International journal of disaster risk reduction最新文献_第4页

Assessment and optimization of airport operational resilience under severe weather conditions: A case study of snowstorm 恶劣天气条件下机场运行弹性评估与优化：以雪灾为例

IF 4.5 1区地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY

International journal of disaster risk reduction

Pub Date : 2026-02-15 Epub Date: 2026-01-19 DOI: 10.1016/j.ijdrr.2026.106021

Yuhui Zhang , Lili Liu , Xiong Peng , Yanan Zhang , Qian Dong

To scientifically assess airport operational systems’ performance and resilience, we developed a comprehensive performance-indicator model based on the operational status of arrival and departure flights. In addressing limitations of conventional departure-rate metrics, we introduced the actual departure rate (ADR) alongside a resilience assessment model. We proposed an IVY-KMEDOIDS clustering algorithm to optimize airport resilience by enhancing the traditional KMEDOIDS algorithm, which groups hours with similar operational conditions into clusters and formulates optimization strategies for departure flights. We analyzed operational and meteorological data from Wuhan Tianhe International Airport (WUH), China, during snowstorms. The results demonstrated that ADR more accurately represented airport performance than conventional metrics and that resilience assessments based on ADR more closely reflected operational reality. The IVY-optimized KMEDOIDS algorithm determined the optimal cluster count from data collected at 11 snowstorm-impacted airports, achieving 20 clusters with a silhouette coefficient of 0.4756, a Davies–Bouldin index value of 1.4119, and a Calinski–Harabasz index value of 102.1020, thereby illustrating superior clustering performance. Hourly departure optimization strategies for WUH improved resilience by

0.13 - 3.18

on the first day and by

0.026 - 0.73

on the second. In robustness validation, the framework demonstrated strong applicability at Chengdu Shuangliu and Chengdu Tianfu airports and exhibited high robustness at four U.S. airports. Airports such as Atlanta and Chicago O’Hare experienced winter storms. This study establishes a scientific basis for airport operational management under severe weather conditions, thereby enhancing resilience and response capabilities.

为了科学地评估机场运行系统的性能和弹性，我们基于到达和离开航班的运行状态开发了一个综合绩效指标模型。为了解决传统离职率指标的局限性，我们引入了实际离职率（ADR）和弹性评估模型。本文通过对传统KMEDOIDS算法的改进，提出了一种IVY-KMEDOIDS聚类算法，将运行条件相似的小时数聚类，并制定出发航班的优化策略，对机场弹性进行优化。我们分析了中国武汉天河国际机场（WUH）在暴风雪期间的业务和气象数据。结果表明，ADR比传统指标更准确地反映了机场绩效，基于ADR的弹性评估更能反映运营现实。经过ivy优化的KMEDOIDS算法从11个受暴风雪影响机场的数据中确定了最优聚类数，得到了20个聚类，剪影系数为0.4756，davis - bouldin指数为1.4119，Calinski-Harabasz指数为102.1020，表明聚类性能优越。每小时出发优化策略在第一天提高了0.13 ~ 3.18，第二天提高了0.026 ~ 0.73。在稳健性验证中，该框架在成都双流和成都天府机场表现出较强的适用性，在四个美国机场表现出较高的稳健性。亚特兰大和芝加哥奥黑尔等机场经历了冬季风暴。本研究为机场在恶劣天气条件下的运行管理提供科学依据，从而提高机场的应变能力和响应能力。

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引用次数: 0

A stochastic rain-on-grid framework for handling spatio-temporal rainfall uncertainty in impact-based flood nowcasting 基于影响的洪水临近预报中处理降水时空不确定性的随机网格降雨框架

IF 4.5 1区地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY

International journal of disaster risk reduction

Pub Date : 2026-02-15 Epub Date: 2026-01-07 DOI: 10.1016/j.ijdrr.2026.105998

Pierfranco Costabile , Margherita Lombardo , Carmelina Costanzo , Ioannis Tsoukalas , Vasilis Bellos

Predicting flash flood impacts remains a major challenge due to intrinsic uncertainty in rainfall spatial-temporal structure and limited understanding of how rainfall organization propagates through hydrological and hydrodynamic processes to generate urban-scale impacts. These limitations hinder the development of reliable impact-based early warning systems for small, fast-responding catchments.

