Disaster Risk Assessment Research Articles

Research on Geological Disaster Risk Assessment Method Based on GIS in Changji City, Xinjiang

This study takes the risk assessment of geological disasters in Changji City as the research object. By reviewing the detailed investigation report and risk survey documents of 1:50000 geological disasters in Changji City, along with the annual verification, investigation, and exploration results of major hidden danger points, we collected and organized the necessary data for the assessment and integrated multidisciplinary knowledge such as geology, GIS technology, and statistics. The study aims to identify the inducing factors, development characteristics, and distribution law of geological disasters in the area, thereby determining the risk assessment factors. To ascertain the weight of these factors, we employed an evidence weight model and a machine learning method. The vulnerability assessment, incorporating existing basic data and vulnerability factors such as population density, building density, and road density, was conducted using fuzzy mathematics for Changji City. Finally, the risk assessment used the ArcGIS analysis function to calculate the risk and vulnerability assessment results. Through ArcGIS, we superimposed the risk grade and vulnerability grade of geological disasters on a grid, ultimately obtaining the risk assessment results for the study area.

Risk assessment of coastal flooding disaster by storm surge based on Elevation-Area method and hydrodynamic models: Taking Bohai Bay as an example

Risk assessment of coastal flooding disaster by storm surge based on Elevation-Area method and hydrodynamic models: Taking Bohai Bay as an example

An empirical study on construction emergency disaster management and risk assessment in shield tunnel construction project with big data analysis

An empirical study on construction emergency disaster management and risk assessment in shield tunnel construction project with big data analysis

An empirical study on construction emergency disaster management and risk assessment in shield tunnel construction project with big data analysis

An empirical study on construction emergency disaster management and risk assessment in shield tunnel construction project with big data analysis

Research on Landslide Disaster Risk Assessment Method Based on GIS and Information Model

In this paper,a geological disaster early warning model is constructed based on GIS,and a susceptibility evaluation system is constructed by using GIS spatial information system to obtain seven influencing factors,including slope,topographic relief,slope shape,rock and soil mass type,geological structure,land use type and vegetation coverage rate.The information quantity value of each influencing factor is determined based on the information model method.At the same time,the hidden points of geological disasters in research area are superimposed and the prone zones are divided to provide reference for the prediction and prevention of geological disasters in this area.

Exploring Cascading Disaster Risk During Complex Emergencies: Chemical Industry Disaster Risk Assessment in the Aftermath of the Kakhovka Dam Bombing in Ukraine.

This risk assessment aims to investigate the analysis of cascading disaster risks from the perspective of the chemical industry and public health subsequent to the Kakhovka dam bombing in Ukraine. The study utilized a modified observational cross-sectional risk assessment method to assess disaster risk. The method involved identifying the location of chemical factories, determining flooded or at-risk factories, analyzing the type and frequency of chemical hazards, assessing population exposure, and plotting a disaster risk metric. Data on chemical industries and flood extent were collected from open-source secondary data. The destruction of the Kakhovka dam in June 2023 led to severe flooding, placing 42 000 individuals at risk. The analysis identified four chemical factories, with 1 affected by flooding and 3 at risk. The overall risk assessment indicated a high likelihood and severe consequences, including loss of life, environmental contamination, and property damage. The combination of complex emergencies and high-risk chemical facilities in Kherson Oblast poses a significant risk of a chemical industry disaster. The interplay between compound and cascading risks during complex emergencies amid the current war further exacerbates the situation, leading to the devastation and destruction of the environment to the detriment of life, and aligns with the characterization of ecocide.

