Vulnerability Assessment Methods Research Articles

Urban Vulnerability Assessments to Climate Change for Members of the European Healthy Cities Network in Turkey: A Case Study

It is a scientific fact that climate change has important negative effects on and ecological sustainability. Especially its increasing effects on human and urban health make settlements more vulnerable. Therefore, government-level actions are important, but local governments have more important roles in climate change mitigation and adaptation. However, the lack of information on combating climate change is the biggest problem for local governments. To overcome this lack of information, action, and inclusive governance systems based on the measurement and monitoring are required. There are many tools and methods for qualitative and quantitative vulnerability assessment for cities. Indicator-Based Vulnerability Assessments are recommended in the relevant literature to assess vulnerability to urban climate impacts. This study, based on the method IBVAs, Turkey Healthy Cities Association member aims to determine the level of vulnerability of cities to climate change. When these 40 settlements/cities were analyzed by vulnerability categories, it was determined that they were distributed as High Vulnerability 0, Medium Vulnerability 5, Low Vulnerability 32, and Durability 3, respectively. It is seen that the biggest deficiencies related to the sub-parameters in the cities are in the Organizational Structures of the Cities, followed by the General Characteristics of the Cities and the Built-Environment respectively.

Minimising cybersecurity risk exposures in industrial control system environments: a techno-human vulnerability analysis approach

ABSTRACT Organisations operating IoT-enabled industrial control systems (ICSs) are concerned about growing cybersecurity risks and impacts to their systems. Cyber-attacks on ICSs demonstrate that technology alone is neither a problem nor a solution to the growing cybersecurity issues affecting these systems. As socio-technical systems, ICSs encompass the functions and interactions of social and technological system elements to enable and/or sustain industrial processes. Thus, a more effective cybersecurity risk management process needs to consider human and technology factors, especially for high-value industrial process targets. Combining critical reviews and gap analysis of existing vulnerability assessment methods with conceptual modelling, a Vulnerability Analysis Critical Impact Point Process (VACIP) methodology is proposed which considers both human and technological vulnerabilities within a cyber-physical system environment to inform an improved insight about attack criticality and impacts. VACIP is validated using a simulated industrial mini testbed; showing that it can enable practicable support for security vulnerability discovery, impact criticality analysis, weak link identification, and prioritised controls. Its novelty is demonstrated in its combination of technology and human vulnerability evaluations in the minimisation of system security exposures. It provides a useful guide for adopting effective cybersecurity risk assessment and exposure reduction strategies.

Climate Risk Assessment Framework in Real Estate: A Focus on Flooding

Climate change exacerbates flood hazards, resulting in risks to real estate values that should be considered by long-term investors. Flood risk presents two major financial risks: market risk and credit risk. Market risk refers to potential property value loss, and credit risk increases the likelihood of mortgage defaults. However, methods and comprehensive data for quantifying global real estate flood risks are lacking. To address this problem, this paper proposes two flood risk assessment frameworks: the local-oriented approach (LOA) and global-oriented approach (GOA). Two hazard and three vulnerability assessment methods are also introduced to support these frameworks. The LOA vulnerability estimates of regions with complete records are required to support the GOA. Taiwan was selected as an example for the LOA assessment, and the results were used to estimate vulnerability overseas in GOA assessments. The results of case studies for buildings located in four cities in different countries were compared. The proposed framework enables investors and asset owners to globally quantify climate risks in real estate, even when the available data are incomplete. Users can choose the most appropriate approach on the basis of the available data and their tolerance for uncertainty.

Climate change and health vulnerability assessments to increase regional climate resilience

