The Disaster Risk, Global Change, and Sustainability Nexus

A new method to compile global multi-hazard event sets

This study presents a new method, the MYRIAD-Hazard Event Sets Algorithm (MYRIAD-HESA), that compiles historically-based multi-hazard event sets. MYRIAD-HESA is a fully open-access method that can create multi-hazard event sets from any hazard events that occur on varying time, space, and intensity scales. In the past, multi-hazards have predominately been studied on a local or continental scale, or have been limited to specific hazard combinations, such as the combination between droughts and heatwaves. Therefore, we exemplify our approach by compiling a global multi-hazard event set database, spanning from 2004 to 2017, which includes eleven hazards from varying hazard classes (e.g. meteorological, geophysical, hydrological and climatological). This global database provides new scientific insights on the frequency of different multi-hazard events and their hotspots. Additionally, we explicitly incorporate a temporal dimension in MYRIAD-HESA, the time-lag. The time-lag, or time between the occurrence of hazards, is used to determine potentially impactful events that occurred in close succession. Varying time-lags have been tested in MYRIAD-HESA, and are analysed using North America as a case study. Alongside the MYRIAD-HESA, the multi-hazard event sets, MYRIAD-HES, is openly available to further increase the understanding of multi-hazard events in the disaster risk community. The open-source nature of MYRIAD-HESA provides flexibility to conduct multi-risk assessments by, for example, incorporating higher resolution data for an area of interest.

The evolution process of ecological vulnerability and its quantitative analysis of influencing factors: a case study of Longdong area

Ecological vulnerability is the main index to evaluate areal environmental stability and monitor the development of ecological environment. Longdong area is a typical Loess Plateau area with complex terrain, serious soil erosion, mineral resource development, and other human activities leading to the ecological vulnerability evolution of the area, but the monitoring of its ecological status and the determination of its factors are still lacking. Based on the ecological characteristics of Longdong area, this study constructed an ecological vulnerability system including natural, social, and economic data and used the fuzzy analytic hierarchy process (FAHP) to study the temporal and spatial evolution of ecological vulnerability from 2006 to 2018. A model for quantitative analysis of the evolution of ecological vulnerability and correlation of influencing factors was ultimately developed. The results showed that (1) from 2006 to 2018, the ecological vulnerability index (EVI) had a minimum value of 0.232 and a maximum value of 0.695. EVI was high in the northeast and southwest of Longdong area and low in the central region. (2) At the same time, the areas of potential vulnerability and mild vulnerability increased, and the areas of slight vulnerability, moderate vulnerability, and severe vulnerability decreased. (3) The correlation coefficient between average annual temperature and EVI exceeded 0.5 in four years, and the correlation coefficient between population density and per capita arable land area and EVI exceeded 0.5 in two years showed significant correlation. The results reflect the spatial pattern and influencing factors of ecological vulnerability in typical arid areas of northern China. Additionally, it served as a resource for researching the interrelationships of the variables affecting ecological vulnerability.

Towards a holistic paradigm for long-term snow avalanche risk assessment and mitigation

In mountain territories, snow avalanches are a prevalent threat. Long-term risk management involves defining meaningful compromises between protection and overall sustainability of communities and their environment. Methods able to (i) consider all sources of losses, (ii) account for the high uncertainty levels that affect all components of the risk and (iii) cope for marked non-stationarities should be employed. Yet, on the basis of a literature review and an analysis of relations to Sustainable Development Goals (SDGs), it is established that snow avalanche risk assessment and mitigation remain dominated by approaches that can be summed up as deterministic, hazard oriented, stationary and not holistic enough. A more comprehensive paradigm relying on formal statistical modelling is then proposed and first ideas to put it to work are formulated. Application to different mountain environments and broader risk problems is discussed.