기후변화 시나리오 기반 연안재해 위험평가 방안 연구

기후변화 시나리오 기반 연안재해 위험평가 방안 연구

Investigation of the microscopic properties of natural structured clay

Conducting quantitative research on the microstructure of soft clay can reveal the essence of its soil mechanical behavior, which is of important practical significance for geological disaster risk assessment and prevention. To quantitatively investigate the microscopic properties of natural structured clay, soft clay soils from various sedimentary environments in the Hangzhou Estuarine Bay area were chosen as the research subject in this study. Subsequently, a comprehensive investigation into the microstructure of clay was conducted, involving X-ray phase analysis and SEM imaging analysis. The results revealed the following: (1) In comparison to the deep clay deposited in fluvial-lacustrine environments, the shallow mucky clay in marine sediments had a higher clay mineral content, accounting for 48%. Illite makes up the majority of it, with minor levels of kaolinite and montmorillonite being present. (2) The shallow mucky clay in the Hangzhou Estuarine Bay area had a typical agglomerate-flocculated structure. In contrast, the deeper clay showed a flocculated structure with less uniform particle sizes, strong stacking randomness, poor directional alignment of soil pores, and tends to form arrangements where edges are adjacent to faces or edges are adjacent to other edges. (3) Compared to the deep clay deposited in fluvial-lacustrine environments, the marine-deposited shallow mucky clay displayed orderly pore arrangements, strong directional alignment, significant pore shape variability, and minimal pore size changes between adjacent pores. The microstructure of soil plays a crucial role in determining the physical, mechanical, and other engineering properties of the soil. This study provides insightful information about the relationship between clay microstructure and geotechnical characteristics in Hangzhou and the surrounding areas.

Risk assessment of flood disasters in the Poyang lake area

Floods are one type of common and catastrophic disaster and cause extensive destruction areas, enormous casualties, and huge economic and environmental losses worldwide. Flood risk assessment is crucial to disaster mitigation and prevention, social stability and prosperity, and economic and environmental sustainability. This work establishes comprehensive risk indices of geoenvironmental, disaster-triggering, disaster-vulnerable, and disaster-preventive factors to improve the rationality of risk assessment. Moreover, a novel combined method of context-perception long short-term memory (LSTM), analytic hierarchy process, and entropy weight is suggested to perform relative accurate risk assessment in the Poyang lake region, one of the worst-hit areas in China. The new context-perception LSTM algorithm can adequately learn comprehensive and significant context characteristics and outperforms the context-based convolutional neural network and conventional LSTM algorithms. The test precision reaches 95.7%, 99.1%, 0.958, and 0.981 in Accuracy, TPR, F1-score, and AUC, respectively. Some significant insights into flood risk are suggested as follows. (1) High flood risk mainly occurs in the densely populated regions with gentle topography close to main streams. The concentrated population and intensive town construction have destroyed surface permeability and soil consolidation and caused high flood risk. (2) In the high-risk urban regions, the operational condition of old soil dikes should be continuously monitored, and the construction of high rock dikes are necessary to effective flood prevention in the future. In the densely-populated and high-risk urban regions, more emergency rescue infrastructures, for example hospitals and emergency shelters, are required to arrange or build. Rational planning of emergency shelters can not only protect people against floods but also reduce government investment. (3) Significant hydrological infrastructures require high-frequency or even near real-time monitoring to timely discover engineering diseases and to avoid huge losses caused by unstable prevention infrastructures during flash floods.

Risk Assessment and Analysis of Geological Disaster of Hydraulic Engineering Environmen

The formation of hydraulic engineering environmental geohazards is mostly caused by human factors, rough investigation, illegal operation, and improper countermeasures can trigger or even magnify the hazardous degree and scope of geohazards. Timely, scientific and accurate assessment of the risk of hydraulic engineering environmental geohazards is an important means to prevent disasters and reduce losses. However, the risk assessment needs to refer to a variety of information, and in many cases, it rely on the work experience of the assessors, so the actual work is carried out in a mixed situation, resulting in a huge disaster hidden danger. It is necessary to sort out the recent assessment work, sum up the experience and analyze the interests in order to point out the direction for future work.

Disaster Risk Assessment for Railways: Challenges and a Sustainable Promising Solution Based on BIM+GIS

Natural hazards constantly threaten the sustainable construction and operation of railway engineering facilities, making railway disaster risk assessment an essential approach to disaster prevention. Despite numerous studies that have focused on railway risk assessment, few have quantified specific damages, such as economic losses and human casualties. Meanwhile, the mechanism of impact damage from various disasters on railway facilities and the propagation of functional failure in railway systems have not been thoroughly summarized and addressed. Thus, it is essential to conduct effective quantitative risk assessments (QRAs) to facilitate the sustainable design, construction, and operation of rail infrastructure. This paper aimed to review and discuss the systematic development of risk assessment in railway engineering facilities. Firstly, we highlighted the importance of disaster QRA for railway facilities. Next, numerous limitations of QRA methods were concluded after conducting a comprehensive review of the risk assessment research applied to railway facilities, such as bridges, tunnels, and roadbeds. Furthermore, true QRA (TQRA) application in railway engineering has faced several significant challenges. Therefore, we proposed a promising TQRA strategy for railway engineering facilities based on the integration of building information modeling (BIM) and geographic information systems (GIS). The proposed BIM+GIS technology is expected to provide sustainable future directions for railway engineering QRA procedures.

