Typhoon Disaster Research Articles

Risk Assessment of Typhoon Disaster Chains in the Guangdong–Hong Kong–Macau Greater Bay Area, China

The typhoon disaster chain is one of the leading climate risks in constructing the Guangdong–Hong Kong–Macau Greater Bay Area (GBA). In this study, the risks of the typhoon disaster chains including typhoon-induced gales, rainstorms, and storm surges in the GBA, as well as the comprehensive risk of typhoon disaster, are investigated at county level by comprehensively analyzing the hazard, exposure, and vulnerability. The results show that the high- and very-high-risk areas of typhoon–gale disaster chain are located in Zhuhai, Zhongshan, Foshan, Dongguan, central-southern Jiangmen, southern Shenzhen, and parts of Huizhou. The high- and very high-risk areas of typhoon–rainstorm disaster chain include Zhuhai, Zhongshan, Shenzhen, central-southern Foshan, northern Dongguan, central Jiangmen, and central Huizhou. Regarding the typhoon–storm surge disaster chain, the areas at high and very high risk are located in Zhuhai, eastern Zhongshan, and the coastal areas of the Pearl River Estuary. In addition, the comprehensive risk of typhoon disaster is very high in Zhuhai and high in Zhongshan, Jiangmen, Dongguan, and Shenzhen. By verifying the spatial correlation between typhoon disaster risk indexes and actual losses, it is found that the comprehensive risk index of typhoon disaster constructed in this study can better reflect the actual losses. Overall, the findings of this study can provide a scientific basis for typhoon disaster prevention and mitigation in the GBA, and it can also serve as a reference for typhoon disaster risk research in other areas.

Soft open points based load restoration for the urban integrated energy system under extreme weather events

With frequent occurrences of extreme natural disasters such as typhoons in urban integrated energy systems (UIES), it is of great significance to cope with different kinds of disturbances. This paper proposes a load restoration method under typhoon weather for urban distribution and natural gas networks based on soft open points (SOP). Firstly, the typhoon wind speed model is introduced and the line fault rates of distribution networks under typhoons are calculated. Secondly, the gas turbine and electric-driven compressor are considered as the coupling units of the integrated electric–gas energy system, and related models are constructed. The fault analysis method of the natural gas network is proposed considering the faults in the distribution network lead by typhoons. Thirdly, SOP installed in the distribution network with the V/f control mode is applied to restore electrical loads and provide voltage support for the loads on the fault side. After that, the loads of the gas network could also be restored because of the restoration of the coupling units. Optimal energy flow is applied to determine the output of the power and gas sources, coupling units and also the loads to be restored. Finally, the fault rate of each line under typhoon disaster is analysed and the correctness and effectiveness of the resilience improving method based on SOP are verified with test systems UIES E33-G14 and UIES E123-G48.

Understanding Human Activities in Response to Typhoon Hato from Multi-Source Geospatial Big Data: A Case Study in Guangdong, China

Every year typhoons severely disrupt the normal rhythms of human activities and pose serious threats to China’s coast. Previous studies have shown that the impact extent and degree of a typhoon can be inferred from various geolocation datasets. However, it remains a challenge to unravel how dwellers respond to a typhoon disaster and what they concern most in the places with significant human activity changes. In this study, we integrated the geotagged microblogs with the Tencent’s location request data to advance our understanding of dweller’s collective response to typhoon Hato and the changes in their concerns over the typhoon process. Our results show that Hato induces both negative and positive anomalies in humans’ location request activities and such anomalies could be utilized to characterize the impacts of wind and rainfall brought by Hato to our study area, respectively. Topic analysis of Hato-related geotagged microblogs reveals that the negative location request anomalies are closely related to damage-related topics, whereas the positive anomalies to traffic-related topics. The negative anomalies are significantly correlated with economic loss and population affected at city level as suggested by an over 0.7 adjusted R2. The changes in the anomalies can be used to portray the response and recovery processes of the cities impacted.

