The emphasis of integrated disaster and risk research has shifted from topical analysis, such as dealing with natural hazard-related disasters, technological accidents, or environmental crises, to a comprehensive analysis of interconnected and mutually interactive risk sources and crises. This interaction has often been framed in the language of “polycrisis” indicating the potentially amplifying and cascading effects of each crisis from one domain to the next. At the same time, the literature on systemic risk also includes the effects of multiple, interacting risks on the functionality and survivability of entire systems such as climate stability, cybersecurity, or energy production. This review article provides first a summary of the literature on both concepts, explicates the commonalities and differences and develops a risk and crisis concept that builds a bridge between the two research traditions. Based on this concept, the review delineates the implementations of a joint understanding of polycrisis and systemic risk for risk assessment, risk and crisis governance, and effective communication to different audiences.

The concept of systemic resilience, as it is understood in the context of climate change adaptation addressing systemic risks and polycrisis, is an inherently normative notion that carries ethical weight. To account for these implications, systemic resilience needs to be supplemented with ethical reflections on a system’s function, why it should be made resilient, and who the resilience serves. Crucially, considerations surrounding various forms of justice, such as participatory, procedural, distributive, and historical, need to be accounted for when making decisions about a community’s resilience in the face of increasing climate hazards. Resilience in the context of systemic risks and climate adaptation currently does not account for its ethical implications. This investigation builds on complexity science research and specifically the expanded concept of systemic resilience. In this article, the concept of systemic resilience is applied to the local level, highlighting its ethical underpinnings in the process. Specifically, a case-study explores the application of the ethically informed version of systemic climate resilience, exploring how the Rhine-Erft catchment in Germany could be assessed on this basis.

This article describes a conceptual approach for effective, inclusive, and integrative governance to cope with polycrisis and systemic risks. These challenges arise from the high complexity of causal relationships, particularly when multiple risks are interconnected, leading to cascading and cross-boundary impacts. Uncertainty in these relationships further complicates mitigation efforts. Our approach focuses on critical elements of systemic risk governance, particularly the “risk governance triangle,” which connects persistent disruptive stressors, risk-absorbing systems, and contextual modifiers. These stressors can be physical (energy, substance, biota) or social (information, power) and interact with exposed targets influenced by their context. We decompose these circumstances into five layers, forming the Pagoda model: natural conditions, institutional arrangements, technical and social infrastructure, the built environment, and individual/social behavior. A central pillar of our proposal is prioritizing bottom-up policy making, creating common deliberative spaces that actively involve stakeholders and citizens.

With multiple risks interacting and shocks proliferating across geographies and sectors, the concept of polycrisis has come to the fore. Polycrisis describes interwoven and overlapping crises that cannot be understood or resolved in isolation. Analysts have suggested that many of the Polycrisis symptoms have been at least partially triggered by negative externalities, that is, costs arising from economic activity that are not covered by market prices and thus not internalized in national and international decision making, leading to suboptimal decisions on climate action, energy and food security, global financial stability, among others. Externalities have generally been framed as negative. Positive externalities, that is, societal benefits that indirectly arise from activities and transactions have less often been considered. International policy debate on disaster risk reduction (DRR) and climate change adaptation (CCA) over the last years, as stipulated by international compacts in 2015 (the Sendai Framework, the SDGs, and the Paris Agreement), has built on positive externality discussion, albeit not explicitly so. Disaster risk reduction and CCA analysts have emphasized the need for orienting risk management investments towards interventions that generate so-called multiple or triple resilience dividends. This means extending the focus in decision making from avoiding and reducing impacts and risks to also considering development (co-)benefits arising irrespective of disaster event occurrence. In this context, the “Triple Dividend of Resilience” (TDR) concept and framework has suggested that in addition to risk reduction benefits (dividend 1), dividends would also arise from benefits associated with unlocked development (dividend 2) as well as from co-benefits (dividend 3), for example, from investments into disaster-safe and energy efficient housing. Yet, despite the increasing burdens imposed by systemic disaster and climate risks and wide-spread recognition of this concept over a decade as well as solid evidence regarding the benefits of reducing risk, it has remained difficult to motivate sustained investment across scales into disaster and climate risk reduction. We argue that this systemic underinvestment is, at least partially, due to a lack of conceptual clarity of the TDR with regard to the framing around the dividend 2, a lack of awareness and solid evidence on the positive externalities, as well as interrelationships between resilience dividends in space and time. Based on a snowballing review of the limited literature on the TDR as well as an examination of empirical and model-based evidence, we present the state of the art on the TDR framework. We examine the various dividends in terms of epistemological and methodological contributions building on empirical and modeling methods for supporting decision making as well as evidence for decision making across scales from local to global. Overall, we suggest that there indeed can be positive externalities and solid co-benefits from disaster and climate risk reduction. Systemic risk research and practice coupled with resilience dividend reasoning may thus help to better identify those dividends for improved decision making on disaster and climate risk (reduction). We further show how analysts and decision makers may better consider those various resilience dividends beyond the reduction of losses as well as assess dependencies in risk and benefits’ creation across micro and macro scales. As we suggest, enhanced methods and better awareness for potential externalities may enable more comprehensive consideration of DRR and CCA interventions with benefits arising at various scales. This may eventually also lead to enhanced disaster risk and climate risk governance, which is key for tackling relevant risk challenges in a polycrisis context.