Estimation of regional and at-site quantiles of extreme winds under flood index procedure

Extreme winds are becoming more common among environmental events with the most catastrophic societal consequences. A regional frequency analysis of Daily Annual Maximum Wind Speed (DAMWS) is necessary not only for a comprehensive understanding of wind hazards but also for infrastructure design and safety, wind energy potential, disaster risk reduction, insurance and risk assessment in a particular region of study. This study investigated regional frequency analysis of DAMWS of Baluchistan and Sindh provinces of Pakistan. L-moments regionalization techniques along with flood index procedure were applied to DAMWS records of 21 stations from 1990 to 2019 across the study area. We intended to find the regional frequency distribution for maximum winds and predict the returns for extreme winds events in the future. Only one station namely Lasbella was found to be discordant. With the help of cluster analysis, the remaining 20 stations were further divided into two homogeneous. Heterogeneity measures validate that both regions are homogenous with allotted stations. Regional quantiles for both regions are estimated through best-fit probability distribution among Generalized Normal (GNO), Generalized Logistic (GLO), Pearson Type 3 (P3), Generalized Pareto (GPA), and Generalized Extreme Value (GEV). Robustness of GLO distribution compared to GEV distribution is assessed through Monte Carlo simulations of relative bias and relative root mean square error. Findings clearly show that GLO distribution is the best for regional modeling. Furthermore, with the help of index flood procedure we determined at-site quantiles of all stations for various return periods. These estimated quantiles are of valuable information for various sectors, including infrastructure, energy, disaster management, and climate resilience, leading to improved planning, development, and risk reduction in the face of wind-related hazards in Sindh and Balochistan provinces of Pakistan.

Risk Assessment of Landslide Collapse Disasters along National Highways Based on Information Quantity and Random Forest Coupling Methods: A Case Study of the G331 National Highway

Based on the data from two field surveys in 2015 and 2022, this paper calculates the weight of values using the entropy weight method and the variation coefficient method, and evaluates risk using the information quantity method. The information quantities of four levels of criteria (hazards, exposure, vulnerability, emergency responses, and capability of recovery) were extracted and inputted into a random forest model. After optimizing the hyperparameters of the random forest using GridSearchCV, the risk assessment was performed again. Finally, the accuracy of the two evaluation results was verified using an ROC curve, and the model with the higher AUC value was selected to create a risk map. Compared with previous studies, this paper considers the factors of emergency responses and recovery capability, which makes the risk assessment more comprehensive. Our findings show that the evaluation results based on the coupling model are more accurate than the evaluation results of the information method, as the coupling model had an AUC value of 0.9329. After considering the indices of emergency responses and capability of recovery, the risk level of the highest-risk area in the study area decreased.

Identification of urban waterlogging indicators and risk assessment based on MaxEnt Model: A case study of Tianjin Downtown

Waterlogging is one of the world's most dangerous climatic hazards, seriously limiting the safety and sustainable development of cities. Analysis of the factors influencing urban waterlogging and disaster risk assessment are of great importance for the prevention and control of waterlogging. The study constructs a framework for assessing Urban Waterlogging Risk (UWR) from four dimensions: natural condition, social capital, infrastructure and built environment, emphasizing the need to understand and address the vulnerabilities and risks faced by cities in terms of waterlogging. On this basis, the MaxEnt model is used to rank the contribution rate of the indicators and identify positive and negative correlations, as well as to assess the risk of waterlogging and identify waterlogging-prone areas, taking Tianjin Downtown as the research object. The results show that: (1) MaxEnt model has strong applicability for waterlogging risk assessment. (2) The elements with the highest impact on urban waterlogging are population density, impervious surface, precipitation, etc., and prove that the regional waterlogging risk increases with the increase of population, building density, and impervious surface. (3) The high-risk area of waterlogging in Tianjin Downtown is concentrated in the central part of the city, which is characterized by a high degree of development and construction and a dense population; the low-risk area is mainly the area with a low degree of construction at the edge of the city, as well as the area with a large green area or water bodies. In this study, a comprehensive framework for assessing UWR was developed, key factors affecting the spatial distribution of UWR were identified, and the MaxEnt model was used to perform the risk assessment with a high degree of accuracy. The study results can provide a theoretical reference for the urban disaster warning and land use optimization.

