In the last few years, the world has experienced numerous extreme droughts with adverse direct, cascading, and systemic impacts. Despite more frequent and severe events, drought risk assessment is still incipient compared to that of other meteorological and climate hazards. This is mainly due to the complexity of drought, the high level of uncertainties in its analysis, and the lack of community agreement on a common framework to tackle the problem. Here, we outline that to effectively assess and manage drought risks, a systemic perspective is needed. We propose a novel drought risk framework that highlights the systemic nature of drought risks, and show its operationalization using the example of the 2022 drought in Europe. This research emphasizes that solutions to tackle growing drought risks should not only consider the underlying drivers of drought risks for different sectors, systems or regions, but also be based on an understanding of sector/system interdependencies, feedbacks, dynamics, compounding and concurring hazards, as well as possible tipping points and globally and/or regionally networked risks.

Multi-risk assessments are being increasingly proposed as a tool to effectively support policy-makers in reducing impacts from natural hazards. The complexity of multi-risk requires assessment approaches capable of capturing multiple components of risk (e.g., different hazards, exposed elements, and dimensions of vulnerability) in a coherent frame of reference, while at the same time providing an intuitive entry point to allow participation of relevant stakeholders. Contributing to the emerging multi-risk literature, we carried out a multi-risk assessment for the Marrakech-Safi region (Morocco)—an important economic and demographic hub in the country that is prone to multiple natural hazards, most notably floods and droughts. Through multiple consultations with local experts and stakeholders, a multi-risk assessment framework was constructed based on a set of single-risks related to flood and drought hazards. For each risk, spatial analysis was employed to assess the hazard exposure component of multi-risk, while a set of vulnerability indicators and stakeholder-informed weights were used to construct a composite indicator of vulnerability at the municipal level. For each municipality, the set of indicators and weights contributing to the composite indicator was designed to be dependent on the combination of risks the municipality is actually confronted with. The two components were aggregated using a risk matrix approach. Results show a significant proportion of municipalities (28%) reaching very high multi-risk levels, with a large influence of drought-related risks, and a prominent contribution of the vulnerability component on the overall multi-risk results. While the approach has allowed the exploration of the spatial variability of multi-risk in its multiple sub-components and the incorporation of stakeholders' opinions at different levels, more research is needed to explore how best to disentangle the complexity of the final multi-risk product into a tool capable of informing policy-makers in the identification of entry points for effective disaster risk governance.

Identifying, characterising, and assessing the complex nature of risks are vital to realise the expected outcome of the Sendai Framework for Disaster Risk Reduction. Over the past two decades, the conceptualisation of risk has evolved from a hazard-centric perspective to one that integrates dynamic interactions between hazards, exposure, system vulnerabilities, and responses. This calls for a need to develop tools and methodologies that can account for such complexity in risk assessments. However, existing risk assessment approaches are hitting limits to tackle such complexity. To this end, we developed a novel complex-risk assessment methodology named Impact Webs, inspired by a conceptual risk modelling approach named Climate Impact Chains that integrates aspects of various other conceptual models used in risk assessments, such as causal loop diagrams and fuzzy cognitive mapping. Impact Webs are developed in a participatory manner with stakeholders and characterise and map interconnections between risks, their underlying hazards, risk drivers, root causes, and responses to risks, as well as direct and cascading impacts across multiple systems and at various scales. In this methodological paper, we show how we developed the Impact Web methodology, including how we derived which elements to include in the model, demonstrating the logic and visual output and listing the steps we followed for construction. As proof of concept, we present the results of a complex-risk assessment in Guayaquil, Ecuador, which investigated how COVID-19, concurrent hazards, and responses propagated risks and impacts across sectors and systems during the pandemic. Reflecting on the utility of Impact Webs, application in case studies demonstrates the methodology's usefulness for understanding complex cause–effect relationships and informing decision-making across different scales. The participatory process of developing Impact Webs with stakeholders uncovers critical elements in systems at risk, and helps to evaluate co-benefits and trade-offs of decisions by uncovering how the outcomes of disaster risk management practices affect people, organisations, and sectors differently. Offering a system-wide perspective for modelling, Impact Webs stand as a valuable methodological contribution for complex-risk assessment.

Current rapid urbanization trends in developing countries present considerable challenges to local governments, potentially hindering efforts towards sustainable urban development. To effectively anticipate the challenges posed by urbanization, participatory modeling techniques can help to stimulate future-oriented decision-making by exploring alternative development scenarios. With the example of the coastal city of Monastir, we present the results of an integrated urban growth analysis that combines the SLEUTH (slope, land use, exclusion, urban extent, transportation, and hill shade) cellular automata model with qualitative inputs from relevant local stakeholders to simulate urban growth until 2030. While historical time-series of Landsat data fed a business-as-usual prediction, the quantification of narrative storylines derived from participatory scenario workshops enabled the creation of four additional urban growth scenarios. Results show that the growth of the city will occur at different rates under all scenarios. Both the “business-as-usual” (BaU) prediction and the four scenarios revealed that urban expansion is expected to further encroach on agricultural land by 2030. The various scenarios suggest that Monastir will expand between 127–149 hectares. The information provided here goes beyond simply projecting past trends, giving decision-makers the necessary support for both understanding possible future urban expansion pathways and proactively managing the future growth of the city.

