The notion of “spatial vulnerability” is present in most disaster studies with a strong geographical connotation and accordingly is adopted at all scales, including the urban. While enabling mapping and visualizing risk patterns at macroscales, this geocentric foundation fails to capture disaster risk dynamics associated with the urban spatial network—an element that plays a significant role in the everyday and emergency functioning of cities, enabling users’ movement and interaction. Yet, urban vulnerability assessment overlooks this aspect and thus leaves urban disaster risk mechanisms partially unexplored. This study investigated the role of the network of urban public open spaces (UPOS) in the creation and progression of urban disaster risk in earthquake-prone settlements. Through a multimethod approach that integrates quantitative and qualitative methods and explores spatial configuration, planning policies, and practices of use of UPOS in everyday and emergency scenarios, our study demonstrated that UPOS configuration plays an active role in urban disaster risk. Urban public open spaces impact risk by influencing the exposure of pedestrians and their capacity for self-protection. The study further reconceptualized spatial vulnerability at the urban scale, as the fraction of vulnerability associated to the spatial network, highlighting the interplay of planning policies and spatial practices in its production and progression. Our findings make the notion of spatial vulnerability less ambiguous at the urban scale, by viewing the variable as an imbalance in capacities and exposure that generates spatially unsafe conditions. This refined conceptualization of spatial vulnerability becomes a lens for a more granular approach to urban disaster risk reduction and city planning by identifying and integrating sociospatial considerations.
Risk governance is a widely used framework in natural and societal risk management research. Risks from natural hazards in urban areas call for the establishment of rigorous and participatory urban risk governance. In this study, we examined participatory risk governance (PRG) of flood risk management (FRM) in Seoul, South Korea. We conducted key informant interviews and implemented a survey with citizens, to explore perceptions of flood risks and risk management, and to examine prospects for improving PRG in Seoul. We found a gap between the perceptions of key informants and citizens. Key informants believed that citizens’ low awareness of flood risks hinders PRG. Yet our research found that citizens’ risk awareness was not low, and risk awareness may not be the main barrier to participation in PRG. Instead, we found that citizens lacked knowledge of FRM actions, and they assigned government bodies a high level of responsibility for FRM, compared to the level of responsibility that citizens assigned to themselves. Moreover, the actors involved in FRM tended not to trust each other, which implies a lack of mutual understanding. To increase the effectiveness of PRG, we suggest a polycentric governance structure anchored by a leading actor group, and active promotion of the participation of actors at multiple levels of governance. Communication between government and citizen participants, designed to foster improved understanding and recognition of one another’s roles and contributions to FRM, will enhance trust and improve the implementation of PRG in Seoul.
Leadership courses in the fire services are highly challenging, and they can seriously exhaust trainees and hamper their self-regulated learning efforts (for example, setting goals, focusing attention, seeking feedback). We theorize that experiences of failure or overload can curtail trainees’ available energy resources on subsequent training days, which, in turn, should affect trainees’ learning efforts. Given instructors’ central role in leadership courses, we hypothesize that supportive and humble instructor behaviors decrease experiences of failure and overload and, thus, increase self-regulated learning. Moreover, we argue that supportive instructor behavior may amplify the positive effects of high energy resources, while humble behavior may alleviate the negative impact of low resource levels. We tested preregistered hypotheses with 118 firefighters participating in two-week leadership courses at a German fire academy. The participants completed short web-based questionnaires before and after classes each day. Multilevel analyses confirmed that perceived daily supportive and humble instructor behavior predicted trainees’ reports of daily self-regulated learning activity. Notably, this effect was independent from positive effects of trainees’ reported energy resources in the morning. Supportive and humble behavior did not moderate the effect of energy resources. Our findings suggest that instructors play a crucial role in facilitating effective learning under challenging training conditions. Furthermore, we offer implications for leaders in fire services, who often conduct trainings with their subordinates.
Due to a lack of resources, rural communities often face challenges when planning catastrophic events. This project involved applying systems thinking and model-based systems engineering to develop a proof-of-concept, multi-method computer simulation and then determining whether the simulation could be used to assess the efficacy of disaster planning approaches on health outcomes in rural communities, as a function of primary healthcare. The project focus was a rural or non-urban healthcare system experiencing a natural hazard. Both system dynamics and discrete event models were incorporated to represent subsystem operations, crucial disaster responses, as well as three key response systems: public health, emergency management, and healthcare. The subsystem models included several components: policies/procedures, communications, resources, exercises/drills/training, healthcare space and staff, and the flow of affected people into and through the system. The combined simulation can serve as a first step to a more comprehensive approach to helping rural communities achieve more efficient and effective healthcare planning for disaster responses.
