Progress in Disaster Science最新文献

Disasters, disaster risks, and disaster risk management (DRM) present complex temporalities that must be taken into consideration when conducting evaluations that assist the choice of new strategies. Given the non-linearity of change, including long-term perspectives can modify the evaluation results and recommendations, but little is known about how time horizons are selected in DRM evaluation. This exploratory study investigates the determinants that affect what time horizon is considered in DRM evaluation. 12 semi-structured interviews with professional evaluators from different parts of the world were conducted in spring 2022. Their experiences indicate that the interpretation of what is long term in DRM evaluation is context-dependent. The factors determining if time horizons are expanded or narrowed relate to four categories: the actors involved in the evaluation, the purpose of the evaluation, the resources available to conduct the evaluation, and the specific DRM context. It is concluded that DRM evaluation seems to be quite similar to other public policy evaluations, except the DRM context that plays an important role by determining the timing of the evaluation, which itself affects what time horizon should be and/or is considered.

Since the first School Safety Program launched by the Ministry of Education and Training in 2007, Vietnam has promoted various multi-sectoral activities to advance school safety nationwide. This study aims to identify the opportunities to advance school disaster safety by assessing policies and practices in Vietnam. A framework adapted from the ASEAN Comprehensive School Safety Framework and School Disaster Resilience Assessment is utilized to evaluate policy coverage and implementation level of school safety in Vietnam. The study systematically reviewed legal documents at national level, followed by questionnaire surveys conducted for primary schools in Da Nang City, which was selected as a pilot evaluation site owing to its vulnerability to natural disasters and extensive records of school safety practices. Results show that the most critical elements of school safety have been reflected in existing policy documents and regulations. However, the gap between policies and implementation remains due to the inadequacy of school safety viewpoint, designated roles and responsibilities, resources, and guidelines for supporting the school safety practices at the local level. The findings emphasize the importance of a national school safety framework that enables institutional and resource arrangements for better practices at the local level.

In disaster response, the overwhelming amount of time-sensitive information and response options, combined with the dynamic nature of disasters, makes decision-making challenging for emergency service providers. Furthermore, it is often not economically feasible for countries to maintain a large number of full-time emergency responders. As such, many countries rely heavily on volunteer emergency responders during major disasters. This means that the success of disaster response often hinges on the efficient use of this volunteer workforce. We propose a framework for a Decision Support System (DSS) designed to optimize the use of volunteers by emergency services. This framework includes the data management layer, integrating necessary inputs and information; the analytical layer, which serves as the system's processing core; the user interface layer; and the decision-making layer. We argue that, while significant academic focus has been on the analytical layer, practical implementation requires the integration of all four components. Additionally, we emphasize the need for coordination with a broad spectrum of stakeholders involved in data provision, decision-making, and resource deployment for operationalizing this DSS. We also explore and analyze existing methodologies for developing the analytical layers, the requirements of these models, and the current methodological gaps. The proposed framework establishes a clear roadmap for adopting emergency response approaches that are human-centric, but at the same time, effectively utilize advancements in modeling, optimization, machine learning, and data integration.

Floods exacerbate economic inequality, disproportionately affecting the poor in flood-prone areas while the rich in non-flood-prone regions continue to prosper. While this trend was illustrated conceptually and qualitatively, this study offers the first quantitative evidence that floods widen the economic disparity gap between the rich and poor in flooded and non-flooded areas. Using Household Interview Survey (HIS) data, we analyze the floods of Thailand's Chao Phraya River in 2011 and 2021 to measure the economic impact on households. The economic gap between the non-flooded rich and flooded poor widened from 38,539 Baht in 2011 to 104,897 Baht in 2021, a 2.7-fold increase. Surprisingly, the poor in our study differed from the hypothesis in that there was still improving economic growth, albeit small. Floods decrease the poor's ability to accumulate wealth – 9.2%, as opposed to 60.7% for the rich – although their impact on widening disparity for households of the same economic stratum was far greater for the poor (widened 18×) than for the rich (widened 4.7×). Finally, we propose ‘net total cash’ as a better measure of economic change compared to ‘income’ or ‘expenditure’, minimizing external influences like the COVID-19 pandemic, which in 2021 caused income to plummet and expenditure to rise.

Climate change is expected to affect the frequency and magnitude of floods, which are among the costliest hazards in Europe. As natural hazards have a significant impact on infrastructure and people's lives and their habitats, novel measures to cope with climate change need to be considered. Different types of measures, such as green, grey and hybrid solutions, can be used to mitigate the impacts of natural hazards. Green measures (also referred to as nature-based solutions) are currently being promoted in the European Union, but several barriers to implementing these measures exist. The question arises as to what hinders the wider implementation of green measures and therefore results in a preference for conventional grey measures in some countries. This study examines the differences in the perceived effectiveness, feasibility and acceptance of different types of flood risk management measures in three European countries (Slovenia, Czechia, and the Netherlands). The results show statistically significant differences in the perceived effectiveness, feasibility and acceptance of the studied measures. With respect to individual measures, respondents in all three countries tend to view conventional grey measures (dams and cisterns) as more effective and acceptable than green and hybrid measures. However, grey measures are perceived as difficult to implement. The results reveal that the perceived effectiveness and acceptability of the measures are related. The major drivers affecting the differences in the perceptions of different measures are the countries of the respondents and the sociodemographic variables of income and age. In contrast to other studies, experiences with past floods and private insurance are not statistically significant. Our results thus indicate that, along with individual behaviour, aggregate social drivers should be considered when implementing flood risk management measures across the EU.

