Regional Resilience Research Articles

Elite cohesion and resilience of the Russian regions: the case of Belgorod Oblast

ABSTRACT What accounts for the ability of regional elites to respond to the challenges posed by the Russian war against Ukraine? This study argues that elite cohesion elevates the ability of subnational elites to cope and adapt to crises. It employs social network analysis of a novel biographical data set of elites’ connections in Belgorod Oblast, the border region that has been severely affected by the war. The analysis reveals that the war has made a relatively minor impact on the structure of the elite network as it has retained its original characteristics. Furthermore, it shows that the outsider governor has not only managed to strengthen his own position among the elites but also to reinforce elite cohesion. By bringing together different elite groups, the governor has enhanced their ability to perform under substantial stress. These findings advance our understanding of the sources of resilience in personalist autocracies.

Exploring supply chain and regional resilience through the analysis of the transport dimension

Despite the key role that global supply chains (GSC), and more specifically, the transport and logistics function, might play in the performance of regions, there is a lack of analytical tools that turn the data generated by supply chain operations into quantitative metrics allowing policymakers to identify early signals of potential vulnerabilities and assess how resilient the GSC are at regional level. In an effort to fill this gap, we present a Transportation Resilience Index (TRI) that permits evaluating how transport chains affect supply chain resilience and, consequently, regional resilience. Our index, based on publicly available data –statistics on foreign trade flows provided by the Spanish Customs, the World Bank’ Logistics Performance Index and the UNCTAD’ Bilateral Liner Shipping Connectivity Index − differentiates between the determinants over which the company has direct decision-making control, and those linked to the selection of the supply market (market and macro dimensions). The TRI is applied to the Spanish regions (NUTS2) by using the Benefit-of-the-Doubt (BoD) approach to Data Envelopment Analysis (DEA) and applying a Common Set of Weights (CSW) for the selection of the weights to the index components. In our specific analysis, the market and macroeconomic components account for 84% of the total weight of the TRI. Despite the lower relative weight of the company dimension, the high degree of homogeneity in the market and macroeconomic scores means the company dimension plays a key role in the relative resilience of the Spanish regions.

Conflict mitigation as a means of climate change adaptation: Lessons for policy and development practice

In this article, we examine the ways conflict can drive climate change vulnerability and, in turn, argue that conflict mitigation can act as a means of climate change adaptation. We identify three key ways in which conflict mitigation enhances adaptation opportunities: (a) addressing conflict dynamics increases opportunities to address climate risks; (b) grounded analysis of conflict dynamics often reveals high-value opportunities for climate change-oriented programs as well as potential maladaptations to be avoided; and (c) conflict mitigation interventions which rely heavily on governance can be leveraged in climate change adaptation efforts. This has multiple implications for global climate change policy, especially when one considers key climate security outcomes emanating from international policy discussions such as COP 28. We conclude this article by identifying three under-examined—and practical—lines of inquiry that would address key knowledge gaps in how to fortify climate resilience in conflict-affected regions.

Resilience evaluation research on coping with rainstorm inundation under the perspective of full cycle: A case study of Beijing-Tianjin-Hebei region

With the development of global warming and urbanization, the risk of cities being affected by rainstorms is increasing and the safety of lives and properties of residents as well as the sustainable development of the urban economy and society, are facing crucial threats. As a giant complex system, the interior of a city is highly complex and interconnected. The concept of urban resilience has become an effective way of guiding cities to cope with rainstorm inundation perturbations from the perspective of the wholeness of a system. We aimed to integrate the time dimension into the study of resilience in response to rainstorm inundation to gain a deeper understanding of the process of rainstorm inundation generation and development as well as the resilience mechanism in this process. In this study, based on the basic principles of urban resilience and the occurrence and evolution mechanisms of rainstorm inundation, we propose a novel resilience evaluation method to cope with rainstorm inundation from the perspective of the entire cycle. The full-cycle process from ``rainstorm event'' to ``inundation disaster'' is divided into four phases: rainstorm incubation, rainstorm occurrence, inundation persistence, and inundation recession phases and the resilience objectives of each phase are proposed to form a regional resilience indicator set for coping with rainstorm inundation. The Google Earth Engine (GEE) platform was used to identify the spatial and temporal patterns of regional rainstorm inundation, identify the contributing indicators of specific regional rainstorm inundation, combine hierarchical analysis and expert decision analysis to determine the weight of each indicator, and build a regional resilience evaluation model to cope with rainstorm inundation. On this basis, we conducted regional resilience evaluation and type spectrum research to cope with rainstorm inundation, identify the resilience index of the research unit based on the VIKOR method, identify the regional resilience pattern under the full-cycle perspective, divide the resilience types, generate the resilience zoning map and resilience obstacle indicators, and provide guidance on the timeline for improving resilience in the region.

