Strengthening the systemic resilience of communities, cities, regions, and countries —i.e. their ability to resist, recover, adapt, and transform under rising uncertainty— is gaining urgency. Yet empirical evidence remains fragmented, definitions and metrics are inconsistent, and robust methods for understanding resilience dynamics are still emerging. Advancing disaster- and climate-resilient development therefore requires innovative frameworks, assessment methodologies, and actionable strategies that explicitly address multi-hazard and cascading risk contexts.
This session invites inter- and transdisciplinary contributions on systemic resilience to multi-hazards, including studies on single hazards that reveal broader mechanisms, drivers, or strategies. Topics include but are not limited to:
• Conceptual and analytical frameworks for assessing and modelling resilience (e.g. indicators, process- vs. outcome-based metrics, agent-based modelling, remote sensing).
• Mechanisms of resilience to compound and cascading hazards, linking infrastructures, ecosystems, and institutions.
• Strategies and interventions for building systemic resilience, including digital tools, AI, adaptive planning, nature-based solutions, early warning systems, built infrastructure, and the roles of social capital and adaptive capacity in enabling transformation.
• Justice and equity perspectives: integrating local knowledge, historical lessons, cultural legacies, and ethical considerations into climate-resilient development.
• Drivers, constraints, and enabling conditions across social, economic, ecological, technological, political, and psychological domains.
• Comparative or longitudinal studies identifying resilience mechanisms and context-specific interventions across scales.
• Stakeholder engagement through citizen science, participatory approaches, and co-production bridging research and practice.
Disaster recovery is increasingly challenged by cascading and compounded hazards that unfold while urban systems are still partially restored. Yet, most resilience assessments focus on single hazards or static system performance, overlooking the intermediate recovery phase and its evolving dynamics over time. The intermediate recovery phase refers to the period when residents begin to resume activities such as commuting, accessing healthcare, and education, while infrastructure systems remain only partially functional and still vulnerable to further disruptions. This paper examines the impact of multi-hazard interactions on systemic resilience during the intermediate recovery window, using transportation accessibility as a proxy for understanding broader urban functioning.
We develop a network-based modelling approach to evaluate the impact of flooding and flood exposure on a transportation network undergoing recovery from earthquake-induced damage. The approach combines graph-theoretical network analysis with spatial flood modelling to evaluate how cascading disruptions impact connectivity and undermine access to critical services. Three complementary performance metrics are employed: (i) network centrality to identify structurally critical corridors, (ii) accessibility to essential amenities such as shelters, hospitals, and markets, and (iii) disruption-adjusted mobility flows that capture functional losses under inundation. The framework is applied to Antakya, Türkiye, following the February 2023 earthquake and subsequent flooding.
Model results indicate that flooding exacerbates accessibility losses in Antakya’s earthquake-damaged transportation network, where recovery depends on a limited number of structurally critical corridors. Accessibility impacts are unevenly distributed, with temporary shelters and essential services, some of which are located in flood-exposed areas, becoming intermittently inaccessible when key routes are impassable. Our findings reveal that even seemingly localized flood events along these corridors can trigger systemic network effects, rerouting flows onto longer secondary paths, increasing travel distances, and isolating already vulnerable communities during the recovery process.
Beyond physical damage, observations from the field trip suggest that residents and displaced communities have adapted to this uncertainty by informally sharing real-time routing information through social media and messaging platforms. This emergent bottom-up coordination reflects community adaptive capacity in navigating infrastructure constraints during the intermediate recovery phase, where road accessibility changes frequently due to ongoing reconstruction and intermittent disruptions.
Overall, the results suggest that recovery trajectories can become more fragile during the intermediate recovery phase, when infrastructure systems are partially restored but remain structurally and operationally weakened by prior damage. In this state, systems have a reduced capacity to absorb any additional hazards, meaning that flooding can generate impacts that exceed those expected under normal system operations. The findings contribute empirical evidence to debates on systemic resilience and highlight the importance of moving beyond single-hazard recovery strategies toward multi-hazard, network-aware assessments.
How to cite: Aydin, N. Y., Balakrishnan, S., and van der Jagt, M.: Systemic Resilience under Compound Hazards: Insights into Multi-Hazard Earthquake–Flood Recovery Dynamics in Antakya, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10941, https://doi.org/10.5194/egusphere-egu26-10941, 2026.
Compound, consecutive, and cascading hazards increasingly challenge the systemic resilience of critical infrastructure. Among these, the power grid—vital to nearly every facet of society—is uniquely exposed to interdependent stressors from space weather, terrestrial weather, and wildfire. Traditional single-hazard frameworks are insufficient to capture the dynamic, non-linear interactions across these domains thereby being incapable of understanding systemic dynamics and shaping resilience.
Drawing on enriched historical event records, statistical network analysis, and sustained engagement with grid operators, we present a new framework for assessing how multi-hazard interactions influence grid resilience. We share event-based storylines—physically self-consistent reconstructions of past events and plausible future pathways—and emergent patterns that reveal both known and previously unrecognized mechanisms of compounding and cascading failure, recovery, and adaptive response. Through investigation of a previously unexamined multi-hazard system (space weather, terrestrial weather, and wildfire) we uncover novel complex behaviors that reframe how resilience and system flourishing can be understood and designed for.
Our findings advance methodologies for multi-hazard resilience assessment by integrating physical hazard processes with socio-technical dynamics, including network structure, operator decision-making, and institutional constraints under deep uncertainty.
We further outline an emerging global initiative aimed at collective, transdisciplinary action to collect efforts and groups advancing resilience analyses for these ‘wicked problems’ and to collectively explore translating them into adaptive strategies and governance frameworks. By translating multi-hazard insights into actionable knowledge, we offer both methodological tools and institutional pathways for advancing resilience analysis under conditions of deep uncertainty and systemic interdependence.
How to cite: McGranaghan, R., Lenhart, S., LaHaye, N., Blumsack, S., Marchetti, Y., Cathcart, A., Spanbauer, C., and Taylor, E.: From Entanglement to Action: Systemic Resilience to Multi-Hazards in the U.S. Power Grid, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-22025, https://doi.org/10.5194/egusphere-egu26-22025, 2026.
Urbanization and climate change are reshaping the global landscape of urban flood exposure. However, existing assessments struggle to accurately evaluate the spatiotemporal dynamics, drivers, and urban adaptive capacity of future global flood exposure, largely due to overlooking the dynamic expansion of urban populations in tandem with physical boundaries, the lack of systematic quantification of uncertainties in climate-urban interactions under multiple scenarios, and the absence of comprehensive multidimensional resilience evaluations at the urban scale. Here, we developed an integrated framework coupling multi-scenario simulation of urban expansion and population distribution, multi-GCM driven flood hazard assessment, and multidimensional resilience evaluation to quantify the dynamics and uncertainties of global urban flood exposure, as well as its correlation with multidimensional resilience. We show that by 2050, the global urban population exposed to 1-in-100-year floods will rise from 588 million to 850 million. Urban expansion and population growth are the dominant drivers, contributing 71.4% of new exposure, significantly outweighing the impact of climate-driven floodplain expansion. Notably, the proportion of exposed population in future urban expansion zones is projected to be universally higher than in existing urban areas, a trend particularly acute in developing nations such as Vietnam. Further hierarchical regression analysis reveals a significant negative correlation between ecological resilience and exposure changes, validating the effectiveness of Nature-based Solutions in mitigating flood exposure. Identifying resilience deficits in 150 cities with significantly surging exposure, we advocate for a shift from reliance on singular engineering defenses to a multidimensional adaptation paradigm-incorporating strict urban growth boundary controls and ecological resilience enhancement-tailored to specific drivers to ensure global urban sustainability.
How to cite: Gong, B. and Liu, Z.: Global Assessment of Urban Flood Exposure and Multidimensional Resilience, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4255, https://doi.org/10.5194/egusphere-egu26-4255, 2026.
With the intensification of global climate change and the frequent occurrence of extreme weather events, cities, as concentrated areas of population and economic activity, are increasingly vulnerable to climate impacts. Traditional response models struggle to address sudden and compound climate risks in a timely manner. In this context, digital-intelligent technologies, represented by big data, artificial intelligence, the Internet of Things, and digital twins, are becoming key enabling tools for systematically enhancing urban climate resilience. Their core value lies in reshaping the paradigm of urban climate risk management through data-driven precise perception, intelligent analysis, and forward-looking decision-making, shifting the approach from passive response to proactive adaptation.
Digital-intelligent empowerment enhances urban climate resilience primarily across several dimensions: comprehensive and precise perception with dynamic monitoring, intelligent analysis and risk early warning, and coordinated response with smart regulation. Taking Shanghai as an example, the intelligent dispatch system for drainage facilities and its applications were introduced. This exploration demonstrates that digital-intelligent empowerment not only improves the efficiency of risk response but also promotes climate-adaptive transformation throughout the entire process of urban planning, construction, and management.
Nevertheless, digital-intelligent empowerment faces challenges such as data barriers, technological costs, the digital divide, and uncertainties inherent in the models themselves. In the future, it is essential to strengthen cross-departmental data sharing and standard interoperability, focus on the applicability and cost-effectiveness of technologies, ensure technological inclusiveness, and adhere to a systemic resilience-building path that integrates "digital-intelligent tools" with institutional design, ecological infrastructure, and social participation.
How to cite: Guo, R., Li, A., and Xu, B.: Digital-Intelligent Empowerment for Enhancing Urban Climate Resilience, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4313, https://doi.org/10.5194/egusphere-egu26-4313, 2026.
High-Impact Low-Probability (HILP) events pose a growing challenge for contemporary risk assessment and management. These events are characterized by severe consequences, systemic disruptions and limited historical precedent, which constrains the applicability of conventional probabilistic risk assessment methods. As a result, HILP events are often underestimated or excluded from standard decision-making processes. At the same time, their frequency is increasing due to rising interconnections among social, ecological, and infrastructural systems. which amplify the potential for cascading and non-linear effects, allowing disruptions originating in one sector or location to propagate rapidly across multiple domains.