Sustainable Development Goals and risks: The Yin and the Yang of the paths towards sustainability

The United Nations 2030 Agenda and Sustainable Development Goals (SDGs) define a path towards a sustainable future, but given that uncertainty characterises the outcomes of any SDG-related actions, risks in the implementation of the Agenda need to be addressed. At the same time, most risk assessments are narrowed to sectoral approaches and do not refer to SDGs. Here, on the basis of a literature review and workshops, it is analysed how SDGs and risks relate to each other's in different communities. Then, it is formally demonstrated that, as soon as the mathematical definition of risks is broadened to embrace a more systemic perspective, acting to maintain socio-environmental systems within their sustainability domain can be done by risk minimisation. This makes Sustainable Development Goals and risks "the Yin and the Yang of the paths towards sustainability". Eventually, the usefulness of the SDG-risk nexus for both sustainability and risk management is emphasized.

International R&D diffusion in disaster management: a systematic review

There are several challenges to the international diffusion of research and development (R&D) in disaster management. The present study aimed to examine a paradigm shift in international R&D diffusion in the field. Qualitative content analysis was used as the methodology in comparing commercialization-based versus humanity-based international R&D diffusion in terms of international organizations, developed nations, and developing nations. A key finding is that the field needs to shift from commercialization-based to humanity-based international R&D diffusion, while enhancing international cooperation, equality and human rights, and networking, among other factors. Compared with previous studies, this research reviewed a paradigm shift in international R&D diffusion in disaster management in a more comprehensive and timely manner.

Disaster risk reduction in mountain areas: an initial overview on seeking pathways to global sustainability

As disasters cripple the world's prospects for sustainable development, protecting the most vulnerable groups exposed to hazards is one of the main challenges facing humanity. Owing to the systemic nature of risk and the interactions and interdependencies between upland and lowland systems, healthy and productive mountain households and livelihoods are essential to global sustainability. This paper argues that, building on existing international frameworks, and integrated knowledge and praxis, the development of a global policy agenda should be established to build sustainable peace, sustainable security, and development.

Assessment of the Role of Nearshore Marine Ecosystems to Mitigate Beach Erosion: The Case of Negril (Jamaica)

Coastal and marine ecosystems are supplying a wide range of services. With accelerated Sea Level Rise, intensification of waves and storm surge severity and increasing anthropogenic pressures, these areas are under multiple threats and society may not receive the same level of ecosystems services. This study aims at measuring the trend of beach erosion and at identifying and quantifying the role of some coastal and marine ecosystems in mitigating beach erosion in the region of Negril (Jamaica). In this location, the tourism industry provides the main source of economic revenue. Even at the national level, the two beaches are important assets linked with 5% of the national revenue as 25% of the hotel rooms are located around Negril. In Jamaica, the tourism industry is a significant component of national GDP. 25% of hotel rooms are located around the two beaches of Negril, which have lost an average of 23.4 m of width since 1968. Given the importance of Negril’s beaches to their economy, the Government of Jamaica asked UNEP to conduct a study to identify causes of beach erosion in Negril and potential solutions to address trends of beach erosion, in the context of future sea level rise scenarios induced by climate change. This paper addresses the current beach erosion status and future trends under different climate scenarios. We explain how, by using remote sensing, GIS, wave modelling and multiple regressions analysis associated with national, local and community consultations, we were able to identify and quantify the role of ecosystems for mitigating beach erosion. We show that larger widths of coral and seagrass meadows reduce beach erosion.

Using Organigraphs to Map Disaster Risk Management Governance in the Field of Cultural Heritage