MCDM-Based Wildfire Risk Assessment: A Case Study on the State of Arizona

The increasing frequency of wildfires has posed significant challenges to communities worldwide. The effectiveness of all aspects of disaster management depends on a credible estimation of the prevailing risk. Risk, the product of a hazard’s likelihood and its potential consequences, encompasses the probability of hazard occurrence, the exposure of assets to these hazards, existing vulnerabilities that amplify the consequences, and the capacity to manage, mitigate, and recover from their consequences. This paper employs the multiple criteria decision-making (MCDM) framework, which produces reliable results and allows for the customization of the relative importance of factors based on expert opinions. Utilizing the AROMAN algorithm, the study ranks counties in the state of Arizona according to their wildfire risk, drawing upon 25 factors categorized into expected annual loss, community resilience, and social vulnerability. A sensitivity analysis demonstrates the stability of the results when model parameters are altered, reinforcing the robustness of this approach in disaster risk assessment. While the paper primarily focuses on enhancing the safety of human communities in the context of wildfires, it highlights the versatility of the methodology, which can be applied to other natural hazards and accommodate more subjective risk and safety assessments.

The Global Evolution of Ecological Communication Studies in Disasters: A Bibliometric Analysis

The urgency of ecological communication is critical, given the increasingly complex and urgent challenges caused by disasters. The purpose of this research is to evaluate the development of studies on disaster-related ecological communication. This study uses bibliometric analysis, in which the data source comes from the Scopus database. The analysis tool used is Vosviewer. The findings of this study indicate that the number of publications discussing ecological communication in disasters has increased significantly in recent years. The main focus of the research findings includes disaster prevention, risk assessment, climate change, and natural disasters. This research provides important insights into the role of communication in responding to disasters and environmental challenges and building community resilience. Ecological communication research trends in disasters open prospects to expand understanding and develop effective communication strategies to face environmental challenges and disasters in the future. The results of this research can be used as a basis for developing more effective communication strategies in facing environmental challenges in the future.

Spatio-temporal variation and dynamic risk assessment of drought and flood disaster (DFD) in China

It is important to understand the variations of Drought-Flood-Disaster (DFD) from the past to future for disaster management decision-making under the backdrop of global warming. This study explored the spatio-temporal variations of DFD risks in China from the past (2000–2020) to future (2020–2100) based on the natural and socio-economic datasets. The main findings include: (1) The spatial pattern of disaster vulnerability decreased from 2000 to 2100. The overall vulnerability distribution showed a spatial pattern of high east and low west, and its eastern distribution presented high north and low south. (2) The drought hazard danger degree showed a trend of decreasing first and then increasing with obvious spatial heterogeneity. The flood hazard danger degree had a decreasing spatial distribution from southeast to northwest, with an overall gradually increasing trend. (3) The DFD risks showed a spatial pattern of high east and low west, and were more closely related to disaster vulnerability. Overall, the flood and drought risks had good consistency at the highest level (VI), mainly distributed in the North China Plain, Northeast Plain, eastern Sichuan, and southern Guangdong. This level means that the most severe damage to life and property will occur in these regions. (4) The DFD showed the direction of “north(east)-south(west)”, and the main axis of the ellipse moved north eventually. The DFD hot spots were mainly distributed in North China and the middle and lower reaches of the Yangtze River. The DFD cold spots were mainly distributed in the southwest, Qinghai-Tibet region, and Gansu province.

