Exposure to natural hazard events unassociated with policy change for improved disaster risk reduction

Valuation of marine integrated disaster management amidst global warming in Southern Coast of Java, Indonesia

This research explores the valuation of integrated disaster management in the coastal regions of Southern Java, Indonesia, a locale increasingly threatened by the impacts of global warming, which exacerbates marine disasters such as earthquakes and tsunamis. Employing a choice experiment methodology, the study assesses the willingness to pay among local households for various strategies designed to enhance earthquake preparedness. Three distinct scenarios are examined, each reflecting varying levels of integration and sophistication: (1) Educational empowerment and localized alert integration, which emphasizes community education and rapid, self-directed evacuation practices tailored to the immediate onset of tsunamis following seismic events. This scenario advocates for the '20-20-20' rule, underscoring self-evacuation as the most dependable survival method; (2) Strategic evacuation enablement, focusing on the logistics of evacuation and infrastructure development to facilitate timely community response; and (3) Integrated marine disaster management, which merges educational, technological, logistical, and ecological elements into a comprehensive strategy.

The role of large reservoirs in drought and flood disaster risk mitigation: A case of the Yellow River Basin

The acceleration of water cycle processes in the context of global warming will exacerbate the frequency and intensity of extreme events and predispose to drought and flood disasters (DFD). The Yellow River Basin (YRB) is one of the basins with significant and sensitive impacts of climate change, comprehensive assessment and prediction of its DFD risk are of great significance for ecological protection and high-quality development. This study first constructed an evaluation index system for drought disaster risk and flood disaster risk based on hazard, vulnerability, exposure and the role of large reservoirs. Secondly, the weights of each evaluation index are established by the analytic hierarchy process. Finally, based on the four-factor theory of disasters, an evaluation model of DFD risk indicators is established. The impact of large reservoirs on DFD risk in the YRB is analyzed with emphasis. The results show that from 1990 to 2020, the drought disaster risk in the YRB is mainly distributed in the source area of the Yellow River and the northwest region (11.26-15.79 %), and the flood disaster risk is mainly distributed in the middle and lower reaches (30.04-31.29 %). Compared to scenarios without considering large reservoirs, the area at risk of high drought and high flood is reduced by 45.45 %, 44.22 % and 31.29 % in 2000, 2010 and 2020, respectively. Large reservoirs in the YRB play an important role in mitigating DFD risk, but their role is weakened with the enhancement of the emission scenario. Under the influence of different scenario models, the DFD risk in the YRB in 2030 and 2060 will increase, and the area of high drought and high flood risk in the middle and upper reaches of the basin will increase by 0.26-25.15 %. Therefore, the YRB should play the role of large reservoirs in DFD risk defense in its actions to cope with future climate change, while improving non-engineering measures such as early warning and emergency management systems to mitigate the impacts of disasters.

Under which conditions do extreme events support a paradigm shift? Studying focusing events during two centuries of Swiss flood risk management

Extreme weather events affect many areas around the world. How a country or region reacts to it can take many forms. In this article, we concentrate on policy responses, as typically found in laws, acts, or strategies. Recent research in climate change adaptation or environmental governance concluded that the degree of severity of extreme events is a crucial indicator that policy action should be taken. The event alone is a necessary, but insufficient condition for policies to be introduced. In this context, we ask: Which conditions must be at stake so that an extreme event is able to deploy its focal power and induce policy introduction or change? To answer this question, we studied more than two centuries of flood risk management in Switzerland. We relied on qualitative and quantitative data, as well as process tracing techniques, to relate event characteristics, media, political, and policy contexts to policy change in flood risk management. Results indicate that two conditions made floods turn into focusing events and support paradigm shift: high economic damage and a policy subsystem's actor constellation favorable to change. We are convinced that our results are also replicable for other natural disasters and other countries than only Switzerland.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10113-024-02316-2.

