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

Clear or compliant? The tension between regulatory requirements and public comprehension in boil water advisories 清晰还是顺从？监管要求和公众对煮沸水的理解之间的紧张关系

IF 4.5 1区地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY

International journal of disaster risk reduction

Pub Date : 2025-12-27 DOI: 10.1016/j.ijdrr.2025.105982

Kyudong Kim , Euijin Yang , Keri K. Stephens , Mir Rabby , Roselia Mendez Murillo , Matthew S. McGlone , Sergio Castellanos , Kasey M. Faust

Risk communications should provide clear messages to the public so people can take appropriate actions to protect their health and safety. Boil Water Advisories (BWAs), for instance, help safeguard communities from water quality issues. This study evaluates BWA effectiveness by analyzing 85 advisories from four Texas metropolitan areas, collected from press releases and social media platforms (e.g., Facebook). The evaluation focused on two main aspects: content compliance, to assess if the content meets state-wide requirements; and readability, to determine if the general public can easily understand the information. The results show that while press releases generally include essential content by adhering to the Texas Commission for Environmental Quality (TCEQ) guidelines, social media posts often lack essential information, such as mandatory language for the severity of the water contamination, action items, and contact details for real-time updates. Water utilities face challenges balancing regulatory compliance with effective public guidance. They can benefit from adapting communications across different platforms while maintaining appropriate reading levels for diverse audiences. Specifically, while press releases can meet regulatory standards with comprehensive content, their higher reading difficulty often makes them inaccessible to many audiences. Social media requires brief communication that cannot easily be compliant, but those messages are easier to understand. This study offers insights to help utilities enhance multi-channel BWA communication strategies and suggests regulatory agencies develop more realistic guidelines that acknowledge communication platform constraints while ensuring effective public response during water-related emergencies.

风险沟通应向公众提供明确的信息，使人们能够采取适当的行动来保护自己的健康和安全。例如，沸水警报（BWAs）有助于保护社区免受水质问题的影响。本研究通过分析来自德克萨斯州四个大都市地区的85份咨询报告来评估BWA的有效性，这些报告收集自新闻稿和社交媒体平台（如Facebook）。评估主要集中在两个方面：内容合规性，评估内容是否符合全州要求；而可读性，则决定一般公众是否能容易地理解信息。结果表明，虽然新闻稿通常包括遵守德克萨斯州环境质量委员会（TCEQ）指导方针的基本内容，但社交媒体帖子往往缺乏基本信息，例如对水污染严重程度的强制性语言、行动项目和实时更新的联系方式。水务公司面临平衡法规遵从与有效公众指导的挑战。他们可以从适应不同平台的通信中受益，同时为不同的受众保持适当的阅读水平。具体来说，虽然新闻稿内容全面，符合监管标准，但其较高的阅读难度往往使许多受众无法阅读。社交媒体要求简短的交流，不容易被顺从，但这些信息更容易理解。本研究为公用事业公司加强多渠道BWA通信策略提供了见解，并建议监管机构制定更现实的指导方针，以承认通信平台的限制，同时确保公众在与水有关的紧急情况下有效响应。

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引用次数: 0

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 : 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

Identifying climatic hazard importance factors for bridges using expert-based fuzzy analytic hierarchy process 基于专家的模糊层次分析法识别桥梁气候灾害重要因素

