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What We Measure Matters: The Case of the Missing Development Data in Sendai Framework for Disaster Risk Reduction Monitoring
Ksenia Chmutina, Jason von Meding, Vicente Sandoval, Michael Boyland, Giuseppe Forino, Wesley Cheek, Darien Alexander Williams, Claudia Gonzalez-Muzzio, Isabella Tomassi, Holmes Páez, Victor Marchezini
2021, 12(6): 779-789.   doi: 10.1007/s13753-021-00382-2
Abstract(26) PDF
Abstract:
keep_len="250">The Sendai Framework for Disaster Risk Reduction 2015−2030’s (SFDRR) framing moved away from disaster risk as a natural phenomenon to the examination of the inequality and injustice at the root of human vulnerability to hazards and disasters. Yet, its achievements have not seriously challenged the long-established capitalist systems of oppression that hinder the development leading to disaster risk creation. This article is an exploratory mapping exercise of and a collective reflection on Sustainable Development Goals (SDGs) and SFDRR indicators—and their use in measuring progress towards disaster risk reduction (DRR). We highlight that despite the rhetoric of vulnerability, the measurement of progress towards DRR remains event/hazard-centric. We argue that the measurement of disaster risk could be greatly enhanced by the integration of development data in future iterations of global DRR frameworks for action. The Sendai Framework for Disaster Risk Reduction 2015−2030’s (SFDRR) framing moved away from disaster risk as a natural phenomenon to the examination of the inequality and injustice at the root of human vulnerability to hazards and disasters. Yet, its achievements have not seriously challenged the long-established capitalist systems of oppression that hinder the development leading to disaster risk creation. This article is an exploratory mapping exercise of and a collective reflection on Sustainable Development Goals (SDGs) and SFDRR indicators—and their use in measuring progress towards disaster risk reduction (DRR). We highlight that despite the rhetoric of vulnerability, the measurement of progress towards DRR remains event/hazard-centric. We argue that the measurement of disaster risk could be greatly enhanced by the integration of development data in future iterations of global DRR frameworks for action.
A Critical Review of Social Resilience Properties and Pathways in Disaster Management
A. M. Aslam Saja, Melissa Teo, Ashantha Goonetilleke, Abdul M. Ziyath
2021, 12(6): 790-804.   doi: 10.1007/s13753-021-00378-y
Abstract(19) PDF
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keep_len="250">Resilience as a concept is multi-faceted with complex dimensions. In a disaster context, there is lack of consistency in conceptualizing social resilience. This results in ambiguity of its definition, properties, and pathways for assessment. A number of key research gaps exist for critically reviewing social resilience conceptualization, projecting resilience properties in a disaster-development continuum, and delineating a resilience trajectory in a multiple disaster timeline. This review addressed these research gaps by critically reviewing social resilience definitions, properties, and pathways. The review found four variations in social resilience definitions, which recognize the importance of abilities of social systems and processes in disaster phases at different levels. A review of resilience properties and pathways in the disaster resilience literature suggested new resilience properties—“risk-sensitivity” and “regenerative” in the timeline of two consecutive disasters. This review highlights a causal pathway for social resilience to better understand the resilience status in a multi-shock scenario by depicting inherent and adaptive resilience for consecutive disaster scenarios and a historical case study for a resilience trajectory in a multiple disaster timeline. The review findings will assist disaster management policymakers and practitioners to formulate appropriate resilience enhancement strategies within a holistic framework in a multi-disaster timeline. Resilience as a concept is multi-faceted with complex dimensions. In a disaster context, there is lack of consistency in conceptualizing social resilience. This results in ambiguity of its definition, properties, and pathways for assessment. A number of key research gaps exist for critically reviewing social resilience conceptualization, projecting resilience properties in a disaster-development continuum, and delineating a resilience trajectory in a multiple disaster timeline. This review addressed these research gaps by critically reviewing social resilience definitions, properties, and pathways. The review found four variations in social resilience definitions, which recognize the importance of abilities of social systems and processes in disaster phases at different levels. A review of resilience properties and pathways in the disaster resilience literature suggested new resilience properties—“risk-sensitivity” and “regenerative” in the timeline of two consecutive disasters. This review highlights a causal pathway for social resilience to better understand the resilience status in a multi-shock scenario by depicting inherent and adaptive resilience for consecutive disaster scenarios and a historical case study for a resilience trajectory in a multiple disaster timeline. The review findings will assist disaster management policymakers and practitioners to formulate appropriate resilience enhancement strategies within a holistic framework in a multi-disaster timeline.
A Global Analysis of the Relationship Between Urbanization and Fatalities in Earthquake-Prone Areas
Chunyang He, Qingxu Huang, Xuemei Bai, Derek T. Robinson, Peijun Shi, Yinyin Dou, Bo Zhao, Jubo Yan, Qiang Zhang, Fangjin Xu, James Daniell
2021, 12(6): 805-820.   doi: 10.1007/s13753-021-00385-z
Abstract(18) PDF
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keep_len="250">Urbanization can be a challenge and an opportunity for earthquake risk mitigation. However, little is known about the changes in exposure (for example, population and urban land) to earthquakes in the context of global urbanization, and their impacts on fatalities in earthquake-prone areas. We present a global analysis of the changes in population size and urban land area in earthquake-prone areas from 1990 to 2015, and their impacts on earthquake-related fatalities. We found that more than two thirds of population growth (or 70% of total population in 2015) and nearly three quarters of earthquake-related deaths (or 307,918 deaths) in global earthquake-prone areas occurred in developing countries with an urbanization ratio (percentage of urban population to total population) between 20 and 60%. Holding other factors constant, population size was significantly and positively associated with earthquake fatalities, while the area of urban land was negatively related. The results suggest that fatalities increase for areas where the urbanization ratio is low, but after a ratio between 40 and 50% occurs, earthquake fatalities decline. This finding suggests that the resistance of building and infrastructure is greater in countries with higher urbanization ratios and highlights the need for further investigation. Our quantitative analysis is extended into the future using Shared Socioeconomic Pathways to reveal that by 2050, more than 50% of the population increase in global earthquake-prone areas will take place in a few developing countries (Pakistan, India, Afghanistan, and Bangladesh) that are particularly vulnerable to earthquakes. To reduce earthquake-induced