International journal of disaster risk reduction最新文献

{"title":"Multilevel optimization strategy for enhancing seismic safety and energy performance in school building portfolios","authors":"Abbas FathiAzar,&nbsp;Serena Cattari","doi":"10.1016/j.ijdrr.2025.105822","DOIUrl":"10.1016/j.ijdrr.2025.105822","url":null,"abstract":"<div><div>This study addresses two critical gaps in current seismic risk mitigation practices for school infrastructure. First, it introduces a safety-oriented, multi-level decision-making framework that systematically integrates structural safety, cost-efficiency, and implementation feasibility into a unified methodology. Unlike conventional approaches that often treat safety as one of several competing objectives, the proposed framework enforces life-safety as a non-negotiable constraint throughout the prioritization process. This emphasis emerges directly from stakeholder engagement. Second, the study fills an important scale-related gap by operationalizing risk assessment and intervention planning at the portfolio level. In doing so, it provides a crucial link between territorial-scale assessments and building-specific evaluations. Applying the framework to a portfolio of Italian school buildings shows its effectiveness, with results revealing strong variability in risk metrics and confirming that factors like the number of stories and construction period significantly influence both safety and loss. Retrofit cost-effectiveness is shown to depend strongly on initial building conditions, with older and more vulnerable structures delivering greater safety gains per unit of investment. Although energy retrofits were analyzed separately, findings suggest that standalone energy upgrades offer limited financial viability, reinforcing the value of integrated seismic-energy strategies.</div></div>","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":"130 ","pages":"Article 105822"},"PeriodicalIF":4.5,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145109742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stochastic modeling of radar-derived maximum estimated size of hail for scenario-based hail loss estimation","authors":"Katsuichiro Goda ,&nbsp;Yao Li ,&nbsp;Sudesh Boodoo ,&nbsp;Julian Brimelow ,&nbsp;Keith Porter ,&nbsp;Gregory A. Kopp","doi":"10.1016/j.ijdrr.2025.105819","DOIUrl":"10.1016/j.ijdrr.2025.105819","url":null,"abstract":"<div><div>This study develops a stochastic method for simulating the maximum estimated size of hail (MESH) values at locations within a hail swath and conducts a scenario-based hail loss estimation at regional scale. The method is based on MESHmax (which is obtained by taking the maximum value of MESH data over a hailstorm per location) and hail insurance loss data for the June 13th^, 2020, July 2nd^, 2021, and August 5th^, 2024 Calgary hailstorms. The stochastic MESHmax modeling identifies the hail swath (centerline and surrounding points) using MESH data and characterizes MESHmax along the centerline of the hail swath and at off-centerline locations. In the proposed method, spatial correlations of the MESHmax values along the centerline and off-centerline locations are considered. In addition, an empirical vulnerability curve is developed by relating MESHmax to insurance losses for residential properties. The scenario-based hail loss estimation generates numerous realizations of regional MESHmax maps and integrates them with a hail vulnerability curve for residential properties that is derived from the insurance loss data of three recent hailstorms in Calgary. An illustrative hail loss estimation is performed by considering a hypothetical event similar to the June 13th^, 2020 Calgary hailstorm. Using the developed scenario-based hail loss estimation tool, the probability distribution of the regional hail loss can be obtained. The stochastic simulation of the 2020 hailstorm is capable of reasonably hindcasting actual loss in that event. The sensitivity analysis results highlight significant influences of spatial variability of MESHmax values and uncertainty of the insurance loss generations.</div></div>","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":"130 ","pages":"Article 105819"},"PeriodicalIF":4.5,"publicationDate":"2025-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145097205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"National exposure model for industrial structures in Chile","authors":"Felipe Sánchez ,&nbsp;Paula Aguirre ,&nbsp;Hernán Santa María","doi":"10.1016/j.ijdrr.2025.105816","DOIUrl":"10.1016/j.ijdrr.2025.105816","url":null,"abstract":"<div><div>The 2010 Maule mega-earthquake produced estimated damage in Chile of 30 billion dollars, of which until today, the percentage corresponding to the cost associated with damage to industrial structures is unknown. This has generated concern regarding what will happen in the next major seismic event. Therefore, the need arises to incorporate seismic risk information in government disaster risk reduction measures.