In response to these challenges, the AGILE project develops a comprehensive methodology to understand, assess, manage and communicate HILP events through a systemic, risk-agnostic and resilience-oriented framework. Rather than focusing on individual hazards or isolated assets, AGILE conceptualizes risk as an emergent property of interacting systems and emphasizes the capacity of territories to absorb shocks, maintain critical functions and adapt to future conditions. The methodology is structured into three tiers of increasing analytical depth, enabling progressive refinement as data availability, modelling capacity and stakeholder engagement evolve.
The framework is applied to the Metropolitan City of Venice, a highly relevant testbed due to its exposure to multi-hazard risks and relevant interdependencies among environmental systems, cultural heritage, tourism, infrastructure, and governance.
The first Tier consisted in a workshop-based approach involving experts from different sectors of society. Participants engaged in a serious game designed to qualitatively identify shared vulnerabilities and critical points. During the game, a catastrophic scenario was created based on hazards randomly drawn from a specially designed card deck. Participants analyzed the scenario, attempting to anticipate potential cascading dynamics and identify common points of failure. These exercises encourage lateral and systems-oriented thinking, with a strong focus on cascading effects across interconnected functions and sectors.
Building on the outcomes of the first Tier, the second Tier focused on physical and decision-making interdependencies among critical infrastructures and on cascading effects. Through a dedicated workshop, stakeholders translated qualitative insights into interdependency matrices that capture the strength and direction of interactions among infrastructures. These matrices were then used to construct a simplified network of structural and functional dependencies, enabling the identification of systemic vulnerabilities, bottlenecks, and critical nodes, and supporting the analysis of potential cascading failures within the urban system.
The third Tier develops a spatial, dynamic, quantitative model of selected critical functions within the municipality, showing how the risk can propagate through the system and evaluates possible resilience improvements by adopting methods such as Network Sciences, Agent Based Modelling and Machine Learning.
The system is represented as a network of networks, in which critical functions, such as mobility, energy, and water management, are modelled as interconnected units. This representation enables the analysis of both localized disruptions and their propagation across the wider urban and regional system.
Overall, the case study demonstrates how the AGILE framework supports a systemic understanding of cascading effects and resilience pathways under HILP conditions, providing a robust foundation for resilience-oriented planning and decision-making.
How to cite: Torresan, S., Ferrario, D. M., Casagrande, S., Maraschini, M., D'Antiga, F. M., Ghaffarian, S., Mulder, F., Pescaroli, G., Trump, B. D., Linkov, I., and Palma-Oliveira, J.: Understanding resilience to High-Impact Low-Probability events: a tiered stress testing methodology implemented in the municipality of Venice , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12897, https://doi.org/10.5194/egusphere-egu26-12897, 2026.
Approaches for climate change adaptation (CCA) planning have traditionally been built around risk-avoidance and loss-reduction models, with co-benefits treated as secondary considerations. This narrow focus overlooks the wider societal, economic, and environmental benefits — as well as potential trade-offs— that CCA may have, which contributes to persistent underinvestment in adaptation and misses opportunities to advance sustainable development. This gap underscores the need for more integrated approaches that comprehensively understand the CCA's multifaceted impacts. Different decision-making frameworks have been proposed, but the application and understanding of resilience-based approaches remain limited, particularly concerning their actionability and evidence base. To this effect, this paper introduces a comprehensive framework for embedding the Multiple Resilience Dividends (MRD) lens into the full CCA planning cycle to better capture the broad value of adaptation actions. Building on and extending the “triple resilience dividend” concept, the MRD approach recognises that adaptation interventions generate a diverse set of direct and indirect effects—beneficial and adverse—across interconnected systems, sectors, scales, and timeframes. By placing MRD thinking at the core of key planning stages—including problem framing, risk assessment, option identification, appraisal, decision-making, implementation, and monitoring and evaluation—we explain how CCA can shift from siloed, risk-centric practices toward integrated, multi-objective, and transformational strategies. The proposed framework highlights how MRD supports systems thinking, strengthens stakeholder-centred design, enhances legitimacy, reveals synergies and trade-offs, and improves the robustness and viability of adaptation pathways. Through an illustrative example in a coastal urban context, we show how MRD-informed planning can unlock more equitable, cost-effective, and sustainable adaptation portfolios. Overall, we argue that operationalising MRD offers a critical pathway for accelerating climate resilience by reframing adaptation as a generator of multiple dividends rather than a cost focused solely on risk reduction.
How to cite: Higuera Roa, O., Sakic Trogrlic, R., Bachmann, M., Hochrainer-Stigler, S., and Mechler, R.: Leveraging Multiple Resilience Dividend Concept for Transformative Adaptation Planning, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21569, https://doi.org/10.5194/egusphere-egu26-21569, 2026.
Spatial planning can play a key role in strengthening the long-term resilience of urban systems. As an inherently integrative task, it cannot focus only on single hazards, but must also consider how spatial structures and development patterns influence exposure and vulnerability to multiple hazards, as well as how planned changes to land-use may exacerbate or reduce risks. In order to do this, spatial planners require accessible risk information and user-oriented tools that can be incorporated into existing planning processes.
This contribution presents a case study of the Stuttgart region in Germany, drawing on lessons learned from ongoing interdisciplinary research co-producing climate risk analyses with planning practice. The research focuses on integrating urban heat and pluvial flooding hazard maps with exposure and vulnerability indicators related to urban form, critical and sensitive infrastructure, and social structures. The study addresses how climate risk and resilience research, spatial data and analyses, and planning processes and institutions can be integrated more effectively to support climate-resilient development across scales.
We use examples from the case study to illustrate how research and planning can be linked to enable more risk- and justice-oriented planning in relation to the following four aspects: 1) infrastructure systems and their interdependencies, including cascading risks; 2) socio-spatial inequalities, differential vulnerability, and risks to social infrastructure; 3) interactions between policy and planning at different levels (local, regional and state); and 4) user-oriented, digital, map-based tools to facilitate collaboration between planning and other sectors and stakeholders.
Building on the insights from the case study, we identify ways in which spatial planning can be supported to strengthen climate resilient development through improved risk data, digital tools and analytical methods in strategic spatial planning. The conclusion outlines the remaining challenges, knowledge gaps and priority tasks for research and practice in enabling spatial planning to address multi-hazard risks.
How to cite: McMillan, J., Hampel, F., Birkmann, J., and Handmer, J.: Advancing spatial planning for resilient urban-regional systems: Insights from the Stuttgart region, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19019, https://doi.org/10.5194/egusphere-egu26-19019, 2026.
Resilience is a generally desirable attribute for people and systems, but conventional approaches to strengthen resilience increasingly struggle with both identifying and promoting resilience for the extraordinary uncertainty and variety of shocks and stresses communities face today. A significant limitation of most approaches is their narrow event focus, as increasingly events and stresses run into each other, trigger cascading problems or occur simultaneously – leaving little “downtime” for recovery and building resilience. Many risks are now seen as systemic and the social and political context is increasingly referred to as the “polycrisis” or “permacrisis”. For many people and communities these identified risks and crises come on top of increasing livelihood, housing and health insecurity. While there is general consensus that mechanisms, methods and strategies for resilience should support those who are most in need, many standard resilience assessments fall short of this aim. Intersectionality gives a more explicit focus on justice and equity, and should help to ensure that the development of systemic resilience does not bypass the most vulnerable.
Interestingly, we observe increasing systemic risks and polycrises in both the global South and the global North, for example when people recovering from severe floods are also impacted by livelihood disruption (eg from the collapse of tourism or loss of crops), extreme heat , aftershocks of the COVID pandemic, and the social and economic fallout from geo-politics.
Methods and approaches are urgently needed that can manage resilience for these continuous and complex states of crisis as conventional resilience is not enough. Systemic resilience is one such approach. It focuses on connections and “system” dynamics, where having connections across networks, systems, sectors and geographies, increases the robustness of the resulting resilience. We first develop criteria for community systemic resilience and identify barriers and facilitating factors. We outline different dimensions of the polycrises and different dimensions of losses and damages that occur within cascades of shocks and crises. We argue that there is a need to avoid administrative and political traps which can constrain the development of flexibility in resilience. Warnings, information sharing, and supporting the development of processes that increase flexibility and adaptability are key. They should avoid path dependence and siloed approaches as they and resistance to learning are major issues. However, it might not necessarily be about transformation as often suggested. There are also questions about the types of data appropriate in circumstances that evolve rapidly in surprising ways.
How to cite: Handmer, J., Preinfalk, E., Birkmann, J., and McMillan, J.: Uncertainty, systemic resilience and intersectionality – developing a research agenda, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18200, https://doi.org/10.5194/egusphere-egu26-18200, 2026.
When disasters strike in sequence, systems behave fundamentally differently than single-event resilience theory predicts. Single-event frameworks assume each shock can be analyzed independently, but sequential impacts alter system dynamics in ways that isolated analysis cannot capture. For example, as compound hazards intensify under climate change, this mismatch between theory and reality leaves critical systems vulnerable to cascading effects invisible to traditional risk assessment.
With this in mind, we developed a theoretical framework based on damped oscillator dynamics to track how sequential shocks reshape system behavior. Our approach introduces two governing parameters: the disaster budget, representing cumulative impact allocated across all events, and the disaster horizon, defining the temporal window within which multiple disasters unfold. Together, these parameters enable systematic analysis of resilience under stochastic variations in disaster timing and magnitude across the parameter space that defines system characteristics.
Monte Carlo simulations across 6 million system realizations reveal a fundamental transition in system behavior. Early in disaster sequences, systems maintain functional tolerance independent of disaster frequency. But as sequences lengthen, tolerance degrades nonlinearly until systems cross into functional intolerance, allowing us to characterize how sequential disasters erode resilience.
The transition point depends critically on interacting factors. Compressed time horizons accelerate the shift to functional intolerance, while extended horizons delay critical failures by several additional events. Recovery standards interact in unexpected ways: identical disaster sequences produce dramatically different failure patterns depending solely on performance expectations. Neither factor alone predicts system fate; their interaction determines outcomes, demanding integrated assessment approaches.
Lastly, we employ synergy indices to quantify whether sequential effects are compounding, additive, or antagonistic. Analysis reveals that position coupling dominates system behavior, suggesting that resilience investments should prioritize reducing cumulative displacement through rapid recovery or direct mitigation of subsequent impacts.