To address these challenges, we introduce a Stochastic Rain-on-Grid framework that explicitly accounts for rainfall uncertainty by coupling a high-resolution stochastic rainfall generator with a 2D hydrodynamic model operating at the watershed scale. The framework is applied to a representative high-impact flash flood event affecting a piedmont urbanized area characterized by complex interactions between mountain and urban flooding processes. Using 100 equiprobable synthetic storms reproducing the statistical properties of the observed radar rainfall (200 m, 2 min), we assess how rainfall spatio-temporal variability alone influences catchment response and street-level flood impacts.

Results show substantial variability in simulated hydrographs despite statistically similar rainfall inputs, while this variability systematically attenuates at the street scale, leading to more stable hazard classifications. This indicates that impact-based hydrodynamic indicators are more robust targets for early warning systems than traditional hydrograph-based metrics. Analysis of rainfall structure metrics reveals that spatial and temporal coefficients of variation consistently correlate with impact severity. Building on these relationships, we propose the Storm Variability Diagram, which classifies equiprobable events by expected impact and significantly reduces uncertainty in hazard mapping through ensemble partitioning.

Overall, this study provides a proof-of-concept for impact-oriented uncertainty assessment through a modular and transferable framework, supporting uncertainty-aware flash flood forecasting.

由于降雨时空结构的内在不确定性以及对降雨组织如何通过水文和水动力过程传播以产生城市规模影响的理解有限，预测山洪影响仍然是一个主要挑战。这些限制阻碍了为小型、快速反应集水区开发可靠的基于影响的预警系统。为了应对这些挑战，我们引入了一个随机降雨网格框架，该框架通过将高分辨率随机降雨发生器与在流域尺度上运行的二维水动力模型相结合，明确地解释了降雨的不确定性。该框架应用于一个具有代表性的山前城市化地区的高影响山洪事件，该地区的山洪过程与城市洪水过程之间存在复杂的相互作用。利用100个等概率合成风暴再现了观测到的雷达降雨（200米，2分钟）的统计特性，我们评估了降雨时空变化如何单独影响流域响应和街道洪水影响。结果显示，尽管统计上的降雨输入相似，但在模拟水文中存在实质性的变异性，而这种变异性在街道尺度上系统地减弱，从而导致更稳定的灾害分类。这表明基于冲击的水动力指标比传统的基于水文的指标更适合早期预警系统。降雨结构指标分析表明，时空变异系数与影响严重程度一致。在这些关系的基础上，我们提出了风暴变率图，该图根据预期影响对等概率事件进行分类，并通过集成划分显著降低了危险制图中的不确定性。总体而言，本研究通过模块化和可转移的框架，为影响导向的不确定性评估提供了概念验证，支持不确定性意识的山洪预报。

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引用次数: 0

Recurrent risk and the disaster loop: A forensic approach to urban flooding 复发性风险和灾害循环：城市洪水的法医方法