Applying ontology learning and multi-objective ant colony optimization method for focused crawling to meteorological disasters domain knowledge

The focused crawler based on semantic analysis is a research hotspot in the field of information retrieval. The domain ontology is generally applied to construct the topic model of the focused crawler. In order to overcome the limitations of builders' knowledge reserve and subjective consciousness in the process of constructing artificially ontology, a semi-automatic construction method of domain ontology based on ontology learning technology combining the latent Dirichlet allocation and the Apriori algorithm is proposed in this article. When evaluating the relevance between a hyperlink and a specific topic, the joint evaluation method considering both the web text and the link structure is usually used. However, the traditional weighted sum method is difficult to reasonably determine the optimal weights of these evaluating indicators. To solve this problem, a multi-objective optimization model for link evaluation and a subsequent multi-objective ant colony optimization algorithm (MOACO) are proposed. In the MOACO, a method of the nearest farthest candidate solution (NFCS) is combined with the fast non-dominated sorting to select a set of Pareto-optimal hyperlinks and guide the crawlers’ search directions. The experimental results of the focused crawling on the domain knowledge of typhoon disasters and rainstorm disasters prove that the ability of the proposed focused crawlers to retrieve topic-relevant webpages.

Cross-sectoral preparedness and mitigation for networked typhoon disasters with cascading effects

Urban disaster management is currently limited, because it treats typhoon disasters in isolation and does not consider the cascading effects when multiple disasters interact. In addition, the current literature does not clearly recognize cross-sector collaboration networks, which is a countermeasure for reducing the risks of urban disasters and maintaining sustainable development. This study adopted a complex network approach to examine the cascading effects of typhoon disasters and to identify the types of hazard events and vulnerability paths for urban areas. Cross-sector collaboration networks were constructed to identify the network parameters that facilitate collaborative behaviors among different sectors. Using a comparative analysis of cases (Japan and the Philippines), two weighted complex networks were constructed to simulate disaster cascading effects in urban systems. The results can be summarized as four aspects: (1) For the node degree centrality, rainstorms had the highest values in the typhoon disaster network of Japan and the Philippines. (2) Considering the node betweenness centrality, rainstorms played an extremely crucial role in typhoon disasters with cascading effects in Japan. In contrast, landslides were the most difficult disasters to mitigate in the Philippines. (3) After the analysis of node and edge removal strategy, the global efficiency of network decreased from 0.092 and 0.084 to 0.064, indicating all intentional removal strategies led to better disaster management performance than random removal strategies. (4) The results of the Exponential Random Graph Model (ERGM) indicate that network structures and node attributes were the main factors affecting the formation of cross-sector collaborative networks. These results provide information and increase understanding about the typhoon disasters with cascading effects in urban systems. This study furnishes effective disaster prevention and reduction strategies for urban managers to improve urban sustainability and resilience.

Examining the relationship between media representations of typhoon-related issues and public risk perception

Japan is prone to typhoons and has accumulated a wide range of knowledge about preparing for typhoon disasters. With the development of the Internet, risk information associated with typhoon disasters has increased in online sites. In the pre-emergency phase, media coverage serves as an important guideline for individual disaster mitigation actions. However, depending on which aspects of risk are portrayed in media, attention may be focused only on a few specific risky areas or events. When people do not perceive risk correctly, the risk message can be misleading for mitigation actions. This study conducted a quantitative content analysis to examine how the risk of typhoons was understood by users through online news stories concerning Typhoon Hagibis in 2019 during the pre-emergency phase. Our results found that perception of typhoon risk was distorted by previous typhoon disaster coverage. Additionally, disinformation that could cause confusion in disaster prevention behaviors, was spread on online message boards. Bulletin boards have the potential to inform many people of social norms that encourage them to be well prepared for typhoons. According to the content analysis of online comments, online users indicated that mandatory orders from the government provide the only excuse for missing work during a crisis. Risk managers should monitor the spread of inaccurate information about disaster prevention activities and convince companies to conduct pre-disaster preparedness planning with employees. Clear presentation of social norms on disaster prevention make it easier for people to take disaster prevention actions.

