山洪对私人住户造成破坏的主要原因

IF 3 3区 环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES
Daniela Rodríguez Castro, Kasra Rafiezadeh Shahi, Nivedita Sairam, Melanie Fischer, Guilherme Samprogna Mohor, Annegret Thieken, Benjamin Dewals, Heidi Kreibich
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引用次数: 0

摘要

山洪暴发造成大量人员伤亡和巨大的经济损失。了解灾害过程对实施有效的山洪风险管理至关重要。然而,人们对山洪暴发期间发生的破坏过程知之甚少,尽管它们很严重。为了获得更多的知识,在2021年洪水之后,在比利时和德国的受影响地区开展了独立的数据收集行动。由此产生的数据集包括比利时Vesdre山谷的420座受损住宅建筑,莱茵兰-普法尔茨(德国)的Ahr山谷的277座和北莱茵-威斯特伐利亚(德国)的332座。各区域共统一了30个可能影响损害的变量,为灾害特征、暴露资产的脆弱性、居民的应对能力和社会经济因素提供了宝贵的见解。基于机器学习的分析揭示了危险变量的重要性,例如水深和沉积物运输,特别是对建筑物的破坏。除此之外,暴露(居住区域)和物理脆弱性因素(建筑类型和墙壁类型)也在确定受影响地区的建筑损坏方面发挥作用。对于内容物损坏,除了水深和居住面积外,社会经济脆弱性(建筑物所有权状况)和应急措施也是重要的预测因素。这些造成山洪灾害的主要驱动因素可用于开发更准确的灾害模型,从而改进山洪风险评估,加强风险沟通,并支持更好的防灾战略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Key Drivers of Flash Flood Damage to Private Households

Key Drivers of Flash Flood Damage to Private Households

Flash floods cause high numbers of casualties and enormous economic damage. Good knowledge of the damage processes is crucial for the implementation of effective flash flood risk management. However, little is known about the damage processes that occur during flash floods, despite their severity. To gain more knowledge, independent data collection initiatives were carried out in the affected areas of Belgium and Germany after the 2021 floods. The resulting datasets include 420 damaged residential buildings in the Vesdre valley in Belgium, 277 in the Ahr valley in Rhineland-Palatinate (Germany) and 332 in North Rhine-Westphalia (Germany). A total of 30 potential damage-influencing variables were harmonized across the regions, providing valuable insights into hazard characteristics, the vulnerability of exposed assets, the coping capacity of inhabitants, and socio-economic factors. Machine learning-based analysis reveals the significant importance of hazard variables, such as water depth and sediment transport, particularly for building damage. In addition to these, exposure (living area) and physical vulnerability factors (building type and wall type) also play a role in determining building damage across the affected regions. For content damage, besides water depth and living area, socio-economic vulnerability (ownership status of the building) and emergency measures were found to be important predictors. These key drivers of building and content damage from flash floods can be utilized to develop more accurate damage models, thereby improving flash flood risk assessments, enhancing risk communication, and supporting better preparedness strategies.

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来源期刊
Journal of Flood Risk Management
Journal of Flood Risk Management ENVIRONMENTAL SCIENCES-WATER RESOURCES
CiteScore
8.40
自引率
7.30%
发文量
93
审稿时长
12 months
期刊介绍: Journal of Flood Risk Management provides an international platform for knowledge sharing in all areas related to flood risk. Its explicit aim is to disseminate ideas across the range of disciplines where flood related research is carried out and it provides content ranging from leading edge academic papers to applied content with the practitioner in mind. Readers and authors come from a wide background and include hydrologists, meteorologists, geographers, geomorphologists, conservationists, civil engineers, social scientists, policy makers, insurers and practitioners. They share an interest in managing the complex interactions between the many skills and disciplines that underpin the management of flood risk across the world.
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