Sequential disasters produce emergent behaviors that single-event analysis cannot predict. The disaster budget and disaster horizon concepts provide theoretical machinery for anticipating when systems will transition from tolerance to intolerance, enabling multi-event resilience analysis where single-event frameworks fail. This framework transforms the central question of resilience from "can systems recover from a disaster?" to "how many disasters can systems tolerate before crossing irreversible thresholds?" which constitutes a critical reframing as compound and cascading hazards become the norm under environmental change.
How to cite: Weiss, R. and Zobel, C.: The Tolerance Threshold: How Sequential Disasters Transform System Resilience, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7172, https://doi.org/10.5194/egusphere-egu26-7172, 2026.
Background and Objectives. Systemic resilience to multi-hazards requires addressing interdependencies between ecological and climatic risks, yet current frameworks often treat environmental and societal dynamics in isolation. This study synthesizes evidence from a decade of global risk assessments (WEF Global Risks Reports, 2016–2025) and IPBES-IPCC scientific evaluations to propose an integrated "risk-nexus" governance framework. We aim to: (1) delineate cascading pathways between climate-biodiversity risks and socioeconomic systems; (2) identify tipping points in critical ecosystems (e.g., coral reefs, tropical forests, peatlands) that amplify multi-hazard impacts; and (3) evaluate strategies for enhancing systemic resilience through synergistic interventions.
Methods. We analyzed time-series data from WEF reports on risk severity, interconnectedness, and cascading patterns, complemented by IPBES-IPCC case studies on threshold-driven ecosystems. Network analysis was used to map risk propagation pathways, while a scenario-based approach assessed the efficacy of Nature-based Solutions (NbS), adaptive governance, and early-warning systems in mitigating compound hazards.
Key Findings. (i) Risk Coupling: Extreme weather, biodiversity loss, and ecosystem collapse exhibit strong clustering in global risk networks, acting as core nodes that amplify food, water, and health crises; (ii)Threshold Effects: Ecosystems like coral reefs (at 1.5°C warming) and Amazon forests (at 20–25% deforestation) face nonlinear collapse, triggering cascading socioecological disruptions. (iii) Synergistic Strategies: NbS—such as coastal mangrove restoration and forest landscape resilience—simultaneously mitigate hazards, sequester carbon, and sustain livelihoods when embedded in adaptive governance. Early-warning systems tied to ecological thresholds (e.g., soil moisture, heat stress indices) reduce latency in response.
Conclusions and Relevance. Systemic resilience hinges on bridging siloed risk management via a "risk identification–threshold warning–response decision" framework. This approach aligns climate adaptation, biodiversity conservation, and disaster risk reduction, offering actionable pathways for multi-hazard resilience. Our findings underscore the need to integrate ecological thresholds into policy triggers and prioritize nexus governance to navigate polycrisis contexts.
Keywords: Systemic Resilience, Multi-Hazards, Climate-Biodiversity Nexus, Thresholds, Nature-based Solutions, Cascading Risks.
How to cite: Yu, D.: A Risk-Nexus Approach to Systemic Resilience: Integrating Biodiversity-Climate Interactions into Multi-Hazard Governance, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9789, https://doi.org/10.5194/egusphere-egu26-9789, 2026.
Linking climate extremes to observed losses and damages is critical for understanding risk and guiding loss and damage responses. I present a conceptual framework, grounded in social and sustainability sciences, that integrates climate extremes, attribution, observed impacts, and responses into a common analytical framework. A visual schematic illustrates causal pathways through exposure, vulnerability and risk to realised losses and damages. The conceptual framework highlights both formal, institutional responses and informal everyday, and resistance responses. Feedback loops connect outcomes to core system elements, supporting pathways toward sustainable societies. This framework accommodates compound events, slow-onset change, multi-scale dynamics, and both economic and non-economic losses, offering a flexible analytical framework for systematic analysis, co-produced decision support, and bridging gaps between physical climate science and social science research.
How to cite: Boyd, E.: Linking climate extremes, attribution, and loss and damage responses: A conceptual framework, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20766, https://doi.org/10.5194/egusphere-egu26-20766, 2026.
Waterway transport is a cornerstone of green, low-carbon logistics, yet it is increasingly vulnerable to multi-hazards — ranging from extreme weather and flooding to infrastructure failures and traffic congestion. To address these threats, the project "Internet of Ships" (船联网) was initiated 10 years ago across the Yangtze River Delta and the Grand Canal. This project aims to transform traditional shipping into a highly resilient, intelligent system that connects ships, the shore, and land-based management centers to one another. To ensure this system could withstand real-world systemic shocks, the project team analyzed over 5,000 surveys and conducted 120 field studies. This research led to a systematic strategy that directly enhances the waterway resilience: 1. Multi-Hazard Sensing on infrastructure and vessels for early warnings before a minor issue turns into a systemic failure. 2. Data Fusion for Rapid Response in case of emergency to avoid cascading effects through the network. 3. Smart Emergency Coordination to rescue and re-routes traffic and to retain the network functions even under stress. 4. Operational Efficiency is improved by establishing the Waterway ETC (non-stop lock passage) that alone saves 590 million RMB annually by reducing idling time — making the system more efficient and less prone to the cascading delays often seen in multi-hazard events. Ultimately, this research demonstrates that digital soft infrastructure can reinforce physical hard infrastructure, creating a shipping network that is not only green but robust enough to recover quickly from diverse environmental and operational hazards.
How to cite: Liu, Z. and Sun, T.: Enhancing systemic resilience to multi-hazards in inland waterways: A 10-year evaluation of the "Internet of Ships" strategy in the Yangtze River Delta, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6374, https://doi.org/10.5194/egusphere-egu26-6374, 2026.
Climate change, combined with socioeconomic dynamics, is increasingly generating multi-hazard, compounding, and cascading risks, where extreme events occur simultaneously or in close succession and interact across social, ecological, and infrastructural systems. While growing attention has been given to understanding interacting and compound hazards and exposure, far less research has examined how resilience and vulnerability factors themselves interact in multi-hazard contexts. In particular, there is limited empirical evidence on whether the capacities that enhance resilience to one hazard also contribute to, or potentially undermine, resilience to other hazards. As a result, decision-makers often lack guidance on which adaptation actions are robust under compounding and cascading risk scenarios.
Improving understanding of these dynamics is critical because adaptation interventions can generate both co-benefits and unintended consequences across hazards. Measures designed to enhance resilience against a single extreme event may lead to maladaptation by diverting scarce resources, reinforcing inequalities, or increasing exposure to other risks. Conversely, integrated interventions may enhance resilience to multiple hazards simultaneously. Identifying such synergies and trade-offs is essential for effective, efficient, and equitable adaptation planning, particularly in resource-constrained settings.
We examine these challenges through a case study of Kuwait City, focusing on extreme heat and flooding as interacting climate risks in an arid urban context. Methodologically, the study combines a community resilience measurement framework, called Climate Resilience Measurement for Communities (CRMC), with complex system mapping using Fuzzy Cognitive Mapping (FCM). A mixed-methods data collection strategy was employed, including an online household survey of 778 respondents, interviews with 13 key informants, and analysis of secondary data, to measure 76 resilience indicators related to flood and heat risks in Kuwait. In addition, participatory system-mapping sessions with local stakeholders were conducted to elicit and co-develop cognitive maps capturing relationships and interdependencies among resilience components and adaptation actions, drawing on local knowledge and experience. The combined FCMs were used to assess the co-benefits and unintended consequences of adaptation measures for flood and heat in Kuwait.
We present this participatory system-mapping approach as a useful method for identifying interdependencies across climate risks, enabling the systematic identification of co-benefits and unintended consequences in a multi-hazard environment. By explicitly capturing interlinkages among resilience components and adaptation actions, the study argues that complex climate risk interactions must be considered when identifying and prioritising effective adaptation strategies. This study advances understanding of systemic resilience in multi-hazard contexts and supports the design of adaptation strategies that account for compounding risks and interconnected resilience pathways.
How to cite: Mehryar, S. and Alsahli, M.: Assessing Co-Benefits and Unintended Consequences of Climate Adaptation Through Resilience Interdependencies, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13473, https://doi.org/10.5194/egusphere-egu26-13473, 2026.
Recent advances in socio-technical systems have increased interdependencies among system components and created conditions in which the impacts of disasters can readily propagate across space and time. Consequently, contemporary disasters tend to be complex and large-scale, driven by multiple interacting causes rather than being explained by single triggering factors such as floods or landslides.
These characteristics emphasise the importance of identifying disaster causes in the pre-event phase to support prevention and preparedness strategies, beyond a sole focus on post-event response. In particular, the emergence of new risks associated with recent extreme weather events and climate change constrains the feasibility of reliable prediction, highlighting the need for systematic analysis of recurring causal factors and their interaction patterns observed in past disasters.
In response to these needs, causal analysis methods have evolved from first- to third-generation approaches. While first- and second-generation methods are effective in identifying single causes or failures of protective measures, they are limited in explaining modern disasters characterised by complex interactions among multiple actors and structural, environmental, institutional, and technological factors. By contrast, third-generation approaches consider system-wide control structures and non-linear causal relationships, enabling the analysis of preventive interventions even under conditions of uncertainty.
This study analyses 206 official accident investigation reports to examine recurring causal factors and damage amplification mechanisms. Representative causal analysis methods were selected for each generation, and the reports were analysed based on the key components required by each method. The results indicate that the extent to which essential components are addressed varies across causal analysis methods. In addition, structural and systemic causes account for a higher proportion than causes attributable to human error, and patterns of interaction among causal factors are found to be highly complex. Based on these findings, this study proposes an interpretive causal analysis framework for analysing the causes of summer river-related disasters in Korea, taking into account the limitations of single-cause–oriented analytical approaches.
How to cite: Min, S.-G., Shin, H. Y., Yang, S. H., Kim, J. E., and Choi, S. Y.: Interpreting the Causes of Summer River Disasters in Korea: An Analysis of Accident Investigation Reports, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9042, https://doi.org/10.5194/egusphere-egu26-9042, 2026.
