International journal of disaster risk reduction最新文献_第10页

Earth observation informed modelling of flash floods 对地观测为山洪暴发的模拟提供了信息

IF 4.5 1区地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY

International journal of disaster risk reduction

Pub Date : 2026-01-01 Epub Date: 2025-12-24 DOI: 10.1016/j.ijdrr.2025.105977

C. Scott Watson , Maggie Creed , Januka Gyawali , Sameer Shadeed , Jamal Dabbeek , Divya L. Subedi , Rojina Haiju

More frequent extreme rainfall events in a changing climate increase the risk of flash flooding. However, the flood hazard modelling required to reduce disaster risk in urban environments is often limited by the availability of data required for model calibration and validation. Here, we use a historical flood event captured by 5 m resolution satellite imagery to inform future flood hazard assessments in the West Bank, Palestine. Flooding in January 2013 affected over 12,500 people and large areas of agricultural land. Vegetation loss and damage were captured using a normalised difference vegetation index (NDVI), which was used as a reference flood extent. The physics-based HEC-RAS flood model best reproduced this NDVI-derived inundation extent (F1 score = 0.76), although the FastFlood model was able to produce a similar inundation pattern (F1 score = 0.74) over 300 times faster. Simulated flood depths from both models were similar. Climate analysis revealed that the January 2013 rainfall corresponded to a historical return period of between 1 in 5 and 1 in 10 years. In comparison, a 1 in 100-year rainfall event (RX1day (maximum 1-day precipitation) of 148 mm) based on historical data (1985–2014) could increase by almost 40 % (to 205 mm) in the mid-future (2041–2060), which could cause 23 % (4 km²) greater inundation compared to the 2013 event. Although the patterns of future precipitation in the region are uncertain, our flood hazard maps can support urban planning and infrastructure development to manage storm water runoff.

在不断变化的气候中，更频繁的极端降雨事件增加了山洪暴发的风险。然而，减少城市环境灾害风险所需的洪水灾害建模往往受到模型校准和验证所需数据的可用性的限制。在这里，我们使用5米分辨率卫星图像捕获的历史洪水事件，为巴勒斯坦西岸未来的洪水灾害评估提供信息。2013年1月的洪水影响了12500多人和大片农田。植被损失和破坏采用归一化植被指数（NDVI）作为参考洪水范围。基于物理的HEC-RAS洪水模型最好地再现了ndvi衍生的淹没范围（F1得分= 0.76），尽管FastFlood模型能够产生类似的淹没模式（F1得分= 0.74）快300多倍。两个模型模拟的洪水深度相似。气候分析显示，2013年1月的降雨符合5年1次至10年1次的历史重现期。相比之下，基于历史数据（1985-2014）的百年一遇的降雨事件（RX1day（最大1天降水）为148毫米）在未来中期（2041-2060）可能增加近40%（达到205毫米），这可能导致比2013年事件增加23%（4平方公里）的淹没。尽管该地区未来降水的模式尚不确定，但我们的洪水灾害图可以为城市规划和基础设施建设提供支持，以管理暴雨径流。

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引用次数: 0

The fundamental causes of disaster vulnerability: Subsistence agricultural land loss in rural Malawi 易受灾害影响的根本原因：马拉维农村生存农业用地的丧失

IF 4.5 1区地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY

International journal of disaster risk reduction

Pub Date : 2026-01-01 Epub Date: 2025-12-01 DOI: 10.1016/j.ijdrr.2025.105943

S. Livne , S. Chibvunde , M. Mwendera , M.B. Aron , N. Davidovitch , F. Munyaneza , A. Rosenthal

Land access is one of the strongest predictors of disaster vulnerability for extreme weather events in rural, low-income environments. In Southern Africa, smallholder farmers face accelerating land loss from both slow-onset stressors, such as declining soil fertility and acute stressors such as cyclones. However, the complex mechanisms through which land loss perpetuates disaster vulnerability require a deeper examination of the lived experience of rural farmers.

In this study, we examined how agricultural land loss functions as a fundamental cause of disaster vulnerability in rural Malawi, drawing on Blaikie's land degradation framework and using qualitative methods. Between 2020 and 2024, we conducted in-depth interviews with 49 community members and 44 disaster responders across Neno and Chikwawa Districts, following Cyclones Idai, Ana, and Freddy, supplemented by participant observations and spatial analysis.

