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Recent studies have been reporting more extreme, compounding impacts from multi-hazards than from single hazard events owing to complex interrelationships of hazard, exposure and vulnerability in a multi-hazard setting. However, our current understanding of multi-hazard impacts is primarily based on case studies of individual events. To complement this, we examine the disaster records of the global emergency events database EM-DAT for the period 2000–2018 for evidence of multi-hazard risk dynamics. We develop an algorithm to identify multi-hazard events which uses the information on associated hazards as well as spatiotemporal relationships between disaster records in EM-DAT. We then perform a statistical analysis to assess potential risk dynamics in reported impacts of selected hazard pair types. We identified that twice as many hazards are part of multi-hazard events when considering a spatial overlap of at least 25 % and a time lag of at most 1 year between disaster records in addition to the information of associated hazards. These multi-hazard events account for 78 % of the total damages, 83 % of the total people affected and 69 % of the total deaths in the reported disasters. The statistical comparison indicates that there are different patterns of how impacts compound depending on the impact metric as well as the hazard type. However, as a general trend, hazard pairs seem to have at least as or more impact than two isolated single hazards. To capture the patterns and to integrate them into risk analysis and decision making, we propose the development of generic archetypes of multi-hazard risk dynamics. Despite the well-known limitations of EM-DAT related to completeness of the records as well as reliability of the impact data, which prevents detailed analyses of the data, we found the database useful for exploring high-level patterns at the global scale. Nonetheless, the uncertainties and limitations encountered highlight that future research should be directed at improving and supporting the multi-hazard and impact information in EM-DAT. [ABSTRACT FROM AUTHOR]

This study synthesizes the current understanding of the hydrological, impact, and adaptation processes underlying drought‐to‐flood events (i.e., consecutive drought and flood events), and how they interact. Based on an analysis of literature and a global assessment of historic cases, we show how drought can affect flood risk and assess under which circumstances drought‐to‐flood interactions can lead to increased or decreased risk. We make a distinction between hydrological, socio‐economic and adaptation processes. Hydrological processes include storage and runoff processes, which both seem to mostly play a role when the drought is a multiyear event and when the flood occurs during the drought. However, which process is dominant when and where, and how this is influenced by human intervention needs further research. Processes related to socio‐economic impacts have been studied less than hydrological processes, but in general, changes in vulnerability seem to play an important role in increasing or decreasing drought‐to‐flood impacts. Additionally, there is evidence of increased water quality problems due to drought‐to‐flood events, when compared to drought or flood events by themselves. Adaptation affects both hydrological (e.g., through groundwater extraction) or socio‐economic (e.g., influencing vulnerability) processes. There are many examples of adaptation, but there is limited evidence of when and where certain processes occur and why. Overall, research on drought‐to‐flood events is scarce. To increase our understanding of drought‐to‐flood events we need more comprehensive studies on the underlying hydrological, socio‐economic, and adaptation processes and their interactions, as well as the circumstances that lead to the dominance of certain processes. This article is categorized under:Science of Water > Hydrological ProcessesScience of Water > Water Extremes [ABSTRACT FROM AUTHOR]

Coastal flood risk is a serious global challenge facing current and future generations. Several disaster risk reduction (DRR) measures have been posited as ways to reduce the deleterious impacts of coastal flooding. On a global scale, however, efforts to model the future effects of DRR measures (beyond structural) are limited. In this paper, we use a global-scale flood risk model to estimate the risk of coastal flooding and to assess and compare the efficacy and economic performance of various DRR measures, namely dykes and coastal levees, dry-proofing of urban assets, zoning restrictions in flood-prone areas, and management of foreshore vegetation. To assess the efficacy of each DRR measure, we determine the extent to which it can limit future flood risk as a percentage of regional GDP to the same proportional value as today (a "relative risk constant" objective). To assess their economic performance, we estimate the economic benefits and costs of implementing each measure. If no DRR measures are implemented to mitigate future coastal flood risk, we estimate expected annual damages to exceed USD 1.3 trillion by 2080, directly affecting an estimated 11.5 million people on an annual basis. Low- and high-end scenarios reveal large ranges of impact uncertainty, especially in lower-income regions. On a global scale, we find the efficacy of dykes and coastal levees in achieving the relative risk constant objective to be 98 %, of dry-proofing to be 49 %, of zoning restrictions to be 11 %, and of foreshore vegetation to be 6 %. In terms of direct costs, the overall figure is largest for dry-proofing (USD 151 billion) and dykes and coastal levees (USD 86 billion), much more than those of zoning restrictions (USD 27 million) and foreshore vegetation (USD 366 million). These two more expensive DRR measures also exhibit the largest potential range of direct costs. While zoning restrictions and foreshore vegetation achieve the highest global benefit–cost ratios (BCRs), they also provide the smallest magnitude of overall benefit. We show that there are large regional patterns in both the efficacy and economic performance of modelled DRR measures that display much potential for flood risk reduction, especially in regions of the world that are projected to experience large amounts of population growth. Over 90 % of sub-national regions in the world can achieve their relative risk constant targets if at least one of the investigated DRR measures is employed. While future research could assess the indirect costs and benefits of these four and other DRR measures, as well as their subsequent hybridization, here we demonstrate to global and regional decision makers the case for investing in DRR now to mitigate future coastal flood risk. [ABSTRACT FROM AUTHOR]