fatalities, enhanced resilience of buildings and urban infrastructure generally in these few countries should be a priority. Urbanization can be a challenge and an opportunity for earthquake risk mitigation. However, little is known about the changes in exposure (for example, population and urban land) to earthquakes in the context of global urbanization, and their impacts on fatalities in earthquake-prone areas. We present a global analysis of the changes in population size and urban land area in earthquake-prone areas from 1990 to 2015, and their impacts on earthquake-related fatalities. We found that more than two thirds of population growth (or 70% of total population in 2015) and nearly three quarters of earthquake-related deaths (or 307,918 deaths) in global earthquake-prone areas occurred in developing countries with an urbanization ratio (percentage of urban population to total population) between 20 and 60%. Holding other factors constant, population size was significantly and positively associated with earthquake fatalities, while the area of urban land was negatively related. The results suggest that fatalities increase for areas where the urbanization ratio is low, but after a ratio between 40 and 50% occurs, earthquake fatalities decline. This finding suggests that the resistance of building and infrastructure is greater in countries with higher urbanization ratios and highlights the need for further investigation. Our quantitative analysis is extended into the future using Shared Socioeconomic Pathways to reveal that by 2050, more than 50% of the population increase in global earthquake-prone areas will take place in a few developing countries (Pakistan, India, Afghanistan, and Bangladesh) that are particularly vulnerable to earthquakes. To reduce earthquake-induced fatalities, enhanced resilience of buildings and urban infrastructure generally in these few countries should be a priority.
Leveraging Hazard, Exposure, and Social Vulnerability Data to Assess Flood Risk to Indigenous Communities in Canada
Liton Chakraborty, Jason Thistlethwaite, Andrea Minano, Daniel Henstra, Daniel Scott
2021, 12(6): 821-838.   doi: 10.1007/s13753-021-00383-1
Abstract(26) PDF
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keep_len="250">This study integrates novel data on 100-year flood hazard extents, exposure of residential properties, and place-based social vulnerability to comprehensively assess and compare flood risk between Indigenous communities living on 985 reserve lands and other Canadian communities across 3701 census subdivisions. National-scale exposure of residential properties to fluvial, pluvial, and coastal flooding was estimated at the 100-year return period. A social vulnerability index (SVI) was developed and included 49 variables from the national census that represent demographic, social, economic, cultural, and infrastructure/community indicators of vulnerability. Geographic information system-based bivariate choropleth mapping of the composite SVI scores and of flood exposure of residential properties and population was completed to assess the spatial variation of flood risk. We found that about 81% of the 985 Indigenous land reserves had some flood exposure that impacted either population or residential properties. Our analysis indicates that residential property-level flood exposure is similar between non-Indigenous and Indigenous communities, but socioeconomic vulnerability is higher on reserve lands, which confirms that the overall risk of Indigenous communities is higher. Findings suggest the need for more local verification of flood risk in Indigenous communities to address uncertainty in national scale analysis. This study integrates novel data on 100-year flood hazard extents, exposure of residential properties, and place-based social vulnerability to comprehensively assess and compare flood risk between Indigenous communities living on 985 reserve lands and other Canadian communities across 3701 census subdivisions. National-scale exposure of residential properties to fluvial, pluvial, and coastal flooding was estimated at the 100-year return period. A social vulnerability index (SVI) was developed and included 49 variables from the national census that represent demographic, social, economic, cultural, and infrastructure/community indicators of vulnerability. Geographic information system-based bivariate choropleth mapping of the composite SVI scores and of flood exposure of residential properties and population was completed to assess the spatial variation of flood risk. We found that about 81% of the 985 Indigenous land reserves had some flood exposure that impacted either population or residential properties. Our analysis indicates that residential property-level flood exposure is similar between non-Indigenous and Indigenous communities, but socioeconomic vulnerability is higher on reserve lands, which confirms that the overall risk of Indigenous communities is higher. Findings suggest the need for more local verification of flood risk in Indigenous communities to address uncertainty in national scale analysis.
Are Disasters a Risk to Regional Fiscal Balance? Evidence from Indonesia
Astrid Wiyanti, Alin Halimatussadiah
2021, 12(6): 839-853.   doi: 10.1007/s13753-021-00374-2
Abstract(32) PDF
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keep_len="250">Indonesia is an archipelago country and is fairly vulnerable to disasters. While disasters generally affect government revenue and expenditure, their effects likely vary by country. This study examines the effect of disasters on the fiscal balance, revenue, and expenditure of local governments. We used panel data and fixed effects methods to estimate the degree to which disaster severity influences budgetary solvency at the district and provincial levels in Indonesia between 2010 and 2018. This study revealed that disasters can strain fiscal balance at the district and provincial levels due to a decrease in own-source revenue and an increase in social assistance expenditure, capital expenditure, consumption expenditure, and unexpected expenditure. The district expenditure most threatened by disasters is consumption expenditure, while the provincial expenditure most threatened is unexpected expenditure. We also found that an increase in capital expenditure can lead to financial burden due to delays of planned projects or post-disaster reconstruction. Based on these findings, it is clear that some forms of insurance or other financing schemes are necessary to mitigate the adverse impacts of disasters on regional fiscal balance. Indonesia is an archipelago country and is fairly vulnerable to disasters. While disasters generally affect government revenue and expenditure, their effects likely vary by country. This study examines the effect of disasters on the fiscal balance, revenue, and expenditure of local governments. We used panel data and fixed effects methods to estimate the degree to which disaster severity influences budgetary solvency at the district and provincial levels in Indonesia between 2010 and 2018. This study revealed that disasters can strain fiscal balance at the district and provincial levels due to a decrease in own-source revenue and an increase in social assistance expenditure, capital expenditure, consumption expenditure, and unexpected expenditure. The district expenditure most threatened by disasters is consumption expenditure, while the provincial expenditure most threatened is unexpected expenditure. We also found that an increase in capital expenditure can lead to financial burden due to delays of planned projects or post-disaster reconstruction. Based on these findings, it is clear that some forms of insurance or other financing schemes are necessary to mitigate the adverse impacts of disasters on regional fiscal balance.
