FRAMe: Empirically informed agent-based modeling of flood resilience in the Mekong River Basin

The FRAMe (Flood Resilience Agent-Based Model) serves as a framework designed to simulate flood resilience dynamics at the community level, focusing on a rural settlement in the Mekong River basin. Integrating empirical data from extensive surveys, Bayesian networks, and hydrological simulations, the framework quantifies resilience as a trade-off between robustness (resistance to damage) and adaptability (capacity for dynamic response). Agents include households, governments, and other institutional actors, linked by social and governance networks that facilitate knowledge transfer, resource distribution, and risk communication. FRAMe incorporates mechanisms for policy interventions and individual and collective decision-making, grounded in Protection Motivation Theory and MoHuB frameworks. The framework utilizes geographic data to achieve a spatially explicit design. Sensitivity analyses across five key parameter groups covering network structure, knowledge dissemination, and policy intensity demonstrate the model's robustness and allow systematic evaluation of intervention effects. Simulation results show that increasing the intensity of government assistance reduces average recovery time by around 50 % and improves system-level robustness by about 30 %. In contrast, enhancing emergency relief primarily improves adaptability (approximately 10 %) and shortens recovery time, with limited effect on robustness. Higher knowledge dissemination roughly doubles adaptability but also introduces greater variability in robustness. By examining policy scenarios and agent behavior, FRAMe aims to inform adaptive flood management strategies and foster the improvement of community resilience.•The agent-based model is described using the ODD+<i>D</i> protocol.•A brief model user's guide is provided.•The model validation and sensitivity analysis processes that have been conducted are explained.