IF 4.5 1区地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY

International journal of disaster risk reduction

Pub Date : 2026-02-15 Epub Date: 2026-01-23 DOI: 10.1016/j.ijdrr.2026.106028

José de Jesús Flores Durán , Irasema Alcántara-Ayala

Floods are among the most widespread and recurrent disasters worldwide, with particularly severe impacts in rapidly urbanising regions of developing countries such as Mexico, where inequality, governance constraints, and unplanned land-use change intensify exposure and vulnerability. Flood risk in Guadalajara, Mexico, stems from long-standing socio-spatial, institutional, and historical processes rather than isolated hydrometeorological events. Drawing on a forensic, retrospective longitudinal approach, this study reconstructs the causal pathways through which exposure and vulnerability have been generated, consolidated, and reproduced over time. The findings show how successive phases of urbanisation on unsuitable land, socio-spatial segregation, and uneven infrastructure provision have produced a recurrent pattern of flooding across the municipality. Institutional responses—centred predominantly on reactive, engineering-based measures—have mitigated immediate impacts while reinforcing the structural conditions that sustain risk. To interpret these cyclical dynamics, the study introduces the disaster loop. This conceptual model captures the self-reinforcing mechanisms through which governance practices, development trajectories, and territorial transformations continually regenerate risk conditions over time. By revealing the historical and systemic origins of Guadalajara's recurrent flooding, the analysis underscores the need for integrated, corrective, and prospective territorial planning capable of interrupting the feedback processes that normalise disaster risk and, instead, strengthening capacities to reduce it. The insights generated are relevant to rapidly urbanising contexts where inequality and governance fragmentation converge to reproduce extensive, chronic disaster patterns.

洪水是世界范围内最广泛和最经常发生的灾害之一，对墨西哥等发展中国家快速城市化地区的影响尤为严重，在这些地区，不平等、治理限制和无计划的土地利用变化加剧了风险和脆弱性。墨西哥瓜达拉哈拉的洪水风险源于长期的社会空间、制度和历史过程，而不是孤立的水文气象事件。本研究采用法医、回顾性的纵向方法，重建了暴露和脆弱性随着时间的推移而产生、巩固和再现的因果途径。研究结果表明，在不合适的土地上，城市化的连续阶段，社会空间隔离，以及不平衡的基础设施供应，如何在整个城市产生了反复出现的洪水模式。制度性的应对——主要集中在被动的、基于工程的措施上——减轻了直接影响，同时强化了维持风险的结构性条件。为了解释这些周期性动态，本研究引入了灾难循环。这个概念模型捕获了自我强化的机制，通过这些机制，治理实践、发展轨迹和领域转换随着时间的推移不断地再生风险条件。通过揭示瓜达拉哈拉经常性洪水的历史和系统根源，分析强调了需要进行综合、纠正和前瞻性的领土规划，以中断使灾害风险正常化的反馈过程，而不是加强减少灾害风险的能力。所产生的见解与快速城市化背景有关，在这种背景下，不平等和治理碎片化汇聚在一起，重现了广泛的、长期的灾难模式。

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引用次数: 0

The effect of evacuation decisions on flash flood preparedness in Fujairah, UAE: When the waters rise are we ready in desert country? 撤离决定对阿联酋富查伊拉山洪防备的影响：当水位上涨时，我们在沙漠国家准备好了吗？

IF 4.5 1区地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY

International journal of disaster risk reduction

Pub Date : 2026-02-15 Epub Date: 2026-01-12 DOI: 10.1016/j.ijdrr.2026.106013

Dr Praveen Maghelal , Dr Sudha Arlikatti , Dr Michael Lindell , Dr Khawla Saeed Al Hattawi , Mr Bader Abdulaziz Omar Al Jaberi , Ms Ghala Mohammed Mansour

The United Arab Emirates (UAE), known for its dry desert climate, receives only 140–200 mm (5.5–8.0 in) of rainfall per year. Over the past decade there has been a notable increase in the intensity of rain and occurrences of flash flooding in the Emirates of Dubai, Sharjah, Ras Al Khaimah and Fujairah. Although these events have caused fatalities and large-scale economic losses, there has been very little research about the increasing vulnerabilities of the population to flash flooding or about community preparedness and response to this hazard. The present study aims to fill this gap by examining households' decisions to evacuate in response to flooding and their intentions to prepare for future floods. A questionnaire based on the Protective Action Decision Model (PADM) was administered to 223 residents in the Emirate of Fujairah. The resulting data analysis identified several significant predictors of flash flood evacuation. These include risk perceptions, both positive and negative affective responses, and receipt of warnings from government authorities and news media platforms. Other significant predictors were the number of elderly people in the household, the respondent's age, and home ownership. There were significant differences among flood preparedness actions that households intend to take, as well as differences between evacuees and non-evacuees in their expectations of adopting permanent relocation and structural mitigation. The insights derived from this study can strengthen emergency management agencies' support for household preparedness and response to future flash floods.

