Natural Hazards Review

Estimation of tornado wind speed can be extremely difficult, especially near the ground where tornado damage occurs. Because of limitations of in situ measurements, ground-based damage surveys continue to be the most commonly used method to estimate the near-surface wind speed. This study discusses a comprehensive damage assessment of Naplate, Illinois (IL) tornado that occurred in February 2017. The damage survey included the following damage indicators: residential buildings, trees, and traffic signs. Additional data from social media images were collected and used to supplement the damage assessment. This comprehensive data set of damage indicators was used to estimate the characteristics of the Naplate, IL tornado. Multiple wind-speed estimation methods, each suited to a subset of the damage indicators, were applied to estimate the near-surface wind field of the tornado. The results from all independent methods were compared to create a cross-validated estimation of the surface tornado wind field. The similarity between estimates derived from different damage indicators and methods increases confidence in the wind speed estimation and validates the independent application of any of the methods presented, with each being appropriate for given circumstances and data availability.

The strength and speed of modeling software has increased drastically in recent years. As it does so, researchers across a variety of fields work to determine how most effectively to utilize this strength and speed. Many of them have turned to interdisciplinarity as a means of creating more representative models. This is the case for disaster research as this area of interest involves many intricately interdependent systems. In working on interdisciplinary projects, past research has noted several barriers to complete integration, including differences in language and methodology, institutional structures not conducive to interdisciplinary collaboration, and nuanced tension between disciplines. Many solutions to these issues have been presented: facilitated conversation, increased institutional support, and several others. However, one area of difficulty for which comprehensive solutions have not yet been realized is data integration. This is indeed a challenge that lays at the heart of meaningful interdisciplinarity. The data are frequently telling an intricately interwoven story, and the more these data can be analyzed in a cohesive manner the more likely it is that researchers will be able to harness their predictive power to reduce disasters. In order to understand what efforts have been made at data integration, 29 papers are systematically reviewed in order to extract the nature of previous attempts, reasons for integration, challenges, shortcomings, and recommendations for future work. The papers analyzed most commonly referenced the different syntax and data types as a challenge of integration. Regarding shortcomings of integration efforts, the most common concern was that of model parameterization bias and substantial uncertainties. As a recommendation for future work, the papers most commonly suggested more standardization of data and methods across collaborating disciplines and from one project to the next in order to avoid these shortcoming and challenges.

In the aftermath of disasters, material convergence (the influx of material donations) can cause extreme negative impacts and has been described as a second disaster. Donations that are nonpriority or low-priority goods, or in excess of need, can have negative impacts on transportation into and storage within the affected area. For routine supply chains, successful supply access partially lies in the ability to adapt to changing circumstances. This paper draws on data collected after Hurricane Sandy in 2012 and two tornadoes outside of Oklahoma City in May 2013. Interviews were conducted with individual actors in emergent donation supply chains to understand how they made and understood the effectiveness of their efforts and later coded for how central adaptability is viewed for achieving this success. A critical finding in our study was that how actors in the supply chain define success influences whether or not adaptation is construed as necessary or important, generating important implications for how to best confront the challenge of nonpriority items entering into the emergent disaster relief supply chain to the point of no return.

This study investigated how disaster types, namely those with shorter and longer warning lead times, contextualized individuals’ preparatory actions, especially those associated with their response efficacy perception (i.e., the belief that preparations are effective in risk reduction) and age. The working sample included 1,304 respondents from the 2017 US National Household Survey. Logistic regressions showed that individuals with higher levels of response efficacy perception were more likely to prepare after learning information about how to prepare. Respondents in areas prone to short lead-time disasters were less likely to prepare than those in areas exposed to longer lead-time disasters. Response efficacy perception was more important for taking action to prepare for short lead-time disasters, which was observed only among older adults but not among younger adults. These findings revealed the impacts of disaster types and response efficacy perception on disaster preparedness and older adults’ unique vulnerability and resilience, which could guide policymaking and interventions to promote national disaster preparedness tailored to regional peculiarities.