Critical infrastructure (CI) is exposed to natural hazards that may lead to the devastation of these infrastructures and burden society with the indirect consequences that stem from this. The vulnerability is a key determinant for understanding, assessing and reducing natural hazard-induced risks to these infrastructures. To date, however, essential vulnerability information for CI is distributed across literature instead of being accessible through a centralized dataset. This study, through a systematic literature review, synthesises the state-of-the-art of fragility and vulnerability curves for CI assets of energy, transport, water, waste, telecoms, health and education in context of natural hazards and offers a unique physical vulnerability database. The publicly available centralized database that contains over 1,250 curves can directly be used as input for risk assessment studies that evaluate the expected or potential damages to assets due to flooding, earthquakes, windstorms and landslides. The literature review highlights that vulnerability development has mainly focused on earthquake curves for a wide range of infrastructure types. Windstorms have the second largest share in the database, but are especially limited to energy curves. While all CI systems require more vulnerability research, additional efforts are needed for telecommunication which is largely underrepresented in our database. [ABSTRACT FROM AUTHOR]

Hydrological extremes, such as droughts and floods, can trigger a complex web of compound and cascading impacts (CCI) due to interdependencies between coupled natural and social systems. However, current decision‐making processes typically only consider one impact and disaster event at a time, ignoring causal chains, feedback loops, and conditional dependencies between impacts. Analyses capturing these complex patterns across space and time are thus needed to inform effective adaptation planning. This perspective paper aims to bridge this critical gap by presenting methods for assessing the dynamics of the multi‐sector CCI of hydrological extremes. We discuss existing challenges, good practices, and potential ways forward. Rather than pursuing a single methodological approach, we advocate for methodological pluralism. We see complementary or even convergent roles for analyses based on quantitative (e.g., data‐mining, systems modeling) and qualitative methods (e.g., mental models, qualitative storylines). The data‐driven and knowledge‐driven methods provided here can serve as a useful starting point for understanding the dynamics of both high‐frequency CCI and low‐likelihood but high‐impact CCI. With this perspective, we hope to foster research on CCI to improve the development of adaptation strategies for reducing the risk of hydrological extremes. Plain Language Summary: Droughts and floods can have significant impacts on both natural and social systems. These impacts are often interconnected, resulting in a complex chain of events. In this perspective paper, we aim to assist researchers in understanding the dynamics of compound and cascading impacts (CCI) caused by hydrological extremes. We provide an overview of various methods that can be utilized to assess and analyze interconnected impacts. To begin, we address the ongoing challenges associated with CCI research, such as the limited availability of comprehensive impact data spanning multiple sectors and over extended periods. Subsequently, we present a range of qualitative and quantitative methods that can be employed to analyze CCI dynamics, supported by case study examples. Finally, we conclude with six recommendations to advance the research in this field. Key Points: Systematic efforts to collect data on impacts across multiple sectors, systems, and years are requiredMethodological pluralism is necessary to fully address the complexity of compound and cascading impacts (CCI) and their underlying risk driversInvestigation of the risks of multi‐sector impacts should be guided not only by probability but also by plausibility considerations [ABSTRACT FROM AUTHOR]