Preliminary Risk Assessment of Geological Disasters in Qinglong Gorge Scenic Area of Taihang Mountain with GIS Based on Analytic Hierarchy Process and Logistic Regression Model

Qinglong Gorge Scenic Area (QGSA) boasts stunning natural landscapes, characterized by towering peaks and extensive cliffs. Nevertheless, the intricate geological backdrop and distinctive topographical conditions of this area give rise to various geological disasters, posing a substantial safety concern for tourists and presenting ongoing operational and safety management challenges for the scenic area. In light of these challenges, this study placed its focus on the geological disasters within QGSA and sought to assess risks across various scales. The assessment was accomplished through a combination of methods, including field surveys conducted in 2022, remote sensing interpretation, and comprehensive data collection and organization. For the geological disaster risk assessment of the scenic area, this research selected seven key indicators, encompassing terrain factors, geological elements, structural characteristics, and other relevant factors. The assessment utilized a logistic regression model, which yielded satisfactory results with an AUC value of 0.8338. Furthermore, a model was constructed incorporating seven indicators, encompassing factors such as population vulnerability, material susceptibility, and the vulnerability of tourism resources. To assess vulnerability to geological disasters, the Analytic Hierarchy Process (AHP) was employed, resulting in a CR of 0, thus ensuring the reliability of the findings. The outcomes of the risk assessment indicate that the low-risk area covers a substantial expanse of 5.45 km2, representing 53.66% of the total area. The moderate-risk area extends over 3.59 km2, constituting 35.43%, while the high-risk area encompasses 0.72 km2, accounting for 7.14%. Additionally, the very high-risk area encompasses 0.38 km2, making up 3.77% of the total area. Consequently, building upon the findings of the risk assessment, this paper introduces a risk classification and control prevention system. This system provides invaluable insights for disaster prevention and control in mountainous and canyon-type scenic areas.

Assessment of Urban Local High-Temperature Disaster Risk and the Spatially Heterogeneous Impacts of Blue-Green Space

Urban high-temperature disasters have gradually emerged as a significant threat to human society. Therefore, it is crucial to assess and identify areas at risk of such disasters and implement urban planning measures aimed at mitigating their impact. Additionally, a multitude of studies have demonstrated the significant cooling effect of urban blue-green spaces (UGBS), which play a pivotal role in urban environments. Incorporating a UBGS layout into planning and evaluation processes has substantial potential for mitigating high-temperature disasters. This paper presents the construction of a set of assessment processes for mitigating urban high-temperature disaster risk using a UBGS structure layout specifically for the main urban area of Harbin, China. We employed GIS and multi-source remote sensing imagery to develop local climate zone (LCZ) maps applicable to the designated study area. The differentiated impact of UBGS factors on high-temperature disaster risk was determined using the multi-scale geographical weighted regression model (MGWR). The results showed the following: (a) There was an overall low risk level, with 19.61% of the high-risk areas concentrated within the second ring road, forming a spatial pattern characterized by “one line, one cluster”. (b) The risk of the building category LCZs was generally higher than that of the natural category LCZs. The risk of the architectural LCZs could be summarized as the risk of low-density LCZs being smaller than that of the high-density LCZs, except LCZ 5. The mean value of the LCZ 2 and LCZ 5 types was the highest. (c) Through indicator screening, AREA_MN, SHAPE_MN, PD, and NP were found to be significant determinants influencing the risk, and the effectiveness and spatial differentiation of these main factors exhibited notable disparities. (d) By comparing different LCZ types, we concluded that the mitigation effect of these factors on risk may be interfered with by building height (BH); NP may be positively interfered with by BH; and PD and SHAPE_MN may be negatively interfered with by BH. The research results provided a new perspective and practical scientific basis for high-temperature disaster risk-mitigation planning based on UBGSs under LCZ classification.

Experimental and Statistical Study on the Formation Characteristics and Discrimination Criteria of River Blockages Caused by Landslides

The discrimination of river blockages is very important for the risk assessment of landslide disasters and secondary hazards. Experimental studies and statistical analyses were carried out to explore the formation process and discriminant criteria of river blockages caused by landslides. An adjustable slide chute was designed and built to conduct forty-five landslide experiments. According to the experimental results, river blockage was identified as having six types based on the differences between the water depth and the height of the landslide dam, and the degree of river blockage increased from 70% to 100% as the chute angle, particle size, and landslide volume increased. It is also found that landslide volume controls the landslide dam height and degree of blockage, and particle size and slide angle control both the landslide velocity as it enters the river and the cross-section shape of the landslide dam. To investigate more influence factors, a statistical investigation of 60 real landslide cases was carried out, and it revealed that some geometric attributes related to landslide volume have the highest correlation with river blockage, especially landslide thickness. Finally, an improved probability model was proposed to assess the possibility of complete blockage, and it has overall accuracies of 91.1% and 83.3% when applied to predict experimental landslide cases and real landslide cases, respectively.