Determining geo-disaster chains probabilities and disaster mitigation mode: A meta-analytical perspective

In a harsh geological environment, different geo-disasters might co-occur or be in a chain sequence. Currently, existing research in related fields documents numerous instances of disaster chains and responses, which provided this study with important materials for determining disaster chains probability and summarized the disaster prevention and mitigation (DPM) mode. In this study, through the depth of the geo-disaster chains cases and the DPM cases, enabled a mitigation mode analysis summary. We take the case of geo-disaster chains as an example for this study, and represent 20 typical geo-disaster chains by data fusion and structuring of 139 geo-disaster chains cases.The probability assessment of geo-disaster chains is crucial for risk management and regional resilience. We introduced a Bayesian network (BN) model to describe the process of geo-disaster chains formation to map the structure and assess the joint probability of geo-disaster chains. The BN results showed that the longer the disaster chains length, the smaller the probability of the chains occurring. Among these, the probability of “Collapses-landslides-debris flows–barrier lakes–flash floods” is the lowest (0.069). Through sensitivity analysis, it is found that precipitation is the most sensitive factor in the development of geo-disaster. Interpretive structural modeling (ISM) is employed to examine the DPM index system across three key aspects: disaster emergency preparation, disaster response, and disaster recovery, and the conceptualized interaction among these components. ISM results showed that government policy intervention and scientific DPM measures can effectively reduce the losses caused by the development of geo-disaster chains. This research combined the occurrence process of the disaster chains with the disaster response process, and determined the entire chains of characterization from disaster understanding to disaster response, and helped reduce the vulnerabilities caused by disasters.

GIS-Based Regional Seismic Risk Assessment for Dubai, UAE, Using NHERI SimCenter R2D Application

Over the last two decades, the UAE’s construction sector has grown significantly with the development of tall buildings, but the region faces seismic risks. Similar concerns in China led to earthquake simulation research on a city scale. The objectives include developing programming for parallel computing and creating simplified models for estimating losses. The challenges include computational complexity and uncertainties in various modules. In 1995, the structural engineering community adopted performance-based engineering principles, shifting to a probabilistic design process. The Computational Modeling and Simulation Center (SimCenter) implemented this into a generic software platform, with the 2010 release of Regional Resilience Determination (R2D) automating the methodology. A research plan aims to advance realistic seismic simulation in the UAE, integrating studies and custom developments. The goal is to create an end-to-end seismic risk assessment framework aligned with digital trends, such as BIM and GIS. The investigation focuses on a virtual dataset for tall buildings, considering variations in location, material properties, height, and seismic activity. For the studied archetypes, the average expected losses include a 3.6% collapse probability, a 14% repair cost, 22 days repair time per asset, and almost 1.5% total population injuries, ranging from 1% for the lowest severity to 0.15% for the highest.

Enhancing Seismic Performance: A Comprehensive Study on Masonry and Reinforced Concrete Structures Considering Soil Properties and Environmental Impact Assessment