Abstract Background The impacts of climate change on health and healthcare systems exhibit complex interrelationships, varying across time and space. Population groups already disadvantaged due to their demographics, health, socioeconomic status, or geographical location tend to be particularly vulnerable to climate-related health risks. Our work aims to develop a method for a systematic quantitative vulnerability assessment to make regional vulnerabilities comparatively measurable. Methods Building on the WHO framework on Climate Change and Health Vulnerability and Adaptation Assessment (2021) a data mapping process was carried out to identify and validate vulnerability factors and quantitative indicators on a small-scale spatial resolution for the five dimensions: demographic, socioeconomic, biological/health, sociopolitical, and geographic/climate. Regional vulnerability scores for each indicator were calculated and visualized as geographic maps and circular barplots to allow for easily understandable interpretation. Results A set of 25 quantitative vulnerability indicators from a multitude of data sources - combining register data, survey data, and geospatial data - was compiled. Main challenges were the identification of sociopolitical vulnerability factors suitable for Austria and data availability on a small-scale level. The indicator set was used to identify regions that are particularly vulnerable due to their population composition, disease burden, and geographical location (e.g. regions in Eastern Austria with high shares of persons < 65 years of age, unemployment, and heat days). Conclusions Systematically assessing vulnerabilities in key dimensions is central to identifying regionally specific pressure points, allowing for a quantitative baseline to derive adequate and tailored climate change adaptation measures to sustain future health. Systematic assessment provides essential insights for policymakers, public health officials, and disaster management agencies.

Evaluating Ecological Drought Vulnerability from Ecosystem Service Value Perspectives in North China

Existing studies on the vulnerability assessment of ecological drought often focus on analyzing vegetation phenotypic characteristics, overlooking the impact of drought on ecosystem services. This study proposes an ecosystem vulnerability assessment method under ecological drought stress from the perspective of ecosystem service value (ESV), considering the characteristics and interactions of hazard-causing factors and hazard-bearing bodies. The spatiotemporal evolution of ecological drought, the spatial characteristics of ecosystem vulnerability, and the vulnerability characteristics of different ecosystem types in the North China region from 1991 to 2021 were evaluated. The results showed that: (1) ecological drought exhibited a trend of intensification followed by alleviation, with the most severe droughts occurring between 2002 and 2011, affecting up to 64.3% of the region; (2) ESV was mainly influenced by vegetation cover and precipitation gradients, displaying a spatial pattern of high values in the southeast and low values in the northwest, with total ESV averaging CNY 18.23 trillion; (3) grasslands exhibited higher sensitivity to drought compared to forests, and the sensitivity was higher in summer and autumn than in winter and spring. This method assessed the vulnerability of ecological drought from the perspective of ecosystem services, providing a new approach for a more comprehensive understanding of the impact of drought on ecosystem service functions.

Integrating machine learning algorithms and fuzzy AHP for assessing livelihood vulnerability in Southwestern Coastal Bangladesh

The people living in the coastal regions of Bangladesh rely significantly on nature for their livelihoods, which renders them sensitive to climate change. The aim of this study is to determine the key indicators which contribute more to livelihood vulnerability of disaster-prone Gabura union in southwestern coastal Bangladesh. To achieve this goal, three machine learning algorithms are employed for determining the key indicators of livelihood vulnerability. Subsequently, a livelihood vulnerability index (LVI) is constructed using these key indicators with the weighting of indicators facilitated by Fuzzy AHP method. And finally, a livelihood vulnerability map (LVM) is generated to visualize the spatial distribution and analysis of livelihood vulnerability within the union. The study employs a mixed-methods approach, including questionnaire surveys, focus group discussions, key informant interviews, and remote sensing image analysis. A household survey of 950 households tracked livelihood vulnerability using 25 indicators across three domains of vulnerability, e.g., exposure, sensitivity, and adaptive capacity. ArcGIS and Google Earth Engine facilitated spatial data analysis. The Gabura Union exposed high vulnerability (LVI 0.63), driven by elevated exposure (0.61) and sensitivity (0.59) and lower adaptive capacity (0.30). The Livelihood Vulnerability Map (LVM) illustrates vulnerability across wards of the union, emphasizing high vulnerability zones on the periphery of the union, along the Kopothakho and Kholpetua rivers while central part of the union shows a moderate vulnerability level. The study's novelty lies in effectively integrating multiple methods for livelihood vulnerability assessment. Policymakers should target interventions focusing on areas along the Kopothakho River, to enhance community resilience.