Sexual and reproductive health (SRH) services are crucial for women especially during disasters, to reduce maternal mortality and morbidity from miscarriages, unsafe abortions, and post-abortion complications. This study explored the SRH interventions provided during disaster response. A systematic review was conducted to identify what menstrual regulation (MR), safe abortion (SA), and post-abortion care (PAC) approaches/interventions exist to promote resilience in the health system in disaster settings; what intervention components were most effective; and challenges and opportunities to meeting SRH rights. Five electronic databases were searched, resulting in 4194 records. Following the screening process, seven publications were included. The intervention-related information in each publication was assessed based on availability, accessibility, acceptability, and quality. Two SRH approaches/interventions were found. The effectiveness of intervention components could not be conducted due to the limited number of relevant studies. Challenges were found at facility and community levels, and opportunities included overcoming them, making MR, SA, and PAC integral to the mitigation phase, and policy change to overcome barriers related to unaffordability and inaccessibility. Recommendations are provided to encourage research and policy towards improving neglected SRH in disaster settings to realize Sustainable Development Goal 3 and the Global Strategy and Sendai Framework’s priority to promote disaster-resilient health systems.
Global and national policy frameworks emphasize the importance of people’s participation and volunteers’ role in disaster risk reduction. While research has extensively focused on volunteers in disaster response and recovery, less attention has been paid on how organizations involved in disaster risk management can support volunteers in leading and coordinating community-based disaster risk reduction. In 2019, the New Zealand Red Cross piloted the Good and Ready initiative in Auckland, Aotearoa New Zealand, with the objective to empower local people in resilience building with a focus on volunteers and community participation. This research examined the positive and negative outcomes of Good and Ready and investigated volunteers’ experiences in the disaster resilience initiative. It involved the codesign of a questionnaire-based survey using participatory methods with Good and Ready volunteers, the dissemination of the survey to gather volunteers’ viewpoints, and a focus group discussion with participatory activities with Red Cross volunteers. The findings highlight that a key challenge lies in finding a balance between a program that provides flexibility to address contextual issues and fosters communities’ ownership, versus a prescriptive and standardized approach that leaves little room for creativity and self-initiative. It pinpoints that supporting volunteers with technical training is critical but that soft skills training such as coordinating, communicating, or facilitating activities at the local level are needed. It concludes that the sustainability of Good and Ready requires understanding and meeting volunteers’ motivations and expectations and that enhancing partnerships with local emergency management agencies would strengthen the program.
Unequal social media attention can lead to potentially uneven distribution of disaster-relief funds, resulting in long-term inequality among regions after disasters. This study aimed to measure inequalities in social media attention to regions during disasters and explore the role of official media in reducing such inequality. This is performed by employing social media, official media, and official aggregated statistics regarding China’s rainstorm disasters. Through a set of panel-data regressions and robustness tests, three main conclusions were drawn: (1) There were inequalities among regions regarding social media attention they received during rainstorm disasters. For disasters of the same magnitude, regions with low economic outcome per capita received less attention on social media. (2) Official media can reduce inequality in social media attention during disasters. Official media statements can encourage netizens to pay attention to disaster-stricken areas, and especially the overlooked underdeveloped areas. (3) Of all the measures taken by official media, timely, accurate, and open disclosure of disaster occurrences proved to be the most potent means of leveling the playing field in terms of social media attention; contrarily, promotional or booster-type messages proved futile in this regard. These findings revealed the vulnerabilities within social media landscapes that affect disaster relief response, shedding light on the role of official guidance in mitigating inequalities in social media attention during such crises. Our study advises social media stakeholders and policymakers on formulating more equitable crisis communication strategies to bridge the gap in social media attention and foster a more balanced and just relief process.