Extreme rainfall and flash flooding are increasing in frequency and severity across the Mediterranean region. Such events cause loss of life, disrupt livelihoods, damage critical infrastructure and ecosystems, lead to cascading effects across society, the economy and nature, and generate long-lasting social, economic and environmental impacts. In October 2024, a severe DANA(Depresión Aislada en Niveles Altos, an atmospheric cut-off low) event affected the province of Valencia, Spain, producing very intense rainfall totals and widespread flooding that overwhelmed urban, fluvial and emergency response systems and caused immense human tragedy. The event was dubbed one of the worst floods in Europe although there are striking similarities to the Central European floods following the cut-off low "Bernd" in 2021. This shows that still, even in extreme flood disasters, limited attention is often paid to how existing technical, institutional, and community-based capacities can be better enabled to reduce risk and strengthen resilience. Flood post-event analyses tend to focus on meteorological severity and emergency response performance, while broader learning on how risk is created, governed and reduced across the full disaster risk management (DRM) cycle remains insufficiently developed. For this DANA event, we have applied the Post Event Review Capability (PERC) forensic analysis methodology. It has produced a series of findings based on a comprehensive post-event review of the October–November 2024 DANA in Valencia, Spain. The event resulted in extensive human, economic and environmental impacts across a densely populated and highly exposed region. The analysis examined how DRM systems functioned in practice, identifying successes, limitations and missed opportunities across preparedness, response, recovery and corrective as well as prospective risk reduction, jointly forming the elements of the DRM cycle. The findings highlight the critical importance of anticipatory governance, people-centred early warning systems and the structured integration of community and psychosocial dimensions in flood risk management, offering lessons that are locally actionable and relevant to other flood-prone regions facing similar climate-driven risk dynamics, of which there are plenty across the Mediterranean region and beyond.
How to cite: Szoenyi, M. and Millor Vela, D.: PERC Disaster forensics on the catastrophic 2024 DANA flood event in Valencia, Spain, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16762, https://doi.org/10.5194/egusphere-egu26-16762, 2026.
Climate change is intensifying compound and cascading disasters, yet conventional assessment frameworks focused on single hazards, while being methodologically and practically more straightforward, often fail to capture the systemic, interdependent dynamics that shape community climate resilience. There is an urgent need for robust and practical methods to assess resilience across multiple hazards at the community scale, where climate impacts are felt most strongly and where much investment in improving resilience is needed.
This presentation showcases the Climate Resilience Measurement for Communities (CRMC), developed by the Zurich Climate Resilience Alliance, an innovative framework that addresses this critical gap. The CRMC has evolved from its origins as a single-hazard Flood Resilience Measurement for Communities - where it was applied in over 400 communities globally - to become the first community-level tool to holistically assess resilience to multiple climate hazards in parallel, currently including floods, heatwaves, wildfires and storms. The framework takes a systemic approach, measuring 26 general resilience indicators plus hazard-specific indicators across five domains: human, social, natural, physical and financial capitals. Crucially, the CRMC is explicitly designed to identify co-benefits across hazards and avoid unintended consequences.
We will share new research from Fire to Flourish (Monash University), which partnered with the Zurich Climate Resilience Alliance to develop the wildfire layer of the CRMC and apply it in eight regional Australian communities. This is the first holistic, systems-based measurement of community wildfire resilience. Five communities were assessed for both wildfire and flood resilience, demonstrating multi-hazard assessment functionality and enabling direct comparison of how communities fare across different hazards and identification of general versus hazard-specific resilience gaps. These CRMC assessments provided actionable evidence for community-level decision-making and prioritisation, enabling measurement of resilience changes over time, and integrated stakeholder engagement through participatory data collection directly with community members. It facilitates learning between hazards within the same measurement process, revealing how strengths in resilience to one hazard can inform strategies for others.
Strong patterns emerged across the assessments, revealing systemic strengths in community preparedness and hazard awareness, alongside critical gaps in long-term planning, investment in critical infrastructure, and the responsiveness of emergency planning to local people and place. The multi-hazard assessments revealed that communities often scored better on specific hazard responses than on general resilience measures such as energy, communication and transport systems, highlighting the importance of these foundational systems for overall resilience. Importantly, the process of measurement itself built resilience through learning and community engagement.
This work demonstrates that systemic resilience to multiple hazards can be meaningfully measured at community scale to inform local priorities, support systems change, and guide investment in climate-resilient development.
How to cite: Keating, A. and D'Arcy, Z.: Measuring Community Resilience to Multiple Climate Hazards: The CRMC Approach and Australian Experience, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16121, https://doi.org/10.5194/egusphere-egu26-16121, 2026.
As climate change intensifies compound and cascading hazards, conventional single-risk frameworks often fail to capture the systemic nature of community vulnerability and adaptive capacity. To address this, we revisit the theoretical foundations of the Flood and Climate Resilience Measurement for Communities (F/CRMC), a tool grounded in the Sustainable Rural Livelihoods (SRL) framework (Scoones, 1998). While the F/CRMC has generated extensive longitudinal data across five capitals (social, human, physical, financial, and natural) in over 500 global communities, its evaluative potential can be best realized by re-integrating the SRL lens to evaluate how livelihood strategies and institutional processes mediate resilience across different evaluative contexts.
We propose a methodology that re-categorizes FRMC indicators based on their functional role within the SLF cycle across three evaluative contexts:
- Vulnerability Context vs. Baseline Assets: We differentiate between indicators that define the external environment (enabling conditions) and those representing internal community capitals using comparative post-event data
- Proxies for Structures and Processes: By analyzing data from 2018–2025, we track how longitudinal changes in specific indicators - such as local leadership or inter-community coordination, serve as empirical proxies for the "transforming structures and processes" and contribute directly to livelihood outcomes or indirectly with changed livelihood assets/capitals.
- Dynamic Pathways: We investigate how the interplay between assets and interventions leads to measurable resilience outcomes.
Our findings reveal that certain indicators are not merely "assets" but act as catalytic drivers that influence the entire SLF loop. For example, social capital indicators frequently transition from "outcomes" of successful interventions to "enablers" of future livelihood strategies. Our results demonstrate that the SRL framework provides a robust mechanism for understanding systemic resilience, as it explicitly links assets to the transforming structures and processes that enable or constrain change. By mapping these dynamics, we critically assess the operability of indicators according to different evaluative purposes. This research bridges the gap between theoretical social science and large-scale empirical practice, offering actionable insights for evaluating resilience changes that are context-sensitive and strategically aligned with sustainable, multi-hazard resilience goals.
How to cite: Hyun, J. H., Guimaraes, R., and Keating, A.: Re-centering the Livelihoods Framework for Understanding Systemic Resilience Pathways: A Multi-Context Evaluation using Resilience Assessment Indicators and Data, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7516, https://doi.org/10.5194/egusphere-egu26-7516, 2026.
Resilience policy often looks through the lens of “absorptive–adaptive–transformative” change, but empirical evidence on how communities actually move between these states, and what reliably triggers these transitions, remains sparse. We address this gap with the use of repeated, standardized community flood-resilience measurements from the Flood Resilience Measurement for Communities (FRMC). The FRMC is a systems-based 5C–4R framework (human, social, physical, financial, natural capital; robustness, redundancy, resourcefulness, rapidity) which is designed to generate comparable evidence for action and which is validated in a large-scale global community application.
We reorganize FRMC sources into an absorptive–adaptive–transformative ladder and analyse the change across two time periods, baseline and endline. As the FRMC is a multi-country dataset which spans distinct community types, we have the opportunity to combine (i) global patterns of capacity change, (ii) a typology of five empirically grounded community clusters (rural/urban, risk and vulnerability, capital endowments), and (iii) boosted regression trees model to identify dominant drivers, interactions, and recurrent inflection points.
There are three results which stand out. First, systems change follows a loose sequence. First improvements in shock-proofing and recovery performance lead to improvements in diversification and learning, which then in turn enable growth in governance and investment. Secondly, exposure shapes the pace and direction of change, that is low recurring flood impact behaves like a learning regime that strengthens absorptive and adaptive capacity, while chronic moderate to high exposure has a strong negative effect across all three capacities and most strongly impacts transformational capacity. Thirdly, threshold-and-handoff dynamics recur across clusters, specifically early warning and faster, more inclusive recovery efforts protect livelihoods and create the opportunity for adaptive capacity growth. Remittances and women’s secondary education show repeated positive effects and once governance awareness and participation cross mid-level thresholds, communities more consistently initiate structural shifts (e.g., re-planning, relocation, livelihood transitions). In high-capacity urban settings, we detect diminishing returns to further absorptive capacity investment and emerging trade-offs where rapid development is associated with reduction in natural capital, which are findings consistent with mal-adaptation risk.
The analysis shows how repeated resilience measurement can operationalise “systems change” as observable transitions with identifiable prerequisites, ceilings, and trade-offs. These can support interventions, secure core absorptive capacity functions, breach adaptive capacity thresholds via institutional/economic programs, then steer finance, education, and participation toward structural redesign.
How to cite: Velev, S.: Understanding systems change through resilience measurement: global evidence from repeated community flood-resilience assessments, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13200, https://doi.org/10.5194/egusphere-egu26-13200, 2026.
Floods are Nepal’s most frequent and high-impact natural hazard, posing growing risks to communities’ livelihoods and well-being. Using survey data from 61 Nepalese communities collected at baseline and endline through the Flood Resilience Measurement for Communities (FRMC) framework, this study investigates three dimensions of community flood resilience: temporal changes across the five capitals and five DRM cycle stages, the influence of flood hazard exposure, and the relationship between resilience and socio-economic well-being. By integrating FRMC with hazard data and development indicators from the national Census, we classify communities into resilience trajectories, identify which capitals buffer the impacts of hazards, and explore associations with poverty, education, and health outcomes. Results show how resilience evolves, what shapes it, and why it matters for broader development and climate policy. These findings underscore the importance of context-sensitive, multi-dimensional resilience measurement and highlight opportunities to leverage resilience as a development multiplier in climate and disaster policy. At the local level, the findings provide an evidence base for municipalities and community organizations to target resilience investments, identify which capacities buffer flood risks, and integrate disaster risk reduction into development planning.