Millions are living in shelters around the world, often for decades. Architects are rarely trained in shelter design and as a result speculative designs are frequently impractical or insensitive to occupants. In addition, aid agency staff can lack engineering or architectural knowledge, so need support during shelter procurement. Evidence gathered by the authors in seven countries over three years revealed poor conditions within many shelters, including condensation, excessive temperatures, lack of privacy and poor air quality, all of which contribute to increased morbidity and mortality. To address this, the paper proposes a design assessment platform, the Shelter Assessment Matrix (SAM), covering 34 issues. SAM also includes guidance documents that allow users to upskill themselves on a range of topics. The tool was tested in three ways: (i) 11 agency staff were asked to assess the same shelter. The mean score was 45.7/100, standard deviation (SD) 2.96. The narrow SD indicated that SAM provided consistent scoring. (ii) 187 previously deployed shelters were evaluated and scored between 27 and 78. This suggests that SAM generates a range of scores, and that shelters could be improved. This evaluation also provides the first contextualised performance analysis of shelters around the world, and a repository for others to judge their designs against. (iii) Use of the platform resulted in considerable measured uplifts in building science and cultural knowledge. SAM has been made freely available online and has been used by agencies to materially improve the design of shelters for thousands of individuals in four countries.

Natural meteorological and climatological hazards and vulnerable vegetation are frequent triggers of natural disasters, such as wildfires. These cause loss of life and significant economic damage, likely to increase due to climate and socio-economic changes. The increase in wildfires in recent decades has affected the decision-making of technocrats and policy experts and created the need for more sophisticated risk management. This paper develops a theoretical framework for reducing the economic impact of wildfire risk on forests. Also provides insight into land use decisions regarding losses that this increased risk of forest land management can cause. The impact of wildfire risk on economic land value is evaluated by comparing three scenarios, i.e. the deterministic risk-adjusted land expectation value with its risk-free counterparts calculated assuming the stationary risk and predicted increasing risk as time goes by. Also, for this purpose, we evaluate the economically optimal length rotation period pine stands and the risk premium. Fire risk is described as the probability of pine stands destruction due to their age and meteorological conditions in the experimental area Záhorská lowland (western Slovakia). Our findings highlight the importance of alerting forest policymakers to carefully incorporate assessment of the increasing risk of random natural disasters due to climate change into sustainable forest management. The study's results will also help current or future forest owners estimate and evaluate the economic/investing risk when buying or selling forest land.

This study proposes measuring access to shelters and wildfire risks in tandem rather than in isolation to prevent wildfires from turning into human disasters. By leveraging a human-centered design approach in California, which has an active wildfire history and experience with some of the deadliest wildfires, three key findings are discerned. First, California experiences undesirable resource allocation where regions with a high risk of wildfire are surrounded by regions with a low level of access to emergency shelters, and regions with a low risk of wildfire are surrounded by regions with a high level of access to emergency shelters. Second, neither access to shelters nor wildfire risk is evenly distributed across space. This uneven distribution, however, discriminates against exurban areas. As one moves away from core cities, higher wildfire risk and comparatively limited access to emergency shelters are noticed, underscoring the heightened susceptibility of exurban areas to wildfires. Third, in contrast with existing research solely focusing on wildfire risk, it is revealed that the elderly, people with disabilities, and Hispanics are at a higher risk of experiencing high wildfire risk and low access to shelters. The findings suggest instilling equity into wildfire preparedness strategies while minimizing the gap in access to resources between disadvantaged and advantaged communities, given the trichotomy of exposure to the hazard (risk of wildfire), proximity to aid (access to shelters), and vulnerability to threat (community characteristics).

Being susceptible to natural disasters, Bangladesh is one of the most disaster-prone countries. Among the various natural calamities, droughts are a frequent occurrence in the western region of the country. Hence, this study first compared the efficacy of five bias-corrected Regional Climate Models (RCMs) - MIROC, NOAA, MPI, IPSL, and CCCma - for the Western region of Bangladesh with observed monthly precipitation and subsequent SPI values. Various evaluation methods- RMSE, Taylor Diagram, Mann–Whitney U Test, and t-test, were applied to precipitation and SPI3 values for the historical base period. Through these analyses, the MIROC model exhibited the highest level of accuracy. Accordingly, future projections for short-term droughts (SPI-3) and their characteristics were conducted using the ensemble of top three climate model under the RCM 8.5 W/m² scenario. Short-term droughts are anticipated to become less frequent and severe in the 2060s and 2080s compared to the 2020s. Nonetheless, North-West region is projected to be more drought-prone than South-West until 2100. This research shows the importance of evaluating the better-fitting RCMs for assessing historical droughts and making reliable projections for the future. The methodology and findings can be employed in evidence-based decision-making and applied in other drought-prone areas to understand future drought risks.

The east coast of India, especially the coastal region of Odisha, is highly threatened by tropical cyclones. This study develops a detailed risk map for tropical cyclones in the coastal districts of Odisha at the micro level, focusing on the assessment of risk factors at the block level. Using a multi-criteria decision making (MCDM) approach, the study considers four primary risk components: Exposure, vulnerability, susceptibility, and mitigation options. The Explainable Artificial Intelligence (XAI) framework, which uses the XGBoost model in conjunction with SHAP values, is applied to identify and elucidate the factors influencing risk levels in 69 blocks. Results indicate that about 65% of the area is at high risk to tropical cyclone, especially in the northeastern and central regions. In particular, 32 blocks are classified as high to very high-risk zones. The study shows a contrast in risk levels, with blocks in the northeast and southeast at higher risk, while blocks in the southern regions such as Ganjam and Puri and in the central parts of Kendrapara and Baleswar districts are at lower risk. The findings from this study are crucial for local authorities to identify vulnerable areas and improve cyclone preparedness and risk management strategies in Odisha.