阿拉伯联合酋长国（UAE）以其干燥的沙漠气候而闻名，每年的降雨量只有140-200毫米（5.5-8.0英寸）。在过去十年中，迪拜、沙迦、哈伊马角和富查伊拉等酋长国的降雨强度和山洪暴发次数显著增加。虽然这些事件造成了死亡和大规模的经济损失，但很少有关于人口对山洪暴发日益脆弱的研究，也很少有关于社区对这种危险的准备和反应的研究。本研究旨在通过考察家庭在应对洪水时的撤离决定以及他们为未来洪水做准备的意图来填补这一空白。根据保护行动决策模型（PADM）对富查伊拉酋长国的223名居民进行了问卷调查。由此产生的数据分析确定了几个重要的山洪疏散预测因素。这些包括风险认知，积极和消极的情感反应，以及收到政府当局和新闻媒体平台的警告。其他重要的预测因素是家庭中老年人的数量，受访者的年龄和房屋所有权。家庭准备采取的防洪行动之间存在显著差异，撤离者和非撤离者对采取永久性搬迁和结构性缓解措施的期望之间也存在显著差异。从本研究中获得的见解可以加强应急管理机构对家庭准备和应对未来山洪暴发的支持。

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引用次数: 0

Road transport resilience under extreme rainfall: Integrating multiple impact factors and delay propagation 极端降雨条件下道路运输弹性：综合多影响因素和延迟传播

IF 4.5 1区地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY

International journal of disaster risk reduction

Pub Date : 2026-02-15 Epub Date: 2026-01-21 DOI: 10.1016/j.ijdrr.2026.106024

Jie Liu , Zizhen Xu , Li Wan , Kristen MacAskill

Extreme rainfall significantly affects road transport networks through flood, reduced visibility, and traffic signal failures. However, existing research does not integrate all three of these impact factors, and triggered delay propagation across the network under rainfall conditions is not thoroughly captured in resilience assessments. This study achieves this by embedding these impacts within a dynamic traffic assignment framework based on the link transmission model, which enables a detailed representation of network-wide delay propagation under rainfall conditions. Network performance is evaluated using the average delay per time slice, and a dimensionless, delay-based resilience index is defined as the ratio of cumulative delay under normal conditions to that under an extreme-rainfall scenario. A case study of the large-scale road network in Greater London and its surrounding cities reveals that spillover delays (delay increase outside the rainfall-affected areas) constitute 0.42, 0.34, and 0.27 of the total delay increase for the 1-in-30, 1-in-100, and 1-in-1000-year rainfall scenarios, respectively. The corresponding mean resilience values are 0.79, 0.66, and 0.59, which means that cumulative delays under these scenarios are approximately 27 %, 52 %, and 69 % higher than under normal conditions. Moreover, attributes of the rainfall-affected areas—such as traffic demand, road length, area size, and high-risk flooded segment length—demonstrate significant correlation with network resilience, as indicated by the good model fit observed under the 1-in-30-year rainfall scenarios. The proposed framework captures the spatio-temporal evolution of delays and diagnoses congestion hotspots under extreme rainfall, thereby providing decision support for traffic management and emergency response in urban road networks.