Approximately 20,000 people are killed annually on average by building and infrastructure collapses and failures caused by seismic activities. In earlier times, seismic design codes and specifications set minimal requirements for life safety performance levels. Earthquakes can be thought of as recurring events in seismically active areas, with severity states ranging from serviceability to ultimate levels. Buildings designed in accordance with site-specific response spectra, which take into account soil properties based on ground motion amplification data, are better at withstanding such forces and serving their design purposes. This study aims to investigate the site response of reinforced and masonry buildings, considering the effect of soil properties based on the amplification of ground motion data, and to compare the life cycle assessment of the buildings under consideration based on the design and the site-specific response spectrum. In terms of soil properties and site-specific response spectra, STRATA is used to determine the site-specific response for the considered locations for a return period of 475 years for 100 realizations based on the randomization of site properties. For structural analysis, AxisVM software, which is a compatible finite element analysis, is used for building design and analysis, generating comparative results based on the design- and site-specific spectra. To determine and identify potential failures in the model, response spectra were applied to understand the difference in horizontal deflection in two different instances (for elastic design- and site-specific spectra). After building design and analysis is performed, a life cycle analysis in terms of environmental impact assesments using OpenLCA and IdematLightLCA is done. This is done to ascertain the additional expenses in terms of ecocosts and carbon footprints on some failed elements in the structure which are required to make the buildings more resilient when the site-specific response spectrum is applied and to compare the potential economic losses that may occur based on ecological costs. The study presents a comprehensive investigation into the seismic response of masonry and reinforced concrete buildings in Győr, Hungary, incorporating advanced geophysical techniques like multichannel surface wave (MASW) and structural analysis software, AxisVM. Additionally, tailored retrofitting strategies are explored to enhance structural resilience in seismic-prone regions. Significant ground amplifications in soil properties across different profiles are revealed, emphasizing the effectiveness of these strategies in reducing structural deflection and improving resilience. Highlights of the results are observed where the site-specific response spectra are higher than the EC8 design response spectrum. Furthermore, the research underscores the substantial environmental impact, considering both ecocosts and CO2 emissions associated with retrofitting measures, highlighting the importance of sustainable structural interventions in mitigating seismic risks.

Evaluasi Kebijakan BPBD Kabupaten Pangandaran dalam Upaya Pengurangan Risiko Bencana di Kabupaten Pangandaran

This study assesses the performance of the Regional Disaster Management Agency (BPBD) in Pangandaran Regency by analyzing its policies and reviewing disaster reduction reports. Utilizing a literature review method, with a focus on BPBD Pangandaran Regency's policy documents, the evaluation links the Strategic Plan (Renstra) to outcomes in the Performance Accountability Report (LAKIP). The Renstra outlines disaster prevention, emergency response, and post-disaster policies, translated into programs to enhance the region's disaster management capacity, measured by the Regional Resilience Index. Despite an improved index attributed to successful handling of 125 disasters in 2022, including fires, tornadoes, landslides, floods, and earthquakes, the study notes challenges such as a lack of updates in crucial documents and insufficient human resources impacting BPBD Pangandaran's performance. While the agency has achieved a 100% performance realization in various programs, attention to document updates and resource allocation is essential for more efficient disaster management in Pangandaran Regency.

Seismic performance evaluation of exterior reinforced concrete beam-column connections retrofitted with economical perforated steel haunches

The exterior beam-column joint (BCJ) within reinforced concrete (RC) frame structures is acknowledged as a vulnerable component prone to seismic failure. This article proposes a practical and economical strengthening method for exterior BCJs using a perforated steel haunch system. This method is designed to mitigate damage in BCJs and improve the seismic performance of the structure. Employing finite element modeling (FEM) techniques, the study evaluates the impact of perforated steel haunches on the BCJs’ behavior and performance. The investigation involves creating nine distinct models, each representing a BCJ with a steel haunch system. These models include a control model without any perforations and eight variations with different levels of perforation (ranging from 10% to 50%) within the steel haunch system. Furthermore, the study analyzes the influence of perforation shapes on the connections’ performance, considering square, circular, hexagonal, and triangular shapes. The results reveal that utilizing a steel haunch without perforations significantly increases the load-carrying capacity of a BCJ by about 89%. Additionally, circular or square-shaped perforations, up to 30–35% within the steel haunch, effectively prevent the joints’ failure and promote the ductile behavior. These findings hold the potential to advance the design methodology for RC joints subjected to seismic loads, thereby enhancing the structural resilience in earthquake-prone regions.

SOLAR BASED SMART AGRICULTURE ROBOT

In response to the evolving demands of contemporary agriculture, the Solar-Based Smart Agriculture Irrigation Robot project represents an innovative integration of robotics and renewable energy to enhance the efficiency and sustainability of farming practices. This project aims to develop a versatile, autonomous robot equipped with a suite of functionalities, including automated irrigation, vegetation management, seeding, and targeted watering. Powered by a 2S Li-ion battery pack, supported by a 12W solar panel, the robot demonstrates a commitment to eco-friendly energy use and operational resilience in off-grid agricultural regions. Through a user-friendly mobile app interface, farmers can remotely control and monitor the robot, revolutionizing farm management. The project's significance lies in its potential to address challenges such as water scarcity and labor shortages, contributing to precision agriculture and fostering a greener future for farming practices. This abstract encapsulates the project's dedication to technological innovation, efficiency, and sustainable agriculture.