Risk Information Sources for Snow Disaster Risk Preparedness in Scotland
Josephine Adekola, Fabrice Renaud, Carol Hill
2021, 12(6): 854-866.   doi: 10.1007/s13753-021-00386-y
Abstract(13) PDF
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keep_len="250">Heavy snow disruptions are common and costly occurrences in the UK, including Scotland. Yet, heavy snow remains an underresearched aspect of disaster risks in Scotland. This study critically examined the 2018 heavy snow event in Scotland referred to as the “Beast from the East” (BfE) in order to explore the different sources of information used by the public in preparation for and response to heavy snow emergencies. Our study also examined the effectiveness of BfE risk communication between authorities and the public and sought to determine if there is a relationship between risk information received and the intention to mitigate risk. Data were collected through a semistructured survey from (n = 180) residents of the Annandale and Eskdale region of Dumfries and Galloway, Scotland. Our analysis shows that public authority information sources were the most sought-after information sources, followed by online and web sources. We found statistically significant differences between groups (such as age, gender, and mobility/disability) in terms of using risk information sources. Further analysis shows that the relationship between information received and the intention to mitigate risks is not linear but influenced by intervening variables such as work pressures, financial commitment, and stakeholders’ expectations. We argue that where full adherence to official risk advice is required, policymakers should carefully consider issues around these three factors. Heavy snow disruptions are common and costly occurrences in the UK, including Scotland. Yet, heavy snow remains an underresearched aspect of disaster risks in Scotland. This study critically examined the 2018 heavy snow event in Scotland referred to as the “Beast from the East” (BfE) in order to explore the different sources of information used by the public in preparation for and response to heavy snow emergencies. Our study also examined the effectiveness of BfE risk communication between authorities and the public and sought to determine if there is a relationship between risk information received and the intention to mitigate risk. Data were collected through a semistructured survey from (n = 180) residents of the Annandale and Eskdale region of Dumfries and Galloway, Scotland. Our analysis shows that public authority information sources were the most sought-after information sources, followed by online and web sources. We found statistically significant differences between groups (such as age, gender, and mobility/disability) in terms of using risk information sources. Further analysis shows that the relationship between information received and the intention to mitigate risks is not linear but influenced by intervening variables such as work pressures, financial commitment, and stakeholders’ expectations. We argue that where full adherence to official risk advice is required, policymakers should carefully consider issues around these three factors.
Fostering Children’s Participation in Disaster Risk Reduction Through Play: A Case Study of LEGO and Minecraft
Loïc Le Dé, JC Gaillard, Anthony Gampell, Nickola Loodin, Graham Hinchliffe
2021, 12(6): 867-878.   doi: 10.1007/s13753-021-00375-1
Abstract(16) PDF
Abstract:
keep_len="250">This article focuses on children’s participation in disaster risk reduction. It draws on a 2018 study done in New Zealand with 33 school children who conducted participatory mapping with LEGO and the video game Minecraft to assess disaster risk in their locality and identify ways to be more prepared. The research involved participatory activities with the children actively involved in the co-design, implementation, and evaluation of the initiative. A focus group discussion was also conducted to assess the project from the viewpoint of the schoolteachers. The results indicate that LEGO and Minecraft are playful tools for children to participate in disaster risk reduction. The research identifies four key elements of genuine children’s participation, including the Participants, Play, the Process, and Power (4 Ps). This framework emphasizes that fostering children’s participation in disaster risk reduction requires focusing on the process through which children gain power to influence decisions that matter to them. The process, through play, is child-centered and fosters ownership. The article concludes that Play is essential to ground participation within children’s worldviews and their networks of friends and relatives. This article focuses on children’s participation in disaster risk reduction. It draws on a 2018 study done in New Zealand with 33 school children who conducted participatory mapping with LEGO and the video game Minecraft to assess disaster risk in their locality and identify ways to be more prepared. The research involved participatory activities with the children actively involved in the co-design, implementation, and evaluation of the initiative. A focus group discussion was also conducted to assess the project from the viewpoint of the schoolteachers. The results indicate that LEGO and Minecraft are playful tools for children to participate in disaster risk reduction. The research identifies four key elements of genuine children’s participation, including the Participants, Play, the Process, and Power (4 Ps). This framework emphasizes that fostering children’s participation in disaster risk reduction requires focusing on the process through which children gain power to influence decisions that matter to them. The process, through play, is child-centered and fosters ownership. The article concludes that Play is essential to ground participation within children’s worldviews and their networks of friends and relatives.
Impact of Virtual Disaster Collaboration Exercises on Disaster Leadership at Hospitals in Saudi Arabia
Mohammed Ali Salem Sultan, Amir Khorram-Manesh, Eric Carlström, Johan Berlin, Jarle Løwe Sørensen
2021, 12(6): 879-889.   doi: 10.1007/s13753-021-00376-0
Abstract(20) PDF
Abstract:
keep_len="250">This study measured the impact of virtual three-level collaboration (3LC) exercises on participants’ perceived levels of collaboration, learning, and utility (CLU) at hospitals in the southern region of Saudi Arabia. Our 3LC exercise is a tabletop training tool used to facilitate disaster education and document CLU. This model enables the practitioner to acquire new knowledge and promotes active learning. An English version of the CLU scale, the validated Swedish survey tool, was applied to 100 healthcare managers or leaders in various positions at both the operational and tactical levels after conducting the 3LC exercises. The response rate was 100%, although not all questions were answered in some cases. The results show that most participants strongly agreed that the exercises focused on collaboration (r2 = 0.767) and that they had acquired new knowledge during the exercises. There was a statistically significant association between participation in the collaboration exercises and perceived learning (r2 = 0.793), as well as between perceived learning and utility (r2 = 0.811). The collaboration exercises enhance the perceived effects of CLU. They also improve the