Application of the DRASTIC-LU/LC method combined with machine learning models to assess and predict the vulnerability of the Rmel aquifer (Northwest, Morocco)

The Rmel aquifer, located in the Tangier-Tetouan-Al Hoceima region of northwest Morocco, covers approximately 240 km2 and faces increasing pollution threats due to population growth and economic development. This study assesses aquifer vulnerability to pollution, and compares the performance of various machine learning models integrated with the DRASTIC-LU/LC method. The research used a dataset of 52 water samples analyzed for nitrate concentrations, considering eight factors influencing vulnerability: aquifer depth, net recharge, aquifer lithology, soil texture, topography, vadose zone impact, hydraulic conductivity, and land use. An information gain test was applied to evaluate the importance of these factors. Four machine learning algorithms were used with the DRASTIC-LU/LC method: multilayer perceptron (MLP), the bagging algorithm (BA), K-nearest neighbors (KNN), and extremely randomized trees (ERT). Model performance was assessed via the area under the ROC curve (ROC-AUC) to measure accuracy. The ERT model combined with DRASTIC-LU/LC achieved the highest accuracy (AUC = 0.929), followed by BA (AUC = 0.925), MLP (AUC = 0.852), and KNN (AUC = 0.787). In comparison, the original DRASTIC-LU/LC model had an AUC of 0.530. The results highlight significant vulnerability variation across the Rmel aquifer, with high to very high levels in the southern and northwestern regions, and moderate to low levels in the northeast and central areas. Vulnerability maps were validated by comparing the observed nitrate concentrations in the water samples, confirming model accuracy. Groundwater depth, net recharge, and hydraulic conductivity were identified as the most significant factors influencing vulnerability. This study demonstrates the effectiveness of integrating machine learning models with the DRASTIC-LU/LC method for accurate aquifer vulnerability assessment, offering valuable tools for public policy and groundwater management.

A Review of Methods to Assess Groundwater Vulnerability to Pollution

Groundwater resources that are increasingly being cherished for most socioeconomic development are exposed to varied pollutant sources. Studies have shown that they are vulnerable to various impacts such as climatic change, human impacts and also pollution from seawater intrusion in coastal areas. The susceptibility of a groundwater body to pollution indicates extent to which its quality is at risk of being compromised by contaminants. Assessments of this vulnerability are classified based on scale (site, local, regional) or objective (such as risk management or protection zoning) and also distinguish between source and resource vulnerability maps, as well as specific and intrinsic vulnerability maps. Groundwater vulnerability assessment methods differ based on several factors, including the availability and spatial distribution of quantitative and qualitative data, the objectives and scale of the mapping, the costs of model development, and the particular hydrogeological characteristics of the aquifer under investigation. The National Research Council has classified these methods into three primary categories: process-based methods, statistical methods, and overlay/index methods. Among these, the overlay/index method is widely employed for conducting large-scale assessments of aquifer sensitivity and groundwater vulnerability. It is especially advantageous in developing countries due to the easily accessible data required for its implementation.

Identification and Evaluation of Vulnerable Links in a Distribution Network with Renewable Energy Source Based on Minimum Discriminant Information

With the increase in the proportion of photovoltaic and wind power access, the scale and form of distribution networks are becoming more and more complex. The traditional single distribution network vulnerability assessment method is difficult to use to identify the vulnerable links in the distribution network. Therefore, this paper proposes a method for identifying and evaluating vulnerable links in distribution networks based on minimum discriminant information. First, considering the influence of distributed grid connection, an improved probabilistic power flow calculation method is proposed, which improves the calculation efficiency and accuracy. Second, considering the correlation degree, transmission capacity, and voltage stability of branches in the distribution network, the identification index of vulnerable lines is defined. Based on power quality and operating state, the identification index of vulnerable nodes in a distribution network is defined. Finally, based on the indicators of vulnerable nodes and vulnerable lines, the vulnerable links in the distribution network are comprehensively evaluated based on the principle of minimum discriminant information, and the vulnerable links of the entire distribution network are evaluated according to different degrees of vulnerability. The rationality and effectiveness of the proposed method are verified via an example analysis of actual power grid data.

Climate change vulnerability assessment in the new urban planning process in Tanzania