极端降雨通过洪水、能见度降低和交通信号故障严重影响道路交通网络。然而，现有的研究并没有整合所有这三个影响因素，并且在恢复力评估中没有完全捕获降雨条件下触发的网络延迟传播。本研究通过将这些影响嵌入到基于链路传输模型的动态流量分配框架中来实现这一目标，该框架能够详细表示降雨条件下全网范围的延迟传播。使用每个时间片的平均延迟来评估网络性能，并将无量纲、基于延迟的弹性指标定义为正常条件下累积延迟与极端降雨情况下累积延迟的比值。对大伦敦及其周边城市大规模路网的案例研究表明，在30年一遇、100年一遇和1000年一遇的降雨情景下，溢出延迟（受降雨影响区域以外的延迟增加）分别占总延迟增加的0.42、0.34和0.27。相应的平均弹性值分别为0.79、0.66和0.59，这意味着在这些情景下的累积延迟比正常情况下大约高出27%、52%和69%。此外，受降雨影响区域的属性（如交通需求、道路长度、面积大小和高风险淹没路段长度）与网络恢复力具有显著相关性，这表明在30年1次降雨情景下观察到良好的模型拟合。该框架捕捉了极端降雨条件下交通延误的时空演变，并对拥堵热点进行了诊断，从而为城市道路网络的交通管理和应急响应提供决策支持。

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引用次数: 0

Understanding unmet needs during community wildfire recovery: A case study of smoke damage impacts after the 2021 Marshall Fire 了解社区野火恢复期间未满足的需求：2021年马歇尔火灾后烟雾损害影响的案例研究

IF 4.5 1区地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY

International journal of disaster risk reduction

Pub Date : 2026-02-15 Epub Date: 2026-01-13 DOI: 10.1016/j.ijdrr.2026.106017

Catrin M. Edgeley

Efforts to understand, assess, and address diversifying recovery needs have growing relevance as wildfires continue to impact communities. However, little is known about social experiences navigating gaps in assistance funding and support or “unmet needs” in post-fire spaces, particularly for indirect impacts like smoke damage. Determining how affected residents access available information and make decisions related to unmet needs can aid the development of resources and programs that support rapid identification of, and response to, emergent or undocumented impacts during recovery processes. This study explores household experiences with smoke damage as an unmet need during recovery following the 2021 Marshall Fire in Boulder County, Colorado, USA. Semi-structured interviews with residents and professionals who dealt with smoke damage revealed a wide spectrum of impacts. Decisions to act on smoke damage were influenced by risk perceptions and personal capacity to undertake self-guided recovery in the absence of a formalized process for navigating remediation. These experiences underscored a distinct absence of scientific and management expertise, legal protections or standards, and assistance related to smoke damage identification and remediation, catalyzing distrust in officials and ambiguity regarding whether smoke damaged homes could become safe again. Together, these conditions created cascading uncertainties for residents with smoke damaged homes that motivated long-term health concerns. Unmet needs after wildfire appeared to emerge because of misconceptions about impact severity, limited professional capacity, and adherence to rigid recovery structures that restrict professionals’ ability to identify and incorporate non-traditional impacts into existing processes. Findings informed suggestions for improving smoke damage recovery processes, inviting consideration of policy and more inclusive assistance to support recovery from indirect wildfire impacts.

随着野火对社区的持续影响，了解、评估和解决多样化恢复需求的努力变得越来越重要。然而，对于在援助资金和支持方面的差距或火灾后空间的“未满足需求”方面的社会经验知之甚少，特别是对于烟雾损害等间接影响。确定受影响的居民如何获取可用信息并做出与未满足需求相关的决策，有助于开发资源和项目，以支持在恢复过程中快速识别和响应紧急或未记录的影响。本研究探讨了2021年美国科罗拉多州博尔德县马歇尔火灾后恢复期间未满足需求的烟雾损害家庭经历。对处理烟雾损害的居民和专业人士进行的半结构化采访揭示了广泛的影响。在缺乏正式的导航补救程序的情况下，风险认知和个人自我引导的恢复能力会影响对烟雾损害采取行动的决定。这些经验突出表明，明显缺乏科学和管理专门知识、法律保护或标准，以及与烟雾损害识别和补救有关的援助，助长了对官员的不信任，对烟雾受损的房屋能否再次变得安全的模糊性。这些条件加在一起，给房屋被烟雾破坏的居民带来了一连串的不确定性，引发了长期的健康担忧。由于对影响严重程度的误解、有限的专业能力以及严格的恢复结构限制了专业人员识别非传统影响并将其纳入现有流程的能力，野火后出现了未满足的需求。调查结果提出了改善烟雾损害恢复过程的建议，邀请考虑政策和更具包容性的援助，以支持从间接野火影响中恢复。

