Disaster Risk Evaluation Research Articles

Research on the Disaster Management of China’s Ethnic Minority Autonomous Regions in the Development of Modernization Construction—Taking Mabian Yi Autonomous County in Southern Sichuan as an Example

Many ethnic minority autonomous regions in China, mainly in mountainous areas, have caused great harm to people’s life and property safety due to frequent geological disasters. Therefore, it has become an urgent task for the government to create a system for predicting, preventing and effectively responding to disasters, and to strengthen the ability of relevant regions to jointly resist disasters. This paper takes Mabian Yi Autonomous County as the research object, and studies the disaster management of Mabian Yi Autonomous County. The research focuses on geological disaster vulnerability evaluation, geological disaster hazard evaluation, geological disaster risk evaluation, and geological disaster carrying capacity evaluation. The two elements of geological disaster risk evaluation are vulnerability evaluation and hazard evaluation. The main element of geological disaster carrying capacity evaluation is risk evaluation. Through evaluation, it is found that the central and eastern regions of Mabian Yi Autonomous County can be used as population concentration areas and develop modern agriculture and tourism. The western and northeastern regions can be used as nature reserves. Based on the above evaluation results, the disaster management opinions of Mabian Yi Autonomous County are given. This makes the government have a certain reference basis in the preparation of regional construction policy planning. From the perspective of unique disaster management, this paper provides the government with a political governance model for ethnic minority areas through the harmonious development of man and nature, to achieve a goal of sustainable development.

Emergy-Theory-Based Evaluation of Typhoon Disaster Risk in China’s Coastal Zone

The evaluation of typhoon disaster risk is a widely discussed global topic. Currently, the index system method has become a common approach for the evaluation of typhoon disaster risk. However, the indices within the system are calculated independently, and subjective human factors significantly influence the assignment of index weights. The existing studies lack purely quantitative assessment methods, which makes the studies less precise and more difficult for other researchers to replicate. To bridge this gap, this study employs emergy analysis methods based on thermodynamics to develop a typhoon disaster risk evaluation index system for China’s coastal zone. Without the interference of weights and other human factors, the system contains various quantitative indices, including aggregate impelling energy, typhoon intensity emergy, adaptability emergy, the vulnerability index, and the integrated typhoon hazard index. Subsequently, these indices and socio-economic data were spatialized, and the evaluation of typhoon disaster risk was conducted at the city grid level in the coastal zone of China. The findings reveal that the high-risk areas for typhoon disasters in China are concentrated in prefecture-level cities along the southeast coast. The typhoon disaster risk index is higher in the southern region compared to the northern region, with a decreasing trend in the distribution of the integrated typhoon hazard index from coastal to inland areas. The aim of this study is to use a new quantitative evaluation method (emergy) to evaluate typhoon disasters. It also serves as a theoretical foundation and technical support for national and local governments in the formulation of policies for disaster prevention and reduction.

Holistic evaluation of climate risk to prioritise adaptation measures for ecosystems

The holistic approach has been applied to disaster risk evaluation at various scales, ranging from the urban to the national level, utilising deterministic and probabilistic physical risk results that concentrate on structures, infrastructure, and population effects. This article proposes a methodology to holistically evaluate the climate risk for ecosystems. Furthermore, the article proposes a prioritisation of adaptation measures based on their results, taking into account the physical risk, the ecological fragility conditions, and the strategic relevance of ecosystems exposed to these conditions. The calculation includes three composite indicators. The ecological fragility factor (FEF) estimates the capacity (or lack of capacity) of the ecosystem to absorb and recover, revealing vulnerabilities that may not be immediately evident but that can profoundly affect the long-term health and stability of the ecosystem. The ecosystem strategic relevance factor (FSR) helps to understand its fundamental role in supporting biodiversity and ecosystem services. The physical risk assessment does not account for the environmental and ecological aspects quantified through indicators in the FEF and FSR. A total risk index, RT, is calculated based on a probabilistic climate risk evaluation and the previously mentioned factors. This methodology is applied to the climate risk evaluation of Colombian ecosystems. The authors conducted this evaluation in close collaboration with Colombia's Ministry of Environment and Sustainable Development, funded by the Inter-American Development Bank. Its application yields crucial insights for informed decision-making and strategic planning in climate adaptation efforts.