Our analysis revealed that land degradation operates simultaneously as symptom, cause, and result of broader socioeconomic vulnerabilities. Land degradation reflects pre-existing rural-urban inequalities driven by increasing demands for charcoal and agricultural products. When intersecting with cyclones, degraded land accelerates soil loss and forces displacement. Subsequently, land degradation becomes a result of harmful adaptation strategies, as communities turn to illegal charcoal production, creating feedback loops that increase future disaster risk.

Climate change disrupts traditional coping mechanisms by compressing temporal patterns of disaster and recovery, creating double exposure to acute and slow-onset stressors that intersect with existing socioeconomic disparities. The findings demonstrate that disaster vulnerability persists because current policies fail to address land access as a fundamental cause, leaving underlying inequalities in resource access unaddressed.

在农村和低收入环境中，土地获取是极端天气事件的灾害脆弱性最强有力的预测因素之一。在南部非洲，由于土壤肥力下降等缓慢发生的压力因素和飓风等急性压力因素，小农面临着加速的土地流失。然而，土地损失使灾害脆弱性持续存在的复杂机制需要对农村农民的生活经验进行更深入的研究。在本研究中，我们借鉴Blaikie的土地退化框架并使用定性方法，研究了农业土地流失如何成为马拉维农村灾害脆弱性的根本原因。在2020年至2024年期间，在飓风“伊代”、“安娜”和“弗雷迪”之后，我们对尼奥和奇克瓦瓦地区的49名社区成员和44名救灾人员进行了深入访谈，并辅以参与者观察和空间分析。我们的分析表明，土地退化同时是更广泛的社会经济脆弱性的症状、原因和结果。土地退化反映了对木炭和农产品需求不断增加所导致的城乡不平等。当与飓风相交时，退化的土地加速了土壤流失，迫使人们流离失所。随后，土地退化成为有害的适应策略的结果，因为社区转向非法木炭生产，形成了增加未来灾害风险的反馈循环。气候变化通过压缩灾害和恢复的时间模式，破坏了传统的应对机制，造成双重暴露于急性和缓慢发作的压力源，这些压力源与现有的社会经济差距相交。研究结果表明，灾害脆弱性仍然存在，因为目前的政策未能将土地获取作为根本原因，导致资源获取方面的潜在不平等问题得不到解决。

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引用次数: 0

A place-based framework to understand family disaster recovery 了解家庭灾难恢复的基于地点的框架

IF 4.5 1区地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY

International journal of disaster risk reduction

Pub Date : 2026-01-01 Epub Date: 2025-12-11 DOI: 10.1016/j.ijdrr.2025.105962

Gemma Sou

This paper develops a place based framework to explain how families recover from disasters. Using longitudinal patchwork ethnography in Puerto Rico following Hurricane Maria it proposes that family recovery is determined by a dynamic interplay between ‘etic facilitators’ (recovery assistance, public infrastructure, labour markets and social assistance, and market dynamics) and ‘emic facilitators’ (families' resources and subjective recovery priorities). The framework explains how families strategically adapt their emic capacities to shifting conditions in post-disasters contexts, determining heterogeneous recovery pathways and speeds. It also provides critical empirical insight into the recovery of intangibles within domestic life and gendered recovery burdens. This framework will be of interest to those seeking to understand how families navigate disasters and offers actionable guidance for designing more equitable, context-sensitive recovery policies.

本文开发了一个基于地点的框架来解释家庭如何从灾难中恢复。在飓风玛丽亚之后，在波多黎各使用纵向拼凑人种学，提出家庭恢复是由“内在促进因素”（恢复援助、公共基础设施、劳动力市场和社会援助以及市场动态）和“内在促进因素”（家庭资源和主观恢复优先事项）之间的动态相互作用决定的。该框架解释了家庭如何战略性地调整自身能力以适应灾后环境的变化，确定不同的恢复途径和速度。它还为家庭生活中无形资产的恢复和性别恢复负担提供了关键的经验见解。这一框架将有助于了解家庭如何应对灾害，并为设计更公平、对具体情况敏感的恢复政策提供可行的指导。

引用次数: 0

Coming together enabled adaptive capacity in responding to the Whakaari /White Island eruption: A grounded theory study 结合在一起使适应能力，以应对Whakaari /怀特岛喷发：一个接地理论研究