High school students’ trust and risk perception of typhoon disaster: Moderating role of government ability in disaster management

Under global warming and environmental changes, coastal cities have witnessed significant typhoon disasters that attract considerable attention from scholars. Existing studies mainly focused on typhoon disaster prevention and reduction by examining the impact of the public's trust on risk perception. However, these studies overlooked the influence of government ability, even though government plays an important role in disaster management. Therefore, this study takes Ningbo, China as an example to analyze the impact of trust on risk perception and explore the role of government ability on the referred relationship. High school students are taken as the research targets as they are vulnerable but important in typhoon disaster mitigation, which may have been overlooked in existing studies. Regression is used to examine these relationships. The findings of this study are as follows. First, students' trust in meteorological departments, expert institutions, and government agencies positively impact economic, personal, and environmental risk perception. Second, government ability negatively moderates the relationships between students' trust in meteorological departments and expert institutions and all types of risk perception. Moreover, it only has a significant negative moderating effect on the relationship between students' trust in government agencies and economic risk perception. The study reveals the moderating role of government ability between trust and risk perception and provides references for further study on the relationship between trust and risk perception.

Research on the Construction of Typhoon Disaster Chain Based on Chinese Web Corpus

China is one of the countries most affected by typhoon disasters. It is of great significance to study the mechanism of typhoon disasters and construct a typhoon disaster chain for emergency management and disaster reduction. The evolution process of typhoon disaster based on expert knowledge and historical disaster data has been summarized in previous studies, which relied too much on artificial experience while less in-depth consideration was given to the disaster exposure, the social environment, as well as the spatio-temporal factors. Hence, problems, such as incomplete content and inconsistent expression of typhoon disaster knowledge, have arisen. With the development of computer technology, massive Web corpus with numerous Web news and various improvised content on the social media platform, and ontology that enables consistent expression new light has been shed on the knowledge discovery of typhoon disaster. With the Chinese Web corpus as its source, this research proposes a method to construct a typhoon disaster chain so as to obtain disaster information more efficiently, explore the spatio-temporal trends of disasters and their impact on human society, and then comprehensively comprehend the process of typhoon disaster. First, a quintuple structure (Concept, Property, Relationship, Rule and Instance) is used to design the Typhoon Disaster Chain Ontology Model (TDCOM) which contains the elements involved in a typhoon disaster. Then, the information extraction process, regarded as a sequence labeling task in the present study, is combined with the BERT model so as to extract typhoon event-elements from the customized corpus. Finally, taking Typhoon Mangkhut as an example, the typical typhoon disaster chain is constructed by data fusion and structured expression. The results show that the methods presented in this research can provide scientific support for analyzing the evolution process of typhoon disasters and their impact on human society.

Damage prediction of transmission lines under typhoon disasters considering multi-effect

Aim: It is necessary to study the resilience of transmission lines under typhoon disasters considering multi-effect, because typhoon disasters pose a great threat to coastal transmission lines and existing research ignored multi-effect and obtained conservative results. Method: This paper proposes a method to predict the damage of transmission towers under typhoon disasters considering the multi-effect of tower-line coupling, aging, corrosion, guy wire reinforcement, etc. The tower-line coupling effect uses a two-step reliability model. The first step calculates the damage probability of transmission lines. Then, we couple the wind load of transmission lines to towers through binomial distribution. The second step calculates the damage probability of transmission towers. The aging effect uses two-parameter Weibull distribution to calculate the aging failure probability. The corrosion effect uses the uniform corrosion theory to calculate the corrosion failure probability. The guy wire reinforcement is realized by increasing the mean value of design wind load for strength curves. Next, this paper uses probability addition equation to integrate multi-effect and obtained the final damage prediction results. Finally, we used the 110-kV THJ (TieHaiJia) line in Guangdong province, China under Typhoon “Mangkhut” in 2018 as an example to check the accuracy of proposed method. Results: The results show that the comprehensive failure probability is close to 1, and the reinforcement effect can only reduce the failure probability by 0.003. Conclusion: It is concluded that considering the tower-line coupling effect to improve failure probability is closer to practice, but the reinforcement effect should not be blindly improved.

Factors Affecting Human Damage in Heavy Rains and Typhoon Disasters.