How to cite: Chapagain, D., Clercq-Roques, R., Velev, S., Hochrainer-Stigler, S., Hyun, J.-H., Guimaraes, R., Keating, A., Shrestha, A., and Mechler, R.: Resilience in Transition: Temporal Dynamics, Climate Exposure, and Development Linkages of Community Flood Resilience in Nepal, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12679, https://doi.org/10.5194/egusphere-egu26-12679, 2026.
To cope with the growing risks brought by climate-related disasters, it’s crucial that communities strengthen their adaptive capacity. In this context, social protection plays a key role and should be seen as an essential part of the policy response. This study investigates whether perceived access to formal and informal social protection mechanisms influences changes in climate adaptive capacity over time across flood-prone communities worldwide. Using data from the Flood Resilience Measurement for Communities (FRMC) tool, we analyse responses from over 200 communities. Adaptive capacity indicators were constructed from baseline and endline data, and regression models were applied to assess the role of different perceived social protection mechanisms to changes in adaptive capacity. Results show that perceived access to loans is consistently associated with improved adaptive capacity, particularly in communities recently affected by floods. Perceived formal support from governments or NGOs benefits lower-adaptive capacity communities but has diminishing returns in higher-capacity contexts in the baseline. Perceived informal support from family members shows no influence. These findings underscore the importance of financial mechanisms and context-specific strategies in designing social protection systems that effectively foster climate resilience.
How to cite: Guimaraes, R.: Does the Perceived Access to Social Protection Mechanisms Strengthen Adaptive Capacity? A Global Study of Flood-Prone Communities, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4776, https://doi.org/10.5194/egusphere-egu26-4776, 2026.
Extreme urban flooding poses a significant threat to cities, triggering complex cascading failures across critical infrastructure systems (CISs). This study develops a modular modeling framework using MATLAB Simulink to simulate the interconnected dynamics of electricity, water supply, and telecommunication systems based on their functional interdependencies. The cascading simulation was driven by inundation data derived from an InfoWorks ICM model of central Guangzhou, considering a combined 500-year rainfall and tidal level scenario. The spatiotemporal propagation of disaster impacts through the CISs was examined, with particular emphasis on facility-level anomaly triggers and the evolution of failure chains. The system performance for electricity, water, and telecommunications plummeted from 63.1%, 63.2%, and 21.8% at the rainfall’s end to 33.6%, 3.2%, and 2.7% two days later due to sustained cascading effects. A significant spatial mismatch between direct flood inundation zones and areas suffering from service outages was identified, highlighting the necessity of looking beyond the flood footprint in emergency management. This research provides a scalable framework for quantifying infrastructure resilience and supporting cross-sector disaster mitigation strategies.
How to cite: Huang, X., Chen, W., and Huang, G.: Modeling and Analysis of Urban Critical Infrastructure Dynamic Cascading Failures in Urban Floods Based on Simulink, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3657, https://doi.org/10.5194/egusphere-egu26-3657, 2026.
Climate change and urbanization exacerbate flooding and pose challenges to the development of sustainable cities. Mitigation measures for flood resilience improvement and risk reduction, such as green infrastructure, have attracted stakeholders’ attention. It is essential to accurately examine how flood resilience is affected by these strategies. Existing performance-based flood resilience metrics neglect the enhanced ability of the physical environment to manage flood threats once GI has been deployed, which hinders the accurate revelation of the resilience-related effects of GI. This study proposed a novel performance-based metric integrating the resilience-enhancing effects of GI and performed comparative analyses to accurately reveal the effects of GI. The results suggest that GI enhances system performance in severely inundated areas. The in-situ impacts of the GI are more pronounced in terms of the most unfavorable state of the system's functioning, recovery from the most unfavorable state to the equilibrium state, and adaptation and recovery rates from flooding.
How to cite: Zheng, J. and Huang, G.: A novel performance-based metric for revealing the resilience-enhancing effects of green infrastructure, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3671, https://doi.org/10.5194/egusphere-egu26-3671, 2026.
Taiwan is highly susceptible to frequent debris flow disasters due to its steep terrain, fragile geological structures, and intense rainfall from typhoons. To mitigate these risks, the Agency of Rural Development and Soil and Water Conservation (ARDSWC) under the Ministry of Agriculture (MOA) established a rainfall-based debris flow warning system in 2005, adopting the critical rainfall model proposed by Jan (2004). This system utilizes Effective Accumulated Rainfall (EAR)—combining current event rainfall and 7-day antecedent rainfall—as the primary indicator for debris-flow warning. Through statistical analysis of historical rainfall events, specific warning criteria have been set for townships prone to debris flows across Taiwan, classified into 9 levels ranging from 200 to 600 mm at 50-mm intervals. Consequently, warning issuance is triggered when the EAR exceeds these designated criteria. Based on a dataset of 252 officially recorded debris flow events and their associated warning records spanning from 2005 to 2025, this study assesses the effectiveness of warning operations using four performance indices: Capture Rate of Warning Issuance (C1, reflecting operational effectiveness), Capture Rate of Warning Criteria (C2, evaluating the appropriateness of criteria setting), Disaster Occurrence Rate within Issued Warnings (C3, indicating occurrence probability in warned areas), and Disaster Warning Coverage (C4, evaluating if events occurred within designated potential zones). The results show that both C1 and C2 achieved 67.5%, C3 was 8.4%, and C4 reached 90.8%. Overall, the debris flow warning system has proven to be operationally mature and highly effective in disaster mitigation. Approximately 70% of debris flow events were preceded by warnings that facilitated preemptive resident evacuation. Since the implementation of the system, casualties have been significantly reduced, notably with zero debris flow-related fatalities recorded over the past decade. Furthermore, the majority of events occurred within identified potential risk zones. Nevertheless, facing climate-change-induced extreme rainfall and post-seismic slope instability, continuous optimization of warning protocols and criteria remains essential to ensure robust early warning capabilities.
Keywords: debris flow, early warning system, performance evaluation
How to cite: Zeng, Y.-C., Jan, C.-D., Wang, J.-S., Chen, C.-Y., and Lin, Y.-T.: Performance Evaluation of Taiwan’s Rainfall-Based Debris Flow Warning System: A 20-Year Operational Analysis (2005–2025), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4822, https://doi.org/10.5194/egusphere-egu26-4822, 2026.
Climate change has become a critical global issue, significantly affecting runoff formation and flow regimes, thereby increasing the frequency of flooding. The Vietnamese Mekong Delta (VMD) is particularly affected due to fluctuating Mekong River flows and extreme weather events. Despite the challenges of living in a flood-prone environment, local communities have shown remarkable flood resilience capacity in managing floods. This study simulates how farmers and government agencies improve and maintain systematic flood resilience using an Agent-Based Modeling (ABM). Cho Moi District, An Giang Province, is taken as a case study, as it represents a region with successful flood resilience under the South Vam Nao Project. The ABM features two primary agent types: 113 farmers, categorized by income level (high, medium, and low income), who vary in their capacity and knowledge to implement flood resilience measures; and the local and central governments, who act as political influencers capable of initiating large-scale engineering interventions. The model aims to quantify cumulative economic losses before, during, and after flood events based on different levels of applied flood resilience measures. Farmers decide whether to live with tolerable flood depths or take actions such as building temporary structures or elevating properties. The model also examines the impact of the government’s large-scale engineering projects, including high- and low-dike systems, as well as other infrastructure. This study presents a valuable simulation for assessing dynamic flood resilience across multiple flood events over extended periods, as well as testing flood resilience scenarios for future resilience potentials. The findings have potential applications to other real-world cases.
Keywords: Agent-Based Modeling, flood resilience measures, engineering measures, economic loss simulation, South Vam Nao scheme.
How to cite: Ho, T. P., Yang, L. E., Garschagen, M., Tri, V. P. D., Feng, W., and Ly, T. N.: Modeling multi-actor flood resilience strategies in the Vietnamese Mekong Delta, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4931, https://doi.org/10.5194/egusphere-egu26-4931, 2026.
Intensified climate change and anthropogenic pressures have rendered forests increasingly vulnerable to disturbances such as droughts, heatwaves, wildfires, and land-use change, leading to complex social, ecological, and economic impacts. Forests are social-ecological systems that provide numerous services to humans and co-evolve with human activities, governance, and management practices. Therefore, forest resilience, its capacity to withstand, adapt to, and recover from disturbances, depends not only on ecological processes but also on social and institutional conditions. However, most studies investigating forest resilience have primarily focused on biophysical dimensions, with limited attention given to social aspects.
To address this gap, the current study proposes a new framework for assessing social resilience in forests by operationalizing key social resilience principles, which include fostering complex adaptive system thinking (P4), encouraging learning and experimentation (P5), broadening participation (P6), and promoting polycentric governance (P7). Relevant social, economic, and governance indicators were identified through a literature review and global datasets. These indicators were then standardized to ensure equal weighting priority regardless of their original scale. To manage multicollinearity and eliminate redundant indicators, the Variance Inflation Factor (VIF) analysis was performed, and the final selection of indicators was guided by theoretical relevance and balanced domain representation. Principal Component Analysis (PCA) was then applied to derive indicator weights, and a social resilience value was calculated and spatially mapped as a weighted sum of standardized indicators.
Applying this framework at the global scale reveals clear spatial patterns in social resilience across forest regions. The results show that high social resilience is concentrated in parts of Europe, North America, and Australia, while low resilience clusters appear in several tropical and developing regions, including parts of Sub-Saharan Africa, Southeast Asia, the Amazon Basin, and Central Africa. When comparing social resilience with biodiversity, mismatches can be observed in tropical regions where highly biodiverse forests coincide with communities that have low social resilience and institutional capacity. These regions emerge as hotspots of vulnerability to climate and anthropogenic pressures, including drought, fire, deforestation, and socio-economic disturbances. This misalignment highlights the importance of considering social and institutional capacity when designing and implementing climate and biodiversity policies, as ecological effectiveness is likely to depend on local governance, social capital, and adaptive capacity, as well as on whether interventions are aligned with local needs, knowledge, and institutional capacity to coordinate, learn, and respond to change.
How to cite: Anamaghi, S. and Kalantari, Z.: Linking Social Resilience and Biodiversity Across Global Forests, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5155, https://doi.org/10.5194/egusphere-egu26-5155, 2026.