IF 4.5 1区地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY

International journal of disaster risk reduction

Pub Date : 2026-01-01 Epub Date: 2025-12-18 DOI: 10.1016/j.ijdrr.2025.105975

Adele Ferguson , Siri Wiig , Kim Ward , Rachael Parke

引用次数: 0

Objective versus subjective landslide risk: A case of Cache Creek Landslide in California 客观与主观滑坡风险：加利福尼亚州Cache Creek滑坡的一个案例

IF 4.5 1区地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY

International journal of disaster risk reduction

Pub Date : 2026-01-01 Epub Date: 2025-11-20 DOI: 10.1016/j.ijdrr.2025.105910

Timothy D. Stark , Kayley D. Estes , Roxane Cohen Silver , E. Alison Holman , Ben A. Leshchinsky , Farshid Vahedifard

Landslides pose a significant threat to infrastructure, communities, and human life throughout the world. A critical first step toward landslide risk reduction lies in risk awareness and proactive risk mitigation. However, in some cases, a lack of awareness or underestimation of landslide risks among communities and local stakeholders can lead to increased losses from potential landslide events. This study explores divergences between objective and subjective landslide risk assessments, focusing on the Cache Creek Landslide in Lake County, California. The landslide is in a region highly susceptible to various hazards. For the objective assessment of landslide risk, this study utilized imagery from Google Earth and publicly available digital elevation models to track the movements of the Cache Creek Landslide since 1953. Landslide movements over time were analyzed regarding cascading hazards such as heavy precipitation, post-wildfire conditions, and seismic activity. For subjective landslide risk assessment, a survey was conducted among adult residents throughout Lake County. Survey results revealed that most of the residential community surrounding Cache Creek is predominantly unaware of the landslide and the cascading hazards it poses. We argue that engineers and scientists must better convey disaster potential to the public to motivate community and governmental response. These differences in objective findings and subjective perceptions have significant implications, including potential delays in implementing necessary mitigation strategies and increased vulnerability of at-risk populations. Addressing these gaps is essential to enhance landslide risk awareness and foster proactive measures, ultimately reducing the devastating impacts of landslides in vulnerable communities.

山体滑坡对世界各地的基础设施、社区和人类生命构成重大威胁。减少滑坡风险的关键第一步在于风险意识和主动减轻风险。然而，在某些情况下，社区和地方利益相关者缺乏对滑坡风险的认识或低估可能导致潜在滑坡事件造成的损失增加。本研究探讨了客观和主观滑坡风险评估之间的差异，重点是加利福尼亚州湖县的Cache Creek滑坡。滑坡发生在各种灾害易发地区。为了客观评估滑坡风险，本研究利用谷歌Earth的图像和公开的数字高程模型来跟踪自1953年以来Cache Creek滑坡的运动。滑坡运动随着时间的推移分析了级联危害，如强降水、野火后条件和地震活动。为了进行主观滑坡风险评价，对莱克县的成年居民进行了调查。调查结果显示，卡什克里克周围的大多数居民对山体滑坡及其造成的连锁危害基本上一无所知。我们认为，工程师和科学家必须更好地向公众传达潜在的灾害，以激励社区和政府作出反应。这些客观调查结果和主观看法的差异产生了重大影响，包括在执行必要的缓解战略方面可能出现延误，以及高危人群的脆弱性增加。解决这些差距对于提高滑坡风险意识和采取积极措施至关重要，最终减少滑坡对脆弱社区的破坏性影响。

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引用次数: 0

A historical analysis of factors driving the daily prioritization of wildland fires in California 对推动加州野火每日优先次序的因素的历史分析

IF 4.5 1区地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY

International journal of disaster risk reduction

Pub Date : 2026-01-01 Epub Date: 2025-12-15 DOI: 10.1016/j.ijdrr.2025.105967

Dung Nguyen , Erin J. Belval , Yu Wei , David E. Calkin

During periods of heightened wildland fire activity in the United States, multiagency coordinating groups must prioritize among multiple on-going fires to allocate scarce suppression resources. While many studies have explored factors that influence wildfire suppression expenditures and personnel allocation, understanding the specific factors that affect daily wildfire prioritization has remained unexplored. In this study, we first examine wildfire reporting and ranking processes across different regions of the United States to provide insight into criteria used for fire ranking. We then focus on examining the 12 criteria used for ranking fires daily by California's multiagency coordination group. We developed a computer program to replicate the California prioritization process and found that fire rankings generated by this program align well with the historical rankings, indicating close adherence of California's fire managers to their ranking rules. A correlation analysis revealed weak correlations among the 12 criteria, suggesting that no criterion should serve as a proxy for another during fire priority evaluations. We further applied a Random Forest machine learning model, which identified threats and damage to structures, fire size, and evacuations as the most impactful criteria in determining fire priority. Our findings can benefit wildfire decision makers by providing clear insights into the existing wildfire priority assessment process, so that adjustments to the process can be made for better management outcomes. Policymakers can also leverage these insights to develop evidence-based fire management policies, regulations, and practices that promote more efficient responses to fire risks while fostering greater public trust in fire management efforts.