Evaluating causative factors for landslide susceptibility along the Imphal-Jiribam railway corridor in the North-Eastern part of India using a GIS-based statistical approach

The Northeast part of India is experiencing an increase in infrastructure projects as well as landslides. This study aims to prepare the landslide susceptibility map of Tamenglong and Senapati districts, Manipur, India, and evaluates the state of landslide susceptibility along the Imphal-Jiribam railway corridor. Efficient statistical methods such as frequency ratio (FR), information value (IoV), weight of evidence (WoE), and weighted linear combination (WLC) were used in model preparation. A total of 322 landslide points were randomly divided into training (70%) and testing (30%) datasets. Nine causative factors were utilized for landslide susceptibility mapping (LSM). The importance of which was obtained using the information gain (IG) method. FR, IoV, WoE, and WLC were used to prepare the LSM using the training datasets and nine causative factors. Moreover, the accuracy and consistency were evaluated using AUC-ROC, precision, recall, overall accuracy (OA), balanced accuracy (BA), and F-score. The validation results showed that all methods performed well with the highest AUC and precision values of 0.913 and 0.95, respectively, for the IoV method, while the WLC method had the highest OA, BA, and F-score values of 0.808, 0.81, and 0.812, respectively. Finally, the results from LSM were used to evaluate the state of landslide susceptibility along the Imphal-Jiribam railway corridor. The results showed that 34% of the areas had high and very high susceptibility, while 40% were under less and significantly less susceptibility. The Tupul landslide area lay in medium susceptibility where the disastrous landslide occurred on 30 June 2022. Susceptibility values around the Noney and Khongsag railway station ranged from high to very high susceptibility. Thus, the study manifests the need for LSM preparation in rapidly constructing areas, which in turn will help the policymakers and planners for adopting strategies to minimize losses caused due to landslides.

Evolution of natural disaster terminologies, with a case study of the covid-19 pandemic

Disaster, catastrophe, and cataclysm are some English terminologies that describe the severity of adverse events. Civilians, reporters, and professionals often use these terminologies to communicate and report any event's severity. This linguistic method is the most practical way to rapidly reach all levels of local/regional/national, and international stakeholders during disasters. Therefore, disaster terminologies play a significant role in disaster management. However, attaining the actual magnitude of a disaster's severity cannot be comprehended simply by using these terminologies because they are used interchangeably. Unfortunately, there is no consistent method to differentiate disaster terminologies from one another. Additionally, no globally accepted standard technique exists to communicate the severity level when disasters strike; one observer's 'disaster' can be another's 'catastrophe'. Hence, a nation's ability to manage extreme events is difficult when there are no agreed terminologies among emergency management systems. A standard severity classification system is required to understand, communicate, report, and educate stakeholders. This paper presents perceptions of people about disaster terminologies in different geographical regions, rankings and differences in disaster lexical and lexicon. It explores how people perceive major events (e.g., the Covid-19 pandemic), and proposes a ranking of disaster terminologies to create a severity classification system suitable for global use.

Individual Earthquake Resilience Scale: Psychometric Properties of the Turkish Version

INTRODUCTION

The Individual Earthquake Resilience Scale was developed with the aim of measuring individual resilience in the context of earthquake disasters. The purpose of this study was to adapt the Individual Earthquake Resilience Scale into Turkish and examine its psychometric properties.

METHODS

A total of 419 adult individuals (65.2% females, median age = 43.35) participated in the study. The psychometric properties of the scale were examined in terms of content validity, face validity, construct validity, criterion-related validity, and reliability. Translation and back-translation processes were conducted.

RESULTS

Confirmatory factor analyses revealed that the scale has a 4-factor structure. In terms of criterion-related validity, a positive relationship was found between Individual Earthquake Resilience and the Short Psychological Resilience Scale. The reliability of the scale was assessed using Cronbach's alpha coefficient. The total scale had a Cronbach's alpha score of 0.892. The Individual Earthquake Resilience Questionnaire subscales had Cronbach's alpha scores of 0.620, 0.817, 0.776, and 0.692, respectively.

DISCUSSION

The study confirmed that the 4-factor structure of the Individual Earthquake Resilience Scale met the required standards for validity and reliability at an acceptable level. This validates its use in assessing individual resilience within the context of earthquakes in a Turkish-speaking population.

Resilience patterns of human mobility in response to extreme urban floods

Large-scale disasters can disproportionately impact different population groups, causing prominent disparity and inequality, especially for the vulnerable and marginalized. Here, we investigate the resilience of human mobility under the disturbance of the unprecedented '720' Zhengzhou flood in China in 2021 using records of 1.32 billion mobile phone signaling generated by 4.35 million people. We find that although pluvial floods can trigger mobility reductions, the overall structural dynamics of mobility networks remain relatively stable. We also find that the low levels of mobility resilience in female, adolescent and older adult groups are mainly due to their insufficient capabilities to maintain business-as-usual travel frequency during the flood. Most importantly, we reveal three types of counter-intuitive, yet widely existing, resilience patterns of human mobility (namely, 'reverse bathtub', 'ever-increasing' and 'ever-decreasing' patterns), and demonstrate a universal mechanism of disaster-avoidance response by further corroborating that those abnormal resilience patterns are not associated with people's gender or age. In view of the common association between travel behaviors and travelers' socio-demographic characteristics, our findings provide a caveat for scholars when disclosing disparities in human travel behaviors during flood-induced emergencies.

