Periodic Reporting for period 1 - STORIES (Spatial-Temporal Dynamics of Flood Resilience)
Okres sprawozdawczy: 2023-04-01 do 2025-09-30
Floods are destructive. But even so, flood prone areas are generally the most developed areas around the world (e.g. coasts, river deltas, flood plains, hilly valleys). This indicates that human societies are able to manage flood impacts and live with floods, i.e. human societies hold a capacity of resilience to floods. The emerging scientific concept of flood resilience specifically targets this phenomenon, but it is yet far too little developed to be of substantial use. The Spatial-Temporal Dynamics of Flood Resilience (STORIES) project aims to establish a fundamental theory and methodology for the field and lead its frontier.
Existing approaches often treat resilience as a static condition rather than as an evolving process shaped by behavioral adaptation, governance interactions, and socio-economic change. Against this backdrop, STORIES seeks to advance a new scientific understanding of flood resilience as a dynamic, multi-scalar, and socially embedded phenomenon. The project’s overall objective is to develop innovative frameworks and empirically informed models that reveal how flood resilience evolves over time and across scales—from households and communities to urban systems and river basins. Combining fieldwork, historical analysis, and computational modeling, STORIES integrates data from diverse contexts in China and Southeast Asia to explore how governance structures, institutional trust, and local learning processes influence resilience pathways. This interdisciplinary approach merges natural sciences, engineering, and social sciences, with particular emphasis on behavioral dynamics, social networks, and policy design.
The expected impact of STORIES extends beyond academic innovation. By quantifying resilience trajectories and identifying key leverage points for governance and planning, the project generates actionable insights for climate adaptation policies worldwide. Its findings are directly relevant to building more adaptive, equitable, and sustainable flood management systems. Through its integration of social-scientific perspectives with computational and environmental modeling, STORIES demonstrates the indispensable role of social sciences and humanities in understanding and fostering resilience in the face of escalating climate risks.
Existing approaches often treat resilience as a static condition rather than as an evolving process shaped by behavioral adaptation, governance interactions, and socio-economic change. Against this backdrop, STORIES seeks to advance a new scientific understanding of flood resilience as a dynamic, multi-scalar, and socially embedded phenomenon. The project’s overall objective is to develop innovative frameworks and empirically informed models that reveal how flood resilience evolves over time and across scales—from households and communities to urban systems and river basins. Combining fieldwork, historical analysis, and computational modeling, STORIES integrates data from diverse contexts in China and Southeast Asia to explore how governance structures, institutional trust, and local learning processes influence resilience pathways. This interdisciplinary approach merges natural sciences, engineering, and social sciences, with particular emphasis on behavioral dynamics, social networks, and policy design.
The expected impact of STORIES extends beyond academic innovation. By quantifying resilience trajectories and identifying key leverage points for governance and planning, the project generates actionable insights for climate adaptation policies worldwide. Its findings are directly relevant to building more adaptive, equitable, and sustainable flood management systems. Through its integration of social-scientific perspectives with computational and environmental modeling, STORIES demonstrates the indispensable role of social sciences and humanities in understanding and fostering resilience in the face of escalating climate risks.
During the reporting period (April 2023 – September 2025), the STORIES project has made substantial scientific progress in advancing knowledge and methodology for understanding flood resilience as a dynamic social–ecological process.
Field-based empirical research formed the foundation of the project. Extensive household surveys, interviews, and institutional mapping were carried out across China and Southeast Asia, generating over 2,500 valid responses from diverse flood-prone areas, including the Mekong Delta in Vietnam, the Tea-Horse Road region in Yunnan and Sichuan, and selected urban centers. These data capture behavioral adaptation, governance dynamics, and community responses to flooding, forming the basis for comparative and model-based analyses.
Using these datasets, the project developed a suite of empirically informed agent-based models (ABMs) and Bayesian network analyses to simulate interactions among households, governments, and institutions. The major FRAMe model integrates social survey data, behavioral theories, and governance structures to quantify resilience as evolving robustness and adaptability. Additional models simulate urban governance networks and policy diffusion in Chinese cities, revealing how trust and institutional diversity shape resilience outcomes.
At the regional level, a systematic synthesis of 460 studies identified and classified 85 flood resilience measures across Mekong Basin countries, providing a new comparative framework for analyzing regional adaptation strategies. Complementary research linked hydrological, planning, and governance analyses to assess trade-offs in green infrastructure and urban design for flood mitigation. Historical analyses extended the project’s scope by reconstructing past flood events to trace long-term adaptation processes.