IF 4.5 1区地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY

International journal of disaster risk reduction

Pub Date : 2025-12-24 DOI: 10.1016/j.ijdrr.2025.105971

Shereen Altamimi , Liping Fang , Lamya Amleh

Bridges are critical components of ground transportation infrastructure, yet current design provisions remain rooted in historical climate assumptions that diverge sharply from projected future conditions. As climate change progresses, particularly under higher-emission scenarios such as RCP8.5, infrastructure managers require a systematic and quantitative basis for identifying hazards that pose significant risk to bridges and for prioritizing adaptation measures. This study develops and validates an adaptive fuzzy analytic hierarchy process (FAHP) protocol for deriving climatic hazard importance factors (CHIFs) across a three-tier hierarchy that links four hazards (temperature, wind, rainfall, and ice accretion) to bridge systems and components. Expert judgment was elicited from structural engineers, researchers, and asset managers through a fuzzy pairwise comparison method. For a representative simply supported concrete bridge, rainfall emerged as the most critical hazard (CHIF = 0.35), followed by temperature (0.26), wind (0.22), and ice accretion (0.17). The protocol produces CHIFs not only at the overall bridge level but also at the system and component levels, enabling targeted adaptation strategies—for example, drainage improvements for decks (CHIF = 0.48) and cold-weather sealing for expansion joints (CHIF = 0.34). The methodology offers four key contributions: (1) a replicable, uncertainty-aware framework for multi-hazard weighting applicable to any geographic context, (2) quantitative inputs for revising Canadian Highway Bridge Design Code load combinations, (3) decision support for prioritizing the rehabilitation of climate-vulnerable components, and (4) network-level asset ranking to guide limited adaptation budgets. By translating expert insight into scale-ready metrics, the protocol bridges the gap between climate projections and engineering decision-making.

桥梁是地面交通基础设施的重要组成部分，但目前的设计条款仍然植根于历史气候假设，与预测的未来条件大相径庭。随着气候变化的进展，特别是在RCP8.5等高排放情景下，基础设施管理者需要一个系统和定量的基础来识别对桥梁构成重大风险的危害，并确定适应措施的优先次序。本研究开发并验证了一种自适应模糊层次分析法（FAHP）方案，用于跨三层层次推导气候危害重要因子（CHIFs），该三层层次将四种危害（温度、风、降雨和冰积聚）与桥梁系统和组件联系起来。通过模糊两两比较的方法，从结构工程师、研究人员和资产管理者中获得专家判断。对于具有代表性的简支混凝土桥，降雨是最关键的危害（CHIF = 0.35），其次是温度（0.26），风（0.22）和冰积聚（0.17）。该方案不仅在整个桥梁层面，而且在系统和组件层面产生CHIF，从而实现有针对性的适应策略，例如，甲板的排水改善（CHIF = 0.48）和伸缩缝的寒冷天气密封（CHIF = 0.34）。该方法提供了四个关键贡献：(1)适用于任何地理环境的可复制的、具有不确定性意识的多灾害加权框架；(2)为修订加拿大公路桥梁设计规范荷载组合提供定量输入；(3)为气候脆弱部件的优先修复提供决策支持；(4)为有限的适应预算提供网络级资产排名指导。通过将专家的见解转化为规模就绪的指标，该协议弥合了气候预测和工程决策之间的差距。

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引用次数: 0

Harnessing social sensing for real-time flood event reconstruction: A digital autopsy of the 2024 Valencia DANA 利用社会传感进行实时洪水事件重建：2024年瓦伦西亚DANA的数字尸检

IF 4.5 1区地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY

International journal of disaster risk reduction

Pub Date : 2025-12-24 DOI: 10.1016/j.ijdrr.2025.105966

José Giner Pérez de Lucia , Adrián López-Ballesteros , Julio Fernández-Pedauyé , Javier Senent-Aparicio , José M. Cecilia

Extreme rainfall and flash-flood events in the Western Mediterranean pose persistent challenges for real-time monitoring and emergency response. Traditional hydrometeorological networks often provide limited spatiotemporal coverage during rapidly evolving events, leading to localized blind spots. This study reconstructs the impacts of the October 2024 catastrophic floods in Valencia using more than 156,000 geolocated messages from X (formerly Twitter) as a form of social sensing. These citizen-generated data were integrated with hydrological and hydraulic modeling to contextualize reported flood dynamics and response gaps. Advanced Natural Language Processing (NLP) techniques were applied to extract spatiotemporal patterns of public perception, emergency reactions, and infrastructure disruptions. In addition, a Retrieval-Augmented Generation (RAG) system was implemented to transform unstructured messages into structured event summaries, providing actionable insights during the disaster window. The analysis revealed a clear temporal alignment between social media activity and flood progression, with online reporting peaking shortly after critical impact thresholds. Cross-validation with hydrological simulations confirmed the potential of social sensing to detect localized effects often missed by conventional monitoring, while also exposing the limitations of relying solely on proxy digital traces. Overall, the Valencia case demonstrates the feasibility of integrating human-sensed information with physically based models to enhance situational awareness and support adaptive, data-driven disaster risk reduction in urban environments.