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引用次数: 0

Understanding multi-hazard risk for U.S. coastal cities 了解美国沿海城市的多重灾害风险

IF 4.5 1区地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY

International journal of disaster risk reduction

Pub Date : 2026-02-15 Epub Date: 2026-01-21 DOI: 10.1016/j.ijdrr.2026.106023

Subash Poudel , Sunil Bista , Saurav Bhattarai , Sanjib Sharma , Rocky Talchabhadel

Coastal cities are threatened by a wide range of hazards, including sea-level rise, erosion, storm surges, flooding, and extreme weather events. In this study, we focus on understanding multi-hazard risk across twenty coastal cities in the United States by accounting for a range of potential hazards, socioeconomic conditions, adaptive capabilities, and infrastructure vulnerability. We employ a Multi-Hazard Risk Index by analyzing in situ ground observations, remotely sensed information, and re-analyzed datasets. We explore the interplay between hazards, exposure, and vulnerability. Across the selected twenty cities, our results show substantial variation in risk levels, ranging from 40 to 80. We notice that Gulf Coast cities (New Orleans and Miami) experience higher sea-level risk trends, while West Coast cities (Los Angeles and San Francisco) show comparatively lower exposure. Northeastern Atlantic cities (New York and Jersey City) face higher vulnerability, while Southeastern Atlantic cities, such as Charleston, show lower vulnerability, reflecting differences in susceptibility and adaptive capacity. These relative risk scores provide city planners and policymakers with important insights and a framework to assess their city's risk levels and make informed decisions for targeted resilience strategies.

沿海城市受到各种灾害的威胁，包括海平面上升、侵蚀、风暴潮、洪水和极端天气事件。在这项研究中，我们通过考虑一系列潜在危害、社会经济条件、适应能力和基础设施脆弱性，重点了解美国20个沿海城市的多灾害风险。我们通过分析现场地面观测、遥感信息和重新分析的数据集，采用了多灾害风险指数。我们探索危险、暴露和脆弱性之间的相互作用。在选定的20个城市中，我们的结果显示风险水平有很大的变化，从40到80不等。我们注意到，墨西哥湾沿岸城市（新奥尔良和迈阿密）经历了更高的海平面风险趋势，而西海岸城市（洛杉矶和旧金山）的风险相对较低。东北大西洋城市（纽约和泽西城）的脆弱性较高，东南大西洋城市（如查尔斯顿）的脆弱性较低，反映了易感性和适应能力的差异。这些相对风险评分为城市规划者和决策者提供了重要的见解和框架，以评估其城市的风险水平，并为有针对性的弹性战略做出明智的决策。

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引用次数: 0

The role of social infrastructure in community-based disaster resilience: A case study of the 2024 Noto Peninsula earthquake 社会基础设施在社区抗灾能力中的作用：以2024年诺托半岛地震为例

IF 4.5 1区地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY

International journal of disaster risk reduction

Pub Date : 2026-02-15 Epub Date: 2026-01-28 DOI: 10.1016/j.ijdrr.2026.106033

Mikio Ishiwatari , Shoko Nomura , Sakiko Kanbara , Shalini Matharage , Daniel Aldrich

