Applying fuzzy weighting and TOPSIS for flood risk assessment in flood-prone areas within watershed basins
To quantitatively measure flood risk in flood-prone areas within watershed basins,we proposed an integrated risk measurement model based on fuzzy weighting-TOPSIS.Twelve risk indicators were identified,considering factors related to causative factors,disaster-prone environments,and disaster-bearing bodies,encompassing flood hazard,exposure,and vulnerability indicators.We utilized the Triangular Fuzzy Analytic Hierarchy Process(TFAHP),enhanced with fuzzy logic,to compute the weights of these indicators.The flood risk assessment was conducted utilizing the concept of relative closeness within the Technique for Order Preference by Similarity to the Ideal Solution(TOPSIS).As an illustration,the flood risk in three local government areas(Liverpool,Fairfield,and Canterbury-Bankstown)within the Georges River Basin in Australia was evaluated.The results reveal that distance to river-elevation weighting,maximum 3-day rainfall,and land use type are the primary contributors to flood risk,with weights of 0.312,0.164,and 0.137,respectively.Flood risk levels exhibit significant variations among regions.Medium to high-risk areas are concentrated in the central-eastern part of Liverpool,the eastern part of Fairfield,and the central part of Canterbury-Bankstown,while the western and southern regions of Liverpool demonstrate relatively low flood risks.The integrated TFAHP-TOPSIS model identifies 15.6％more medium to high-risk areas compared to the individual TFAHP method,and 17.1％more than the single TOPSIS method,effectively identifying additional potential flood risks.Furthermore,a comparison with a historical disaster validation set confirms the superiority of the TFAHP-TOPSIS integrated model.This integrated approach harnesses the strengths of both TFAHP and TOPSIS,enhancing its effectiveness in assessing flood risk.It discerns the variances in indicator contributions through TFAHP,effectively leveraging decision-makers'subjective expertise.Concurrently,TOPSIS establishes the relative superiority and inferiority order of solutions based on objective information from indicator attribute values,ensuring decision objectivity.The assessment outcomes offer valuable insights for devising disaster prevention strategies in flood-prone areas within watersheds.
public safetypotential flood riskmultiple-criteria decision makingTriangular Fuzzy Analytic Hierarchy Process(TFAHP)Technique for Order Preference by Similarity to the Ideal Solution(TOPSIS)
万方数据
维普