西地中海的极端降雨和突发洪水事件对实时监测和应急反应构成了持续的挑战。传统的水文气象网络在快速演变的事件中往往提供有限的时空覆盖，导致局部盲点。这项研究使用来自X（以前的Twitter）的超过156,000条地理定位信息作为社会感知的一种形式，重建了2024年10月瓦伦西亚灾难性洪水的影响。这些市民生成的数据与水文和水力建模相结合，以了解报告的洪水动态和响应差距。先进的自然语言处理（NLP）技术被应用于提取公众感知、紧急反应和基础设施中断的时空模式。此外，还实现了检索增强生成（retrieve - augmented Generation， RAG）系统，将非结构化消息转换为结构化事件摘要，在灾难窗口期间提供可操作的见解。分析显示，社交媒体活动与洪水进展之间存在明显的时间一致性，在线报道在关键影响阈值后不久达到峰值。与水文模拟的交叉验证证实了社会传感检测常规监测经常错过的局部效应的潜力，同时也暴露了仅依赖代理数字痕迹的局限性。总的来说，瓦伦西亚案例证明了将人类感知信息与基于物理的模型相结合的可行性，以增强态势感知，并支持城市环境中自适应的、数据驱动的灾害风险降低。

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引用次数: 0

Revealing growing and disparate vulnerability in the U.S. power system: A spatiotemporal analysis of nationwide outages from 2014 to 2023 揭示美国电力系统日益增长和不同的脆弱性：2014年至2023年全国停电的时空分析

IF 4.5 1区地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY

International journal of disaster risk reduction

Pub Date : 2025-12-23 DOI: 10.1016/j.ijdrr.2025.105980

Bo Li , Junwei Ma , Olufemi A. Omitaomu , Ali Mostafavi

Power systems are increasingly challenged by a range of external and internal threats that undermine their reliability and resilience. Power system vulnerability, the proneness of the power system to disruptions, can be empirically characterized through the observable manifestations of power outages. However, existing research remains limited in spatial coverage, temporal scope, and analytical consistency, and lacks comprehensive, longitudinal, large-scale, and fine-grained analyses to capture the spatiotemporal dynamics of vulnerability. Recognizing this, we analyzed 179,053,397 county-level power outage records with a 15-min interval across 3,022 US counties during 2014–2023. Applying a framework encompassing frequency, duration and intensity, we systematically assessed the dynamics of U.S. power system vulnerability. Results reveal an escalating trend over the past decade, with outages becoming more frequent, prolonged, and intense. Nationally, cumulative customer outage time reached 7.86 billion customer-hours, with a median of 0.64 million per-county over the past decade, underscoring significant service disruptions. Coastal regions, especially in California, Florida, and New Jersey, experienced more frequent and longer outages, while some inland areas exhibited higher outage intensity relative to their customer base. Moreover, we observed a strengthening association between social vulnerability and outage metrics over time, indicating that counties with higher social vulnerability experienced more severe and frequent outages, creating “dual-burden” regions where social disadvantage and infrastructural vulnerability compound each other. These findings provide a nationwide and longitudinal characterization of power system vulnerability in the U.S., offering empirical insights to inform practitioners in prioritizing investments for a more reliable, resilient and equitable energy infrastructure.

