Search results

The purpose of this study is to introduce the top-level design ideas and the overall architecture of earthquake early-warning system for high speed railways in China, which is based on P-wave earthquake early-warning and multiple ways of rapid treatment.

The paper describes the key technologies that are involved in the development of the system, such as P-wave identification and earthquake early-warning, multi-source seismic information fusion and earthquake emergency treatment technologies. The paper also presents the test results of the system, which show that it has complete functions and its major performance indicators meet the design requirements.

The study demonstrates that the high speed railways earthquake early-warning system serves as an important technical tool for high speed railways to cope with the threat of earthquake to the operation safety. The key technical indicators of the system have excellent performance: The first report time of the P-wave is less than three seconds. From the first arrival of P-wave to the beginning of train braking, the total delay of onboard emergency treatment is 3.63 seconds under 95% probability. The average total delay for power failures triggered by substations is 3.3 seconds.

The paper provides a valuable reference for the research and development of earthquake early-warning system for high speed railways in other countries and regions. It also contributes to the earthquake prevention and disaster reduction efforts.

Using the strong motion data of K-net in Japan, the continuous magnitude prediction method based on support vector machine (SVM) was studied.

In the range of 0.5–10.0 s after the P-wave arrival, the prediction time window was established at an interval of 0.5 s. 12 P-wave characteristic parameters were selected as the model input parameters to construct the earthquake early warning (EEW) magnitude prediction model (SVM-HRM) for high-speed railway based on SVM.

The magnitude prediction results of the SVM-HRM model were compared with the traditional magnitude prediction model and the high-speed railway EEW current norm. Results show that at the 3.0 s time window, the magnitude prediction error of the SVM-HRM model is obviously smaller than that of the traditional τ_c method and P_d method. The overestimation of small earthquakes is obviously improved, and the construction of the model is not affected by epicenter distance, so it has generalization performance. For earthquake events with the magnitude range of 3–5, the single station realization rate of the SVM-HRM model reaches 95% at 0.5 s after the arrival of P-wave, which is better than the first alarm realization rate norm required by “The Test Method of EEW and Monitoring System for High-Speed Railway.” For earthquake events with magnitudes ranging from 3 to 5, 5 to 7 and 7 to 8, the single station realization rate of the SVM-HRM model is at 0.5 s, 1.5 s and 0.5 s after the P-wave arrival, respectively, which is better than the realization rate norm of multiple stations.

At the latest, 1.5 s after the P-wave arrival, the SVM-HRM model can issue the first earthquake alarm that meets the norm of magnitude prediction realization rate, which meets the accuracy and continuity requirements of high-speed railway EEW magnitude prediction.

The 2019 Global Assessment Report on Disaster Risk Reduction (GAR) cites earthquakes as the most damaging natural hazard globally, causing billions of dollars of damage and killing thousands of people. Earthquakes have the potential to drastically impact physical, social and economic landscapes; to reduce this risk, earthquake early warning (EEW) systems have been developed. However, these technical EEW systems do not operate in a vacuum; the inequities in social systems, along with the needs of diverse populations, must be considered when developing these systems and their associated communication campaigns.

This article reviews aspects of social vulnerability as they relate to ShakeAlert, the EEW system for the USA. The authors identified two theories (relationship management theory and mute group theory) to inform self-reflective questions for agencies managing campaigns for EEW systems, which can assist in the development of more inclusive communication practices. Finally, the authors suggest this work contributes to important conversations about diversity, equity and inclusion (DEI) issues within early warning systems and earthquake preparedness campaigns in general.

To increase inclusivity, Macnamara (2012) argues that self-reflective questioning while analyzing perspective, philosophy and approaches for a campaign can help. Specific to EEW campaigns, developers may find self-reflective questions a useful approach to increase inclusion. These questions are guided by two theories and are explored in the paper.

Several research limitations exist. First, this work explores two theories to develop a combined theoretical model for self-reflective questions. Further research is required to determine if this approach and the combination of these two theories have adequately informed the development of the reflective questions.

The authors could find little peer-reviewed work examining DEI for EEW systems, and ShakeAlert in particular. While articles on early warning systems exist that explore aspects of this, EEW and ShakeAlert, with its very limited time frames for warnings, creates unique challenges.