ability of participants to adapt situational strategies to achieve a safer society. Although exercises were conducted virtually, they were well received by the participants and achieved a value M = 4.4 CLU score, which opens up new dimensions in collaboration simulation exercises. This study measured the impact of virtual three-level collaboration (3LC) exercises on participants’ perceived levels of collaboration, learning, and utility (CLU) at hospitals in the southern region of Saudi Arabia. Our 3LC exercise is a tabletop training tool used to facilitate disaster education and document CLU. This model enables the practitioner to acquire new knowledge and promotes active learning. An English version of the CLU scale, the validated Swedish survey tool, was applied to 100 healthcare managers or leaders in various positions at both the operational and tactical levels after conducting the 3LC exercises. The response rate was 100%, although not all questions were answered in some cases. The results show that most participants strongly agreed that the exercises focused on collaboration (r2 = 0.767) and that they had acquired new knowledge during the exercises. There was a statistically significant association between participation in the collaboration exercises and perceived learning (r2 = 0.793), as well as between perceived learning and utility (r2 = 0.811). The collaboration exercises enhance the perceived effects of CLU. They also improve the ability of participants to adapt situational strategies to achieve a safer society. Although exercises were conducted virtually, they were well received by the participants and achieved a value M = 4.4 CLU score, which opens up new dimensions in collaboration simulation exercises.
The Importance of Digital Elevation Model Selection in Flood Simulation and a Proposed Method to Reduce DEM Errors: A Case Study in Shanghai
Kepeng Xu, Jiayi Fang, Yongqiang Fang, Qinke Sun, Chengbo Wu, Min Liu
2021, 12(6): 890-902.   doi: 10.1007/s13753-021-00377-z
Abstract(22) PDF
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keep_len="250">Digital Elevation Models (DEMs) play a critical role in hydrologic and hydraulic modeling. Flood inundation mapping is highly dependent on the accuracy of DEMs. Various vertical differences exist among open access DEMs as they use various observation satellites and algorithms. The problem is particularly acute in small, flat coastal cities. Thus, it is necessary to assess the differences of the input of DEMs in flood simulation and to reduce anomalous errors of DEMs. In this study, we first conducted urban flood simulation in the Huangpu River Basin in Shanghai by using the LISFLOOD-FP hydrodynamic model and six open-access DEMs (SRTM, MERIT, CoastalDEM, GDEM, NASADEM, and AW3D30), and analyzed the differences in the results of the flood inundation simulations. Then, we processed the DEMs by using two statistically based methods and compared the results with those using the original DEMs. The results show that: (1) the flood inundation mappings using the six original DEMs are significantly different under the same simulation conditions—this indicates that only using a single DEM dataset may lead to bias of flood mapping and is not adequate for high confidence analysis of exposure and flood management; and (2) the accuracy of a DEM corrected by the Dixon criterion for predicting inundation extent is improved, in addition to reducing errors in extreme water depths—this indicates that the corrected datasets have some performance improvement in the accuracy of flood simulation. A freely available, accurate, high-resolution DEM is needed to support robust flood mapping. Flood-related researchers, practitioners, and other stakeholders should pay attention to the uncertainty caused by DEM quality. Digital Elevation Models (DEMs) play a critical role in hydrologic and hydraulic modeling. Flood inundation mapping is highly dependent on the accuracy of DEMs. Various vertical differences exist among open access DEMs as they use various observation satellites and algorithms. The problem is particularly acute in small, flat coastal cities. Thus, it is necessary to assess the differences of the input of DEMs in flood simulation and to reduce anomalous errors of DEMs. In this study, we first conducted urban flood simulation in the Huangpu River Basin in Shanghai by using the LISFLOOD-FP hydrodynamic model and six open-access DEMs (SRTM, MERIT, CoastalDEM, GDEM, NASADEM, and AW3D30), and analyzed the differences in the results of the flood inundation simulations. Then, we processed the DEMs by using two statistically based methods and compared the results with those using the original DEMs. The results show that: (1) the flood inundation mappings using the six original DEMs are significantly different under the same simulation conditions—this indicates that only using a single DEM dataset may lead to bias of flood mapping and is not adequate for high confidence analysis of exposure and flood management; and (2) the accuracy of a DEM corrected by the Dixon criterion for predicting inundation extent is improved, in addition to reducing errors in extreme water depths—this indicates that the corrected datasets have some performance improvement in the accuracy of flood simulation. A freely available, accurate, high-resolution DEM is needed to support robust flood mapping. Flood-related researchers, practitioners, and other stakeholders should pay attention to the uncertainty caused by DEM quality.
A Rapid Prediction Model of Urban Flood Inundation in a High-Risk Area Coupling Machine Learning and Numerical Simulation Approaches
Xingyu Yan, Kui Xu, Wenqiang Feng, Jing Chen
2021, 12(6): 903-918.   doi: 10.1007/s13753-021-00384-0
Abstract(23) PDF
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keep_len="250">Climate change has led to increasing frequency of sudden extreme heavy rainfall events in cities, resulting in great disaster losses. Therefore, in emergency management, we need to be timely in predicting urban floods. Although the existing machine learning models can quickly predict the depth of stagnant water, these models only target single points and require large amounts of measured data, which are currently lacking. Although numerical models can accurately simulate and predict such events, it takes a long time to perform the associated calculations, especially two-dimensional large-scale calculations, which cannot meet the needs of emergency management. Therefore, this article proposes a method of coupling neural networks and numerical models that can simulate and identify areas at high risk from urban floods and quickly predict the depth of water accumulation in these areas. Taking a drainage area in Tianjin Municipality, China, as an example, the results show that the simulation accuracy of this method is high, the Nash coefficient is 0.876, and the calculation time is 20 seconds. This method can quickly and accurately simulate the depth of water accumulation in high-risk areas in cities and provide technical support for urban flood emergency management. Climate change has led to increasing frequency of sudden extreme heavy rainfall events in cities, resulting in great disaster losses. Therefore, in emergency management, we need to be timely in predicting urban floods. Although the existing machine learning models can quickly predict the depth of stagnant water, these models only target single points and require large amounts of measured data, which are currently lacking. Although numerical models can accurately simulate and predict such events, it takes a long time to perform the associated calculations, especially two-dimensional large-scale calculations, which cannot meet the needs of emergency management. Therefore, this article proposes a method of coupling neural networks and numerical models that can simulate and identify areas at high risk from urban floods and quickly predict the depth of water accumulation in these areas. Taking a drainage area in Tianjin Municipality, China, as an example, the results show that the simulation accuracy of this method is high, the Nash coefficient is 0.876, and the calculation time is 20 seconds. This method can quickly and accurately simulate the depth of water accumulation in high-risk areas in cities and provide technical support for urban flood emergency management.