This article introduces a new approach for stress-testing the resilience of critical infrastructures exposed or potentially exposed to adverse events, polycrises, or disasters. This approach focuses on extreme threats (x-threats or XTs) and the functionality testing during such events. The methodology relies on resilience indicators, considering both the threat side and the asset side of adverse events. This enables simultaneous consideration of factors such as increased intensity, impact potential, complexity, systemic risks, and interconnectedness or cascading effects. The resilience of critical infrastructures is analyzed across phases of the resilience cycle: analysis of potential risk, preparation, absorption, recovery, and adaptation/transformation. The proposed stress-testing approach builds on the author’s previous work in EU projects and standards organizations (ISO—the International Organization for Standardization, DIN—German Institute for Standardization), incorporating recent developments like the EU regulations (the Critical Entities Resilience CER Directive) and the use of AI in resilience analysis. Specifically, it extends the stress-testing concept proposed in DIN SPEC 91461 and links it to applications for resilience assessment within EU projects and industry.

Virtual water trade plays a pivotal role in alleviating water scarcity in rapidly urbanizing drylands, and accurately assessing the spillover of local water scarcity pressure to other regions through such trade is essential for sustainable development in these areas. However, systematic research on the spillover of water scarcity risks through virtual water trade and its transmission pathways in arid and semi-arid regions remains relatively limited. Taking the Hohhot-Baotou-Ordos-Yulin (HBOY) urban agglomeration as an example, this study integrated the multi-regional input-output model and structural path analysis to assess the spillover of water scarcity risk through virtual water trade and trace key transmission paths. We found that over 90% of HBOY’s water scarcity risk was transferred to regions experiencing severe or extreme water stress. Spatially, Inner Mongolia and Ningxia were the primary recipients, absorbing 37.2% and 14.5% of HBOY’s total spillover of water scarcity risk, respectively. Sectorally, 62.0% of the risk spillover originated from HBOY’s agriculture, light industry, and construction sectors and was passed to the agricultural sector in external regions. The most important risk transmission path was from HBOY’s agriculture to Inner Mongolia’s agriculture, accounting for 18.3% of HBOY’s total risk spillover. Additionally, potential loss due to insufficient external virtual water supply constituted nearly one-third of HBOY’s total economic loss from water scarcity. We recommend that rapidly urbanizing drylands and their trade partners should actively develop a cross-regional collaborative management system to mitigate the adverse effects of risk spillover.

Understanding the impacts of compound hazards on economic systems is essential for integrated disaster risk management. However, quantifying the ripple effects remains challenging, especially as the relative contributions of each hazard are unclear. Compared to the uncertainty of demand-driven impacts, supply-side shocks are more pronounced and quantifiable, providing a practical pathway to separate the effects. This study proposed a supply-side methodological framework for assessing the ripple effects of compound hazards, focusing on the contributions of each hazard to overall economic disruptions. Overall production capacity loss rates (PCLRs) across industries were evaluated using on-site survey data. A time series model, utilizing urban travel intensity big data, was used to estimate the PCLRs attributable to the COVID-19 pandemic. A mixed multi-regional input–output (mixed-MRIO) model was constructed to assess the ripple effects. The framework was applied to the 17 July 2020 flood in Enshi City, Hubei Province, China, during the COVID-19 pandemic. The results indicate that overall ripple effects exceeded direct production capacity losses. The ratio of production capacity losses attributed to the flood versus the pandemic was approximately 6:4, but it increased to 7:3 for ripple effects. Economic core cities exhibited greater economic stability as evidenced by lower loss rates, while more dependent small- and medium-sized cities were more vulnerable. The secondary industry was sensitive to floods, and the tertiary industry to the pandemic. The study highlights the importance of integrating field surveys and travel intensity big data with economic modeling to evaluate ripple effects, offering new insights into compound hazards impact assessment and management strategies.