电力系统越来越多地受到一系列外部和内部威胁的挑战，这些威胁破坏了电力系统的可靠性和弹性。电力系统的脆弱性，即电力系统对中断的倾向性，可以通过可观察到的停电现象来经验地表征。然而，现有研究在空间覆盖、时间范围、分析一致性等方面存在不足，缺乏全面、纵向、大尺度、细粒度的脆弱性时空动态分析。认识到这一点，我们分析了2014-2023年美国3022个县的179,053,397次县级停电记录，间隔15分钟。应用一个包含频率、持续时间和强度的框架，我们系统地评估了美国电力系统脆弱性的动态。结果显示，在过去十年中，中断变得更加频繁、持续时间更长、强度更大。在全国范围内，累计客户中断时间达到78.6亿客户小时，在过去十年中，每个县的平均中断时间为64万小时，凸显了严重的服务中断。沿海地区，特别是加利福尼亚州、佛罗里达州和新泽西州，经历了更频繁和更长时间的停电，而一些内陆地区相对于其客户群表现出更高的停电强度。此外，我们还观察到，随着时间的推移，社会脆弱性和停电指标之间的联系越来越强，这表明社会脆弱性较高的国家经历了更严重、更频繁的停电，形成了社会劣势和基础设施脆弱性相互复合的“双重负担”地区。这些发现提供了美国电力系统脆弱性的全国性和纵向特征，为从业者提供了经验见解，为更可靠、更有弹性和更公平的能源基础设施的优先投资提供了信息。

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引用次数: 0

Citizen participation in flood risk management: Usability Insights from the RiverCure Portal 洪水风险管理中的公民参与：来自RiverCure门户网站的可用性见解

IF 4.5 1区地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY

International journal of disaster risk reduction

Pub Date : 2025-12-22 DOI: 10.1016/j.ijdrr.2025.105961

Mafalda Cravo , Jacinto Estima , Alberto Rodrigues da Silva , João Matos , Ana M. Ricardo , Rui M.L. Ferreira

Extreme weather events have become increasingly frequent and severe, with rain-induced floods and inundations remaining the deadliest form of natural disaster. Mitigating their impacts requires tools that support all phases of the flood risk management cycle. The RiverCure Portal (RCP) is a web-based platform with geographic information system capabilities, that integrates the definition of geographic contexts with sensor data and hydrodynamic modeling tools, enabling decision-makers and researchers to assess and respond to flood risks. This paper presents and evaluates an extension to the RCP that incorporates citizen science features, enabling the contribution of field-collected data related to extreme weather events, and promoting citizen education and engagement. A focus group provided formative feedback during development, informing iterative improvements. The final version of the RCP was evaluated through a usability study involving 15 participants, achieving a System Usability Scale score of 84.67 out of 100, indicating high perceived usability.

极端天气事件变得越来越频繁和严重，降雨引发的洪水和淹没仍然是最致命的自然灾害形式。减轻其影响需要支持洪水风险管理周期各个阶段的工具。RiverCure Portal （RCP）是一个具有地理信息系统功能的基于网络的平台，它将地理环境的定义与传感器数据和水动力学建模工具集成在一起，使决策者和研究人员能够评估和应对洪水风险。本文提出并评估了RCP的扩展，该扩展结合了公民科学特征，使与极端天气事件相关的现场收集数据能够做出贡献，并促进公民教育和参与。焦点小组在开发期间提供形成性反馈，告知迭代改进。RCP的最终版本通过一项涉及15名参与者的可用性研究来评估，达到了系统可用性量表的84.67分（满分100分），表明高感知可用性。

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引用次数: 0

Short- and long-term impacts of relocation and buffer zones: the Indian Ocean Tsunami 2004 to 2024 搬迁和缓冲区的短期和长期影响：2004年至2024年印度洋海啸

IF 4.5 1区地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY

International journal of disaster risk reduction

Pub Date : 2025-12-20 DOI: 10.1016/j.ijdrr.2025.105974

Joern Birkmann , Nishara Fernando , Ali Jamshed , Hannes Lauer , Riyanti Djalante