在美国野火活动加剧的时期，多机构协调小组必须在多个正在进行的火灾中优先分配稀缺的灭火资源。虽然许多研究已经探索了影响野火扑灭支出和人员分配的因素，但了解影响日常野火优先级的具体因素仍未得到探索。在本研究中，我们首先考察了美国不同地区的野火报告和排名过程，以深入了解用于火灾排名的标准。然后，我们将重点研究加州多机构协调小组用于每日火灾排名的12个标准。我们开发了一个计算机程序来复制加州的优先级排序过程，发现该程序生成的火灾排名与历史排名非常吻合，表明加州的火灾管理人员严格遵守他们的排名规则。相关分析显示，12个标准之间的相关性较弱，这表明在火灾优先级评估中，没有一个标准可以作为另一个标准的代理。我们进一步应用了随机森林机器学习模型，该模型确定了对建筑物的威胁和破坏、火灾规模和疏散作为确定火灾优先级的最有效标准。我们的研究结果可以为野火决策者提供对现有野火优先级评估过程的清晰见解，从而对该过程进行调整，以获得更好的管理结果。决策者还可以利用这些见解来制定基于证据的火灾管理政策、法规和实践，以促进更有效地应对火灾风险，同时增强公众对火灾管理工作的信任。

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引用次数: 0

Prioritisation Recommendation Mapping (PrioReMap): A method for supporting relief coordination in flood disaster response 优先排序推荐映射（PrioReMap）：一种支持洪水救灾协调的方法

IF 4.5 1区地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY

International journal of disaster risk reduction

Pub Date : 2026-01-01 Epub Date: 2025-12-03 DOI: 10.1016/j.ijdrr.2025.105949

Moritz Schneider , Lukas Halekotte , Tina Comes , Frank Fiedrich

To effectively coordinate the response to a flood disaster, decision-makers have to prioritise areas that are in most urgent need of assistance. This prioritisation often has to be carried out under time pressure and on the basis of incomplete information, creating a high cognitive load for decision-makers. Methods that integrate Bayesian networks into GIS to draw spatial inference can inform this prioritisation process. However, existing approaches are not equipped to address the time pressure and unclear information-scape that is typical for a flood disaster. In this work, we present a novel spatial inference method for area prioritisation that is designed to address these time and information constraints. The core of this method is a GIS-informed Bayesian network, integrated into an expected loss framework, that can be set up during the preparation phase. The method can then quickly provide area prioritisation recommendations for disaster relief, which has the potential to support decisions-makers during the response phase. In this way, our method provides a means of shifting some of the most time-consuming aspects of the decision-making process from the time-critical disaster response phase to the less critical preparation phase. To illustrate how our method can support rapid and transparent area prioritisation, we present a case study of an extreme flood scenario in Cologne, Germany.

为了有效地协调对洪水灾害的反应，决策者必须优先考虑最迫切需要援助的地区。这种优先排序通常必须在时间压力和不完整信息的基础上进行，这给决策者带来了很高的认知负荷。将贝叶斯网络集成到GIS中以绘制空间推理的方法可以通知此优先级过程。然而，现有的方法无法解决洪水灾害中典型的时间压力和信息不清晰的问题。在这项工作中，我们提出了一种新的区域优先级空间推理方法，旨在解决这些时间和信息限制。该方法的核心是一个基于gis的贝叶斯网络，该网络集成到一个可在准备阶段建立的预期损失框架中。然后，该方法可以迅速为救灾提供地区优先级建议，这有可能在响应阶段支持决策者。通过这种方式，我们的方法提供了一种将决策过程中一些最耗时的方面从时间关键的灾难响应阶段转移到不那么关键的准备阶段的方法。为了说明我们的方法如何支持快速和透明的区域优先排序，我们提出了德国科隆极端洪水情景的案例研究。

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引用次数: 0

A large-scale seismic risk approach accounting for local site effects and modelling of building exposure based on open-access datasets 基于开放获取数据集的考虑局部场地效应和建筑暴露建模的大规模地震风险方法

