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我国Natech事件分布规律及涉水Natech事件致因分析 被引量:1

Characteristics of Natech Incidents in China and A Preliminary Cause Analysis of Precipitation Triggered Natechs
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摘要 为弥补我国自然—技术事件(Natech事件)案例研究空白,基于多种数据挖掘方法对近20 a公开报道的自然灾害诱发的技术事故案例进行收集整理,建立了Natech事件数据库。对该类事件时空分布、行业分布进行交叉分析后发现:Natech事件季节特征明显,暴雨和大风是主要肇因,建筑业和交通运输业脆弱性较强。在引入不利气象情景对涉水Natech事件造成死亡失踪人数进行相关分析后发现:多种行业组合下的涉水Natech事件导致的死亡失踪人数与事件发生前4~5 d的降水量变化率(PSPD)存在显著相关关系(r>0.3,p<0.01),该相关关系对于研判和防范连续降水时Natech事件风险具有重要参考价值。 To fill the data gap of Natech researches in China focusing on technological incidents triggered by natural hazards,this paper reports our efforts of collecting Natech incidents in China over the last 20 years,which leads to a preliminary Natech incidents database(Natech-DB in China).With Natech-DB the spatiotemporal distribution pattern of China Natech cases are analyzed for several major industries.Generally,Natechs occur or reported most frequently in summer,caused by storm and gale;construction and transportation are the major industries involving reported Natechs.Harnessing recorded meteorological variables over the leading days of each Natech case,our retrospective regressive analysis revealed that fatality number,including the missing,of a storm-or-flood-caused Natech holds significant correlation(r>0.3,p<0.01)with the rain change rate namely,Precipitation Slope over Preceding Days(PSPD),4—5 days prior to the incident.This finding benefits the prognosis of and preparing for Natech incidents in cases of days-lasting precipitation events.
作者 张媛 孟耀斌 叶涛 ZHANG Yuan;MENG Yaobin;YE Tao(Faculty of Geographical Science,Beijing Normal University,Beijing 100875,China;Academy of Disaster Reduction and Emergency Management Ministry of Emergency Management&Ministry of Education,Beijing 100875,China;School of National Safety and Emergency Management,Beijing Normal University,Beijing 100875,China)
出处 《灾害学》 CSCD 北大核心 2022年第1期185-191,共7页 Journal of Catastrophology
基金 国家重点研发计划(2018YFC1801603) 应急管理部委托项目“十四五”灾害事故规律特征及风险防范研究。
关键词 Natech 自然灾害 时空分布特征 暴雨 洪水 中国 Natech natural disasters spatiotemporal distribution storm flood China
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