On Evidence-Based Practice in Disaster Risk Reduction
David E. Alexander
2021, 12(6): 919-927.   doi: 10.1007/s13753-021-00381-3
Abstract(9) PDF
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keep_len="250">Disaster science and scholarship are forever expanding and there are increasing calls to base disaster risk reduction policies on the evidence produced by such work. Using examples and argument, this opinion piece examines the nature of evidence. It defines evidence-based practice and considers how it has developed and become important to disaster risk reduction. A definition of what constitutes evidence is difficult to achieve but it must be made in relation to whether the data and information collected can usefully be interpreted and employed to change things for the better. Case histories from past and present centuries show that evidence can sometimes be argued over endlessly. In other cases it is roundly ignored. In yet other instances, false conclusions derived from evidence can become evidence in their own right. Nevertheless, there are situations in disaster risk reduction in which evidence is sorely needed but is clearly lacking. The effectiveness of counter-terrorism measures is one such area. In conclusion, evidence is valuable, above all if there is willingness to use it to support policy formulation, especially in a simple, transparent manner. Subjective interpretation can never be entirely removed from the use of evidence, and evidence alone will not stimulate the policy formulators to improve their decision making. Disaster science and scholarship are forever expanding and there are increasing calls to base disaster risk reduction policies on the evidence produced by such work. Using examples and argument, this opinion piece examines the nature of evidence. It defines evidence-based practice and considers how it has developed and become important to disaster risk reduction. A definition of what constitutes evidence is difficult to achieve but it must be made in relation to whether the data and information collected can usefully be interpreted and employed to change things for the better. Case histories from past and present centuries show that evidence can sometimes be argued over endlessly. In other cases it is roundly ignored. In yet other instances, false conclusions derived from evidence can become evidence in their own right. Nevertheless, there are situations in disaster risk reduction in which evidence is sorely needed but is clearly lacking. The effectiveness of counter-terrorism measures is one such area. In conclusion, evidence is valuable, above all if there is willingness to use it to support policy formulation, especially in a simple, transparent manner. Subjective interpretation can never be entirely removed from the use of evidence, and evidence alone will not stimulate the policy formulators to improve their decision making.
Mobile Alert and Warning in the United States and Japan: Confronting the Challenges of International Harmonization
Hamilton Bean, Ana Maria Cruz, Mika Shimizu, Keri K. Stephens, Matthew McGlone, Sharon Strover
2021, 12(6): 928-934.   doi: 10.1007/s13753-021-00380-4
Abstract(24) PDF
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keep_len="250">A U.S.-Japan expert workshop on mobile alert and warning was held online 8–10 September 2021. Funded by the Japan Foundation’s Center for Global Partnership (CGP) and responding to the Sendai Framework for Disaster Risk Reduction 2015–2030, the workshop compared U.S. and Japanese mobile alert and warning contexts, systems, policies, and messages to investigate possibilities for international harmonization of mobile device-based early warning. The workshop’s sessions revealed two interrelated issues that repeatedly surfaced among workshop participants: culture and policy. The workshop illuminated several possibilities and problems confronting U.S., Japanese, and global stakeholders as they develop, deploy, and seek to improve the effectiveness of mobile alert and warning systems and messages. A U.S.-Japan expert workshop on mobile alert and warning was held online 8–10 September 2021. Funded by the Japan Foundation’s Center for Global Partnership (CGP) and responding to the Sendai Framework for Disaster Risk Reduction 2015–2030, the workshop compared U.S. and Japanese mobile alert and warning contexts, systems, policies, and messages to investigate possibilities for international harmonization of mobile device-based early warning. The workshop’s sessions revealed two interrelated issues that repeatedly surfaced among workshop participants: culture and policy. The workshop illuminated several possibilities and problems confronting U.S., Japanese, and global stakeholders as they develop, deploy, and seek to improve the effectiveness of mobile alert and warning systems and messages.
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Social Vulnerability to Natural Hazards in Brazil
Beatriz Maria de Loyola Hummell, Susan L. Cutter, Christopher T. Emrich
2016, 7(2): 111-122.   doi: 10.1007/s13753-016-0090-9
[Abstract](0) [PDF 0KB](0)
摘要:
Although social vulnerability has recently gained attention in academic studies, Brazil lacks frameworks and indicators to assess it for the entire country. Social vulnerability highlights differences in the human capacity to prepare for, respond to, and recover from disasters. It varies over space and time, and among and between social groups, largely due to differences in socioeconomic and demographic characteristics. This article provides a social vulnerability index (SoVI®) replication study for Brazil and shows how SoVI® concepts and indicators were adapted to the country. SoVI® Brazil follows the place-based framework adopted in the Social Vulnerability Index initially developed for the United States. Using a principal component analysis (PCA), 45 city-level indicators were reduced to 10 factors that explain about 67 % of the variance in the data. Clearly identified spatial patterns showed a concentration of the most socially vulnerable cities in the North and Northeast regions of Brazil, as well as the social vulnerability of metropolitan areas and state capitals in the South and Southeast regions. The least vulnerable cities are mainly concentrated in the inland regions of the Southeast. Although different factors contribute to the social vulnerability in each city, the overall results confirm the social and economic disparities among Brazilian’s regions and reflect a differential vulnerability to natural hazards at local to regional scales.
Reflections on a Science and Technology Agenda for 21st Century Disaster Risk Reduction
Amina Aitsi-Selmi, Virginia Murray, Chadia Wannous, Chloe Dickinson, David Johnston, Akiyuki Kawasaki, Anne-Sophie Stevance, Tiffany Yeung
2016, 7(1): 1-29.   doi: 10.1007/s13753-016-0081-x
[Abstract](2) [PDF 0KB](0)
摘要:
The first international conference for the post-2015 United Nations landmark agreements (Sendai Framework for Disaster Risk Reduction 2015–2030, Sustainable Development Goals, and Paris Agreement on Climate Change) was held in January 2016 to discuss the role of science and technology in implementing the Sendai Framework for Disaster Risk Reduction 2015–2030. The UNISDR Science and Technology Conference on the Implementation of the Sendai Framework for Disaster Risk Reduction 2015–2030 aimed to discuss and endorse plans that maximize science’s contribution to reducing disaster risks and losses in the coming 15 years and bring together the diversity of stakeholders producing and using disaster risk reduction (DRR) science and technology. This article describes the evolution of the role of science and technology in the policy process building up to the Sendai Framework adoption that resulted in an unprecedented emphasis on science in the text agreed on by 187 United Nations member states in March 2015 and endorsed by the United Nations General Assembly in June 2015. Contributions assembled by the Conference Organizing Committee and teams including the conference concept notes and the conference discussions that involved a broad range of scientists and decision makers are summarized in this article. The conference emphasized how partnerships and networks can advance multidisciplinary research and bring together science, policy, and practice; how disaster risk is understood, and how risks are assessed and early warning systems are designed; what data, standards, and innovative practices would be needed to measure and report on risk reduction; what research and capacity gaps exist and how difficulties in creating and using science for effective DRR can be overcome. The Science and Technology Conference achieved two main outcomes: (1) initiating the UNISDR Science and Technology Partnership for the implementation of the Sendai Framework; and (2) generating discussion and agreement regarding the content and endorsement process of the UNISDR Science and Technology Road Map to 2030.
Influences of Risk Perception and Sense of Place on Landslide Disaster Preparedness in Southwestern China
Dingde Xu, Li Peng, Shaoquan Liu, Xuxi Wang
2018, 9(2): 167-180.   doi: 10.1007/s13753-018-0170-0
[Abstract](2) [PDF 0KB](0)
摘要:
The effects of risk perception and sense of place on disaster preparedness have been widely reported. However, most studies have only demonstrated weak relationships and it is unknown whether these are applicable to China. This study investigated such relationships in hazard-threatened areas of the Three Gorges Reservoir area in southwestern China. Data were collected from 348 farming households in landslide-prone areas. Binary logistic and Tobit regression models were constructed to determine whether risk perception and sense of place influence landslide preparedness. The results show that: (1) Farming households’ awareness of the need to prepare for disasters was relatively low, and disaster preparedness behaviors were mainly based on self-learning. Among the 348 sampled households, 67% exhibited no disaster preparedness behavior, and only 2% adopted four of the five types of disaster preparedness behaviors. About a quarter of farming households consciously learned disaster-related knowledge. (2) Risk perception and sense of place had important influences on disaster preparedness. Respondents who received higher scores on the perception of the probability of a landslide, the threat of a landslide, and the place dependence variables were more likely to adopt a greater number of disaster preparedness behaviors. Respondents with higher scores on the perception of controllability in the case of a landslide were less likely to adopt a greater number of disaster preparedness behaviors. Additionally, individual and household socioeconomic characteristics—education, loss, distance from hazard site, information acquisition channel, and housing material—were all related to household disaster preparedness behavior. This study contributes to the current literature by improving the understanding of the relationships of risk perception and sense of place to disaster preparedness in farming households threatened by geological disasters in southwestern China.
An Analysis of Social Vulnerability to Natural Hazards in Nepal Using a Modified Social Vulnerability Index
Sanam K. Aksha, Luke Juran, Lynn M. Resler, Yang Zhang
2019, 10(1): 103-116.   doi: 10.1007/s13753-018-0192-7
[Abstract](4) [PDF 0KB](0)
摘要:
Social vulnerability influences the ability to prepare for, respond to, and recover from disasters. The identification of vulnerable populations and factors that contribute to their vulnerability are crucial for effective disaster risk reduction. Nepal exhibits multihazard risk and has experienced socioeconomic and political upheaval in recent decades, further increasing susceptibility to hazards. However, we still know little regarding social vulnerability in Nepal. Here, we investigate social vulnerability in Nepal by adapting Social Vulnerability Index (SoVI) methods to the Nepali context. Variables such as caste, and populations who cannot speak/understand Nepali were added to reflect the essence of the Nepali context. Using principal component analysis, 39 variables were reduced to seven factors that explained 63.02% of variance in the data. Factor scores were summarized to calculate final SoVI scores. The highest levels of social vulnerability are concentrated in the central and western Mountain, western Hill, and central and eastern Tarai regions of Nepal, while the least vulnerable areas are in the central and eastern Hill regions. These findings, supplemented with smaller-scale analyses, have the potential to assist village officers, policymakers, and emergency managers in the development of more effective and geographically targeted disaster management programs.
Technologies to Support Community Flood Disaster Risk Reduction
Ian McCallum, Wei Liu, Linda See, Reinhard Mechler, Adriana Keating, Stefan Hochrainer-Stigler, Junko Mochizuki, Steffen Fritz, Sumit Dugar, Miguel Arestegui, Michael Szoenyi, Juan-Carlos Laso Bayas, Peter Burek, Adam French, Inian Moorthy
2016, 7(2): 198-204.   doi: 10.1007/s13753-016-0086-5
[Abstract](1) [PDF 0KB](0)
摘要:
Floods affect more people globally than any other type of natural hazard. Great potential exists for new technologies to support flood disaster risk reduction. In addition to existing expert-based data collection and analysis, direct input from communities and citizens across the globe may also be used to monitor, validate, and reduce flood risk. New technologies have already been proven to effectively aid in humanitarian response and recovery. However, while ex-ante technologies are increasingly utilized to collect information on exposure, efforts directed towards assessing and monitoring hazards and vulnerability remain limited. Hazard model validation and social vulnerability assessment deserve particular attention. New technologies offer great potential for engaging people and facilitating the coproduction of knowledge.
Forest Fire Susceptibility Modeling Using a Convolutional Neural Network for Yunnan Province of China
Guoli Zhang, Ming Wang, Kai Liu
2019, 10(3): 386-403.   doi: 10.1007/s13753-019-00233-1
[Abstract](1) [PDF 0KB](0)
摘要:
Forest fires have caused considerable losses to ecologies, societies, and economies worldwide. To minimize these losses and reduce forest fires, modeling and predicting the occurrence of forest fires are meaningful because they can support forest fire prevention and management. In recent years, the convolutional neural network (CNN) has become an important state-of-the-art deep learning algorithm, and its implementation has enriched many fields. Therefore, we proposed a spatial prediction model for forest fire susceptibility using a CNN. Past forest fire locations in Yunnan Province, China, from 2002 to 2010, and a set of 14 forest fire influencing factors were mapped using a geographic information system. Oversampling was applied to eliminate the class imbalance, and proportional stratified sampling was used to construct the training/validation sample libraries. A CNN architecture that is suitable for the prediction of forest fire susceptibility was designed and hyperparameters were optimized to improve the prediction accuracy. Then, the test dataset was fed into the trained model to construct the spatial prediction map of forest fire susceptibility in Yunnan Province. Finally, the prediction performance of the proposed model was assessed using several statistical measures-Wilcoxon signed-rank test, receiver operating characteristic curve, and area under the curve (AUC). The results confirmed the higher accuracy of the proposed CNN model (AUC 0.86) than those of the random forests, support vector machine, multilayer perceptron neural network, and kernel logistic regression benchmark classifiers. The CNN has stronger fitting and classification abilities and can make full use of neighborhood information, which is a promising alternative for the spatial prediction of forest fire susceptibility. This research extends the application of CNN to the prediction of forest fire susceptibility.
A Dilemma of Language: “Natural Disasters” in Academic Literature
Ksenia Chmutina, Jason von Meding
2019, 10(3): 283-292.   doi: 10.1007/s13753-019-00232-2
[Abstract](2) [PDF 0KB](0)
摘要:
For decades sections of the academic community have been emphasizing that disasters are not natural. Nevertheless, politicians, the media, various international organizations-and, more surprisingly, many established researchers working in disaster studies-are still widely using the expression "natural disaster." We systematically analyzed the usage of the expression "natural disaster" by disaster studies researchers in 589 articles in six key academic journals representative of disaster studies research, and found that authors are using the expression in three principal ways:(1) delineating natural and human-induced hazards; (2) using the expression to leverage popularity; and (3) critiquing the expression "natural disaster." We also identified vulnerability themes that illustrate the context of "natural disaster" usage. The implications of continuing to use this expression, while explicitly researching human vulnerability, are wide-ranging, and we explore what this means for us and our peers. This study particularly aims to stimulate debate within the disaster studies research community and related fields as to whether the term "natural disaster" is really fit for purpose moving forward.
Health Emergency and Disaster Risk Management (Health-EDRM): Developing the Research Field within the Sendai Framework Paradigm
Sharon Tsoon Ting Lo, Emily Ying Yang Chan, Gloria Kwong Wai Chan, Virginia Murray, Jonathan Abrahams, Ali Ardalan, Ryoma Kayano, Johnny Chung Wai Yau
2017, 8(2): 145-149.   doi: 10.1007/s13753-017-0122-0
[Abstract](2) [PDF 0KB](0)
摘要:
The intersection of health and disaster risk reduction (DRR) has emerged in recent years as a field of critical inquiry. Health is recognized as an outcome and a goal of DRR, and the integration of both fields is essential to ensure the implementation of the Sendai Framework for Disaster Risk Reduction 2015-2030. Health Emergency and Disaster Risk Management (Health-EDRM) has emerged as an umbrella field that encompasses emergency and disaster medicine, DRR, humanitarian response, community health resilience, and health systems resilience. In September 2016, an international group of experts met in Hong Kong to assess the current status and potential of the Health-EDRM research field, a research area that these scholars characterized as underdeveloped and fragmented. Key challenges identified include research overlap, lack of strategic research agenda, absence of consensus regarding terminology, and limited coordination between stakeholders. The Sendai Framework provides a useful paradigm within which to shape the research field's strategic development. The WHO Thematic Platform for Health-EDRM Research Group was established to coordinate activities, promote information-sharing, develop partnerships, and provide technical advice to strengthen the Health-EDRM research field. This group will promote the generation of robust and scientific health research to support the meaningful implementation of the Sendai Framework.
Lost for Words Amongst Disaster Risk Science Vocabulary?
Ilan Kelman
2018, 9(3): 281-291.   doi: 10.1007/s13753-018-0188-3
[Abstract](4) [PDF 0KB](0)
摘要:
Like other subjects, disaster risk science has developed its own vocabulary with glossaries. Some keywords, such as resilience, have an extensive literature on definitions, meanings, and interpretations. Other terms have been less explored. This article investigates core disaster risk science vocabulary that has not received extensive attention in terms of examining the meanings, interpretations, and connotations based on key United Nations glossaries. The terms covered are hazard, vulnerability, disaster risk, and the linked concepts of disaster risk reduction and disaster risk management. Following a presentation and analysis of the glossary-based definitions, discussion draws out understandings of disasters and disaster risk science, which the glossaries do not fully provide in depth, especially vulnerability and disasters as processes. Application of the results leads to considering the possibility of a focus on risk rather than disaster risk while simplifying vocabulary by moving away from disaster risk reduction and disaster risk management.
Understanding the El Niño Costero of 2017: The Definition Problem and Challenges of Climate Forecasting and Disaster Responses
Ivan J. Ramírez, Fernando Briones
2017, 8(4): 489-492.   doi: 10.1007/s13753-017-0151-8
[Abstract](1) [PDF 0KB](0)
摘要:
This preliminary study examines the definition problem and challenges of climate forecasting and disaster responses associated with the El Niño costero (coastal) of 2017, which developed rapidly with no warning and had catastrophic effects in Peru. Such a localized El Niño was not documented since 1925. An initial review suggests that in addition to the characteristics of the event (surprise), government responses may have been inadequate (as media reported) because of conflicting forecast reports (U.S. and Peru), which provoked a hydrometeorological debate and stifled decision making. Partly to blame was the El Niño definition problem, which can cause uncertainty and affect perception of risk, depending on which region of the equatorial Pacific one uses to identify an event. Responses were further complicated by the fact that some regions within Peru were experiencing drought prior to the El Niño costero's onset and impacts from the El Niño 2015-2016 were less than expected. Furthermore, a new government was in place, which may have hindered action. Thus, El Niño costero provides lessons to heed, not only with respect to the forecast information, but also with reference to the context of the forecast and disaster setting, which can influence disaster responses to hydrometeorological threats.
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CNKI