</div><div>In recent years, progress has been made in exposure models for residential buildings, but only a small number of investigations include industrial buildings, mainly due to the lack of information available in the databases and the difficulty in obtaining additional information from the private sector. This generates the need to computationally collect and process data obtained from existing databases and information obtained remotely.</div><div>The result of this research consists of the definition of a methodology and subsequent obtaining of an exposure model at the national level that includes the quantification, geographical location and the definition of characteristic typologies of industrial buildings in Chile, through its own flexible taxonomy that provides the necessary information for the subsequent structural modeling of each constructive typology. Given the limited information available and restricted access to industrial sites, the research adopts a hybrid methodology that combines statistical analysis of public cadastral data with remote visual surveys. In addition to obtaining an exposure model, the available information sources are discussed and compared, indicating the associated uncertainties and the assumptions considered.</div></div>","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":"130 ","pages":"Article 105816"},"PeriodicalIF":4.5,"publicationDate":"2025-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145156194","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Social profiles and response patterns during the 2025 Iberian Peninsula power outage. The case of Spain","authors":"Raquel González-Pozo","doi":"10.1016/j.ijdrr.2025.105813","DOIUrl":"10.1016/j.ijdrr.2025.105813","url":null,"abstract":"<div><div>On April 28, 2025, a large-scale power outage disrupted essential services across Spain, Portugal, Andorra, and parts of southern France, leaving more than 50 million people without electricity. The event affected critical infrastructures such as transportation, telecommunications, and healthcare, raising concerns about the population's resilience in the face of unexpected crises. This study focuses on the case of Spain, using data from a representative flash survey conducted after the power outage, and analyzes the population's response with statistical techniques for categorical data, specifically multiple correspondence analysis (MCA). The analysis focuses on three main aspects: emotional impact (fear), material preparedness (emergency kit), and access to information. The results reveal marked differences among social groups. Young adults, women, and the unemployed reported greater emotional vulnerability, while older and inactive individuals were less emotionally affected. Preparedness was also unevenly distributed, with individuals with higher education more likely to be prepared. Regarding access to information, the data show a stronger association between middle-aged individuals, lower emotional impact, and the perception of having received sufficient information during the power outage. By identifying distinct response patterns, the study contributes to a better understanding of the social dimensions of crisis management and complements the existing literature on disasters and unexpected situations.</div></div>","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":"130 ","pages":"Article 105813"},"PeriodicalIF":4.5,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145109740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prioritise risks and improve adaptation strategies in the Veneto coast through the application of a custom AI tool","authors":"Maria Katherina Dal Barco ,&nbsp;Veronica Casartelli ,&nbsp;Marcello Sanò ,&nbsp;Sebastiano Vascon ,&nbsp;Silvia Torresan ,&nbsp;Andrea Critto","doi":"10.1016/j.ijdrr.2025.105818","DOIUrl":"10.1016/j.ijdrr.2025.105818","url":null,"abstract":"<div><div>Climate change has emerged as one of the most severe global challenges of our time, with rising temperatures and unprecedented shifts in climate patterns. Coastal areas are particularly vulnerable, facing compounded impacts from sea-level rise and increasingly frequent extreme weather events, demanding urgent need for proactive and comprehensive adaptation measures to protect coastal regions, recently defined as sentinels of climate change.</div><div>A paradigm shift towards a multi-hazard risk perspective is increasingly recognised as essential in risk assessment and management. Moreover, Artificial Intelligence (AI) have emerged as promising tools to aid decision-making processes in coastal risk management and climate change adaptation. This study introduces COAST-AId, a custom Large Language Model designed to facilitate the analysis and synthesis of diverse information relevant for climate risk assessment and management along the Veneto coast. The tool facilitates the application of the risk assessment framework proposed in the European Climate Risk Assessment analysing the specific climate risk challenges of this region. The framework combines three key dimensions – i.e., risk identification, risk analysis, policy analysis – to prioritise risks and define urgent actions. The application of the COAST-AId tool was performed in close cooperation with local stakeholders involved in the MYRIAD-EU project where a systemic multi-hazard risk framework is considered to support the development of disaster risk management and climate adaptation pathways.