Urban disaster risks show multi-stage evolution and interconnected coupling features. Under time pressure, case-based reasoning (CBR) has emerged as a critical method for risk management decision making. Case-based reasoning tackles target case problems by leveraging solutions from similar historical cases. However, the current case base is inadequate for storing systemic risk cases, thus impeding CBR efficacy. This article presents a city-level integrated case base with a nested cross structure to facilitate the use of CBR in systemic risk management. It comprises a multi-layer vertical dimension and a multi-scale horizontal dimension. The vertical dimension is optimized to a four-layer (environment-hazard-object-aftermath) risk scenario classification system with taxonomy and fuzzy clustering analysis. The horizontal dimension is improved to a three-scale (network-chain-pair) risk association mode using event chain theory and association analysis. Hazard acts as the pivotal link between the two dimensions. An illustrative example displays the use process of the proposed case base, along with a discussion of its CBR-supported applications. Through the digital transformation, the suggested case base can serve government decision making with CBR, enhancing the city’s capability to reduce systemic risk.

With a rise in global tensions among nuclear-armed states, preventative measures against nuclear war have once again attracted attention. However, recovery measures remain heavily neglected. A nuclear winter and its associated climatic effects would devastate global agriculture. Understanding vulnerabilities in post nuclear war trade networks could inform efforts to mitigate collapse risks and enable recovery. We posit that even in a limited nuclear war, key trading chokepoints and infrastructure could be targeted, severely disrupting global trade and supply chains for food, essential medicine, fossil fuels, and fertilizers, resulting in widespread famine and increasing humanity’s vulnerability to unforeseen aftershocks. The precise mechanisms and vulnerabilities in post nuclear war trade and supply chains remain poorly understood. Large fluctuations in price compounded by infrastructure destruction will impact every part of the post catastrophe aid delivery process. The trajectory of this disruption and recovery will be critical in determining the extent of the resulting famine and loss of life. We reviewed the relevant literature for the nuclear winter hypothesis, relevant famine studies, and existing complex adaptive system research on trade and supply chains. Our modeling indicates that expected deaths would peak in 250–550 detonation scenarios, therefore, the medium exchange scenarios should be a priority for future resilience research. We identify three layers of inquiry that would help future modeling work to address nuclear resilience, and recommend their inclusion by the 2025–26 UN Independent Scientific Panel on the Effects of Nuclear War. Importantly, a better understanding of reduced sunlight scenarios is applicable to several classes of catastrophe beyond nuclear exchanges.

Bangladesh aims to become a high-income country by 2041, requiring investment in critical infrastructure sectors. Disruptions in one sector can affect others, so prioritizing actions for key sectors is essential when resources are limited. Since no country has endless resources, the current strategy is to focus on developing infrastructure in order of importance. This means that the most critical infrastructure is given priority when allocating resources. The aim of this study was to identify the critical infrastructure sectors and their interdependencies in Bangladesh. While the science of critical infrastructure protection and resilience is well-developed in high-income and developed economies, this research sheds light on identifying critical infrastructure in developing nations like Bangladesh. To identify the critical infrastructure sectors, a comprehensive literature survey was conducted, which was verified and validated by country experts. Policymakers, practitioners, and researchers were consulted through key informant interviews (KII). Interpretive structural modeling (ISM) was applied to determine the interdependencies among identified sectors. Furthermore, cross-impact matrix multiplication applied to classification (MICMAC) analysis was applied to categorize the identified sectors based on driving power and dependence of sectors. The study found that 14 sectors—energy, information and communication technology (ICT), media and culture, law enforcement, transportation, among others—need extra protection measures. It also identified infrastructures with driving power and dependencies in the country’s context. Additionally, this article offers recommendations for improving policy and institutional actions to enhance the resilience of critical infrastructure in the country.

A simple framework for thinking about risks to health, safety, and the environment is introduced and strategies for eliciting expert judgments about associated uncertainties are described.