The effectiveness and feasibility of different risk reduction and adaptation measures are increasingly discussed, however, limited assessments exist on how measures, such as buffer zones and relocation, are perceived in the short- and long-term. The Indian Ocean tsunami in 2004 is an important case to explore how coastal protection measures were perceived after the event and today, 20 years later. The paper examines how post-disaster relocation and buffer zone policies influenced people's living conditions over 2 decades. Firstly, we assess global patterns of displacement due to natural hazards. The global analysis serves to situate the Sri Lankan case within the broader patterns of disaster-related mobility and displacement. Secondly, we explore short and long-term impacts of relocation and buffer zone policies in Sri Lanka and assess the living conditions and perceptions of these risk reduction and adaptation measures. Thirdly, we examine factors that influence the decision to stay or leave the relocation site, also conducting regression analysis. Fourthly, we propose policy-relevant recommendations in order to improve relocation projects and buffer zone policies. Important factors that influence people's decision to stay or leave the relocation site encompass the access to land, educational infrastructures, transport options and access to markets or jobs. While many institutions involved in designing and implementing buffer zone and relocation policies view these measures as one-time interventions that primarily need a careful planning in the beginning, we rather argue that challenges associated with relocation and buffer zones change over time and thus require continued monitoring and learning.

不同的风险降低和适应措施的有效性和可行性正在得到越来越多的讨论，然而，关于如何在短期和长期内感知缓冲区和重新安置等措施的评估有限。2004年的印度洋海啸是一个重要的案例，可以用来探讨海啸发生后以及20年后的今天人们是如何看待海岸保护措施的。本文考察了20多年来灾后搬迁和缓冲区政策对人们生活条件的影响。首先，我们评估了自然灾害造成的全球流离失所模式。全球分析有助于将斯里兰卡的情况置于与灾害有关的流动和流离失所的更广泛格局中。其次，我们探讨了斯里兰卡搬迁和缓冲区政策的短期和长期影响，并评估了生活条件和对这些风险降低和适应措施的看法。再次，我们考察了影响搬迁决策的因素，并进行了回归分析。第四，提出政策相关建议，以完善移民安置项目和缓冲地带政策。影响人们决定留在或离开搬迁地点的重要因素包括获得土地、教育基础设施、交通选择以及进入市场或就业的机会。虽然许多参与设计和实施缓冲区和搬迁政策的机构将这些措施视为一次性干预措施，主要需要在开始时进行仔细的规划，但我们更愿意认为，与搬迁和缓冲区相关的挑战会随着时间的推移而变化，因此需要持续的监测和学习。

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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 : 2025-12-18 DOI: 10.1016/j.ijdrr.2025.105975

Adele Ferguson , Siri Wiig , Kim Ward , Rachael Parke

引用次数: 0

Shaping local disaster risk governance through multi-stakeholder collaboration: Insights from the public-private-civil partnership approach - Application to the case studies of the municipality of Egaleo (Greece) and Centro Region (Portugal) 通过多方利益相关者合作塑造地方灾害风险治理：来自公私伙伴关系方法的见解-应用于Egaleo市（希腊）和Centro地区（葡萄牙）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 : 2025-12-18 DOI: 10.1016/j.ijdrr.2025.105973

Juliette Rimlinger , Alexandra Jaumouillé , Catherine Freissinet , João Lutas Craveiro , Ana Catarina Zózimo , Manuel M. Oliveira , Maria Manuel Cruz , Evangelia Bakogianni , Dimitrios Tzempelikos , Evrydiki Pavlidi , Athanasios Sfetsos

In the face of growing climate-related risks, traditional top-down models of risk governance increasingly appear inadequate for enabling effective and inclusive local resilience planning. The public-private-civil partnership (PPCP®) approach was developed to foster collaborative governance by involving stakeholders from the public, private, and civil society sectors in co-designing context-sensitive strategies. This article outlines the conceptual foundations and core principles of the PPCP®, based on a review of governance models and social innovation tools, and details its implementation through a series of locally organized Labs. Drawing on experience from two case studies areas (Egaleo in Greece and two municipalities in Portugal's Centro Region), it highlights outcomes such as improved cross-sector dialogue, the co-production of local knowledge, and more collaborative governance practices. The article also identifies key challenges, including low private sector involvement, institutional inertia, and limited civil society mobilization. It concludes with recommendations to overcome these barriers and strengthen the PPCP®’s transformative potential. These findings contribute to ongoing debates on local governance for climate resilience and propose pathways for embedding more inclusive and adaptive participatory processes.