Floods due to heavy rains or typhoons are frequent annual hazards in Japan. This study aims to reduce disaster fatalities and contribute to disaster risk reduction. This retrospective observational study analyzed fatalities caused by heavy rains or typhoons. In Japan, 578 fatalities, related to seven occurrences of heavy rains and 16 typhoons, occurred between 2016 and 2020. Moreover, 13,195 houses collapsed due to hazards. Furthermore, 334 (73.2%) of the 456 fatalities were > 60 years old. Heavy rains caused more local area destruction due to floods and landslides than typhoons although wind- and disaster-related mortalities were found to be caused by typhoons. Human damage was eminent in older people because of their vulnerabilities and possibly dangerous behavior. Many fatalities were due to floods (46.9%) and landslides (44.1%). Indoor and outdoor mortalities due to heavy rains or typhoons were 157 (55.9%) and 124 (44.1%), respectively, and 24 (21.8%) of 124 outdoor mortalities occurred in vehicles. The number of recent flood mortalities in Japan correlates with the number of destroyed houses. Analyzing the victim's locations in the 2020 Kumamoto Heavy Rain using hazard and inundation maps suggested the difficulty of ensuring the safety of people living in dangerous areas. This study showed the characteristics of flood damage by heavy rains and typhoons in Japan and reports that flood damage is increasing because of the hazard size and community aging. Disaster risk reduction, disaster education, and evacuation safety plans for the elderly using hazard maps were important for strengthening disaster resilience.

Resilience Assessment and Improvement for Cyber-Physical Power Systems Under Typhoon Disasters

The cyber-physical deep coupling makes power systems face more risks under small-probability and high-risk typhoon disasters. Resilience describes the ability of cyber-physical power system (CPPS) withstanding extreme disasters and resuming normal operation. To improve the resilience assessment and analysis method of CPPS, first, a CPPS resilience assessment framework that considers the space-time metrics of disasters and the interactions of information systems and power grids is proposed, including fault scenarios extraction, response and recovery analysis, quantitative assessment of resilience. Second, from the perspective of the geographical coupling between OPGW and transmission lines and the control coupling between automatic generation control system (AGC), substation automation system (SAS) and power system, the interaction of information flow and energy flow during the failure period is analyzed. The network flow theory is used to establish an information network traffic model to describe the operating status of the information system at each stage. On this basis, a mixed integer linear programming model for DC optimal power flow considering the information network constraints and a multi-stage bi-level model for cyber-physical collaborative recovery are established. Finally, we take the IEEERTS-79 system as an example to show that the proposed method can improve the quantization accuracy comparing with the assessment method of the conventional power system, and evaluate the enhancement of typical measures at different stages.

Analysis of aquaculture farmers' adaptation behavior toward typhoon disaster in Zhoushan Islands and Dongtou Islands and its influencing factors

Analysis of aquaculture farmers' adaptation behavior toward typhoon disaster in Zhoushan Islands and Dongtou Islands and its influencing factors

令和元年東日本台風災害での長野医療圏エコノミークラス症候群予防検診の経緯と提言

令和元年東日本台風災害での長野医療圏エコノミークラス症候群予防検診が，長野県長野保健所及び長野市保健所の指揮の下，（一社）長野県臨床検査技師会，医療機関など関係団体が協働して行われた．災害対応での新たな取り組みを構築する際に，人と人との直接の対面による情報・意見交換・連携を図る場面が活かされたことが検診体制の整備につながった．一巡目は専門家からの指導のもと，日赤救護班，県検査技師会技師で探索的に行われた．さらに検査機器の中央管理とマニュアル等の整備がされ，二巡目は地域の病院単位の診療チームで広範に行われた．今後の災害時に備えて，一次予防としての早期からの疾病啓発と発生要因となる避難所環境の整備体制，二次予防としての検診の法的根拠の明確化，保健所と検査技師会による手順の整備，地元医療機関，さらに検査機器メーカーとの共同体制などの体制整備が望まれる．

Decision-making method based on game theory and grey theory in a single-value neutrosophic environment and its application to typhoon disaster assessment