Climate change vulnerability assessment is an essential tool for identifying regions that are most susceptible to the impacts of climate change and designing effective adaptation actions that can reduce vulnerability and enhance long-term resilience of these regions. This study explored a framework for climate change vulnerability assessment in the new urban planning process in Jangwani Ward, Tanzania. Specifically, taking flood as an example, this study highlighted the steps and methods for climate change vulnerability assessment in the new urban planning process. In the study area, 95 households were selected and interviewed through purposeful sampling. Additionally, 10 respondents (4 females and 6 males) were interviewed for Focus Group Discussion (FGD), and 3 respondents (1 female and 2 males) were selected for Key Informant Interviews (KII) at the Ministry of Lands, Housing and Human Settlements Development. This study indicated that climate change vulnerability assessment framework involves the assessment of climatic hazards, risk elements, and adaptive capacity, and the determination of vulnerability levels. The average hazard risk rating of flood was 2.3. Socioeconomic and livelihood activities and physical infrastructures both had the average risk element rating of 3.0, and ecosystems had the average risk element rating of 2.9. Adaptive capacity ratings of knowledge, technology, economy or finance, and institution were 1.6, 1.9, 1.4, and 2.2, respectively. The vulnerability levels of socioeconomic and livelihood activities and physical infrastructure were very high (4.0). Ecosystems had a high vulnerability level (3.8) to flood. The very high vulnerability level of socioeconomic and livelihood activities was driven by high exposure and sensitivity to risk elements and low adaptive capacity. The study recommends adoption of the new urban planning process including preparation, planning, implementation, and monitoring-evaluation-review phases that integrates climate change vulnerability assessment in all phases.

GIS based – GALDIT method for aquifer vulnerability assessment to seawater intrusion: Case of a qp2-3 aquifer of Mekong Delta

Recently, seawater intrusion (SWI) in coastal aquifers is a global issue that is exacerbated by sea-level rise, climate change, and an increasing dependency on coastal fresh groundwater resources for water supply. Vietnam's Mekong Delta has a flat topography, a dense river network, and a 700 kilometer coastline covering the region's west and east. The Mekong Delta is facing increasingly serious saline intrusion. This paper describes the results of the examination using the GALDIT method as a model to evaluate the vulnerability of seawater intrusion. The method is used to determine the trend of groundwater contamination by seawater intrusion in the qp2-3 aquifer of the Mekong Delta, this Upper-middle Pleistocene aquifer (qp2-3) is one of the main productive aquifers in the Mekong Delta. The analysis result in 2015 shows a moderate and high level of vulnerability in which the highly vulnerable area is along the Tien River and at the depression cone area in Ca Mau. The analysis is reconducted for the time of 2030 with the predicted values for the groundwater level through the forecasting tool. By comparing the model of two times of 2015 and 2030, the results indicated that the impact of the continuous decline of groundwater level is greater than the impact of sea level rise. If the rate of drawdown is kept the same, by 2030 the highly vulnerability area will have expanded to two-thirds of the Mekong Delta. The GALDIT method is a good approach for saltwater intrusion research and moreover water management, and environmental management, such as evaluating the most sensitive areas for monitoring or imposing restrictions where necessary.

A meta-ensemble machine learning strategy to assess groundwater holistic vulnerability in coastal aquifers

Assessing the vulnerability of groundwater in coastal aquifers is crucial for mitigating risks associated with seawater intrusion and anthropogenic impacts. This study introduces an innovative machine learning (ML)-enhanced methodology that synergizes the strengths of two established vulnerability assessment frameworks, DRASTIC and GALDIT. The hybrid approach overcomes the limitations of each framework—DRASTIC's inadequacies in coastal settings and GALDIT's limited consideration of agricultural and industrial impacts. Utilizing advanced decision tree-based ML algorithms—Adaptive Boosting (AdaBoost), Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LGBM), and Random Forest (RF)—this research was conducted in the Azarshahr Plain, NW Iran. Model efficacy was validated using Pearson's correlation coefficient (r) and distance correlation (DC), with nitrate (NO3−) and total dissolved solids (TDS) serving as proxies for evaluating the DRASTIC and GALDIT models, respectively. The original DRASTIC indices exhibited weak correlations with NO3− (r = 0.24, DC = 0.25), but ML-enhanced models, particularly AdaBoost, showed significant improvements (r = 0.78, DC = 0.79). Similar enhancements were observed with GALDIT, where correlations improved markedly with AdaBoost integration. A sophisticated second-level AdaBoost meta-ensemble was developed to integrate enhanced DRASTIC and GALDIT assessments, achieving superior correlation metrics (r = 0.80, DC = 0.84 for NO3−; r = 0.82, DC = 0.83 for TDS). These results underscore the effectiveness of an integrated ML-based approach in advancing beyond traditional vulnerability assessment methods, providing a more comprehensive, accurate, and robust evaluation of coastal aquifer vulnerability.