面对日益增长的气候相关风险，传统的自上而下的风险治理模式越来越不足以实现有效和包容性的地方复原力规划。公私民间伙伴关系（PPCP®）方法旨在通过让公共、私营和民间社会部门的利益相关者参与共同设计对具体情况敏感的战略，促进协作治理。本文基于对治理模型和社会创新工具的回顾，概述了PPCP®的概念基础和核心原则，并通过一系列地方组织的实验室详细介绍了其实施情况。报告借鉴了两个案例研究领域（希腊的Egaleo和葡萄牙中罗大区的两个城市）的经验，重点介绍了改善跨部门对话、共同生产地方知识和加强合作治理实践等成果。文章还指出了主要挑战，包括私营部门参与度低、制度惰性和公民社会动员有限。最后提出了克服这些障碍和加强PPCP®变革潜力的建议。这些发现有助于当前关于气候适应能力地方治理的辩论，并提出了嵌入更具包容性和适应性的参与性进程的途径。

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引用次数: 0

Waterlogging susceptibility assessment in developed urban area using explainable machine learning methods with different negative sampling strategies 利用可解释的机器学习方法和不同的负抽样策略评价发达城市地区内涝易感性

IF 4.5 1区地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY

International journal of disaster risk reduction

Pub Date : 2025-12-17 DOI: 10.1016/j.ijdrr.2025.105978

Qingshan Zhang , Suhua Zhou , Jie Li , Zhiwen Xu

Exacerbated by global climate change, rainstorm-induced waterlogging has become a frequent hazard threatening sustainable development, causing disruptions from traffic paralysis to casualties. Therefore, it is essential to assess urban waterlogging susceptibility and identify high-risk areas. Although explainable machine learning (ML) shows promise in such assessments, its effectiveness is often limited by data limitation. For instance, rainfall and drainage network data are difficult to obtain, while the commonly used method of subjectively selecting random negative samples (non-waterlogged points) may compromise model classification performance and generalization ability. To address these challenges, we conducted a catchment unit-based framework based on morphological characteristics and proposed three data-driven negative sample sampling strategies (one kernel density estimation (KDE)-based and two K-means-based). Multiple explainable ML models (random forest/extreme gradient boosting/categorical boosting) were trained to assess waterlogging susceptibility in Changsha City. The results indicate that catchment units achieve high evaluation accuracy. The proposed negative sampling methods (mean test AUC ≈0.85) significantly outperform conventional random sampling (mean test AUC <0.75). Notably, the K-means-I clustering strategy achieved superior performance with a mean test AUC exceeding 0.90 across all three machine learning models. The Shapley additive explanation (SHAP) values appeals that the scale and topographic features of catchment units are the primary drivers of waterlogging in Changsha City. This study demonstrates strong applicability in identifying waterlogging risks for urban underpass roads, providing scientific support for flood prevention design in critical urban infrastructures.

由于全球气候变化，暴雨引发的内涝已成为威胁可持续发展的常见灾害，造成交通瘫痪和人员伤亡。因此，对城市内涝易感性进行评估，识别高发区是十分必要的。尽管可解释机器学习（ML）在此类评估中显示出前景，但其有效性通常受到数据限制的限制。例如，降雨和排水网络数据难以获得，而常用的主观选择随机负样本（非涝点）的方法可能会影响模型的分类性能和泛化能力。为了应对这些挑战，我们基于形态特征构建了一个基于集水区单元的框架，并提出了三种数据驱动的负样本采样策略（一种基于核密度估计（KDE）的采样策略和两种基于k均值的采样策略）。采用随机森林/极端梯度增强/分类增强等可解释ML模型对长沙市内涝易感性进行了评价。结果表明，集水区单元具有较高的评价精度。所提出的负抽样方法（平均检验AUC≈0.85）显著优于常规随机抽样方法（平均检验AUC <；0.75）。值得注意的是，在所有三种机器学习模型中，K-means-I聚类策略的平均检验AUC都超过0.90，取得了优异的性能。Shapley加性解释（Shapley additive explanation， SHAP）值表明，流域单元的规模和地形特征是长沙市内涝的主要驱动因素。研究结果对城市地下通道道路内涝风险识别具有较强的适用性，可为城市关键基础设施的防洪设计提供科学依据。

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