Reducing consequences of extreme heat: The role of weather information access

This study investigates the impact of weather information sources on consequences associated with extreme heat events, employing a cross-sectional survey conducted on hospitalized individuals who have experienced heat stress in Central Vietnam. Multiple information channels, including official agencies and social media, were found to significantly reduce the Cost of Illness (COI) associated with heat-related ailments. Social media, in particular, emerged as a potent tool for climate adaptation. Improving the clarity and accessibility of weather information through official channels is crucial, especially for households with varying income levels. Demographic factors such as age and gender should be considered when fine-tuning communication strategies, with special attention given to individuals with underlying medical conditions, who are particularly susceptible to extreme heat effects. These findings underscore the need to maximize the reach of weather-related information and reduce economic burdens on affected populations. This provides valuable insights for policymakers aiming to bolster climate resilience in vulnerable regions like Vietnam, emphasizing the significance of diverse information sources and tailored communication in climate change adaptation.

Harnessing climate services to support community resilience planning: lessons learned from a community-engaged approach to assessing NOAA’s National Water Model

IntroductionInland and coastal flooding and other water-based natural disasters are projected to increase in severity, frequency, and intensity as global temperatures rise, placing a growing number of US communities at risk. Governments at the local, state, and federal levels have been embracing resilience planning to better predict, mitigate, and adapt to such shocks and hazards. A growing number of climate services have been developed to aid communities engaged in these efforts to access, interpret, and make decisions with climate-related data and information. An important tool for potentially supporting this planning is the National Water Model (NWM), created by the National Oceanic and Atmospheric Administration’s (NOAA) National Water Center (NWC). The NWM is a river and streamflow model that can forecast conditions for the continental United States.MethodsHowever, community end-users were not being effectively engaged in ways that result in widespread tool use and adoption. From 2021 to 2023, seven geographically diverse US communities agreed to participate in a study to understand how the NWM might be applied in resilience planning. Interviews and collaborative sessions were conducted with NWC/NOAA staff and community resilience stakeholders in Burlington, VT; Cincinnati, OH; Portland, OR; Charlotte, NC; Boulder, CO; Minneapolis; MN; and Houston, TXResults and DiscussionResults provide an improved understanding of potential applications of the National Water Model and have identified actions to overcome the barriers to its use among municipal and regional resilience planners. This research yielded a set of recommendations, co-developed between the seven communities and NWC/ NOAA staff, for how these barriers could be overcome to facilitate wider use of the NWM and its data and visualization services in resilience planning. This study highlights the NWM’s applicability at shorter timescales in resilience planning and points to a more general need for climate services to accommodate near-, medium-, and longterm time frames. The study also found many community stakeholders who use water science and information in resilience planning have diverse disciplinarily backgrounds. Importantly, the majority were not trained hydrologists or water scientists, pointing to the critical need for climate service developers, including the NWC, to embrace co-development efforts that involve a wider range of end-users, including community resilience planners.

Women’s Empowerment in Agriculture in the Semi-Arid: A Case Study of Northeastern Brazil

ABSTRACT Gender inequality affects agricultural production and rural households’ capacity to build climate resilience, especially in developing countries. However, empirical research on promoting women’s empowerment in the face of environmental threats is limited, particularly in areas vulnerable to the impact of climate change, such as semi-arid regions. This study identifies factors promoting women’s empowerment in semi-arid regions and the mechanisms behind them. This mixed-methods case study was conducted in a semi-arid area in Northeastern Brazil, utilizing household surveys, key informant interviews, and focus groups. Results show that accessing targeted credit lines and extension services was significantly associated with empowerment. The qualitative findings suggest that adopting participatory mechanisms in policymaking and utilizing feminist pedagogy and popular education in the intervention delivery process was crucial to achieving women’s empowerment in the study area. HIGHLIGHTS Climate change increases risks for rural livelihoods, highlighting the need for resilience. Women’s empowerment is key to bolstering agriculture’s resilience in semi-arid regions, such as northeastern Brazil. Participatory approaches in policy design are crucial for women's empowerment success. Inclusion of feminist pedagogy in interventions enhances rural women’s empowerment.