Relationships between COVID-19 and disaster risk in Costa Rican municipalities

The COVID-19 pandemic has had far-reaching impacts on every aspect of human life since the first confirmed case in December 2019. Costa Rica reported its first case of COVID-19 in March 2020, coinciding with a notable correlation between the occurrence of disaster events at the municipal scale over the past five decades. In Costa Rica, over 90% of disasters are hydrometeorological in nature, while geological disasters have caused significant economic and human losses throughout the country's history. To analyze the relationship between COVID-19 cases and disaster events in Costa Rica, two Generalized Linear Models (GLMs) were used to statistically evaluate the influence of socio-environmental parameters such as population density, social development index, road density, and non-forested areas. The results showed that population and road density are the most critical factors in explaining the spread of COVID-19, while population density and social development index can provide insights into disaster events at the municipal level in Costa Rica. This study provides valuable information for understanding municipal vulnerability and exposure to disasters in Costa Rica and can serve as a model for other countries to assess disaster risk.

Big events, little change: Extreme climatic events have no region-wide effect on Great Barrier Reef governance

Extreme climatic events trigger changes in ecosystems with potential negative impacts for people. These events may provide an opportunity for environmental managers and decision-makers to improve the governance of social-ecological systems, however there is conflicting evidence regarding whether these actors are indeed able to change governance after extreme climatic events. In addition, the majority of research to date has focused on changes in specific policies or organizations after crises. A broader investigation of governance actors' activities is needed to more fully understand whether or not crises trigger change. Here we demonstrate the use of a social network analysis of management and decision-making forums (e.g. meetings, partnerships) to reveal the effects of an extreme climatic event on governance of the Great Barrier Reef over an eight-year period. To assess potential shifts in action, we examine the topics of forums and the relative participation and influence of diverse governance actors before, during, and after two back-to-back mass coral bleaching events in 2016 and 2017. Our analysis reveals that there is little change in the topics that receive attention, and in the relative participation and influence of different actor groups in the region. Our research demonstrates that network analysis of forums is useful for analyzing whether or not actors' activities and priorities evolve over time. Our results provide empirical evidence that governance actors struggle to leverage extreme climate events as windows of opportunity and further research is needed to identify alternative opportunities to improve governance.

Dealing with the COVID-19 pandemic: an opportunity to reflect on sustainability research

The COVID-19 pandemic has jolted societies out of normality, possibly creating new conditions for sustainability transformations. What does this mean for sustainability research? Because of the scope of the crisis, researchers have been heavily involved: not only have they had to speed up the pace of scientific production to provide urgently needed COVID-19 knowledge, but they have also been affected citizens. For sustainability science, this calls for an experience-based reflection on the positionality and orientation of research aiming to support sustainability transformations. Twenty sustainability researchers discussed their sustainability research on COVID-19 in three workshops based on the following questions: How does the pandemic—and the measures taken to deal with it—affect sustainable development? What can we learn from the pandemic from the perspective of societal transformation? The present discussion paper emerged from this multidisciplinary exchange among sustainability researchers, considering five topics: impacts of the COVID-19 crisis on sustainability transformations; learning for sustainability transformations; the role of solidarity; governance and political steering; and the role of science in society. Our discussions led to a meta-level reflection on what sustainability research can learn from research on COVID-19 regarding topics and disciplinary angles, time dimensions, the role of researchers, and how adequate preparation for both crises and long-term transformations requires interdisciplinary interaction.

Have Extreme Events Awakened Us?

We may translate anthropogenic climate change as a reaction of our planet to our unsustainable economic activities. This research explores whether environmental policies have been impacted by extreme climatic events like droughts, floods, storms, tornados, and wildfires. We use yearly panel data from 1990 to 2017 for the OECD (Organization for Economic Cooperation and Development) countries to examine such a relationship. To have an impartial analysis, we control major variables influencing environmental policies such as energy consumption, gross domestic product (GDP), population, technology, head of the state’s political affiliation, carbon emission, and waste generation. The analysis results suggest that policymakers make more stringent environmental decisions as the death rate increases and environmental threats become more imminent putting human life is at risk; this correlation is stronger in the case of European Countries.