Assessment of risk intensity in the triffa plain aquifer: Integration of hazard quantification, land use analysis, dynamic vulnerability GCITF, and DRASTIC method

This study aims to assess the level of groundwater pollution risk in the Triffa Plain, stemming from various pollution sources, with a specific focus on agricultural intensification and excessive pesticide use. Data were collected from ABHM (the Moulouya Hydraulic Basin Agency) and ORMVAM (Regional Office of Moulouya Agricultural Development), and a field visit was conducted in July 2023. The study utilized two main methodologies for mapping risk intensity: the COST 620 action and overlaying vulnerability maps with the land use (LU) factor. Vulnerability maps were generated using the original DRASTIC method and the new dynamic vulnerability assessment method, GCITF.The research approach involved comparing the COST 620 risk index (Ri) and the land use risk index (LU) to identify the most suitable method for the study area. Due to challenges in inventorying various point sources of pollution, the study focused on mapping the primary sources of pollution (diffuse, point, and linear). The key findings indicate that the predominant pollution intensity in the region is high, covering 60.66% of the total surface area. These results closely align with those obtained using the European COST 620 approach and the spatial distribution of nitrates. The study demonstrates the reliability of integrating the GCITF method in assessing groundwater contamination risk, highlighting the significant negative impacts of agricultural activities on the Triffa Plain aquifer, primarily due to uncontrolled pesticide and fertilizer use and point sources of pollution.This study suggests that implementing targeted technical solutions for specific pollution sources is crucial for reducing contamination in the Triffa Plain. These pollution risk intensity maps can assist planners and decision-makers in understanding the origin of pollution and identifying necessary actions to minimize contamination risk, contributing to better groundwater management and protection in the region.

Physics-based flood vulnerability assessment for steel portal framed industrial buildings

Steel portal framed industrial buildings have been widely used as warehouses, supermarkets, manufacturing workshops and storage facilities around the world. As such, these buildings make up a significant portion of the building stock. Despite this, there remains a lack of the physics-based flood vulnerability models necessary for undertaking detailed community flood risk management activities (e.g., quantitative risk assessment, cost-benefit analysis of risk reduction and resilience enhancement measures at the building level). To this end, this study developed a physics-based vulnerability assessment method for steel portal framed industrial buildings subjected to hydrostatic and hydrodynamic flood actions. Physical damage induced by flood forces to the building envelope (wall siding and fenestration) and the structural framing (steel portal frames and end wall frames) was considered. Monte Carlo simulations incorporate various flood load cases, probability models of demands and capacities as well as major failure mechanisms of different structural and non-structural components to conduct the damage assessment. The flood vulnerabilities for a prototype industrial building link the physical damage of individual building subassemblies to monetary loss ratios considering various inundation depths, flow velocities and flow directions.

Analysis Vulnerability Website Baleomolcreative dengan Metode Penetration Testing Execution Standard & Vulnerability Assessment Pada Http Response Header Field

This research will analyze web security and how to find out whether there is a vulnerability or what could be called a vulnerability to enter gaps in the Baleomolcreative web, making the web unsafe. In analyzing whether there are vulnerabilities, the Penetration Testing Execution Standard and Vulnerability Assessment methods are used to determine whether there are gaps or vulnerabilities in the Baleomolcreative website that can be exploited by external parties. This method uses tools such as Owasp ZAP, Nikto, and Nmap which can be used to perform vulnerability scanning on a website. In this research, we succeeded in identifying 3 levels of vulnerability on the Baleomolcreative website, namely medium, low, and informational, with a total of 18 alerts generated from notifications on Owasp Zap. The scanning process includes vulnerability testing such as Content Security Policy, Anti-clickjacking Header, Dangerous JS Functions, Permissions Policy, and others.