IF 4.5 1区地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY

International journal of disaster risk reduction

Pub Date : 2026-01-01 Epub Date: 2025-11-27 DOI: 10.1016/j.ijdrr.2025.105936

Gaetano Falcone , Angela Stefania Bergantino , Mario Intini , Gianfranco Urciuoli , Anna d’Onofrio

This study proposes an enhanced macroseismic framework for regional seismic risk assessment that accounts for litho-stratigraphic site effects and refines building exposure modelling using open-access spatial datasets. The methodology is applied to the Campania region in southern Italy, combining official census data with high-resolution building height estimates to disaggregate structural typologies into three classes: low-rise (1-3 storeys), mid-rise (4-7 storeys), and high-rise (≥ 8 storeys), associated with distinct vibration period ranges. In addition, the year of construction and the conservation status of the buildings are considered to refine the vulnerability assessment. Seismic hazard is quantified through period-dependent spectral acceleration, which is then converted to macroseismic intensity. The results reveal significant spatial variability in damage scenarios and repair costs, driven by both structural typology and site conditions. Metropolitan areas exhibit the highest vulnerability and economic impact, with site amplification increasing estimated regional repair costs by over 60 %. The proposed GIS-compatible methodology offers a replicable and policy-relevant tool for supporting seismic risk mitigation, urban resilience planning, and targeted retrofitting strategies.

本研究提出了一个用于区域地震风险评估的增强宏观地震框架，该框架考虑了岩石地层场地效应，并使用开放获取的空间数据集改进了建筑物暴露模型。该方法应用于意大利南部的坎帕尼亚地区，将官方人口普查数据与高分辨率建筑高度估计相结合，将结构类型分为三类：低层（1-3层）、中层（4-7层）和高层（≥8层），与不同的振动周期范围相关。此外，还考虑了建筑的建造年份和建筑物的保护状况，以完善脆弱性评估。通过周期相关的频谱加速度来量化地震危险性，然后将其转换为大震烈度。研究结果显示，受结构类型和场地条件的影响，损坏场景和修复成本在空间上存在显著差异。大城市地区表现出最高的脆弱性和经济影响，场地扩大使估计的区域修复成本增加了60%以上。拟议的与地理信息系统兼容的方法为支持减轻地震风险、城市复原力规划和有针对性的改造战略提供了可复制且与政策相关的工具。

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引用次数: 0

Portfolio-scale seismic fragility of RC bridge columns with series-distributed neural networks 基于串联分布神经网络的组合尺度RC桥柱地震易损性研究

IF 4.5 1区地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY

International journal of disaster risk reduction

Pub Date : 2026-01-01 Epub Date: 2025-12-07 DOI: 10.1016/j.ijdrr.2025.105955

Hoang Vinh Nguyen , Hoang Nam Phan , Duy Hoa Pham , Gianluca Quinci , Fabrizio Paolacci

This paper proposes a novel series-distributed artificial neural network framework for rapidly constructing seismic fragility curves of reinforced-concrete (RC) bridge columns at markedly reduced computational cost. Three coupled surrogate models are trained on datasets generated from nonlinear time-history and pushover analyses of RC piers with randomly sampled geometric and material properties subjected to hazard-consistent ground motions. The first network learns correlations among a reduced set of efficient ground-motion intensity measures (IMs), the second predicts drift demand from IMs and modelling parameters, and the third provides drift capacities for multiple damage states directly from capacity-curve information, thereby incorporating epistemic uncertainty in structural capacity. The trained surrogates are embedded in a Monte Carlo simulation scheme to estimate, in a largely non-parametric manner, the probability that drift demand exceeds capacity at each IM level. A case study on a portfolio of simply supported bridges in the Da Nang area, including selected bridges along National Highway 1A, demonstrates that the framework reproduces benchmark fragility curves from nonlinear analyses while achieving substantial reductions in analysis time. The results highlight systematic differences between rectangular and circular piers and quantify the impact of relaxing internal lognormal assumptions relative to traditional cloud-based fragility derivation. The proposed approach is implementation-ready, which relies on standard structural and ground-motion descriptors, delivers conventional fragility parameters, and is readily scalable to portfolio- and network-level seismic risk assessments and screening.