Climate change, sea level rise, and storm surge events are now significant factors threatening critical water and wastewater infrastructure. Extreme storm events have increased the need for the preparation required to face the challenges of climate change. In October 2012, Hurricane Sandy impacted 13 wastewater treatment facilities in New York City alone, causing millions of dollars in damage. Sandy was only a tropical storm, with a wind speed of $22.35{\mathrm{ms}}^{-1}$ ($50\mathrm{mi}/\mathrm{h}$), when it made landfall in New York; however, it caused havoc because it combined with other local cascading events. The storm damage was caused by cascading synergistic events, including storm surge, sea level rise, and rain, rather than a singular decisive event of factor. The disaster left behind by Superstorm Sandy alone magnifies the dire need to understand the damage scenarios and consequences, and to identify resiliency plans and mitigation strategies that take into account a multitude of parameters that contributed to the intensified and devastating impacts. This work formulated the critical factors into a new concept introduced here as total water level (TWL). Using hydrodynamic models, the flood depths and elevations were calculated for various return periods and hurricane categories for coastal and riverine flooding, considering TWL to demonstrate the role of cascading events. The results show the compound effect of extreme storm events as hurricane surge combines forces with sea level rise and rainfall events; it translated into an additional 2.74–4.26 m of flooding in two studied locations.

Subsidized insurance is often described as a perverse incentive, moral hazard, or maladaptation that perpetuates coastal residencies in vulnerable homes despite increasing safety and economic risks from hurricanes, sea level rise, and other climate change impacts. Insurance is also often described as a positive factor in coastal risk reduction if insurers proactively reward homeowners for upgrades that mitigate losses from hurricanes. The empirical and policy-relevant question remains whether homeowners perceive insurance incentives as perverse or positive. A new survey of 662 North Carolina coastal homeowners shows that most are failing to upgrade their homes to address hurricane risk or plan for coastal retreat but not because they expect insurance to cover losses. Rather those aware of insurance incentives are more likely to live in better-protected residences and take the incentivized actions. Limited awareness of existing policies suggests a need for greater outreach by policymakers, lenders, and insurers.

Critical infrastructure systems are interdependent to ensure normal operations for supporting a national economy and social well-being. In the wake of a disaster, such interdependencies may introduce additional vulnerability and cause cascading failures. Therefore, understanding interdependencies and assessing their impact are essential to mitigate such adverse consequences and to enhance disaster resilience in the long term. There have been various models developed to capture dependencies and interdependencies across infrastructure systems. However, problems of inconsistent usage and a lack of technical guidance hinder practical applications of interdependency models. Therefore, this study presents a new classification of interdependency models based on the following implementation methods: dependency tables, interaction rules, and data-driven approaches. For every class of interdependency model, fundamental assumptions and detailed implementation methods are described, with discussion of appropriate application areas, advantages, and limitations. This study also compares different types of models to facilitate analysts in choosing models based on their needs. Due to the intrinsic complexity of dependencies and interdependencies, there are many challenging modeling issues; this study discusses future research directions to address such challenges.

Our understanding of past natural catastrophes has important implications for catastrophe modeling and disaster risk management, mitigation, and adaptation. To assess past events, loss “normalization” is used to isolate natural and economic factors contributing to economic losses. Conventional normalization adjusts for changes in economic activity using the value of capital stock or gross domestic product (GDP). Due to the limited international availability of capital stock data, most global studies elect to use GDP. However, capital stock may be preferable because it directly measures the value of damageable physical assets. In this study, we present a method for global catastrophe loss normalization using capital stock, and apply this method to normalize hurricane disaster losses in the United States. We assess the robustness of our normalization method by comparing losses to losses derived using public capital stock and GDP data. We find that normalized losses are consistent with losses derived using other measures for capital stock and GDP.

A community resilience model that takes into account the mutual interdependencies between the building portfolio, transportation network, and healthcare system both during and after a seismic event is presented. The model is modularized into independent simulators to facilitate modeling their interdependencies. The transportation network model accounts for the capacity reduction attributed to bridge damage and links blocked by debris from collapsed buildings. It also addresses the increased demand from ambulance trips ferrying injured people to healthcare facilities and trucks hauling away debris. The transportation network model is incorporated into a discrete event simulation environment that models the response of the healthcare system as well as the debris removal process in the aftermath of a seismic event. Measures are proposed to quantify and improve the seismic resilience of each individual system as well as the whole community considering the three systems’ mutual interdependencies. The capability of the proposed model to support hazard mitigation planning is demonstrated through a case study that highlights the effects of interdependencies between the three systems under consideration. Mitigation strategies to improve seismic resilience of a prototype community are proposed and assessed.