Vulnerability evaluation plays a key role in risk assessment and reduction and is essential for defining strategies for climate change adaptation and mitigation. In dealing with the safeguarding of cultural heritage at risk, we are still far from adopting and applying an agreed methodology for vulnerability assessment. With the aim to support practitioners, heritage managers, and policy and decision makers to undertake actions that address the protection of cultural heritage at risk, the methodology set up in the framework of the Interreg Central Europe STRENCH is illustrated and discussed here. Based on three major requirements (susceptibility, exposure, and resilience) and a continuous consultation with local stakeholders, the proposed methodology is applicable for evaluating the vulnerability of built heritage and cultural landscape exposed to hydrometeorological hazards, such as heavy rains, floods, and droughts. The results obtained through its validation on 15 case studies from seven Central European regions are shown to underline the strengths and limitations of the methodological approach. Iterative consultation with local stakeholders was fundamental for the definition of the criteria/subcriteria and related values for the assessment of the requirements. Application to further sites in other contexts would surely contribute to strengthening the reliability of the methodological approach.
In this study, a broad range of supervised machine learning and parametric statistical, geospatial, and non-geospatial models were applied to model both aggregated observed impact estimate data and satellite image-derived geolocated building damage data for earthquakes, via regression- and classification-based models, respectively. For the aggregated observational data, models were ranked via predictive performance of mortality, population displacement, building damage, and building destruction for 375 observations across 161 earthquakes in 61 countries. For the satellite image-derived data, models were ranked via classification performance (damaged/unaffected) of 369,813 geolocated buildings for 26 earthquakes in 15 countries. Grouped k-fold, 3-repeat cross validation was used to ensure out-of-sample predictive performance. Feature importance of several variables used as proxies for vulnerability to disasters indicates covariate utility. The 2023 Türkiye–Syria earthquake event was used to explore model limitations for extreme events. However, applying the AdaBoost model on the 27,032 held-out buildings of the 2023 Türkiye–Syria earthquake event, predictions had an AUC of 0.93. Therefore, without any geospatial, building-specific, or direct satellite image information, this model accurately classified building damage, with significantly improved performance over satellite image trained models found in the literature.
This study presents a probabilistic seismic risk model for the Beijing–Tianjin–Hebei region in China. The model comprises a township-level residential building exposure model, a vulnerability model derived from the Chinese building taxonomy, and a regional probabilistic seismic hazard model. The three components are integrated by a stochastic event-based method of the OpenQuake engine to assess the regional seismic risk in terms of average annual loss and exceedance probability curve at the city, province, and regional levels. The novelty and uniqueness of this study are that a probabilistic seismic risk model for the Beijing–Tianjin–Hebei region in China is developed by considering the impact of site conditions and epistemic uncertainty from the seismic hazard model.
Growing evidence indicates that extreme heat and rain may occur in succession within short time periods and cause greater impacts than individual events separated in time and space. Therefore, many studies have examined the impacts of compound hazard events on the social-ecological system at various scales. The definition of compound events is fundamental for such research. However, there are no existing studies that support the determination of time interval between individual events of a compound rainstorm and heatwave (CRH) event, which consists of two or more potentially qualifying component heatwave and rainstorm events. To address the deficiency in defining what individual events can constitute a CRH event, this study proposed a novel method to determine the maximum time interval for CRH events through the change in CRH event frequency with increasing time interval between individual events, using southern China as a case study. The results show that the threshold identified by the proposed method is reasonable. For more than 90% of the meteorological stations, the frequency of CRH events has reached a maximum when the time interval is less than or equal to the threshold. This study can aid in time interval selection, which is an important step for subsequent study of CRH events.
The integration of gray and green infrastructure has proven to be a feasible approach for managing stormwater in established urban areas. However, evaluating the specific contributions of such coupled strategies is challenging. This study introduced a novel integrated hydrological-hydrodynamic model that takes into account the layout of low-impact development (LID) facilities along with pipeline alignment and rehabilitation. Reliable results from modeling were used to assess the individual contribution of LID and improved drainage facilities to urban flooding mitigation. We selected a natural island in Guangzhou City, China, as the study site. The results indicate that combining three LID measures, namely green roofs, sunken green spaces, and permeable pavements, can reduce total runoff by 41.7% to 25.89% for rainfall recurrence periods ranging from 1 year to 100 years, and decrease the volume of nodal overflow by nearly half during rainfall events of less than 10-year return period. By integrating LID measures with the upgraded gray infrastructure, the regional pipeline overloading condition is substantially alleviated, resulting in a significant improvement in pipeline system resilience. For urban flooding control, it is recommended to integrate sufficient green space and avoid pipe-laying structural issues during urban planning and construction. The findings may assist stakeholders in developing strategies to best utilize gray and green infrastructure in mitigating the negative effects of urban flooding.