Uncertainty Analysis of Post-Failure Behavior in Landslides Based on SPH Method and Generalized Geotechnical Random Field Theory

In slope stability analysis, the inherent heterogeneity and spatial variability of soil significantly influence the aftermath of landslides, including critical aspects like runout distance, influence distance, and volume. This research integrates Smoothed Particle Hydrodynamics (SPH) with random field theory to precisely model the large deformation events in slopes with anisotropic shear parameters, while leveraging Graphics Processing Unit (GPU) parallel computing to expedite the generation of random field samples and SPH simulations. This approach meticulously examines how spatial heterogeneity of soil affects slope instability, simulating soil parameters across varied geological settings. It considers the fluctuation scale of anisotropy, the cross-correlation of cohesion and the angle of internal friction, along with their coefficient of variation (CV), to elucidate their impact on landslide magnitude and severity. This study furnishes a robust tool for a holistic assessment of slope impacts and landslide volumes. Additionally, by delineating the computational efficiency disparities between GPUs and Central processing units (CPUs), it underscores the pronounced efficiency benefits of GPU computing. The insights garnered offer fresh perspectives and methodologies in slope stability analysis and disaster risk evaluation, contributing to the finer prediction and management of this prevalent and grave geological hazard.

Risk Assessment and Control of Geological Hazards in Towns of Complex Mountainous Areas Based on Remote Sensing and Geological Survey

Mountainous areas have become among the most developed areas of geological hazards due to special geological environmental conditions and intensive human engineering activities. Geological hazards are a main threat to urbanization, rural revitalization, and new rural construction in complex mountainous areas. It is of great strategic significance to conduct large-scale geological hazard investigation and risk assessment in urban areas, control the risk of geological hazards at the source and propose risk control measures. In this paper, we established the technical methods of geologic hazard risk assessment and control in complex mountain towns by taking Longlin Town in the mountainous region of Gansu Longnan, China as the study area, with the Quanjia bay debris flows and Panping Village landslides as the typical pilot investigation and assessment. The methods consist of six stages—risk identification, hazard disaster model investigation, risk analysis, vulnerability assessment, risk evaluation and risk management and control measures and proposals. On this basis, the results of geological hazards with different precipitation frequencies (5%, 2%, 1%) are presented. The results show that 75.23% of the regions remained at low risk levels; 24.38% of the regions increased a risk level with decreasing precipitation frequency, and 0.39% of the regions remained at extremely high risk levels under different precipitation frequency conditions. For the Quanjia bay debris flows and Panping Village landslides case, we discussed the geological hazards risk source control contents, management and control technologies, engineering and non-engineering measures of disaster prevention and control for urban disasters and specific disaster areas. This research can provide technical support and reference for disaster prevention and mitigation, and territorial spatial planning.

Aeolian disaster risk evaluation in the African Sahel

The Sahel is facing a serious environmental crisis due to aeolian disaster that has seriously affected the local development and survival of residents. Thus, evaluating the aeolian disaster risk levels and their variation in the Sahel is important. This study established an optimal model by evaluating the applicability of different models in the aeolian disaster risk determination in the Sahel. Using this model, the spatiotemporal changes in the risk subsystem of aeolian disaster (hazard, sensitivity, vulnerability, and restorability) and the aeolian disaster risk in the Sahel from 2000 to 2020 were analyzed. Based on this analysis, the impact of climate change and human activities on the aeolian disaster risk in the Sahel was evaluated. Results revealed that the variable fuzzy recognition (VFR) based on the aeolian disaster risk index (ADRI) model had the highest accuracy, reaching 89.72 %. The middle of the Sahel, located in the desert-grassland transition zone, exhibited a high hazard, sensitivity, and vulnerability, rendering it highly susceptible to aeolian disaster. The proportion of areas with very low and very high aeolian disaster risk levels decreased from 2000 to 2020, while those with low and high levels increased, and the change in moderate risk level areas remained relatively stable. Areas of low, moderate, and high risk are more sensitive to climate change and human activities and are subjected to greater pressure for change. Human activities were the main factor for the change of ADRI in the Sahel, accounting for 69.74 and 58.19 % of the increased and decreased areas of ADRI, respectively. This study evaluated the level of aeolian disaster risk in the Sahel and identified the main driving factors, providing a reference for Sahel countries to better implement the Green Great Wall (GGW) program in Africa, thereby mitigating the adverse effects of aeolian disaster.