The coastal region in mainland China is prone to typhoon winds. However, a systematic analysis of the annual maximum wind speed analysis for typhoon and nontyphoon winds (i.e., mixed wind climate) using the wind records has not been reported for the region. The wind hazard modeling and analysis for mainland China was carried out in the present study by using wind records from 839 meteorological stations and considering mixed wind climates. The identification of typhoon winds from wind records is based on historical typhoon tracks. Both the region of influence approach and the at-site approach were used to estimate the $T\text{-}\mathrm{year}$ return period value of the annual maximum wind speed, $v_T$, according to the wind-producing mechanism. The estimated $v_T$ for typhoon and nontyphoon winds was used to identify regions where typhoon winds dominate the wind hazard. Wind maps for mainland China were developed by combining wind hazards determined from a typhoon wind hazard model and wind records from meteorological stations to estimate $v_T$. A comparison of developed maps to that given in the Chinese structural design code is given.

Seismic resilience is of great concern and vital importance for cities in earthquake zones. It is not only desirable but also mandatory for the cities to prepare an emergency response plan for possible seismic events. One important task is to identify the seismic vulnerable buildings, e.g., soft-story (SS) buildings. The identified SS buildings can be retrofitted to minimize the risk of possible damage and the mitigation plan can be made accordingly to allocate the needed resources to the vulnerable buildings when earthquake strikes. However, it is time-consuming and costly for structural engineers to identify SS buildings manually by walking through each street. This paper presents an integrated approach for automatically detecting and geolocating SS buildings at a city scale. The approach proceeds in multiple steps, including (1) obtaining a list of addresses of engineer-identified SS buildings in city of Santa Monica, CA; (2) extracting the Google Street View images of the SS buildings; (3) labeling the SS building in the images; (4) training a deep convolutional neural network with the annotated images; and (5) testing the trained model on an independent image data set. The detected SS buildings are geocoded in Google map for users to verify the results quickly and virtually.

Managed retreat from hazardous areas is a long-term strategy for mitigating natural disaster risks and adapting to climate change. In the United States, managed retreat is often sponsored by governments through acquiring properties in the aftermath of a major disaster event. This study empirically examined the institutional factors that influence government buyouts of floodplain properties across US counties, with a particular focus on local fiscal conditions and existing flood management practices. The empirical analysis drew on a nationwide panel data set of buyout projects funded through the federal Hazard Mitigation Grant Program over the period 1990–2016. Using a double-hurdle model, the authors found that counties with more property tax revenues and a lower fiscal reliance on property taxes have more postflood buyouts. Results also indicate a negative impact of flood insurance take-up rates and levee protection on a county’s buyouts of flood-prone properties. These findings shed new light on the challenges for government buyouts and possible conflicts among different policy instruments in flood risk management.

This paper explores the role of socioeconomic metrics in the design, planning and operations of civil engineering projects within the specific context of resilience. The inclusion of resilience analysis and design is consistent with the goals of the ASCE Infrastructure Resilience Division (IRD) and related emerging standards and duties of civil engineers. This paper focuses on the practices in design, planning, construction, and operation of civil engineering projects that can deliver social value to communities and offers a set of socioeconomic metrics for consistently measuring these benefits. Socioeconomic metrics benchmark benefits including safety, social equity, health and well-being, prosperity, cohesion and inclusivity, and mobility and accessibility during the whole life-cycle of a project. A review of metrics is presented and expanded with an emphasis on the need for contextual narrative support to their application. The aim is to establish further the use of metrics in civil engineering projects to set values at the community level and formulate them to justify and rationalize resilience interventions and strategies. The reviewed concepts and categorized project metrics can be used by a range of actors in addition to civil engineers, such as urban planners, policy makers, or regional developers, preferably in a collaborative manner across these groups, particularly to help prioritize the investment of resources and funds to achieve resilience. Three project examples at differing levels of complexity are presented to conceptually illustrate the approaches outlined herein.

This paper is focused on the seismic risk assessment of Buzau County in Romania. This county overlays the most active seismic source in the region, namely, the Vrancea intermediate-depth seismic source which has produced nine earthquakes with moment magnitude ${\mathrm{M}}_{\mathrm{W}}\ge 7.0$ in the last two centuries. Over 40% of the population within this county inhabits traditional adobe buildings for which there are very few available fragility or vulnerability functions in the literature. To overcome this shortcoming, in this study, both fragility and vulnerability functions are developed based on recent experimental research performed at the Technical University of Civil Engineering of Bucharest. The seismic risk assessment is performed using two approaches based on both fragility and vulnerability functions. The results of the analyses show considerable differences between the two risk assessment methods and a significant influence of the fragility of the adobe structures on the seismic risk results.