The dominant discourse in global change science is currently defined by narratives of impacts and crisis, utilizing frameworks such as Planetary Boundaries and Tipping Points to diagnose biophysical risks. While essential for risk management, this focus often overshadows a parallel historical truth: the continuous and accelerating capacity of human societies to innovate and adapt. This study proposes a complementary, generative paradigm of positive resilience evolution. Defined as the emergent, co-evolutionary capacity of coupled socio-technological–ecological systems to sustain and enhance livability within a dynamic Earth, the positive perspective reframes humanity from a source of perturbation to a conscious agent of planetary stewardship.
The study articulates the theoretical foundations of this framework through five interactive pillars: Ecological Regeneration, Technological innovation, Social-culture Cohesion, Governance Intelligence, and Adaptive Actions. By integrating resilience theory with complex systems science, a capacity-oriented Resilience Index is established as a quantitative tool to track progress and identify high-leverage points for intervention. This perspective aims to move beyond descriptive vulnerability assessments toward prescriptive resilience engineering, emphasizing "bouncing forward" through intentional transformation. By highlighting documented resilience achievements and positive tipping points, this perspective provides a rigorous, evidence-based foundation for policy and practice.
How to cite: Yang, L. E.: Evolution of socio-ecosystem resilience in the Anthropocene: A positive perspective, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5563, https://doi.org/10.5194/egusphere-egu26-5563, 2026.
The resilience and operation of infrastructure systems are shaped not only by physical interdependencies but also by institutional arrangements embedded in laws, regulations, and administrative guidelines. However, institutional documents are typically written in an actor-centric manner, explicitly describing who manages or oversees a given infrastructure, while leaving infrastructure interdependencies largely implicit. This limits our ability to systematically identify potential cascading risks and coordination blind-spots arising from institutional design. This study proposes a network-based framework to reconstruct hidden infrastructure interconnectivity derived from institutional documents. Legal and regulatory texts related to public sewerage management, as an example, are decomposed using the ABDICO framework (Attribute–Object–Deontic–Aim–Condition–Or else), to systematically construct actor–infrastructure heterogeneous network. To capture indirect and semantically meaningful connections between infrastructures, we define a set of infrastructure-to-infrastructure meta-paths that traverse actor chains, including both pure actor-mediated paths and paths that revisit infrastructure nodes. Building on PathSim, we propose a modified similarity measure that (i) is applicable to asymmetric meta-paths and (ii) employs a global normalization scheme based on the total number of meta-path instances associated with each node. Furthermore, similarity scores derived from multiple meta-paths of varying lengths are aggregated using inverse path-length weighting to define a composite Dependency Index. Results show that infrastructure pairs sharing multiple indirect institutional pathways, particularly those involving smaller degrees, exhibit higher dependency scores, indicating potential latent interdependencies not explicitly stated in institutional texts. By treating hidden connectivity detection as an unsupervised problem, this approach provides a scalable means to explore institutional coupling in infrastructure systems where direct infrastructure inter-links are unavailable. The proposed framework contributes to a novel methodology for institutional network analysis and offers insights into governance-induced infrastructure interdependencies, with implications for infrastructure resilience assessment and policy design under increasing climate-related risks.
Acknowledgement This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Ministry of Science and Technology (RS-2024-00356786).
How to cite: Kim, W., Kim, H., and Park, J.: Measuring the Strength of Infrastructure Interdependency Using Meta-Path-Based Dependency Index, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6198, https://doi.org/10.5194/egusphere-egu26-6198, 2026.
Nature-based solutions (NbS) are widely promoted as a pathway to climate- and disaster-resilient development. However, empirical evidence on how NbS influence the resilience of human societies remains fragmented. Existing studies tend to focus on individual hazards or project-level physical outcomes, while broader social, economic, and institutional dimensions of resilience are often insufficiently addressed. At the same time, high-quality grey literature, particularly regional NbS assessments and policy reports could provide systematic classifications of NbS types, landscape contexts, and governance arrangements, as well as comparative insights from implemented cases. Despite their relevance, such sources are rarely integrated into scientific analyses in a structured manner.
This research develops an integrated, evidence-based framework to investigate the relationships between NbS and social resilience under multi-hazard conditions. Authoritative ASEAN NbS reports are used as a conceptual foundation to define NbS typologies, climate-sensitive landscape categories, and governance dimensions, drawing on insights from 70 documented regional cases and national policy analyses. These policy- and practice-based frameworks are then used to structure and interpret empirical evidence, allowing the identification of how different NbS interventions affect specific dimensions of social resilience, including exposure reduction, livelihood stability, adaptive capacity, and institutional response.
Building on this evidence synthesis, the study extends the analysis into forward-looking scenario assessment using hydrodynamic modelling. The Vietnamese Mekong Delta (VMD) is selected as a critical case due to its high exposure to compound flood hazards, sea-level rise, salinity intrusion, and its strategic role in national development and NbS-oriented adaptation policies. Using LISFLOOD-FP, the study simulates policy-relevant NbS scenarios in coastal and deltaic settings, examining how changes in flood dynamics translate into differentiated social resilience outcomes. By linking policy-informed NbS scenarios and social resilience dimensions, this research advances a systemic understanding of NbS as socio-ecological interventions and offers a transferable framework for resilience assessment in compound and cascading risk contexts.
How to cite: Su, H., Yang, L. E., Ho, T. P., and Feng, W.: Assessing the Social Resilience Impacts of Nature-Based Solutions under Multi-Hazard Contexts: An Integrated Evidence and Modelling Approach, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21747, https://doi.org/10.5194/egusphere-egu26-21747, 2026.
The Bandung Metropolitan Region in West Java, Indonesia, is home to over 9 million people and is exposed to multiple interacting geological and hydrometeorological hazards. Bandung City is located within a basin bounded by the Lembang Fault and the active Tangkuban Perahu volcano to the north. Previous studies indicate that the Lembang Fault is capable of generating an earthquake of up to magnitude 7, potentially subjecting up to one third of the region to severe ground shaking. Parts of the city are also highly susceptible to landslides, which, when combined with seismic activity, create the potential for cascading hazards with compounding impacts. In addition, Bandung frequently experiences flooding and landslides that have displaced tens of thousands of people. The city is further exposed to volcanic hazards from nearby volcanoes, including Tangkuban Perahu to the north and Guntur, Papandayan, and Galunggung to the southeast.
This research explores both single- and multi-hazard events that could impact Bandung City using a combination of qualitative and quantitative approaches. Co-designed with the Bandung City Government, the study responds directly to the need for improved understanding of the city’s hazard landscape and patterns of exposure to inform effective risk reduction and resilience-building interventions. We employ a storyline approach to develop plausible multi-hazard scenarios involving earthquakes, volcanic eruptions, and associated cascading hazards. These scenarios are complemented by quantitative modelling of earthquake and volcanic hazards, including tephra fall, lahars, and pyroclastic density currents, to produce probabilistic hazard footprints for disaster risk management planning. In parallel, we are developing detailed physical and social exposure models using satellite Earth observation, artificial intelligence, and census data integration to identify communities most at risk. Through close collaboration with local authorities, we are engaging directly with these communities via workshops to better understand vulnerability and co-develop targeted interventions that enhance community resilience and support sustainable development by reducing long-term human and economic losses.
How to cite: Crummy, J., Gunawan, E., Hussain, E., Hanifa, R., Sagala, S., and Nurfiani, D.: Understanding multi-hazard risk and resilience in Bandung, Indonesia, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-23160, https://doi.org/10.5194/egusphere-egu26-23160, 2026.
Climate change is reshaping hydrological regimes in European transboundary lakes, intensifying pollution pressures and exposing the limits of existing coordination arrangements. Hydrological extremes increasingly interact with persistent and emerging pollutants, creating compound challenges for legal and institutional frameworks developed under more stable conditions. While resilience has become a central concept in water governance research, we still know comparatively little about how specific legal designs support adaptive capacity across borders.
This paper draws on empirical research from a Swiss National Science Foundation–funded project on transboundary water cooperation in Europe. It examines pollution governance in three transboundary lakes—Lac Léman (France–Switzerland), Lake Lugano, and Lake Maggiore (Switzerland–Italy)—where cooperation duties are often framed in flexible or “best-effort” terms and where EU and non-EU legal orders meet. The analysis compares bilateral agreements, joint commissions, regulatory standards, and coordination practices across the three basins.
The empirical material is analyzed through the lens of legal resilience and adaptive capacity, building on work by Ruhl and by Cosens and Soininen. Five systemic properties—reliability, efficiency, scalability, modularity, and evolvability—are used to assess how legal arrangements facilitate coordination under conditions of uncertainty. The paper questions whether, under certain conditions, flexible legal arrangements (such as best effort obligations) can function as enabling elements of systemic resilience in transboundary water governance, allowing incremental adjustment and locally adapted responses to emerging pollutants and hydrological extremes. We conclude by deriving design implications for transboundary lake agreements facing compound hydrological-pollution pressures.
How to cite: Turley, L., Vanackere, F., and Telle, A.: Legal Resilience at the EU / non-EU Interface: Best-Effort Cooperation in Transboundary Lakes, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21921, https://doi.org/10.5194/egusphere-egu26-21921, 2026.
Effectively bridging the last-mile between precise early warnings and timely evacuations remains a critical challenge in mountain hazard risk reduction. This study examines an innovative governance model developed in China that systematically integrates technological infrastructure, institutional coordination, and community mobilization to address this gap. The model is built upon a high-precision forecasting system, which leverages an integrated space-air-ground observational network, advanced numerical models, and localized historical disaster databases to enable reliable short-term hazard predictions. Operationally, the model establishes a robust inter-agency coordination framework. Meteorological, natural resources, water resources, and emergency management agencies collaborate through institutionalized data-sharing and joint warning-issuance protocols. Warnings are disseminated via a multi-channel communication system—including national emergency broadcasting, SMS, and digital platforms—to ensure comprehensive and rapid coverage. A key innovation lies in embedding technical and managerial capacities within grassroots social governance structures. Through a community-based monitoring network, a grid-based management system, and a point-to-point household verification mechanism, warnings are directly delivered, confirmed, and acted upon at the local level. This process is reinforced by regular emergency drills, detailed evacuation plans, and pre-designated shelters, thereby translating abstract warnings into concrete public action and significantly reducing the decision-to-response time. Empirical evidence demonstrates that this integrated approach enhances local risk perception, improves evacuation efficiency, and contributes to measurable reductions in disaster risk. The model’s effectiveness stems from its capacity to overcome not only the physical dissemination gap but also the socio-cognitive and organizational barriers that often hinder protective action. As a transferable governance solution, it represents a paradigm shift from reactive emergency response to proactive, integrated risk management, offering valuable insights for mountainous regions worldwide facing similar last-mile evacuation challenges.