Sectoral–regional resilience and productive specialization: a comparison among the last three crises

The objective of this paper is to compare the economic resilience of industries and regions along the last four decades, which include the three last major crises for the advanced countries (90s, Great Recession in 2007 and recent COVID-19 pandemic). Productive structure and sectoral specialization are introduced as explaining factor for the different regional behaviors. For this purpose, we estimate both resilience and specialization indices based on employment data. To analyze the relationship between specialization and resilience, a cross-sectional descriptive analysis is complemented by a panel data model that includes some controls. Finally, a regional shift-share analysis contributes to exert some other regional effects affecting economic resilience. The results of this research show some continuities and other significant changes in the regional impact of crises from one to the next. Although there are other effects to have played a role, results show economic specialization is found to have exerted influence on the recovery of certain regions during this period. Recovery periods differ from each crisis and the results might be affected for this dimensionality limitation. Due to the characteristics of the database, the study includes only six sectors. However, general results are generalizable to other regions as the response of employment growth to crises is similar in many advanced regions and specialization patterns does not significantly differ among regions. The paper carries a structural long-term comparison between the last major crises for Spanish regions, which clearly differentiates one from another in their causes and effects. We introduce specialization to explain the different regional resilience patterns. Methodologically, we estimate both sectoral and regional resilience indices for these three crises and relate this resilience to specialization and other explaining factors.

Evaluation and prediction of compound geohazards in highly urbanized regions across China's Greater Bay Area

Natural hazards could have devastating consequences globally, making hazard assessment and spatial prediction crucial for enhancing the resilience of urbanized regions. However, current disaster prediction and assessment research often neglect the compound effects between multiple geohazards highly in urbanized regions. To address the concern, we employed comparative methodology, evaluating four machine learning algorithms—Extreme Gradient Boosting (XGBoost), Random Forest (RF), Back Propagation Neural Network (BP), and Long Short-Term Memory (LSTM)—in the creation of Geohazard Susceptibility Maps (GSM) for the highly urbanized Guangdong-Hong Kong-Macao Greater Bay Area (GBA). Additionally, the study investigated the triggering mechanisms and the compound interaction between multiple geohazards using the conditional vine copula model. The results showed that the XGBoost model outperformed other models (AUC = 0.89) for predicting multiple geohazards. Geohazards were predominantly concentrated in urban areas in the GBA, with surface subsidence being the most severe, followed by collapse and landslide. The primary triggers for multi-geohazards include distance to roads, slope length, and lithology, with slope length and lithology identified as the primary causative factors in urban areas. Urbanization within the GBA increased the probability of multi-geohazards by 10%, compared to their univariate counterparts. Urban regions exhibited increased risks of landslides, surface subsidence, and collapse by approximately 31%, 44%, and 32%, respectively compared to non-urban regions. Additionally, compound geohazards in the GBA were primarily triggered by heavy rainfall, resulting in the formation of landslide-collapse and collapse-landslide geohazard chains. The probability of compound geohazards is approximately 5% lower than that of univariate geohazards. This is because compound geohazards necessitate a higher cumulative rainfall, and the rainfall threshold was approximately 2–3 times higher than that of univariate geohazards. In the cascading hazard pattern, the occurrence of primary geohazards during local heavy rain increased the probability of secondary geohazards by approximately 10%. The study provides essential insights for mitigating compound geohazards in urbanized areas.

Regional economic resilience, productivity growth and sectoral interconnectedness

This paper develops a theoretical model for the conceptualization and empirical analysis of regional economic resilience. Our production function framework is applied to empirically assess the effect of pre-crisis conditions on regional resilience accounting for exogenous changes in technology and changes in production factors. Spatial regression analysis indicates that intersectoral linkages are important factors for explaining the resilience of regions to negative exogenous shocks. A key finding of the study is the positive effect of the interconnectedness of agriculture, construction, and electrical, optical and transport equipment sectors on the ability of European Union regions to absorb the adverse effects of the 2008 economic crisis.

Big Data Review of the Influence of Agricultural Sector Development on Economic Resilience

The agricultural sector in the East Java's GDP structure has been stable at around 11% over the past 5 years, despite disruptions caused by the Covid pandemic. The stable development of the agricultural sector has contributed to the region's increased resilience. This study aims to identify the relationship between factors influencing agricultural development and resilience in East Java and to formulate related development strategies. The method used in this study is Correlation and Regression. Regional resilience is viewed as the output of changes in the rate of GDP growth. Factors in agricultural development are viewed from Agricultural Production, Land Factors using Big data, including LST, NDVI, and NDWI, Internet User Farmers and Farmer Populations. The results of the study indicate that significant influential factors in agricultural development are found in NDVI, NDWI, and Farmer Population. The study shows that for East Java, development strategies through digital farming have not yet been able to increase regional resilience, and conventional agricultural development methods still dominate.

