Climate change can intensify hurricanes, resulting in more extreme compound flooding events. Understanding and predicting compound flooding is crucial for assessing flood risks and enhancing the resilience of coastal areas. This study focuses on projecting the flooding damages caused by hurricanes under warmer climate scenarios. First, we will use a hybrid model that integrates physics, statistics, and machine learning to simulate Harvey-like tropical cyclones under future climate conditions. A high-fidelity hydrodynamic model, driven by the projected rainfall, is used to predict inundation extents in the Houston area. Compound flooding effects, integrating heavy rainfall, storm surge, and sea-level rise scenarios, highlight heightened risks in both coastal and urban areas. Additionally, we will investigate the role of two flood control reservoirs in the domain, which reached their capacity during Hurricane Harvey. We will conduct experimental simulations to explore mitigation strategies, such as increasing reservoir capacity by raising dam heights, to reduce flooding damages. Our findings underscore the urgency of developing adaptive strategies to mitigate future flood damages and enhance resilience in a changing climate.