</div><div>The tool's performance was evaluated by stakeholders, highlighting critical risks in the Veneto coastal as well as opportunities for enhancing coastal resilience and improving risk reduction and adaptation strategies at the regional to local scale.</div></div>","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":"130 ","pages":"Article 105818"},"PeriodicalIF":4.5,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145097206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Perceptions, hopes, and concerns regarding the possibilities of artificial intelligence in weather warning contexts","authors":"Thomas Kox ,&nbsp;Sara Harrison ,&nbsp;Ferdinand Ziegler ,&nbsp;Lars Gerhold","doi":"10.1016/j.ijdrr.2025.105817","DOIUrl":"10.1016/j.ijdrr.2025.105817","url":null,"abstract":"<div><div>Artificial intelligence (AI) is increasingly used in disaster risk reduction, including early warning systems (EWS) for weather hazards. While AI promises faster data processing and improved forecast accuracy, concerns remain about automation bias, reduced human oversight, or accountability, and erosion of professional judgment. Despite rapid technological advances, the perceptions of the weather warning community remain underrepresented in current research. To address this, we conducted an Argumentative Delphi study with experts from the 2024 WMO HIWeather Final Conference. Participants assessed AI's impact on 13 key aspects of weather warnings – including quality, interpretability, accountability, and social bias – and shared hopes and concerns. Overall, participants expressed cautious optimism. AI is expected to improve the goodness of warnings, potentially cascading into broader dimensions of warning efficacy, public trust, and institutional responsibility. However, concerns include over-reliance on AI, erosion of human involvement, and challenges in maintaining a single authoritative voice in warning communication. Rather than viewing AI as replacement for human decision-making, it is seen as decision-support tool that augments professional expertise. Tailored warnings and multilingual communication emerged as promising areas for AI application, though issues of data bias and accessibility remain. Thus, ethical implementation is vital to ensure inclusiveness and alignment global disaster risk reduction goals. Finally, the introduction of AI touches the ‘professional core’ of weather warning as an occupation and prompts experts to define their evolving roles and core competencies in the face of technological advancements. Future research should explore how generative AI may reshape forecasting and the profession itself.</div></div>","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":"130 ","pages":"Article 105817"},"PeriodicalIF":4.5,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145097209","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Future wildfires increase the risk of the residential insurance gap","authors":"Shona Elliot-Kerr ,&nbsp;Erica Marshall ,&nbsp;Trent Penman ,&nbsp;Ella Plumanns-Pouton","doi":"10.1016/j.ijdrr.2025.105814","DOIUrl":"10.1016/j.ijdrr.2025.105814","url":null,"abstract":"<div><div>Altered fire regimes pose unprecedented threats to residential properties in many parts of the world. Consequently, insurers are less willing to insure properties from the threat of wildfire or will do so at an inflated premium. Uninsurance or under insurance (the insurance gap) may have cascading impacts on property values, stranding residential assets, and amplifying economic inequalities. Here, we aim to quantify impacts of future climate-driven wildfires on residential properties, and the risk of the insurance gap from 2024 to 2099. We determine how this differs to historical wildfire impacts, in relation to socio-economic context, and spatial planning schemes. We ran spatially explicit wildfire regime simulations for five case study areas within Southeastern Australia. We compared the simulated wildfire impacts to data on residential properties, socio-economic status, spatial planning schemes, and the historical wildfire impacts from the preceding 75 years. Across all regions, a total of 274,657 houses (16.7 %) were projected to be burnt by wildfire within the next 75 years. Almost all of these houses, 96 %, were projected to experience an increase of at least one fire compared to the last 75 years. Most houses (86.6 %) projected to burn are currently occupied by low or middle class and a quarter were in the bounds of current fire plan building schemes. We suggest that transformative change may be required to help mitigate the potential increases to the residential insurance gap, both in the financial tools available to insure residential assets from wildfire, and the planning of where residences can safely be built into the future.