Chinese Academy of Sciences (CAS) - GoOA

Chinese Science Citation Database

Current Contents/Physical, Chemical and Earth Sciences

DOAJ

Dimensions

EBSCO Discovery Service

EBSCO Political Science Complete

EBSCO Risk Management Reference Center

EMBiology

Gale

GeoRef

Geobase

Google Scholar

INIS Atomindex

Institute of Scientific and Technical Information of China

Journal Citation Reports/Science Edition

Naver

OCLC WorldCat Discovery Service

ProQuest Advanced Technologies & Aerospace Database

ProQuest Agricultural & Environmental Science Database

ProQuest Aquatic Sciences and Fisheries Abstracts (ASFA)

ProQuest Central

ProQuest Earth, Atmospheric & Aquatic Science Database

ProQuest Engineering

ProQuest Environmental Science

ProQuest Materials Science and Engineering Database

ProQuest Military Database

ProQuest Natural Science Collection

ProQuest Oceanic Abstracts

ProQuest SciTech Premium Collection

ProQuest Technology Collection

ProQuest-ExLibris Primo

ProQuest-ExLibris Summon

SCImago

SCOPUS

Science Citation Index Expanded (SciSearch)

Semantic Scholar

TD Net Discovery Service

UGC-CARE List (India)

Impact factor
2.048 (2019)
Five year impact factor
2.728 (2019)
Downloads
286,425 (2019)
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