Expected outcomes include integrated resilience models, comparative datasets, and actionable frameworks for adaptive flood governance. Collectively, these advances establish STORIES as a methodological and conceptual benchmark for cross-scalar, interdisciplinary research on climate and flood resilience.
Field-based empirical research formed the foundation of the project. Extensive household surveys, interviews, and institutional mapping were carried out across China and Southeast Asia, generating over 2,500 valid responses from diverse flood-prone areas, including the Mekong Delta in Vietnam, the Tea-Horse Road region in Yunnan and Sichuan, and selected urban centers. These data capture behavioral adaptation, governance dynamics, and community responses to flooding, forming the basis for comparative and model-based analyses.
Using these datasets, the project developed a suite of empirically informed agent-based models (ABMs) and Bayesian network analyses to simulate interactions among households, governments, and institutions. The major FRAMe model integrates social survey data, behavioral theories, and governance structures to quantify resilience as evolving robustness and adaptability. Additional models simulate urban governance networks and policy diffusion in Chinese cities, revealing how trust and institutional diversity shape resilience outcomes.
At the regional level, a systematic synthesis of 460 studies identified and classified 85 flood resilience measures across Mekong Basin countries, providing a new comparative framework for analyzing regional adaptation strategies. Complementary research linked hydrological, planning, and governance analyses to assess trade-offs in green infrastructure and urban design for flood mitigation. Historical analyses extended the project’s scope by reconstructing past flood events to trace long-term adaptation processes.
Expected outcomes include integrated resilience models, comparative datasets, and actionable frameworks for adaptive flood governance. Collectively, these advances establish STORIES as a methodological and conceptual benchmark for cross-scalar, interdisciplinary research on climate and flood resilience.
The STORIES project has achieved significant scientific and methodological breakthroughs in understanding, modeling, and assessing flood resilience. Core results include the quantification of resilience dynamics using the empirically grounded FRAMe agent-based model, which integrates behavioral, institutional, and hydrological processes to simulate resilience trajectories under varying scenarios. Complementary models of governance networks and urban planning systems have illuminated the non-linear and cross-scale dynamics that determine flood resilience outcomes. These innovations move beyond static index-based approaches, establishing resilience as a dynamic and evolving process shaped by feedbacks between social behavior, governance, and environmental change.
The project’s integrated framework—linking global climate scenarios, planning trajectories, and governance trade-offs—provides an analytical foundation for evidence-based flood risk management and adaptive policy design. Results demonstrate how planning decisions redistribute rather than eliminate risk and how trust, institutional diversity, and social learning critically shape resilience pathways. Historical analyses have further expanded understanding of how collective memory and institutional evolution support long-term adaptation.
The potential impacts are far-reaching. Scientifically, STORIES contributes a new paradigm for resilience research that bridges social, technical, and historical dimensions. Practically, it provides policymakers and planners with actionable insights for designing adaptive governance strategies and optimizing urban resilience measures.
To ensure broader uptake and long-term success, key needs include:
- Further research and demonstration projects to test and validate resilience models across additional geographic and socio-political contexts.
- Integration into international resilience frameworks (e.g. IPCC, UNDRR) to enhance policy relevance.
- Open-access model dissemination and training programs to support practitioners.
- Interdisciplinary collaborations and funding for extending the modeling framework to new climate risks and regions.
With these supports, STORIES can evolve from a scientific innovation into a transformative tool for advancing global flood resilience and climate adaptation policy.
The project’s integrated framework—linking global climate scenarios, planning trajectories, and governance trade-offs—provides an analytical foundation for evidence-based flood risk management and adaptive policy design. Results demonstrate how planning decisions redistribute rather than eliminate risk and how trust, institutional diversity, and social learning critically shape resilience pathways. Historical analyses have further expanded understanding of how collective memory and institutional evolution support long-term adaptation.
The potential impacts are far-reaching. Scientifically, STORIES contributes a new paradigm for resilience research that bridges social, technical, and historical dimensions. Practically, it provides policymakers and planners with actionable insights for designing adaptive governance strategies and optimizing urban resilience measures.
To ensure broader uptake and long-term success, key needs include:
- Further research and demonstration projects to test and validate resilience models across additional geographic and socio-political contexts.
- Integration into international resilience frameworks (e.g. IPCC, UNDRR) to enhance policy relevance.
- Open-access model dissemination and training programs to support practitioners.
- Interdisciplinary collaborations and funding for extending the modeling framework to new climate risks and regions.
With these supports, STORIES can evolve from a scientific innovation into a transformative tool for advancing global flood resilience and climate adaptation policy.