Adaptive Capacity Disparities: Capturing Resiliency Inequalities in Socio-Hydrological Systems

Traditional socio-hydrology models often simplify the human domain, treating populations as homogenous and overlooking disparities that shape real-world flood vulnerability and recovery. This work introduces a socio-hydrology modeling framework that explicitly incorporates community-level differences in adaptive capacity, defined as the degree to which communities can cope with flood events. In this framework, a city is treated heterogeneously, with individual communities having their own characteristics. Using empirical socioeconomic data from diverse metropolitan areas, we parameterize a new Resilience domain to represent inter-community variation in flood recovery, economic growth, and disaster response. Results reveal that disparities in economic conditions between communities can shape resilience outcomes—consistent with Kuznets curve dynamics, where early economic growth may widen recovery gaps before eventual convergence. Additionally, we differentiate between inter- and intra- community inequalities that exacerbate recovery trajectories from temporally compounding flood events. Our results emphasize how empirically based metropolitan socio-economic characteristics shape causal relationships in social-hydrological systems. We show that by incorporating community specific characteristics, city-wide adaptive capacity performance follows the Kuznets curve hypothesis, where increasing economic productivity may unintentionally widen flood resiliency disparities. We further identify how flood resiliency inequalities stem from inter-city, intra-city, and exposure disparities, highlighting how community specific information influences human-flood interactions. Additionally, our model includes an adaptive disaster relief mechanism to simulate the impacts of different resource allocation and response strategies, highlighting how equitable disaster relief policies can reduce resource gaps without compromising overall city growth. By embedding adaptive human behavior, inequality, and policy levers into a systems modeling framework, this study advances socio-hydrology as a tool for assessing coupled human-natural systems in multi-sector dynamics contexts. Our findings underscore the importance of moving beyond average or fixed representations of human systems to inform more equitable and effective urban flood resilience strategies.