Global cultural heritage is threatened by the increasing frequency and severity of natural disasters caused by climate change. International experts emphasise the importance of managing cultural heritage sustainably as part of a paradigm shift in cultural heritage perception, understanding, and management. This paradigm shift has stimulated a need to integrate cultural heritage into pre-existing disaster risk management governance. However, there is currently a lack of robust and practical approaches to map the complex nature of disaster risk management governance. It is here considered that a shared understanding of the respective roles and responsibilities of the different organisations involved in risk management is a critical element in improving the preparedness of cultural heritage sites. The purpose of this article is to present the utility of the Organigraph technique and its main components as a tool to map governance structures, identify key stakeholders, and integrate cultural heritage experts into wider disaster risk management. The article presents a semi-empirical research approach, consisting of four iterative phases in which a series of digital workshops, semi-structured meetings, and bilateral expert meetings were used to co-produce five Organigraphs for heritage sites participating in an ongoing European Project. Our findings suggest that Organigraphs provide a valuable tool at the disposal of practitioners and academics with the potential to provide a basis for cross-national, cross-issue, and cross-scale peer learning between heritage sites. Furthermore, the technique is a valuable self-diagnostic tool to facilitate learning and proactive discussions in the preparedness phase of disaster risk management. Finally, they facilitate the co-creation of solutions through an evolving, interactive platform to integrate data-driven approaches.

Disaster risk management during COVID-19 pandemic

Disaster causing threats and damages to human lives and properties leading toward economic losses can be classified as natural, biological, technological, and societal disasters. Disaster risk management primarily include (i) limiting exposure to hazardous preagents and reducing vulnerabilities and, therefore, chances for disaster to occur; (ii) formulating strategies and preparedness in terms of gathering resources and making a blueprint of actions; (iii) real-time response during a disaster, and (iv) recovery and rehabilitation of affected people. The current pandemic in the form of COVID-19 has given rise to integrating health into the overall disaster risk management strategies. The current chapter aims to develop a framework for integrating health or biological disaster management into the overall disaster risk management protocols and principles. It also suggests a shift from the traditional approach of reactive response after the outbreak/occurrence of the health disaster to a more proactive approach of health risk mitigation by building capabilities across the nation through the development of healthcare services and infrastructure to combat health disasters. Health emergencies or disasters occur due to outbreaks of diseases and indirectly due to other natural calamities or disasters, causing disruption and collapse of healthcare facilities and limiting the access of the majority of people to healthcare services. Sustainable Development Goal-13 mentions the need of urgent actions to be taken and sets targets to combat the impact of climate change causing natural disasters. It is also discussed how to minimize risk and losses during COVID-19 and the required preventive measures to be taken during pandemic in the light disaster risk reduction (DRR) framework. Therefore the guidelines developed in this chapter aim at building a resilient healthcare infrastructure alongside assuring the supply of basic needs viz. water, medicine, food, electricity, and communication during emergencies. It also estimates cost relative to the country’s budget or Gross Domestic Product (GDP) required to build an appropriate healthcare infrastructure for disaster management and performs an economic analysis of cost and benefit.

Terra incognita: the contribution of disaster risk reduction in unpacking the sustainability-peace nexus

The pursuit of sustainable development in the context of global environmental change requires enhanced capability to deal with changing hazard profiles, across scales and geographies. Humans attempt to manage human and natural systems interactions in ways that minimize disaster risks, and the political expression of this ambition is the Sendai Framework for Disaster Risk Reduction 2015-2030 ('Sendai Framework'). These efforts lay the foundation for sustainable development, as since the onset of the Sendai Framework, the policy objective of disaster risk reduction has been explicitly linked to global progress on the Sustainable Development Goals. Separately, peace is a focal point of SDG 16, and widely regarded as foundational to attainment of all SDGs. Meanwhile in academic and policy arenas throughout the 2000s, evidence attests of the amplifying negative impact of climate-related disaster events on increasing violent conflict. What remains underexplored are questions of whether and how effective management of human and natural systems interaction, through disaster risk reduction, can contribute towards conditions of peace through peacebuilding. This paper explores how delivery of the Sendai Framework is necessary for sustainability, and potentially also for peace. In the context of the sustainability-peace nexus, the contribution of disaster risk reduction is terra incognita. This paper aims to deepen understanding of those under-researched tripartite links.