How to cite: Chen, R., Zhang, J., Tan, R., and Zou, Q.: From Warning to Action: An Integrated Governance Model for Last-Mile Evacuation in Mountain Hazard Management, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21290, https://doi.org/10.5194/egusphere-egu26-21290, 2026.
Disaster recovery is often governed not by physical damage alone, but by the ability of communities to mobilize and allocate limited recovery resources across space and time. While recent recovery simulation approaches have demonstrated how resource and service constraints shape aggregate recovery trajectories, such “coarse-grained” metrics provide limited guidance for decision-making during the immediate aftermath of a disaster. In particular, they offer little insight into where and why recovery processes stall across localities during the critical early days following an event, when intervention priorities must be set under uncertainty.
Given a community’s damage state after a hypothetical earthquake scenario, we examine its recovery process, such as clean-up, inspection, and repair, under a suite of recovery resource allocation scenarios. The analysis uses SimCenter’s R2D tool together with embedded infrastructure system operation simulators and the recovery simulator pyrecodes. For each recovery resource allocation scenario, two complementary indicators, namely resource occupancy and first-passage unfinished metric, are introduced. Resource occupancy is defined as the fraction of components within each locality that are actively engaged in a given recovery stage at a specific time. First-passage unfinished metrics are defined as the fraction of components within each locality that are awaiting initiation of a recovery stage by a given day. When evaluated at early time horizons, these indicators reveal spatially heterogeneous recovery bottlenecks that are not apparent from system-level recovery curves.
Recognizing that the availability of recovery resources is difficult to specify before a disaster and may change as additional resources are mobilized in the immediate aftermath of an event, a sensitivity analysis may be necessary for planning optimal recovery resource allocation strategies. To facilitate sensitivity analysis within a reasonable computing time, we combine recovery simulations with a surrogate modelling approach to enable rapid recovery simulations. In particular, polynomial chaos expansion is used as a computationally efficient surrogate to relate alternative resource allocation levels to locality-level recovery indicators. This enables efficient exploration of potential allocation scenarios after a disaster occurs, without requiring repeated high-fidelity recovery simulations, and supports time-constrained decision-making in the early response phase.
By emphasizing early-phase (e.g., debris cleaning), locality-resolved diagnostics of resource bottlenecks, rather than aggregate recovery timelines, this study advances the assessment of systemic resilience in cascading risk contexts. The results demonstrate how existing recovery simulation tools, augmented with efficient surrogate modelling, can provide actionable insights for emergency managers and planners to prioritize interventions and allocate limited recovery resources across interconnected urban systems.
How to cite: Yang, Y.-H., Zhao, J., and Stojadinović, B.: Identifying Early-Phase Recovery Bottlenecks Through Outcome-Based Metrics in an Integrated Regional Resilience Assessment Platform, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10614, https://doi.org/10.5194/egusphere-egu26-10614, 2026.
The Osung Underpass disaster in South Korea in 2023 represents a catastrophic socio-technical system failure, where natural disasters intersect with systemic institutional vacuums. Although this disaster began as a natural disaster, it developed into a complex catastrophe of interconnected causes; Therefore, traditional investigative methodologies have encountered significant limitations in visualizing root causes from a governance perspective. To address these limitations, the present study presents the "Augmented Accimap Framework" shown in Figure 1, which includes four key methodological features.
First, we systematized the institutional analysis by directly adding specific administrative guidelines (L-series codes) to the causal nodes. Secondly, the framework uses a standardized color-coded system—yellow for institutional factors and blue for non-systematic factors—to enhance the granularity of classification. Third, display an 'X' symbol on the cross-hierarchy arrow to visualize communication failures. Fourth, we clearly distinguished between "physical triggers" and "factors that increase human loss" and used red arrows to highlight important causal relationships.
Applying this framework to the Five Star Disaster, we identified 8 systemic factors and 14 non-systemic factors at 5 hierarchical levels. In particular, major causal relationships have been identified at the level of local governments and relevant agencies. The analysis revealed that while the collapse of the levee was a physical trigger, the catastrophic scale of the loss of life was primarily triggered by institutional ambiguity (L01–L03) and communication breakdowns that paralyzed real-time decision-making. Ultimately, by providing a tool that provides visual clarity for causal structuring, this study serves as a solid framework for policymakers to identify potential systemic risks and contribute to the improved resilience of disaster management systems.
How to cite: Shin, H., Kim, J. E., and Choi, S.: Beyond Conventional Forensics: Structuring the Causal Causes of Institutional Failures in the 2023 Five Star Disasters, Augmented Research Through the Accimap Framework, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9113, https://doi.org/10.5194/egusphere-egu26-9113, 2026.
Abstract: Cities are facing multiple meteorological hazards such as heatwaves, wind chill, floods, water scarcity, and tropical cyclones. Nonetheless, the exposure and adaptation of global urban growth to these hazards under climate change are not well addressed. This study assessed the urban population exposed to the aforementioned hazards globally from 2020 to 2050, and analyzed the impacts of adjusting the spatial patterns of future urban expansion on exposure. In 2020, a total of 2.18 billion (49.85%) urban residents worldwide were exposed to at least one severe hazard. Specifically, the urban population exposed to severe heatwaves, wind chill, tropical cyclones, water scarcity, and floods stood at 1.62 billion, 0.01 billion, 0.09 billion, 0.68 billion, and 0.27 billion, respectively. Additionally, 9.13 million (0.21%) urban residents faced concurrent exposure to more than three severe hazards. By 2050, the global urban population at risk of at least one severe hazard is projected to reach 4.31–4.81 billion (72.71%–75.03%). The projected urban population exposed to the five severe hazards mentioned above will be 3.72–4.25 billion (heatwaves), 0.71–0.71 billion (wind chill), 0.18–0.40 billion (tropical cyclones), 1.30–1.36 billion (water scarcity), and 0.35–0.41 billion (floods), respectively. The number of urban residents facing concurrent exposure to more than three severe hazards is expected to rise to 47.62–72.99 million (0.80%–1.14%). Adjusting the spatial pattern of future urban expansion can effectively reduce the urban population exposed to meteorological hazards. Under the scenario of moderate prevention of all hazards, the urban population exposed to heatwaves, wind chill, tropical cyclones, water scarcity, and floods will decrease by 34.64–35.83 million, 14.19–19.22 million, 41.95–51.57 million, 244.91–275.96 million, and 166.03–205.17 million, respectively. This study provides empirical support for delineating global urban growth boundaries for mitigating meteorological disasters.
How to cite: Liu, Z.: Global future urban growth and meteorological disaster risks, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4664, https://doi.org/10.5194/egusphere-egu26-4664, 2026.
With increasing frequency and severity of climate risks, communities are urged to systemically strengthen climate resilience. To do so, Climate Risk Assessments (CRA) support identification, assessment and monitoring of climate risks across hazards, geographic areas and socio-economic sectors. Despite broad application and implementation by research, policy and practice CRA, however, have shown limited integration of the resilience component. In Europe - and increasingly globally - climate risks are rarely unmanaged, as they are shaped by existing response capacities and adaptation measures. In our risk evaluation approach, we seek to integrate resilience capacity with quantified climate estimations, requiring translation and interdisciplinary thinking. We argue that by including a resilience perspective from an early adaptation stage onwards supports systemic resilience building.
Within the EU Horizon 2021 project CLIMAAX, we developed a Risk Evaluation Dashboard designed for application at European regional and community levels. The dashboard is embedded in a comprehensive CRA framework and operationalizes climate risk evaluation through three dimensions: Severity, Urgency, and Resilience Capacity. Resilience Capacity is conceptualized as both a generic and a hazard-specific attribute of a region’s ability to anticipate, cope with, and adapt to climate impacts. In this way, vulnerability and response capacity function as interacting modulating factors of resilience capacity rather than as only separate analytical layers for climate risk.
Through user engagement and empirical data collection within the CLIMAAX project, we assess how qualitative insights can complement quantitative risk estimations and feed into adaptation and resilience building. Further, by effectively integrating diverse perspectives, the dashboard aims to innovatively bridge the translation gap between CRA and resilience building with clear entry points for future CRM endeavors.
How to cite: Bachmann, M., Mechler, R., and Higuera-Roa, O.: From Risk to Resilience: Redefining Multi-Hazard Climate Risk Evaluation by integrating resilience capacity, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6489, https://doi.org/10.5194/egusphere-egu26-6489, 2026.
Climate change is increasing the frequency and intensity of hazards such as heatwaves, heavy rainfall, and wildfires worldwide. As hazards interact and occur in sequence, cascading and compounding impacts are becoming more common, particularly under disturbance regimes where chronic pressures and acute shocks co-occur and reorganize system states through feedbacks and time lags. Similar patterns are emerging in Korea, calling for an integrated framework that links press–pulse dynamics with Pressure–State–Response relationships to identify actionable intervention points. Nature-based solutions are promising for reducing compound disaster risk, but their effectiveness depends on where and how extensively they are implemented. A resilience-oriented synthesis is therefore needed to translate spatial NbS scenarios into clear strategy packages.
This study aims to explain, under press–pulse dynamics, how global climate change scenarios intensify interactions among single hazards within Korea’s social–ecological system and how these interactions expand into compound disaster risk through cascading and compounding pathways. It also aims to restructure variables and causal pathways using a Pressure–State–Response framing in order to identify key regulating factors and priority intervention points. The identified intervention points are operationalized into NbS implementation scenarios that reflect hotspots and exposure-weighted priorities. The effects of these scenarios are then verified through model-based quantitative assessment. Finally, the study organizes which of the four resilience dimensions are embedded in each NbS scenario or are most clearly strengthened and proposes combinable NbS strategy packages aligned with implementation stages.