Exploring disaster impacts on adaptation actions in 549 cities worldwide

Whether disasters influence adaptation actions in cities is contested. Yet, the extant knowledge base primarily consists of single or small-N case studies, so there is no global overview of the evidence on disaster impacts and adaptation. Here, we use regression analysis to explore the effects of disaster frequency and severity on four adaptation action types in 549 cities. In countries with greater adaptive capacity, economic losses increase city-level actions targeting recently experienced disaster event types, as well as actions to strengthen general disaster preparedness. An increase in disaster frequency reduces actions targeting hazard types other than those that recently occurred, while human losses have few effects. Comparisons between cities across levels of adaptive capacity indicate a wealth effect. More affluent countries incur greater economic damages from disasters, but also have higher governance capacity, creating both incentives and opportunities for adaptation measures. While disaster frequency and severity had a limited impact on adaptation actions overall, results are sensitive to which disaster impacts, adaptation action types, and adaptive capacities are considered.

The Trump Administration and the COVID-19 crisis: Exploring the warning-response problems and missed opportunities of a public health emergency

This article examines the Trump Administration's inability to mount a timely and effective response to the COVID-19 outbreak, despite ample warning. Through an empirical exploration guided by three explanatory perspectives-psychological, bureau-organizational, and agenda-political-developed from the strategic surprise, public administration, and crisis management literature, the authors seek to shed light on the mechanisms that contributed to the underestimation of the coronavirus threat by the Trump Administration and the slow and mismanaged federal response. The analysis highlights the extent to which the factors identified by previous studies of policy surprise and failure in other security domains are relevant for health security. The paper concludes by addressing the crucial role of executive leadership as an underlying factor in all three perspectives and discussing why the US president is ultimately responsible for ensuring a healthy policy process to guard against the pathologies implicated in the federal government's sub-optimal response to the COVID-19 crisis.

Multinational enterprises and natural disasters: Challenges and opportunities for IB research

The purpose of this paper is to encourage and to extend research on natural disasters and international business (IB). More specifically, we review the characteristics of natural disasters and the unique challenges they pose to the business environment and examine how they differ from other types of disasters/crises often researched in the IB literature. Next, we investigate the applicability and challenges of core IB theories to the study of natural disasters. By extending new internalization theory (NIT) to overcome challenges of bounded rationality and reliability, we identify effective strategies for managing the threat of natural disasters through establishing multi-sector partnerships and alternative supply chains. Integrating research on the characteristics of natural disasters and the insights from NIT, we propose natural disaster management strategies for multinational enterprises (MNEs) based on varying degrees of geographic scope of natural disasters and MNEs. This paper concludes with proposing new research opportunities for IB scholars in disaster preparedness, cross-organizational collaborations, and supply chain management.

DSMNN-Net: A Deep Siamese Morphological Neural Network Model for Burned Area Mapping Using Multispectral Sentinel-2 and Hyperspectral PRISMA Images

Wildfires are one of the most destructive natural disasters that can affect our environment, with significant effects also on wildlife. Recently, climate change and human activities have resulted in higher frequencies of wildfires throughout the world. Timely and accurate detection of the burned areas can help to make decisions for their management. Remote sensing satellite imagery can have a key role in mapping burned areas due to its wide coverage, high-resolution data collection, and low capture times. However, although many studies have reported on burned area mapping based on remote sensing imagery in recent decades, accurate burned area mapping remains a major challenge due to the complexity of the background and the diversity of the burned areas. This paper presents a novel framework for burned area mapping based on Deep Siamese Morphological Neural Network (DSMNN-Net) and heterogeneous datasets. The DSMNN-Net framework is based on change detection through proposing a pre/post-fire method that is compatible with heterogeneous remote sensing datasets. The proposed network combines multiscale convolution layers and morphological layers (erosion and dilation) to generate deep features. To evaluate the performance of the method proposed here, two case study areas in Australian forests were selected. The framework used can better detect burned areas compared to other state-of-the-art burned area mapping procedures, with a performance of >98% for overall accuracy index, and a kappa coefficient of >0.9, using multispectral Sentinel-2 and hyperspectral PRISMA image datasets. The analyses of the two datasets illustrate that the DSMNN-Net is sufficiently valid and robust for burned area mapping, and especially for complex areas.