Research Hotspots and Frontiers of Mountain Flood Disaster: Bibliometric and Visual Analysis

In the context of climate change, enhanced human activities and ecological changes, the danger level for mountain floods has increased significantly, posing direct or potential hazards to local residents. To determine the current status, focus and trends in mountain flood research, in this study, we visualize the number of publications and citations, the countries and institutions engaged in research, co-citations and key literature, keyword categories and research areas, using keyword timeline analysis and burst detection based on the bibliometric software CiteSpace and VOSviewer and the Web of Sciences core collection database. The results show that the total number of publications and citations in the mountain flood field has experienced rapid growth to date. The United States, China, Germany, the United Kingdom, and Switzerland are the main countries driving the development of the field. The field is of great interest within multiple disciplinary categories and is characterized by multiple research hotspots, multiple research objectives, and cross-fertilization of multiple disciplinary categories. Analysis of the keyword timeline network and highlighted words show that disaster risk evaluation based on remote-sensing technology, the alpine region of the Himalayas, the response mechanisms of heavy rainfall to mountain floods, and the construction of hydrological models, will be research hotspots in the future.

A Study on Risk Assessment of Geological Disasters in Pingba District of Guizhou Province Based on GIS

To conduct regional geological disaster risk evaluation zoning in a scientific and reasonable manner, and provide a decision basis for local territorial spatial planning, geological disaster risk prevention and control, and disaster prevention and mitigation work. This study, on the basis of collecting relevant data sources and field investigation, comprehensively analyzed and studied the geological environmental conditions of disaster pregnancy and the development and distribution pattern of current disasters in Pingba District, built an information volume model for susceptibility evaluation based on the influence factors of known disaster areas, and also reasonably determined the hazard and vulnerability evaluation model by combining the characteristics within Pingba District, thus making the risk evaluation of the county highly accurate, operable and scientific, and the results of its risk evaluation zone zoning are more consistent with he reality within the county. The risk evaluation methods and processes described above are synthesized with a view to providing reference and guidance for their application in similar work.

An empirical study of the key factors affecting herders' purchasing decision on weather index insurance—A case study from inner Mongolia autonomous region, China

The weather index insurance for mutton sheep (WIMS) is the first weather index insurance product that addresses the increased feeding cost-related risk of grassland animal husbandry herders in China. In 2019, the WIMS was implemented as a pilot project in 11 county regions of Xilin Gol League, Inner Mongolia, China. Since the implementation of this product, the purchasing rate has varied from region to region, as the highest purchasing rate was 84.3%, while the lowest was only 1.8%. This research uses the double hurdle model to identify the factors affecting herders' purchasing behavior. This paper reports a survey study of 535 participants herders in the Xilin Gol League. The result indicates that herders' age, disaster risk evaluation, insurance awareness, pasture area, and neighborhood purchasing decision significantly impact herders' purchasing propensity. Disaster evaluation, insurance awareness, pasture area and location significantly impact the purchasing degree of herders. The study suggests that young herders and herders with large pasture areas should be motivated to purchase insurance. In addition, new methods should be applied for the publicity of this insurance product; Investments should be focused on the automatic weather monitoring station projects in pastoral areas to reduce the basis risk of the insurance.

Evaluation of kinematic parameters and characteristics of the source zone of the debris flow in Kongniba Watershed

The characteristics of the source zone of the debris flow watershed is one of the most significant factors governing debris flows initiation, at the same time it also plays a crucial role for disaster risk evaluation. With the aim of obtaining the basic characteristics of the source zone and computing the kinematic parameters, field investigations were conducted comprehensively, combining with the results of remote sensing interpretation, the origin and distribution regulations can be identified, and total amount of the loose solid materials can be determined, the corresponding value is 4.91×106 m3. Using the collected data of this watershed, and with the help of previous theoretical models, the kinematic parameters under different rainfall frequencies are calculated, which including debris flow discharge, total volume of one-time debris flow and the total volume of solid materials. Such parameters are helpful and essential for debris flow disasters evaluation, prevention and designing mitigation measures.

Disaster Risk Evaluation of Superlong Highways Tunnel Based on the Cloud and AHP Model

Comprehensive evaluation of the geological disaster risk of super long tunnels is significant for safety construction. In this paper, we establish a comprehensive evaluation system based on the cloud model and analytic hierarchy process (AHP) theory, considering four kinds of geological hazards, such as water and mud inrush, large deformation, rock burst, and collapse. Then, based on a super long highway tunnel of the Chizhou‐Qimen expressway in China, the construction risk evaluation is carried out. The results show that the evaluation system can accurately judge the disaster risk level of the tunnel under different conditions surrounding a rock. The cloud model theory can realize the mutual transformation of qualitative indicators and quantitative indicators and avoid the problem of intense subjectivity of evaluation indicators. The evaluation system can be used as a new approach to evaluate tunnel risks in similar projects.