PERAN PEMERINTAH DAERAH DALAM PENGURANGAN RISIKO BENCANA MELALUI PENINGKATAN KETAHANAN BENCANA DAERAH DI KABUPATEN TANAH BUMBU

Exploitation of natural resources triggers a decrease in the carrying capacity and capacity of the environment and results in climate change and various kinds of disasters. The objectives of this research are Analyzing the role of the Regional Government in implementing the Regional Resilience Index Improvement Program; Analyzing the inhibiting factors of the Regional Resilience Index improvement that has been carried out by the Tanah Bumbu Regency Government; Determining the priority scale of the Regional Disaster Resilience Improvement Program. Data analysis used in this study is Calculating the percentage of indicator achievement based on the Technical Guidelines for the Regional Resilience Index Assessment Tool, Descriptive analysis of inhibiting factors in increasing the Regional Disaster Resilience Index (71 Indicators) to stakeholders through interviews, Creating a priority scale matrix to determine recommendations. Determination of the priority scale matrix is based on Minimum Service Standards and ranking of relevant stakeholders. The results of research on the role and inhibiting factors of the Tanah Bumbu district government in increasing the Regional Resilience Index are Indicators implemented in the priority of Strengthening Policies and Institutions by 60.00%. Indicators implemented in the priority of Risk Assessment and Integrated Planning amounted to 75.00%. Indicators implemented in the Information System Development, Training and Logistics priority by 69.23%. Indicators implemented in the priority of Thematic Handling of Disaster Prone Areas amounted to 80.00%. Indicators implemented in the priority of Increasing the Effectiveness of Disaster Prevention and Mitigation by 70.00%. Indicators implemented in the priority of Strengthening Disaster Preparedness and Emergency Management by 55.00%. Indicators implemented in the Disaster Recovery System Development priority of 75.00%.

ANTISIPASI SATUAN KOMANDO KEWILAYAHAN TNI AD MENGHADAPI ERA BONUS DEMOGRAFI MENUJU INDONESIA EMAS 2045

This research aims to analyze the anticipation of the regional command units of the Indonesian National Army in facing the era of the demographic bonus towards a Golden Indonesia 2045. As one of the components of the nation, the Indonesian National Army seeks to assist the government in utilizing the demographic bonus so that it becomes a demographic blessing and not a disaster demographics. The theoretical conceptual framework used is the concept of territorial development. The research method used is a qualitative method and data collection techniques in the form of observation, interviews and documentation. The results of this research show that the anticipation of the territorial command units of the national army in facing the demographic bonus is carried out by carrying out territorial development functions (geographic development, demographics, social conditions) and territorial development methods (social communication, regional resilience development, TNI service), as well as ideas innovation in the form of territorial development that focuses on education, health and economic aspects.

Quantitative assessment of building risks and loss ratios caused by storm surge disasters: A case study of Xiamen, China

China is severely affected by storm surge disasters, which result in substantial economic losses and casualties in coastal regions. Assessing the risk of storm surge disasters can provide valuable insights into the expected losses and severity of future impacts, offering critical foresight for disaster prevention and mitigation strategies. This study assesses the quantitative risk of storm surge disasters, focusing on coastal buildings since they are particularly susceptible to storm surges and frequently bear the brunt such disasters. Xiamen city, China, was used as case study. A high-precision numerical model, using Finite Volume Community Ocean Model (FVCOM), was developed to simulate inundation during storm surges. By referencing historical storm surge records, we defined key parameters for probable maximum typhoon-induced storm surge (PMTSS) in Xiamen. These parameters were used to calculate the corresponding inundation range and water depth distribution within the region. Subsequently, the results were integrated with vulnerability curves that represent the susceptibility of buildings in Xiamen to storm surge-induced damage, enabling the quantitative risk assessment for associated loss risks. The study findings offer valuable guidance for urban planning and functional layout design in coastal areas. Furthermore, the findings contribute to understanding storm surge disaster risks and facilitating informed decision-making processes, ultimately enhancing disaster preparedness and resilience in vulnerable coastal regions.