Heatwave Damage Prediction Using Random Forest Model in Korea

Climate change increases the frequency and intensity of heatwaves, causing significant human and material losses every year. Big data, whose volumes are rapidly increasing, are expected to be used for preemptive responses. However, human cognitive abilities are limited, which can lead to ineffective decision making during disaster responses when artificial intelligence-based analysis models are not employed. Existing prediction models have limitations with regard to their validation, and most models focus only on heat-associated deaths. In this study, a random forest model was developed for the weekly prediction of heat-related damages on the basis of four years (2015–2018) of statistical, meteorological, and floating population data from South Korea. The model was evaluated through comparisons with other traditional regression models in terms of mean absolute error, root mean squared error, root mean squared logarithmic error, and coefficient of determination (R2). In a comparative analysis with observed values, the proposed model showed an R2 value of 0.804. The results show that the proposed model outperforms existing models. They also show that the floating population variable collected from mobile global positioning systems contributes more to predictions than the aggregate population variable.

A New End-to-End Multi-Dimensional CNN Framework for Land Cover/Land Use Change Detection in Multi-Source Remote Sensing Datasets

The diversity of change detection (CD) methods and the limitations in generalizing these techniques using different types of remote sensing datasets over various study areas have been a challenge for CD applications. Additionally, most CD methods have been implemented in two intensive and time-consuming steps: (a) predicting change areas, and (b) decision on predicted areas. In this study, a novel CD framework based on the convolutional neural network (CNN) is proposed to not only address the aforementioned problems but also to considerably improve the level of accuracy. The proposed CNN-based CD network contains three parallel channels: the first and second channels, respectively, extract deep features on the original first- and second-time imagery and the third channel focuses on the extraction of change deep features based on differencing and staking deep features. Additionally, each channel includes three types of convolution kernels: 1D-, 2D-, and 3D-dilated-convolution. The effectiveness and reliability of the proposed CD method are evaluated using three different types of remote sensing benchmark datasets (i.e., multispectral, hyperspectral, and Polarimetric Synthetic Aperture RADAR (PolSAR)). The results of the CD maps are also evaluated both visually and statistically by calculating nine different accuracy indices. Moreover, the results of the CD using the proposed method are compared to those of several state-of-the-art CD algorithms. All the results prove that the proposed method outperforms the other remote sensing CD techniques. For instance, considering different scenarios, the Overall Accuracies (OAs) and Kappa Coefficients (KCs) of the proposed CD method are better than 95.89% and 0.805, respectively, and the Miss Detection (MD) and the False Alarm (FA) rates are lower than 12% and 3%, respectively.

Countrywide climate features during recorded climate-related disasters

Climate-related disasters cause substantial disruptions to human societies. With climate change, many extreme weather and climate events are expected to become more severe and more frequent. The International Disaster Database (EM-DAT) records climate-related disasters associated with observed impacts such as affected people and economic damage on a country basis. Although disasters are classified into different meteorological categories, they are usually not linked to observed climate anomalies. Here, we investigate countrywide climate features associated with disasters that have occurred between 1950 and 2015 and have been classified as droughts, floods, heat waves, and cold waves using superposed epoch analysis. We find that disasters classified as heat waves are associated with significant countrywide increases in annual mean temperature of on average 0.13 ^∘C and a significant decrease in annual precipitation of 3.2%. Drought disasters show positive temperature anomalies of 0.08 ^∘C and a 4.8 % precipitation decrease. Disasters classified as droughts and heat waves are thus associated with significant annual countrywide anomalies in both temperature and precipitation. During years of flood disasters, precipitation is increased by 2.8 %. Cold wave disasters show no significant signal for either temperature or precipitation. We further find that climate anomalies tend to be larger in smaller countries, an expected behavior when computing countrywide averages. In addition, our results suggest that extreme weather disasters in developed countries are typically associated with larger climate anomalies compared to developing countries. This effect could be due to different levels of vulnerability, as a climate anomaly needs to be larger in a developed country to cause a societal disruption. Our analysis provides a first link between recorded climate-related disasters and observed climate data, which is an important step towards linking climate and impact communities and ultimately better constraining future disaster risk.