Detection and Disaster Risk Evaluation of Solar Photovoltaic Cells in Satellite Remote Sensing Data

Detection and Disaster Risk Evaluation of Solar Photovoltaic Cells in Satellite Remote Sensing Data

A novel comprehensive quantitative method for various geological disaster evaluations in underground engineering: multidimensional finite interval cloud model (MFICM)

The risk prediction of geological disasters exhibits extreme uncertainty and complexity due to the random distribution of evaluation indexes within a finite interval. To improve the accuracy of disaster prediction results, a new evaluation method is in this study suggested to perform a risk evaluation of geological disasters based on multidimensional finite interval cloud model (MFICM) and combination weighting. The MFICM with a transformation between qualitative concept and quantitative data depicts uncertainties and actual distribution features of indexes in the finite interval. Analytic hierarchy process and principal component analysis are adopted to determine the subjective and objective weights of evaluation indexes, respectively, and the combination weight is calculated by a linear method to reduce the influence of subjective factors. The numerical characteristic parameters of each indexes belonging to various risk levels are first calculated based on established evaluation index system. Subsequently, a multi-dimensional finite interval cloud is generated from a forward cloud generator using MATLAB software. Finally, the comprehensive certainty degrees relative to different levels for each sample are determined combined with combination weight, which achieves a mapping of uncertainty between semantic variables and index values. The proposed method is applied to engineering cases regarding three geological disasters, i.e., water inrush, rock burst and collapse. The obtained results with accuracy and results compared with reference methods show that the MFICM is verified to be practical and universal for the risk evaluation of geological disasters, which improves and enriches the theoretical framework of geotechnical engineering disaster risk evaluation.

Estimating the Key Parameter of a Tropical Cyclone Wind Field Model over the Northwest Pacific Ocean: A Comparison between Neural Networks and Statistical Models

Estimation of maximum wind speed associated with tropical cyclones (TCs) is crucial to evaluate potential wind destruction. The Holland B parameter is the key parameter of TC parametric wind field models. It plays an essential role in describing the radial distribution characteristics of a TC wind field and has been widely used in TC disaster risk evaluation. In this study, a backpropagation neural network (BPNN) is developed to estimate the Holland B parameter (Bs) in TC surface wind field model. The inputs of the BPNN include different combinations of TC minimum center pressure difference (Δp), latitude, radius of maximum wind speed, translation speed and intensity change rate from the best-track data of the Joint Typhoon Warning Center (JTWC). We find that the BPNN exhibits the best performance when only inputting TC central pressure difference. The Bs estimated from BPNN are compared with those calculated from previous statistical models. Results indicate that the proposed BPNN can describe well the nonlinear relation between Bs and Δp. It is also found that the combination of BPNN and Holland’s wind pressure model can significantly improve the maximum wind speed underestimation and overestimation of the two existing wind pressure models (AH77 and KZ07) for super typhoons.

Landslide Susceptibility Mapping Using Ant Colony Optimization Strategy and Deep Belief Network in Jiuzhaigou Region

Landslidesusceptibility mapping (LSM) is the primary link of geological disaster risk evaluation, which is significant for postearthquake emergency response and rebuilding after disasters. Existing LSM studies applying deep learning (DL) methods have shortcomings such as easy overfitting, slow convergence, and insufficient hyperparametric optimization. In response to these problems, this study proposes an ensemble model based on ant colony optimization strategy and deep belief network (ACO-DBN). In ACO-DBN, DL optimization strategies were added to DBN and their combined parameters were optimized with ACO. Next, Pearson's correlation coefficient and random forest importance ranking methods were utilized to optimize landslide causative factors. Then, the Jiuzhaigou earthquake region was selected as an example to explore the applicability of this model. Besides, we conducted the Wilcoxon signed rank test in order to verify that the differences were statistically significant. In a comprehensive comparative all indexes and landslide density, the model proposed in this article shows good rationality, scientificity, and interpretability. The newly occurred landslide site further demonstrates that heuristically optimized DL could make scientific and accurate evaluation of landslide susceptibility.

Route Selection and Disaster Risk Evaluation in the Whole Shikoku Region Starting from Takamatsu, Kagawa Assumed Immediately After the Catastrophe

In order to fulfill the purpose of logistic support for transporting commodities from Kagawa to other prefectures in Shikoku at the catastrophe, the characteristics of an existing emergency routes were clarified. Morever, alternative route selections to avoid the tsunami, landslide and liquefaction of the ground damage caused by the Nankai metathrust earthquakes were examined, and it revealed the disater risks included in the selected route quantitatively. In mountain areas, the necessity to develop the widely-enough roads which are expected to be transported by the large trucks was indicated because current road network has narrow parts intermittently. From the route selection results under multiple scenarios, the importance of considering by comprehensively judging the relationship among ensuring safety, extending the total distance to the destination and making a decision were indicated in case of emergency response.