</div></div>","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":"130 ","pages":"Article 105814"},"PeriodicalIF":4.5,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145109741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel methodology for assessing social vulnerability in depopulating rural communities: Application to Montesinho Natural Park, Portugal","authors":"Sandra Graus ,&nbsp;Tiago Miguel Ferreira ,&nbsp;Graça Vasconcelos ,&nbsp;Javier Ortega ,&nbsp;João Sarmento","doi":"10.1016/j.ijdrr.2025.105815","DOIUrl":"10.1016/j.ijdrr.2025.105815","url":null,"abstract":"","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":"130 ","pages":"Article 105815"},"PeriodicalIF":4.5,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145097208","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Establishing closure criteria for coastal roadways under flooding conditions","authors":"Faezeh Maghsoodifar,&nbsp;Soheil Radfar,&nbsp;Hamed Moftakhari,&nbsp;Hamid Moradkhani","doi":"10.1016/j.ijdrr.2025.105805","DOIUrl":"10.1016/j.ijdrr.2025.105805","url":null,"abstract":"<div><div>The increasing frequency and intensity of floods pose major challenges for transport networks, particularly in coastal cities. In addition to serving as vital arteries for commuter traffic and freight movement, coastal roads form essential links in the urban transportation network, connecting communities, businesses, and critical services. This study presents a framework for assessing the impacts of flooding on transportation systems and establishing road closure criteria for coastal roads with urban connectivity importance. We integrate Delft3D-FM hydrodynamic modeling with empirical road closure data, geospatial analysis, and vehicle stability assessments to evaluate flood hazards and develop practical management criteria. The framework incorporates the effects of sea level rise and more extreme weather events, allowing for an assessment of changing flood hazards over time. Analysis of empirical closure records enables the development of four distinct flood severity thresholds based on depth of inundation. These thresholds incorporate both flood depth and velocity, providing a detailed hazard assessment that supports the development of road closure criteria to address the increasing challenges posed by flooding. Findings indicate that, without proactive adaptation measures, coastal roadways are likely to transition from episodic flooding to chronic inundation. This underscores the importance of adaptive design and operational management strategies to ensure safe and resilient transportation infrastructure.</div></div>","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":"130 ","pages":"Article 105805"},"PeriodicalIF":4.5,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145097202","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A systemic approach to complex landslide risk reduction in coastal tourist areas: The case of Sirolo, central Italy","authors":"Elisa Mammoliti ,&nbsp;Eleonora Gioia ,&nbsp;Davide Fronzi ,&nbsp;Adriano Mancini ,&nbsp;Giorgio Mattioli ,&nbsp;Roberta Bonì ,&nbsp;Fabrizio Pontoni ,&nbsp;Stefano Marabini ,&nbsp;Stefano Mazzoli ,&nbsp;Alberto Tazioli ,&nbsp;Alessandra Negri","doi":"10.1016/j.ijdrr.2025.105810","DOIUrl":"10.1016/j.ijdrr.2025.105810","url":null,"abstract":"<div><div>Coastal landslides in structurally complex and tourist-rich areas, such as the Monte Conero promontory in central Italy, pose significant challenges to environmental stability and public safety. In these settings, complex landslides often involve deep-seated translational movements evolving into sudden debris collapses at the footslope, generating significant hazards in beach areas heavily frequented by tourists. This study develops a conceptual, transferable model for complex landslide behavior in the Sirolo coastal sector in an integrated Hazard–Exposure–Vulnerability framework. The hazard component is investigated by systematically integrating multi-source data, including COSMO-SkyMed and Sentinel-1 Differential Interferometric Synthetic Aperture Radar (DInSAR) data, <em>in-situ</em> inclinometer and piezometric time series, and high-resolution geological and geomorphological field mapping. Rainfall analyses and an Extreme Rainfall Periodic Index (ERPI) were used to explore the correlation between precipitation distribution and kinematic responses of the slope, offering an empirical insight into seasonal hazard modulation. To assess exposure, we developed a deep learning model to estimate beach attendance using limited Google Earth imagery (5 useable acquisition dates, moderate resolution), calibrated with regional tourism statistics, enabling a spatially and temporally explicit assessment of human presence. Finally, to explore vulnerability, a face-to-face survey was carried out to document gaps in visitor awareness of risk and civil-protection procedures. This integrated approach offers enhanced predictive capacity and supports targeted mitigation and communication measures in coastal environments characterized by complex landslides and intense seasonal human activity. To the authors knowledge, this is the first study integrating geological monitoring, rainfall indices, satellite data, deep learning-based exposure, and tourist risk perception into a systemic coastal landslide risk framework.</div></div>","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":"130 ","pages":"Article 105810"},"PeriodicalIF":4.5,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145156082","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}