本文提出了一种新的串联分布式人工神经网络框架，用于快速构建钢筋混凝土桥柱地震易损性曲线，大大降低了计算成本。三个耦合代理模型是在非线性时程数据集上训练的，这些数据集是随机抽样的钢筋混凝土桥墩在危险一致的地面运动下的几何和材料特性。第一个网络学习简化的有效地震动强度测量（IMs）之间的相关性，第二个网络从IMs和建模参数中预测漂移需求，第三个网络直接从能力曲线信息中提供多种损伤状态的漂移能力，从而结合结构能力的认知不确定性。经过训练的代理被嵌入到蒙特卡罗模拟方案中，以非参数的方式估计漂移需求超过每个IM水平容量的概率。对岘港地区简支桥组合（包括1A国道沿线选定的桥梁）的案例研究表明，该框架从非线性分析中再现了基准脆弱性曲线，同时大大减少了分析时间。结果突出了矩形墩和圆形墩之间的系统差异，并量化了相对于传统的基于云的脆弱性推导放宽内部对数正态假设的影响。该方法依赖于标准的结构和地面运动描述符，提供常规的易感性参数，并且易于扩展到投资组合和网络级地震风险评估和筛选。

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引用次数: 0

Quantifying uncertainty in tropical cyclone risk under present and future climates: Implication for disaster risk management in the Philippines 量化当前和未来气候下热带气旋风险的不确定性：对菲律宾灾害风险管理的影响

IF 4.5 1区地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY

International journal of disaster risk reduction

Pub Date : 2026-01-01 Epub Date: 2025-12-15 DOI: 10.1016/j.ijdrr.2025.105968

Wei Jian , Pane Stojanovski , Edmond Yatman Lo

Tropical cyclones (TCs) pose a growing risk to coastal communities in Southeast Asia due to climate change and rapid urbanisation. This study focuses on the National Capital Region of the Philippines, a densely populated and economically vital area. We employ a probabilistic TC wind risk model that integrates high-resolution exposure data and sector-specific vulnerability functions to quantify uncertainty in TC risk under present and future climate conditions. The analysis uses five synthetic TC ensembles: one representing the present climate and four representing future climates driven by different global climate models (GCMs). Each ensemble comprises 10 sets of 1000-year simulations. We systematically assess uncertainty in key risk metrics arising from stochastic variability, vulnerability modelling, and inter-model differences in climate projections. Our results show that TC risk uncertainty attribution is highly sensitive to the composition of the TC ensemble. Vulnerability model uncertainty generally dominates risk variability under the present climate, while climate model choice becomes a comparable source of uncertainty for future risks. However, when TC ensembles contain rare, high-impact outlier sets that substantially deviate from expected stochastic variability, their contribution can exceed either vulnerability or climate model uncertainties, obscuring the projected increase in TC risks observed in more stochastically representative ensembles. These findings highlight the importance of systematically quantifying uncertainty in TC risk modelling, particularly for areas with highly concentrated exposure where small changes in TC tracks can cause considerable shifts in losses. Our methodology supports more transparent and robust risk assessment and communication, with applicability to other TC-prone regions.

由于气候变化和快速城市化，热带气旋（tc）对东南亚沿海社区构成越来越大的风险。本研究的重点是菲律宾的国家首都地区，这是一个人口稠密和经济重要的地区。我们采用了一个概率TC风风险模型，该模型集成了高分辨率暴露数据和特定行业脆弱性函数，以量化当前和未来气候条件下TC风险的不确定性。该分析使用了5个合成的TC集合：1个代表当前气候，4个代表由不同全球气候模式（GCMs）驱动的未来气候。每个集合包括10组1000年的模拟。我们系统地评估了由随机变率、脆弱性建模和气候预测模式间差异引起的关键风险指标的不确定性。研究结果表明，碳汇风险不确定性归因对碳汇集合的组成高度敏感。在当前气候条件下，脆弱性模式的不确定性通常主导着风险变率，而气候模式的选择则成为未来风险的一个可比较的不确定性来源。然而，当温度组合包含罕见的、高影响的离群值，这些离群值大大偏离预期的随机变率时，它们的贡献可能超过脆弱性或气候模式的不确定性，从而模糊了在更具随机代表性的组合中观察到的预估的温度风险增加。这些发现强调了系统地量化TC风险建模中的不确定性的重要性，特别是对于高度集中暴露的地区，TC轨迹的微小变化可能导致相当大的损失变化。我们的方法支持更透明、更有力的风险评估和沟通，适用于其他易发生恐怖袭击的地区。

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引用次数: 0