A unified runup formula for solitary waves on a plane beach

Laboratory experiments to estimate solitary wave runup were performed on three different planar beaches with slopes of 1/4, 1/7 and 1/10, with varying wave heights and water depths. The non-dimensionalised vertical runup (runup over water depth) obtained from present laboratory data and several published sources were plotted against the surf similarity parameter. Best-fitting curves could be obtained for maximum runup on slopes ranging from 1/1 to 1/60 against the surf similarity parameter. Hence an approximate formula is presented for estimation of maximum solitary wave runup on planar beaches of different slopes regardless of whether the waves are breaking or non-breaking. The proposed empirical equation predicts the overall dataset, mostly within 20% scatter for all the laboratory data. Thus, the empirical formula can be used to obtain a quick estimation of maximum runup height for both breaking and non-breaking solitary waves in laboratory experiments, for disaster risk evaluation of wave runups and to verify numerical model runup results.

Study of double combination evaluation of urban comprehensive disaster risk

Aiming at solving the difficult problem of inconsistent single-method evaluation results in comprehensive disaster risk assessment, this paper presents an evaluation method based on a combination of the ranking value and the evaluation value. First, the seven methods of the fuzzy comprehensive evaluation (FCE), the set pair analysis (SPA), the improved grey target analysis (IGT), the fuzzy stochastic simulation (FSS), the grey relational degree analysis (GRA), the extension matter element evaluation (EME), and the technique for order preference by similarity to an ideal solution (TOPSIS) are used to conduct urban comprehensive disaster risk assessment. Second, to ensure the degree of correlation between individual evaluation methods and make full use of more information to achieve the purpose of complementary advantages, the Kendall synergy coefficient, the Spearman rank correlation coefficient, and the comprehensive support coefficient are used as the single-method compatibility consistency test standards. The combined evaluation methods of the cyclic correction model and support model are used to combine the single evaluation results, and the highly coordinated comprehensive disaster risk ranking value and evaluation value are obtained through repeated tests, thus constructing a highly scientific and reasonable dual combination evaluation model. Finally, through analysis and comparison of the final combined ranking and evaluation values of 31 provinces, municipalities directly under the central government and autonomous regions in China under the dual combination mode, it is verified that the dual combination idea can obtain evaluation results with high convergence and credibility, solve the problem of inconsistent evaluation results of multiple methods, provide a new research idea and method for measuring the comprehensive disaster risk of cities, and provide a scientific basis for efficiently serving comprehensive risk prevention management and various urban planning and construction work.

Terrain Hazard Risk Analysis for Flood Disaster Management in Chaohu Basin, China, Based on Two-Dimensional Cloud

Terrain analysis is essential to flood disaster risk evaluation. It is a complicated evaluation process, involving both quantitative and qualitative data analysis. However, quantitative and qualitative data cannot be put into operation directly. Based on stochastic and fuzzy mathematics, cloud models allow interchange between qualitative and quantitative data, dealing with randomness and ambiguity. Two- or multi-dimensional cloud models can solve the problem of multivariable analysis. This study used absolute elevation and neighborhood elevation standard deviation as main factors. Using the model, it demonstrated the construction of qualitative conditions and risk evaluation clouds and established a set of two-dimensional cloud reasoning rules to calculate the joint certainties with all the grids in reasoning rules. By selecting the highest certainty of cloud reasoning, preliminary evaluation results were obtained. For more accurate results, the model algorithm was improved, and further iterations were performed. The results of two-dimensional cloud reasoning showed better dispersion and precision than traditional methods did. The terrain risk distribution of Chaohu Basin, China, agreed with reality with great detail. A new method regarding the risk assessment of flood disaster was also proposed.

Research on Multi-Factor Ice Disaster Risk Evaluation Model for Transmission Line

With the development of the transmission line scale and the improvement of the voltage level, the height and span of the tower are increasing, and the ice disaster occurs frequently in some areas, which has become an important factor affecting the security and stability of the power grid. Based on the analysis of the ice and ice flashover mechanism, this paper firstly discusses ice disaster influencing factors from three main angles, such as, the potential fault of transmission line, operation and maintenance characteristics and meteorological conditions, and then uses multi factor classification method to build the ice disaster risk evaluation model for transmission line. Further, taking the 220kV and above transmission lines in a certain area of South China as a research object, this paper evaluates all the lines and towers ice disaster risk, obtains the lines or towers with high risk level using the model, and the evaluation results have been verified on site. Finally, combined with the rating of risk evaluation factors, this paper formulates a special anti-icing measure to ensure the safe and stable operation of transmission lines.