Social infrastructure plays a critical role in disaster resilience through enhancing social capital. However, empirical evidence linking community-based preparedness activities at social infrastructure to disaster outcomes remains limited. This study examines how Kominkan (community learning centers) in Japan function as social infrastructure to strengthen community disaster resilience through using the 2024 Noto Peninsula earthquake as a case study. The disaster claimed 636 lives and damaged more than 165,000 homes. Qualitative research methods, including site visits to five Kominkan and document analysis, were employed. Communities with established disaster preparedness programs integrated into Kominkan activities demonstrated emergency response capabilities. It was found that pre-disaster preparedness activities translated directly into effective emergency response and supported recovery efforts. Kominkan leveraged pre-existing social networks, leadership, and local knowledge to coordinate rescue operations, manage evacuation shelters, and maintain social cohesion during recovery. The study found that creative integration of disaster preparedness into recreational and cultural activities, such as sports festivals and newsletters, sustained community engagement. Furthermore, embedded local knowledge enabled rapid, context-appropriate decision-making. The multi-functional nature of Kominkan—serving educational and cultural purposes during normal times while maintaining disaster readiness—proved essential.

社会基础设施通过增强社会资本，在抗灾能力方面发挥着关键作用。然而，将社会基础设施的社区备灾活动与灾害结果联系起来的经验证据仍然有限。本研究以2024年诺藤半岛地震为例，探讨日本社区学习中心作为社会基础设施如何增强社区抗灾能力。这场灾难造成636人死亡，超过16.5万所房屋受损。本研究采用质性研究方法，包括实地走访5个小民馆及文献分析。将已建立的备灾方案纳入Kominkan活动的社区展示了应急能力。结果发现，灾前准备活动直接转化为有效的应急反应和支持恢复工作。Kominkan利用已有的社会网络、领导力和当地知识来协调救援行动，管理疏散避难所，并在恢复期间保持社会凝聚力。该研究发现，将备灾创造性地整合到娱乐和文化活动中，如体育节和时事通讯，可以维持社区参与。此外，嵌入的本地知识使快速、适合上下文的决策成为可能。科米肯的多功能性质——在正常时期服务于教育和文化目的，同时保持备灾状态——证明是必不可少的。

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引用次数: 0

Multivariate logistic wind fragility functions of overhead distribution poles 架空配电杆的多变量logistic风脆弱性函数

IF 4.5 1区地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY

International journal of disaster risk reduction

Pub Date : 2026-02-15 Epub Date: 2026-01-07 DOI: 10.1016/j.ijdrr.2026.105996

Muneer Qudaisat , Alice Alipour

Overhead distribution lines are highly vulnerable to extreme wind events, yet fragility modeling remains challenging due to multiple interacting failure mechanisms and strong dependence on asset and site characteristics. This study presents a physics-informed and scalable framework for modeling multivariate wind-induced fragility of overhead utility networks. The approach integrates stochastic wind simulation, generated to match the Kaimal turbulence spectrum and validated using spectral error metrics, with finite-element–based structural analysis to capture governing failure mechanisms, including pole rupture, pole overturning, and conductor tensile breakage. Mode-specific multivariate logistic regression models are calibrated as parameterized, closed-form surrogate fragility functions based on measurable asset, geotechnical, and hazard descriptors, allowing for direct application without the need for repeated finite-element simulations or statistical analysis. The resulting models demonstrate strong and stable predictive performance across pole classes and failure modes, with AUC values exceeding 0.97. Joint failure probability is quantified using both independence-based aggregation and a copula-based formulation that captures dependence between competing failure modes, enabling consistent risk aggregation from individual spans to feeder-level applications. By combining physics-based modeling with computational efficiency and closed-form fragility expressions, the proposed framework supports practical, risk-informed screening and planning of power distribution infrastructure under extreme wind hazards.

