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The IPCC’s Special Report on Climate Change and Cities shows how cities must adapt to climate risks. Urban planners need to create solutions that fit each city’s needs, enhancing urban adaptability and resilience in the context of increasing climate-related risks. Sustainable urban planning, increased citizen awareness, and resilient infrastructure design are crucial in mitigating the growing impacts of climate change on human settlements. Addressing these challenges requires the integration of perspectives from diverse disciplines, including the natural sciences, social sciences, and engineering fields. This article draws on insights from a collaborative effort among experts in these areas, promoting a more coordinated and interdisciplinary approach. By bridging this expertise, we aim to advance resilience practices and awareness, fostering effective urban climate solutions in Texas and beyond. 

This article deals with household-level flood risk mitigation. We present an agent-based modeling framework to simulate the mechanism of natural hazard and human interactions, to allow evaluation of community flood risk, and to predict various adaptation outcomes. The framework considers each household as an autonomous, yet socially connected, agent. A Beta-Bernoulli Bayesian learning model is first applied to measure changes of agents' risk perceptions in response to stochastic storm surges. Then the risk appraisal behaviors of agents, as a function of willingness-to-pay for flood insurance, are measured. Using Miami-Dade County, Florida as a case study, we simulated four scenarios to evaluate the outcomes of alternative adaptation strategies. Results show that community damage decreases significantly after a few years when agents become cognizant of flood risks. Compared to insurance policies with pre-Flood Insurance Rate Maps subsidies, risk-based insurance policies are more effective in promoting community resilience, but it will decrease motivations to purchase flood insurance, especially for households outside of high-risk areas. We evaluated vital model parameters using a local sensitivity analysis. Simulation results demonstrate the importance of an integrated adaptation strategy in community flood risk management.