Myth is a story of archetypical personas who behave in ways and with motives that we recognize in ourselves. We use myth as a way of reminding ourselves of the relationship between motives, actions, and consequences. Myths can serve either as inspirational or cautionary tales, and sometimes as both. But “myth” can also mean a fabricated story intended to create a false impression, and to achieve storytellers’ ends when they have decided the truth will not suffice. We apply the myth of Cassandra to the millennium-long recorded history of giant tsunamis in Japan. After each of these catastrophes, survivors sought to warn future generations of their recurrences. But, each time, their progeny eventually lost the memory of these lessons, and lost their lives when the next monster wave overwhelmed them. Only when they kept the lessons as living knowledge in everyday life, could they manage to escape from monster tsunamis. In this chapter, we use the myth of Cassandra in conjunction with the myth of Prometheus, the bringer of fire to humankind, as a metaphor for Japan’s growing reliance on nuclear power. Government and utility companies built powerful but inherently dangerous cauldrons in the nation’s disaster-prone landscapes, assuring the public they could control the fire’s fury and defend it against nature’s. As images of atomic bomb victims were still vivid and widely shared in Japan, they had to overcome the public fear of radioactivity by fabricating a “myth of safety.” The nuclear disaster made the public distrust the government and utility companies, which lingers in the process of reconstruction from the disaster. Myths can either reveal hidden truths or mask hidden lies. The Japanese people must now learn to distinguish one from the other.

This paper aims to provide a technical insight into the sensors and systems used to monitor and forecast certain natural hazards.

Following a short introduction, this paper describes the systems used to monitor and forecast earthquakes, tsunamis, hurricanes and tornadoes. The sensors used in these systems are considered in detail and some experimental techniques are also discussed.

Numerous national and global systems are used to monitor and predict natural hazards. A wide range of sensors, together with radars and satellite‐based techniques, play a vital role in these. Many new techniques are under study and the most pressing need is for earthquake prediction.

This paper provides a technical review of the role of sensors in natural hazard monitoring and warning systems.

The purpose of this paper is to connect the theoretical idea of warning systems as social processes with empirical data of people’s perceptions of and actions for warning for cyclones in Bangladesh.

A case study approach is used in two villages of Khulna district in southwest Bangladesh: Kalabogi and Kamarkhola. In total, 60 households in each village were surveyed with structured questionnaires regarding how they receive their cyclone warning information as well as their experiences of warnings for Cyclone Sidr in 2007 and Cyclone Aila in 2009.

People in the two villages had a high rate of receiving cyclone warnings and accepted them as being credible. They also experienced high impacts from the cyclones. Yet evacuation rates to cyclone shelters were low. They did not believe that significant cyclone damage would affect them and they also highlighted the difficulty of getting to cyclone shelters due to poor roads, leading them to prefer other evacuation options which were implemented if needed.

Theoretical constructs of warning systems, such as the First Mile and late warning, are rarely examined empirically according to people’s perceptions of warnings. The case study villages have not before been researched with respect to warning systems. The findings provide empirical evidence for long-established principles of warning systems as social processes, usually involving but not relying on technical components.

The impacts and costs of natural disasters on people, properties and environment are often severe when these occur on a large scale and with no warning system in place. The lack of deployment of an early warning system (EWS), low risk and hazard knowledge and impact of natural hazard experienced by some communities in the UAE have emphasised the need for more effective EWSs. This work focuses on developing an integrated framework for EWSs for communities prone to the impact of natural hazards to reduce their vulnerability and improve emergency management arrangements in the UAE.

The essential elements of effective EWS were identified through literature review to develop an integrated framework for EWS. Semi-structured interviews and questionnaires were also used to identify and confirm hindering factors to deployment of effective EWSs in Abu Dhabi and Fujairah Emirates, while areas that require further development were also identified through this means.

The outcome of this research revealed that the warning for natural hazards in the UAE lacked the required elements for effective EWS, whereas the elements which are present are insufficient to mitigate the impacts of natural hazards. The information in this work emphasises the need to improve two elements, and to develop the other two essential elements of EWS in the UAE.

The outcome of this research revealed that the warning for natural hazards in the UAE lacked the required elements for effective EWS, whereas the elements which are present are insufficient to mitigate the impacts of natural hazards. The information in this work emphasises the need to improve two elements and to develop the other two essential elements of EWS in the UAE.

The purpose of this paper is to investigate relationships of urban seismic resilience assessment indicators.

To achieve this aim, construction of the urban seismic resilience assessment indicators system was conducted and 20 indicators covering five dimensions, namely building and lifeline infrastructure, environment, society, economy and institution were identified. Following this, this study used evidence fusion theory and intuitionistic fuzzy sets to process the information from experts then developed the fuzzy total interpretive structure model.

A total of 20 urban seismic resilience assessment indicators are reconstructed into a hierarchical and visual system structure including five levels. Indicators in the bottom level including debris flow risk, landslide risk, earthquake experience and demographic characteristics are fundamental indicators that significantly impact other indicators. Indicators in the top level including open space, gas system and public security are direct indicators influenced more by other indicators. Other indicators are in middle levels. Results of MICMAC analysis visually categorize these indicators into independent indicators, linkage indicators, autonomous indicators and dependent indicators according to driving power and dependence.

This paper attempts to explore relationships of urban seismic resilience assessment indicators with the interpretive structural model method. Additionally, Fuzzy total interpretive structure model is developed combined with evidence fusion theory and intuitionistic fuzzy sets, which is the extension of total interpretive structure model. Research results can assist the analytic network process method in assessing urban seismic resilience in future research.