This study examines how climate change scenarios intensify interactions among single hazards within Korea’s social–ecological system and how these interactions expand into compound disaster risk through cascading pathways. Variables and causal pathways are reorganized using a Pressure–State–Response framework to identify key regulating factors and priority intervention points. These intervention points are translated into national-scale, stepwise NbS land-use and land-cover scenarios based on hotspot and exposure-weighted prioritization under explicit transition rules and constraints. Scenario effects are evaluated using multiple InVEST models and FlamMap, with performance assessed through hotspot and exposure-weighted metrics rather than national means. Results are then synthesized to indicate which resilience dimensions are embedded or most pronounced across scenarios, and combinable NbS strategy packages are proposed across implementation stages.
The compound-disaster causal loop model indicates that the coupling of chronic pressures and acute shocks strengthens inter-hazard linkages and activates cross-scale feedbacks, yielding cascading and compounding impacts in Korea’s social–ecological system. Across hazard types, priority intervention points converge on land-cover structure, hydrological regulation, surface and soil conditions, slope stability, and catchment connectivity. Model-based assessments show that NbS scenarios can reduce hazard risks while generating co-benefits in ecosystem services, particularly in hotspot and high-exposure areas. These effects can be organized into resilience-oriented strategy packages, emphasizing robustness through strengthened regulating functions, redundancy through distributed blue–green networks, resourcefulness through multifunctional NbS portfolios, and rapidity through designs and operations that support faster functional recovery and limit lag-driven amplification.
This work was supported by Korea Environment Industry &Technology Institute (KEITI) through "Climate Change R&D Project for New Climate Regime.", funded by Korea Ministry of Environment (MOE) (RS-2022-KE002123).
How to cite: Bi, J., Kang, S., Lee, J., Kanniah, K. D., and Lee, J.: Elucidating Cascading and Cumulative Mechanisms of Compound Disasters in Korean Social–Ecological Systems and Proposing Nature-Based Solutions Strategies for Enhancing Resilience , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8540, https://doi.org/10.5194/egusphere-egu26-8540, 2026.
Urban flood defense facilities are facing pressure from climate change, infrastructure aging, and the increasing frequency and intensity of extreme rainfall events. Although resilience has been extensively addressed in urban flood management research, most prior studies depend on static indicators or index-based evaluations at city or regional scales, providing limited understanding of the dynamic responses of individual facilities to disturbances. This study presents a mathematical framework for assessing facility-level resilience in urban flood defense systems and for identifying critical thresholds that drive transitions between functional regimes. The proposed framework shows a composite sigmoid function to capture the nonlinear evolution of facility performance during disturbance and recovery phases. Four resilience dimensions, which are Robustness, Redundancy, Rapidity, and Resourcefulness, are explicitly linked to the parameters of the performance function, representing initial structural performance, availability of functional alternatives, recovery rate, and the resource system over time. To address uncertainty arising from incomplete or partially missing resilience indicators, the framework incorporates a probabilistic treatment of survey-based inputs. Missing or uncertain resilience attributes are modeled using probability distributions, allowing resilience dimensions to be represented as stochastic variables rather than fixed values. A systematic parametric analysis is performed by varying each resilience dimension across feasible ranges, while repeated Monte Carlo simulations are conducted to propagate indicator-level uncertainty into the dynamic performance trajectories. This enables the derivation of empirical cumulative distribution functions and density-based representations of resilience outcomes. The simulation results demonstrate pronounced threshold effects and the presence of alternative performance regimes. When resilience dimensions drop below critical levels, facilities fail to regain their original performance and instead converge toward degraded operational states with distinct probability distributions. Moreover, under scenarios of repeated disturbances, insufficient recovery intervals can trigger irreversible regime shifts, with uncertainty in recovery timing further amplifying the likelihood of such transitions, underscoring the critical role of recovery timing in environments exposed to recurrent extreme rainfall. By directly linking resilience attributes with dynamic performance modeling, and by explicitly accounting for uncertainty associated with incomplete resilience information, this framework enhances understanding of multistability and tipping points in engineered flood defense infrastructure.
Acknowledgement This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Ministry of Science and Technology (RS-2024-00356786) and Korea Environmental Industry & Technology Institute grant funded by the Ministry of Environment (RS-2023-00218973).
How to cite: Shin, Y., Heo, E., Hong, J., Park, S., Kim, I., and Park, J.: Identifying Alternative Regimes with Uncertainty in the Performance of a Flood Defense Infrastructure, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8674, https://doi.org/10.5194/egusphere-egu26-8674, 2026.
Under climate change, flood hazards increasingly threaten livelihoods and settlements in plateau mountainous regions, making multiscale flood resilience assessment essential. Taking Dali and Lijiang City in western Yunnan Province, China, as a case study, this study develops a multidimensional flood resilience framework integrating basic conditions, economic and behavioral capacities, and social capital, and evaluates flood resilience at both household and village scales using questionnaire survey and spatial data.
At the household level, Kruskal–Wallis (H) and Mann–Whitney (U) tests reveal a pronounced gradient pattern (H > M > L) for most indicators, reflecting the cumulative effects of resilience factors. In addition, several key indicators exhibit an “H > M ≈ L” pattern, mainly related to social roles, pre-disaster behavioral capacity, and information access, which are critical in distinguishing high-resilience households. Medium-resilience households show relatively stable basic conditions but remain constrained by limited proactive and institutional capacities, while low-resilience households are characterized by multidimensional vulnerabilities such as labor shortages, health constraints, and weak information exchange.
At the village scale, villages are classified into three resilience levels using the Jenks natural breaks method based on Comprehensive Resilience Index (CRI). Satellite image indicates that village-level flood resilience is not simply determined by topographic relief, but by relative position within the regional hydrological system and spatial utilization patterns. High-resilience villages are typically located on river terraces or regional nodes, balancing proximity to water with effective risk avoidance, whereas low-resilience villages are often situated in low-lying convergence areas with constrained drainage and extensive built-up expansion. Medium-resilience villages mainly occupy transitional zones, where locational advantages have not been fully translated into disaster resilience.
Overall, flood resilience exhibits clear hierarchical differentiation and spatial embeddedness across scales, highlighting the critical roles of behavioral capacity, information accessibility, and settlement spatial structure. The findings provide insights for differentiated, scale-sensitive flood resilience strategies in plateau mountainous regions.
How to cite: Wang, Z., Zhu, A., Yang, L. E., Chen, J., Feng, S., Ren, Y., Feng, W., Chen, S., Guo, Y., and Zhang, Y.: Assessment of Flood Disaster Resilience and Optimization Strategies in Plateau Mountainous Regions: A Questionnaire-Based Study in Dali and Lijiang City, Yunnan Province, China, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4945, https://doi.org/10.5194/egusphere-egu26-4945, 2026.
Posters virtual: Wed, 6 May, 14:00–18:00 | vPoster spot 3
EGU26-6236 | Posters virtual | VPS13
Designing Institutional Resilience for Compound Disasters: EOC Structures, Networks, and Adaptive OperationsWed, 06 May, 14:18–14:21 (CEST) vPoster spot 3
Disasters triggered by natural hazards increasingly unfold as compound and cascading events, placing extraordinary demands on the institutions responsible for coordination and decision-making. Emergency Operations Centers (EOCs) sit at the nexus of these multi-hazard crises, linking infrastructures, agencies, and communities, yet their organizational design is rarely examined through a systemic resilience lens. This presentation contributes empirical insights into how EOCs enable—or constrain—resilience under escalating uncertainty.
Drawing on qualitative analysis of U.S. Federal and state EOC doctrine and training materials, this study conceptualizes EOCs as socio-technical systems operating along a continuum between mechanistic (hierarchical and rule-based) and organic (networked and adaptive) organizational structures. Findings reveal that while formal guidance emphasizes mechanistic control to ensure accountability and resource tracking, effective EOC performance during complex and cascading disasters depends heavily on organic processes such as lateral information sharing, informal coordination, and emergent problem-solving. These adaptive mechanisms—critical for responding to interacting hazards and rapidly shifting conditions—remain largely undocumented and are instead learned through experience and social networks.
The analysis further identifies predisaster networking among EOC participants as key enabling conditions for systemic resilience. Pre-established relationships enhance information flow, reduce coordination friction, and support adaptive decision-making when conventional procedures are strained by compound hazards. From a resilience perspective, EOCs function not merely as coordination hubs but as institutional platforms where resistance, recovery, adaptation, and potential transformation are negotiated in real time.
This presentation advances the disaster- and climate-resilience discourse by reframing EOC design as a resilience-building intervention. It offers actionable strategies for strengthening systemic resilience, including integrating organic coordination mechanisms into doctrine, redesigning training and exercises to emphasize adaptive capacity, and evaluating EOC performance beyond compliance metrics. By explicitly addressing institutional dynamics within multi-hazard contexts, this work bridges theory and practice in climate-resilient development.
How to cite: Chang, R.: Designing Institutional Resilience for Compound Disasters: EOC Structures, Networks, and Adaptive Operations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6236, https://doi.org/10.5194/egusphere-egu26-6236, 2026.
EGU26-13004 | Posters virtual | VPS13
Trade-off between short-term resilience and long-term sustainability in infrastructure systemsWed, 06 May, 14:21–14:24 (CEST) vPoster spot 3
Resilience and sustainability are widely recognized as desirable properties of infrastructure systems. Although related, they can become conflicting objectives, especially when resources available to enhance them are limited, making trade-offs between short-term resilience and long-term sustainability inevitable. Despite growing needs of increasing both resilience and sustainability, systematic analyses of such trade-offs remain limited. In this work, we address this gap by developing a stylized, minimalistic stochastic model of system functionality under a sequence of disruptions. The results reveal the nature of the trade-offs between short-term resilience and long-term sustainability and show that, depending on the effectiveness of investments in each, sub-optimal allocations may arise and should be avoided. The analysis establishes clear relationships demonstrating how physical system features and investment strategies interplay to influence the nature of such resilience-sustainability trade-offs.
How to cite: Muneepeerakul, R. and Lin, N.: Trade-off between short-term resilience and long-term sustainability in infrastructure systems, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13004, https://doi.org/10.5194/egusphere-egu26-13004, 2026.