Penerapan Metode Vulnerability Assessment untuk Identifikasi Keamanan Website berdasarkan OWASP ID Tahun 2021

Universities, as educational institutions, are potential targets of cyber attacks. This is inevitable problem, one of which the University of Papua (UNIPA). The purpose this research is to find the security gaps the UNIPA website based on OWASP ID in 2021 and implement mitigation. Type of research is quantitative research with Vulnerability Assessment and Penetration Testing Life Cycle (VAPT) method. The VAPT method in research goes through five stages, namely scope, information gathering, vulnerability assessment, risk assessment, and reporting. The object of research is UNIPA website. Data collection uses primary data, the results of scanning the Zed Attack Proxy (ZAP) application. Data obtained from alerts ID, alerts, risk, and OWASP ID as information on vulnerability of UNIPA website. Research data analysis using OWASP ID. The results our findings, the vulnerability of UNIPA website is influenced by two factors, website security weaknesses and user negligence. Vulnerabilities with alerts ID A1, A2, A3, A4 A5, and A6 are a group website security weaknesses. The solution, vulnerabilities need utilize special systems such as anti-CSRF, CSP, CDN, Strict-Transport-Security Header, and timestamp checking so that the website is proportional. Meanwhile, the vulnerability with alerts ID A7 is a classification of user negligence. The solution is users must use the latest version of the browser. Browsers with latest version have X-Content-Type-Options: nosniff security mechanism to prevent sniffing attacks.

On the development of a standardised method for climate vulnerability and risk assessment (CVRA) for buildings and properties

On the development of a standardised method for climate vulnerability and risk assessment (CVRA) for buildings and properties

A Dual-Layer Complex Network-Based Quantitative Flood Vulnerability Assessment Method of Transportation Systems

Evaluating the vulnerability of urban transportation systems to flood disasters can provide scientific support for urban disaster prevention and mitigation. Current methods for assessing the flood vulnerability of urban roads often overlook the internal relationships within the complex spatial composition of road networks and surface structures. In this study, based on the theory of complex networks, a dual-layer network assessment model is established for evaluating the flood vulnerability of urban transportation systems by coupling basic geographic data with road network vector data. Unlike traditional methods, this model considers the complex relationship between road network structures and ground surfaces, uncovering a correlation between road network structure and road flood vulnerability. By utilizing this model, the flood vulnerability of road networks in Shenzhen, as well as the city’s spatial flood vulnerability, are quantitatively assessed. Based on the quantitative results, we create maps illustrating the distribution of road and spatial flood vulnerability in Shenzhen. The study results reflect that roads highly vulnerable to flooding are mainly located in the central urban area of the southwest, with the flood vulnerability spatially concentrated primarily in the northern and western regions. Using data from government reports, news stories, and other sources over the past five years, we compile recorded instances of urban waterlogging. The quantitative results of the model are consistent with the distribution trend in recorded waterlogging points, indicating that the model’s outcomes are authentic and reliable.

Collapse analysis and robustness assessment of dropped-story steel frame structures based on structural vulnerability theory

ABSTRACT This paper proposes an improved analysis method based on the theory of structural vulnerability, which incorporates structural redundancy and comprehensively analyzes structural vulnerability and robustness by considering the changes in structural stiffness and redundancy after damage to structural members under conventional loading. The improved method takes into account the changes in the strain energy of the structure after the damage of the structural members, which can be more in line with the actual situation of continuity collapse, and solves the complex process of traditional structural vulnerability theory that requires clustering and unclustering, greatly reducing the workload as well as solving the problem of not being able to find the critical members of the structure. The improved method is used to analyze the vulnerability of a 5-story dropped-story steel frame structure, to find the critical members of the structure based on the test data simulated by ABAQUS, to evaluate the robustness, and to propose improvement measures. The results show that the improved vulnerability assessment method is more reasonable and effective and can be applied to different steel frame structures.

A Study on The Heterogeneity of Tropical Cyclone Vulnerability Functions in Different Provinces along The Coastal Areas in China

Coastal regions in China have long been plagued by tropical cyclone (TC) disasters, and TC vulnerability function for disaster-bearing bodies is a widely used quantitative vulnerability assessment method in face of TCs. TC vulnerability functions may vary across different regions due to geographical heterogeneity, hindering this method from universal use. This study systematically collects a 15-year-long dataset from 12 provinces in China. Six alternative TC vulnerability functions are comprehensively investigated by province, and a library of the optimal TC vulnerability functions for three kinds of disaster-bearing bodies, that is, economic, population, and crop in different provinces is developed. The heterogeneity of TC vulnerability in different provinces along the coastal areas in China is then thoroughly analyzed. This paper provides a deeper understanding of the spatial heterogeneity characteristics of disasters and disaster-bearing bodies, and provides good references for local departments to carry out more targeted disaster prevention and reduction work.