PurposeThe Chinese believe that “man will conquer the sky” and “fighting with the sky brings endless joy”. Considering that disaster assessment can be regarded as a two-person, zero-sum game problem between nature and human beings, this paper proposes a multi-attribute decision-making method based on game theory and grey theory in a single-value neutrosophic set environment. Due to the complexity and uncertainty of the decision-making environment, the method builds a decision matrix based on single-valued neutrosophic numbers.Design/methodology/approachFirst, the authors use the single-value neutrosophic information entropy to calculate the attribute weights and the weighted decision matrix. Second, the optimal mixed strategy method based on linear programming solves the optimal mixed strategy for both sides of the game so that the expected payoff matrix can be obtained. Finally, grey correlation analysis is used to obtain the closeness coefficient of each alternative based on the expectation payoff matrix to identify the ranking result of the alternative.FindingsAn example is used to verify the effectiveness of the proposed method, and its rationality is verified through a comprehensive comparison and analysis of the various aspects.Practical implicationsThe proposed decision-making method can be applied to typhoon disaster assessment. Such assessment results can provide intelligent decision support to the relevant disaster management departments, thereby reducing the negative impact of typhoon disasters on society, stabilizing society and improving people's happiness. Further, the method can be used for decision-making, recommendation and evaluation in other fields.Originality/valueThe proposed method uses single-value neutrosophic numbers to solve the information representation problem of decision-making in a complex environment. Under a new perspective, game theory is used to handle the decision matrix, while grey relational analysis converts inexact numbers to exact numbers for comparison and sorting. Thus, the proposed method can be used to make reasonable decisions while preserving information to the extent possible.

A Method Based on Numerical Wind Field and Extreme Learning Machine for Typhoon Wind Speed Prediction of Wind Farm

Typhoon wind speed prediction is of great significance for it can help prevent wind farms from damages caused by frequent typhoon disasters in coastal areas. However, most researches on wind forecast are either for meteorological application or for normal weather. Therefore, this paper proposes a systematic method based on numerical wind field and extreme learning machine for typhoon wind speed prediction of wind farms. The proposed method mainly consists of three parts, IGA-YanMeng typhoon numerical simulation model, typhoon status prediction model, and wind speed simulation model based on an extreme learning machine. The IGA-YanMeng typhoon numerical simulation model can greatly enrich typhoon wind speed data according to historical typhoon parameters. The typhoon status prediction model can predict the status of typhoons studied in the next few hours. And wind speed simulation model simulates the average wind speed magnitude/direction at 10 m height of each turbine in the farm according to the predicted status. The end of this paper presents a case study on a wind farm located in Guangdong province that suffered from the super typhoon Mangkhut landed in 2018. The results verified the feasibility and effectiveness of the proposed method.

A risk management framework for power distribution networks undergoing a typhoon disaster

With the increasing distribution network accidents caused by typhoon disasters, risk management in typhoon scenarios is necessary. A risk management framework for power distribution networks (PDNs) undergoing a typhoon disaster is proposed. First, a risk prediction model of the PDN under typhoon conditions based on the Batts model is developed to predict the loss of load risk (LLR) index and economic loss risk (ELR) index of the PDN before the typhoon lands. Then, a vulnerability index of overhead lines, considering the failure frequency of specific overhead lines and their load importance, is introduced for use in a weak link identification model to identify weak links in the PDN. Finally, a two-time-step risk relief model based on typhoon forecast information and the identified weak links is developed to allocate PDN relief materials to reduce the LLR and ELR during a typhoon disaster. An IEEE RBTS BUS6 system is employed as a test system to verify the risk management strategy. The vulnerability index proposed by the strategy considers both the importance of load and line failure. The risk management strategy adopts a two-time-step model, which reduces the impact of meteorological forecast errors and enables more efficient use of materials. The results show that the proposed framework can take more effective use of relief materials to reduce the loss of PDNs compared with the traditional strategy.

Assessment on typhoon prevention capability of fishing port based on numerical model calculations

Storm surge combined with strong wave induced by typhoon has led to significant losses of life and properties. In order to mitigate the impacts of typhoon disasters and provide early warning, the typhoon prevention capability of Shenjiamen fishing port was evaluated by using the coupled Advanced Circulation model (ADCIRC) and Simulating Waves Near shore model (SWAN). Various numerical experiments were carried out to determine the most dangerous typhoon path. The model result shows that the protection grade of seawall on the side of Xiaogan Island is relatively low. However seawall on the Lujiazhi Island is capable of withstanding category 17 typhoons. Through the comparison of external force on ship and holding force of anchor, the typhoon prevention ability of anchorage was also investigated. The protection grades of anchorage in Shenjiamen fishing port show significant spatial variation. The anchorage between Lujiazhi Island and Zhoushan Island has higher grades, reaching level 16. But the protection grade of anchorage does not exceed 13 at the gate of Shenjiamen fishing port and intersection area of waterway. This study could provide scientific basis for the protection of fishing port and the dispatch of fishing boats during typhoon.

