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基于链式成灾过程的暴雨泥石流成灾效率评估 被引量:2

Evaluation of disaster efficiency of heavy rain and debris flow based on chain disaster process
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摘要 泥石流是我国西南地区主要的地质灾害,由于成灾过程的复杂性,利用模糊评价方法的泥石流危险度评价成为灾害防治的重要手段。但传统评价方法忽视评价指标的内在联系与泥石流的链式成灾过程,导致了评价结果的失真。本文以暴雨泥石流为例将成灾过程划分为积蓄阶段与暴发阶段,选用二阶段DEA模型作为评价方法。并按所代表的成灾条件将原本的指标重新分类,根据每个成灾环节对应的发灾场、致灾力与灾害体现构建了暴雨泥石流二阶段DEA模型。评价后直接得到各阶段的成灾效率排名,并可根据因子冗余情况,分析流域整体或沟道个体的成灾特征,确定对应的防灾措施。 Debris flow is the main geological disaster in Southwest China.Due to the complexity of the disaster process,the risk assessment of debris flow using fuzzy evaluation method has become an important means of disaster prevention.However,traditional evaluation methods ignore the internal connection of evaluation indicators and the chain-type disaster process of debris flow,which leads to the distortion of evaluation results.In this paper,taking heavy rain and debris flow as an example,the disaster process is divided into the accumulation phase and the explosion phase,and the two-phase DEA model is selected as the evaluation method.The original indicators are reclassified according to the disaster conditions represented,and the two-stage DEA model of heavy rain and debris flow is constructed according to the disaster site,disaster capacity and disaster manifestation corresponding to each disaster link.After the evaluation,the ranking of disaster efficiency at each stage can be directly obtained,and the disaster characteristics of the entire basin or the individual channel can be analyzed according to the factor redundancy,and the corresponding disaster prevention measures can be determined.
作者 殷启睿 陈舒阳 刘航钊 丁奎 苏娜 YIN Qirui;CHEN Shuyang;LIU Hangzhao;DING Kui;SU Na(School of Civil Engineering,Central South University,Changsha 410075,China;Central South University of Forestry and Technology,Changsha 410004,China)
出处 《自然灾害学报》 CSCD 北大核心 2021年第3期69-75,共7页 Journal of Natural Disasters
基金 国家自然科学基金(42007419) 湖南省自然科学基金(2020JJ5981)。
关键词 泥石流 危险度评价 数据包络分析 灾害防治 冗余分析 debris flow risk assessment data envelopment analysis disaster prevention and control redundancy analysis
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