Characterising and assessing multi-risk in complex systems is vital to realise the expected outcome of the Sendai Framework for Disaster Risk Reduction. As sectors and systems are increasingly interconnected, the space in which impacts cascade is expanding. This became apparent throughout the COVID-19 pandemic, but can also be seen in the compounding and cross-border effects of climate change and connected extreme events, or from global ripple effects of armed conflicts such as the aggression committed by Russia against Ukraine. Single-hazard and single-risk approaches, while useful in certain contexts, are becoming increasingly insufficient for comprehensively managing risk due to cross-sector and cross-system interactions. There is therefore a need to develop tools that can account for how multiple hazards interact with multiple vulnerabilities of interdependent systems and sectors, which requires a systemic perspective for assessing risks.To this aim, we developed a novel analytical tool to characterise the interconnections between risks, their underlying hazards, risk drivers, root causes and responses to risks and impacts across different systems. The tool draws on the impact chains approach (i.e. conceptual models for climate risk assessment), expanding its linear and sectoral focus towards a system-oriented view. We follow the recommendation of Zebisch et al (2021) and name this tool ‘Impact Webs'. We applied the tool to five case studies in Bangladesh, Ecuador, India, Indonesia and Togo to characterise and assess cascading risks linked to COVID-19, responses to it (e.g. restriction measures) and other hazards that co-occurred during the pandemic (e.g. hydrological, geophysical, climatological). The participatory co-development of the Impact Webs was led by local case study experts and involved desk research, stakeholder workshops and expert/community consultations.These diverse applications at multiple scales showed that Impact Webs are useful to conceptualise and visualise networks of interconnected elements across sectors. Because of the tools suitability to simultaneously analyse the interactions of multiple hazards with multiple pre-existing vulnerabilities, it provided a representation of the multi-risk space in the case studies. This is promising to identify critical elements for further investigation, such as feedback effects, trade-offs and key agents that can influence risks in systems. To this aim, the tool not only accounts for negative impacts, but also how policy responses and societal reactions to policies can lead to additional positive outcomes, as well as unintended consequences, i.e. risks arising from responses. However, given the complexity of systems and system boundaries, it is not possible to characterise all interconnections using Impact Webs. While this simplification of reality is useful for communication purposes, only the most prominent outcomes of the tool are derivable, and although the participatory approach aims to reduce this, results can be influenced by inherent biases. Despite these challenges, we find that Impact Webs are a promising new approach to characterise and assess multi-risk, thereby supporting comprehensive disaster risk management.

In the past decades, and notably the last few years, droughts have severely impacted various interconnected socio-economic sectors and ecosystems across the EU. These impacts encompass, among others, extensive losses in both rain-fed and irrigated agriculture, challenges and constraints in public water supply, disruptions in inland shipping, diminished production of hydropower and thermoelectric energy, impaired functioning of terrestrial and freshwater ecosystems, and implications for the tourism industry. In order to better prepare for future drought events in Europe, knowledge on the drivers, spatial patterns and dynamics of drought risks is urgently needed. The European Drought Risk Atlas responds to that need by mapping hotspots and risk drivers across diverse systems and regions within the EU. Combining conceptual risk models (impact chains) and a data-driven quantitative drought risk assessment based on machine learning, this Atlas represents a significant stride toward impact-driven drought risk analysis in present and projected global warming levels (+1.5°C, +2.0°C, +3.0°C). It provides a detailed and disaggregated perspective on the risks posed by droughts to societies and ecosystems, with a particular focus on agriculture, public water supply, energy, river transportation, freshwater, and terrestrial ecosystems.The data-driven analysis reveals that current levels of drought risk in the EU are already notable, with average annual losses presenting economic and environmental threats in nearly all regions. As expected, the Mediterranean region, particularly the Iberian Peninsula, faces high drought risk under both current and projected climate conditions, driven by the escalating dry conditions associated with global warming. However, while drought risk of certain sectors in Europe follows a north-south gradient of overall mean drying (south) and wetting (north) under climate change, the analysis underscores that each sector reacts distinctly to current and projected hazard conditions, exhibiting sector-specific sensitivity. Eastern and Western Europe may experience complex dynamics due to the interplay between drying and wetting patterns and precipitation variability, resulting in different risk conditions depending on the considered sector. While the analysis may still be refined as new data (observations and future climate simulations) become available, this Atlas represents a unique tool of unparalleled value that can shape future EU preparedness and adaptation policies.