摘要
沿海沿河流低洼地区洪涝频发、损失严重,严重影响流域公共安全,有效识别流域盆地洪泛区内的洪水风险分布至关重要.传统基于单一多准则决策方法的风险测度模型无法兼顾决策者的有效经验和决策的客观合理性,同时计算所得的绝对洪水风险值无法准确识别潜在洪水风险.为解决这一问题,提出了一种优化的集成模型,以澳大利亚乔治河流域洪泛区为例开展洪水风险测度研究.从危险性、暴露度和脆弱性三个维度选取12个风险指标,采用模糊逻辑改进的三角模糊层次分析法优化权重计算过程、集成接近理想点法中相对邻近度的概念完成相对洪水风险测度,最后可视化分析了洪水风险的空间分布状况.结果表明,集成模型识别出的中等及以上风险区比单一三角模糊层次分析法多17.1％,比接近理想点法多15.7％,在识别洪泛区潜在风险上表现更优.利用历史灾情验证集证明了模型的优越性.该研究框架可为流域洪泛区的防灾策略制定提供决策支持.
Abstract
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.
基金项目
国家自然科学基金项目(41906185)
国家自然科学基金项目(U1901602)
青岛市自然科学基金项目(23-2-1-61-zyydjch)
维普
万方数据