Do participants in the bond market care about corporate social responsibility? Evidence from China

PurposeUsing a sample of listed Chinese companies that issued bonds from 2010 to 2019, the authors empirically test the link between CSR and corporate bond pricing, and the mechanism and channels behind this link.Design/methodology/approachThis study systematically examines whether and how corporate social responsibility (CSR) affects the corporate bond market in China.FindingsFirms with better CSR have higher corporate bond credit ratings and lower corporate bond yield spreads. These associations remain stable in robustness checks, including checks that use regional typhoon disaster as an instrumental variable. The effects of CSR are more significant for firms with a worse information environment and for those operating in high-risk environments. Better CSR is associated with less earnings management, fewer financial restatements and less analyst forecast divergence. In addition, the effects of CSR are more pronounced after the 2013 market-oriented reform and when issuers are non-state-owned enterprises.Practical implicationsBecause market participants can incorporate firms' CSR into their decision-making, establishing an effective channel for communicating CSR between issuers and market participants will enhance the effects of CSR.Social implicationsResearchers need to attend to the mechanisms behind the link between CSR and corporate bond pricing, and to the characteristics of strong environmental contingency in emerging markets, specifically the periods and scenarios in which the effects of CSR change.Originality/valueThis study provides systemic evidence that CSR benefits corporate bond pricing through both informational and reputational channels and that the effects of CSR vary by time and firm. These findings enrich the literatures on both the economic consequences of CSR and the determinants of corporate bond pricing, and provide a plausible explanation for mixed findings on the effects of CSR in previous studies.

A Vulnerability Curve Method to Assess Risks of Climate-Related Hazards at County Level

A comprehensive risk assessment of different types of natural disasters at the county level can promote quantitative disaster risk assessment and can provide a scientific basis for the formulation of disaster prevention measures. Focusing on climate-related hazards and based on natural disaster risk assessment theories and methods, this study integrates disaster statistics, meteorological data, geographic information, and other multivariate data to quantify the hazards of various disasters and the vulnerability and exposure of hazard-bearing bodies and conducts an integrated assessment of comprehensive risks of multiple climate-related hazards in Cangnan County, Zhejiang Province. Typhoon disaster risk is high in the central and northern parts of this county and low in its surroundings, with high-risk areas mainly distributed in Lingxi Town to the north. The comprehensive risk distribution patterns of drought and flood disasters in Cangnan County are similar: low in the south and high in the north. With the method of standard deviation, the comprehensive risk of multiple climate-related hazards in Cangnan County shows a distribution pattern of being low in the south and high in the north, with high risk in the northeast and low risk in the northwest and south.

Social media data-based typhoon disaster assessment

Damage assessment plays an important role in disaster management for the enhanced situational awareness, but the data used in the conventional approaches is insufficient for instant damage assessment as it is not timely updated. The social media can serve as an alternative data source to remedy the defects of conventional methods and provide rapid damage assessment. Most studies attempting to interpret social media texts in respect of damage assessment depend on keyword extraction or topic modelling, which may cause high reliance on a domain-specific and exhaustive dictionary, as well as neglection of the abundant semantic information. Therefore, we propose a model to focus on the in-depth understanding of social media texts while involving minimum manual efforts in a semi-supervised manner. This paper introduces a novel method to evaluate the damage extent indicated by social media texts. The damage reports are recognized among the social media messages as damage relation categories by a multi-instance multi-class classifier, and the damage extent implied by the words in a report is quantified by measuring the word similarity with the known damage-related words. The proposed method is validated on tweets collected from Hong Kong and Macau during the two typhoons occurred in 2017. The damage extent map generally agrees with the actual damage reported by authorities and therefore it is shown that the proposed method is able to assess the typhoon damage reliably with little manual work involved.