reservoirs in the most critical category, with high concentration in North Gyeongsang Province. Top-priority sites such as Hagok and Wangsin in Gyeongju matched recent disaster records, confirming the validity of the model. ThisAHP-Entropy-based vulnerability assessment provides a practical tool for phased implementation of flood warning systems for agricultural reservoirs.
Abstract
This study aims to establish a scientific and objective framework for prioritizing agricultural reservoirs for flood warning system implementation inresponse to increasing flood risks from climate change and aging infrastructure. Out of 3,426 reservoirs nationwide, 1,211 were selected through filteringcriteria including safety inspection reports, emergency action plans, reservoir specifications, and flood vulnerability grades. The evaluation frameworkcombines the AHP (analytic hierarchy process) and Entropy weight method, using nine standardized indicators grouped into four categories: watershedcharacteristics, structural characteristics, vulnerability indicators, and downstream risk. Based on weighted composite scores, reservoirs were classifiedinto four risk levels. The results identified 303 reservoirs in the most critical category, with high concentration in North Gyeongsang Province. Top-priority sites such as Hagok and Wangsin in Gyeongju matched recent disaster records, confirming the validity of the model. ThisAHP-Entropy-based vulnerability assessment provides a practical tool for phased implementation of flood warning systems for agricultural reservoirs.