Taiwan has a population of 23.6 million on just $\mathrm{36,000}{\mathrm{km}}^2$. This densely populated area is highly vulnerable to destructive natural hazards and thus the Taiwanese government is constantly focusing on improving its emergency management system. This research explores how the fire service-centric system influences disaster response on the ground in Taiwan. The data come from 28 qualitative, semistructured, in-depth interviews with disaster responders from four disasters in Taiwan between 2014 and 2016. Based on the authors’ findings, the current Taiwanese disaster response system might not be sufficient to cope with disasters with uncertain situations. As a result, the authors suggest (1) adding more networking functions to the current hierarchical system, (2) increasing the diversity of participants in the decision-making processes during responses, and (3) considering incorporating previous disaster research to develop a new response system.

This study analyzes the news media coverage of floods in a major flood-prone state of India, Bihar. Although news media helps shape public perception and political actions, little analysis of this means of communication has been conducted in India. Major topics and issues discussed during the coverage of Bihar floods in years 2013, 2017, and 2019 were provision of food, shelter, and health facilities, failure of the transportation system, waterlogging in urban areas, and failure or management of embankments. There was no skepticism on whether climate change was real. Political parties took contradictory positions: the ruling party attributed floods to a changing climate but other parties, and news media, emphasized the lack of disaster mitigation actions and were uninterested in climate change. This study suggests that it is more important to prepare for disaster mitigation actions around the major issues discussed and communicate them to the public. Media should become a major stakeholder by questioning the authorities about disaster preparations prior to the monsoon season and communicating mitigation actions to the public once disaster has struck, and help both public and government to better manage and mitigate the disaster.

Modern governments strive to enhance their emergency management capacity and establish multiple policy tools that can help reduce damage caused by natural and human hazards. Among these institutional mechanisms, the constitution in Taiwan entrusts presidents with the authority to act immediately in response to an emergency based on the principle of necessity. The objective of this paper is to gain insight into the following questions: (1) How does the Taiwanese government respond to a pandemic and to what extent does this situation affect the Taiwanese governmental emergency response powers? (2) Do the Taiwanese governmental interventions contradict democratic values and civil liberties? By analyzing the boundaries and limitations of the presidential emergency power, demonstrating practical examples of the different views of Taiwanese presidents regarding their use of the emergency power to address catastrophic disasters, and exploring preemptive actions in response to the COVID-19 pandemic, the authors argue two points: (1) Taiwan’s administrative response to COVID-19 reveals a tendency toward having authority vastly centralized at the legislative level through blank-check authorization, and this represents the presumptive allocation of power embodied in the Republic of China Constitution, which has gradually expanded. (2) The vague and unfettered legal authorization by the CDC and the COVID-19 Special Act may diminish the substantial rule of law in the long run. This article demonstrates, by applying the assessment from a variety of key principles of constitutionalism, Taiwan exhibited how it has integrated institutional memories and past lessons. However, there continues to be in Taiwan an overdependent reliance on statutory authorization with the inherent risk of a slippery slope in exploiting legal authorization, coupled with administrative blind spots, that can generate disproportionate public measures. This leverage, we argue, supersedes the president’s discretionary emergency power, enabling emergency legislation without proper oversight, prevailing over ordinary constitutional order, and possibly producing a corrosive effect on civil liberties and the rule of law in the long term.

We propose the usage of social media as the primary way to collect and consolidate disaster data to provide a less costly and faster economic evaluation process. Through a systematic literature review (SLR) of over 406 peer-reviewed papers, this study first offers a taxonomy to show how social media can be applied to economic disaster assessments. Then we deliver an economic assessment to a flooding disaster in Brazil based on text mining of Twitter messages. Finally, we compare our findings with the Brazilian local government’s assessment and the literature. The results prove the feasibility of delivering a multisector disaster economic evaluation report based entirely on social media. The comparison analysis shows that social media is a valuable tool for the design and implementation of public policies, allowing the traceability of the collected information, the identification of unaccounted costs, and inquiries into the amounts and costs estimated by the local government.

Although the need for cultural competence among healthcare service providers and other practitioners has long been recognized, there has been much less focus on this concept in the field of hazards and disaster research. To help fill this gap, this technical note offers a definitional framework for building cultural competence among hazards and disaster researchers and describes a training module that assists with developing such competency. Drawing on the extant literature, this article conceptualizes cultural competence in hazards and disaster research as an ongoing process that contributes to an understanding of the cultural attributes of affected individuals, households, communities, and societies that researchers are attempting to characterize. The four-step process presented here helps researchers move from cultural awareness to cultural knowledge to cultural sensitivity, and ultimately, to cultural competence. This ongoing practice requires reflexivity, respect, and humility. The time and effort involved in developing cultural competence can promote ethical research, improve the research experience for participants, enrich the quality of the data collected, and enhance the overall quality of knowledge creation and mobilization.