架空配电线路极易受到极端风事件的影响，但由于多种相互作用的失效机制以及对资产和场地特征的强烈依赖，脆弱性建模仍然具有挑战性。本研究提出了一个物理信息和可扩展的框架，用于建模架空公用事业网络的多变量风致脆弱性。该方法将随机风模拟（生成用于匹配Kaimal湍流谱并使用谱误差度量进行验证）与基于有限元的结构分析相结合，以捕获控制失效机制，包括极断裂、极翻转和导体拉伸断裂。特定模式的多变量逻辑回归模型被校准为基于可测量资产、岩土和危害描述符的参数化、封闭形式的替代脆弱性函数，允许直接应用，而无需重复的有限元模拟或统计分析。结果表明，该模型在杆类和失效模式下具有强大而稳定的预测性能，AUC值超过0.97。采用基于独立性的聚合和基于copula的公式量化联合失效概率，该公式捕获竞争失效模式之间的依赖性，从而实现从单个跨度到馈线级应用的一致风险聚合。通过将基于物理的建模与计算效率和封闭形式的脆弱性表达式相结合，所提出的框架支持在极端风力灾害下对配电基础设施进行实用的、风险知情的筛选和规划。

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引用次数: 0

Strengthening community disaster resilience in uncertain times: a multi-level analysis of an Australian bushfire 在不确定时期加强社区抗灾能力：对澳大利亚森林大火的多层次分析

IF 4.5 1区地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY

International journal of disaster risk reduction

Pub Date : 2026-02-01 Epub Date: 2026-01-06 DOI: 10.1016/j.ijdrr.2026.106000

Matthew Daly , Tillmann Boehme , Neil Turner , James Aitken , Alan Green , Scott McKinnon , Christine Eriksen , Paul Cooper

This paper examines how community groups develop resilience over time through influencing and interacting with different societal levels throughout the phases of the disaster management cycle: prevention, preparation, response, and recovery. This provides an opportunity for a more insightful and holistic understanding of the factors involved in resilience. The macro/governmental level shapes governance of bushfire management and resources; the micro level reflects the actions of individual and households; while the meso level represents local community groups providing a bridge between the two through trust-based integration and collaboration.

This four-year longitudinal study used a complexity analysis framework to reveal latent tensions, as well as strong social relationships and community connections. These had implications for the emergent, local-specific responses to the bushfires, based on community attributes, needs and characteristics. The work reveals the importance of the meso level as a bridge between the governmental and individual levels, which can support tailoring, reconfiguring, and organising resources to strengthen resilience. These findings also have implications for shared responsibility, as community-based organisations may disagree with objectives at other levels, eroding resilience across the entire system. The analysis in this paper indicates that careful, flexible integration of the locally specific knowledge, meso level coordination, relationship-building, and transparent information-sharing that community-based organisation can provide, can be beneficial in effectively managing the multiple complexities of disasters.

本文考察了社区团体如何在灾害管理周期的各个阶段（预防、准备、响应和恢复）通过影响和互动不同的社会层面，随着时间的推移发展复原力。这为更深刻和全面地理解弹性所涉及的因素提供了机会。宏观/政府层面塑造了森林火灾管理和资源的治理；微观层面反映个人和家庭的行为；而中观层面则代表地方社区团体，通过基于信任的整合和协作在两者之间架起一座桥梁。这项为期四年的纵向研究使用了一个复杂性分析框架来揭示潜在的紧张关系，以及强大的社会关系和社区联系。这对基于社区属性、需求和特征的紧急、当地特定的森林火灾响应具有影响。这项工作揭示了中观层面作为政府和个人之间的桥梁的重要性，它可以支持裁剪、重新配置和组织资源以增强复原力。这些发现也对共同责任产生了影响，因为以社区为基础的组织可能不同意其他层面的目标，从而侵蚀了整个系统的弹性。本文的分析表明，以社区为基础的组织可以提供的地方特定知识、中尺度协调、关系建立和透明信息共享的谨慎、灵活的整合，可能有助于有效地管理灾害的多重复杂性。

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