Climate change has led to an increase in global temperature and frequent intense precipitation, resulting in a rise in severe and intense urban flooding worldwide. This growing threat is exacerbated by rapid urbanization, impervious surface expansion, and overwhelmed drainage systems, particularly in urban regions. As urban flooding becomes more catastrophic and causes significant environmental and property damage, there is an urgent need to understand and address urban flood susceptibility to mitigate future damage. This review aims to evaluate remote sensing datasets and key parameters influencing urban flood susceptibility and provide a comprehensive overview of the flood causative factors utilized in urban flood susceptibility mapping. This review also highlights the evolution of traditional, data-driven, big data, GISs (geographic information systems), and machine learning approaches and discusses the advantages and limitations of different urban flood mapping approaches. By evaluating the challenges associated with current flood mapping practices, this paper offers insights into future directions for improving urban flood management strategies. Understanding urban flood mapping approaches and identifying a foundation for developing more effective and resilient urban flood management practices will be beneficial for mitigating future urban flood damage.

Urban flooding is prevalent in low-lying, coastal regions, where subtle topographic variation, shallow groundwater, and impervious surfaces govern inundation dynamics. This study evaluates urban flood susceptibility across Miami-Dade County by integrating flood-conditioning factors, including elevation, slope, rainfall, land use/land cover, distance to roads and open water, stream power index (SPI), topographic wetness index (TWI), groundwater depth, and flow accumulation within an Analytical Hierarchy Process (AHP)-based weighted overlay framework. The AHP-derived weights demonstrated strong consistency (consistency ratio = 0.022) and were applied to reclassify each conditioning factor into five flood susceptibility classes—very low to very high. The model performance was evaluated using the Federal Emergency Management Agency (FEMA) flood zone, and the findings demonstrated that the AHP-based framework effectively differentiates flood susceptibility at a fine urban scale, achieving strong predictive performance; area under the Curve (AUC) = 0.85. The results also reveal pronounced spatial variability in flood susceptibility, with northeastern urbanized areas, particularly in Hialeah, Miami Gardens, Miami Lakes, and Downtown Miami, exhibiting higher susceptibility compared to the northwestern Everglades region. Overall, this study presents a robust urban flood susceptibility framework that supports improved flood risk assessment and decision-making in complex urban coastal environments.

Groundwater dynamics in South Florida play an important role in shaping the hydrologic balance of the region. This study investigated long-term trends in groundwater elevation, surface water stages, and their interactions across Water Conservation Areas 3A and 3B, Everglades National Park, coastal watersheds, and Florida Bay. Time series decomposition of long-term groundwater elevation (1997 to 2022) was used to identify trends, seasonal patterns, and anomalies. Analysis of groundwater elevations revealed statistically significant regime shifts defining distinct phases of decrease (2005–2015) and increase (2016–2022) associated with changes in rainfall patterns and water management. Average groundwater elevation has increased in recent years, with upstream areas showing stronger associations with surface water flow volumes, while coastal areas showed stronger correlations with sea level changes. This distinction suggests separate hydrological mechanisms for the observed trends: upstream recharge likely dominates in freshwater marshes, whereas coastal areas are associated with sea level variability. Groundwater levels in coastal areas now remain above the ground surface even during dry periods, associated with external factors such as sea level rise. The relationships between surface water stages and groundwater elevations in most parts of the study area were linear, whereas coastal regions, parts of the Water Conservation Areas 3A and 3B and northern parts of the Taylor Slough were nonlinear. In Florida Bay, sea level variability was a dominant driver of surface water variability (88.3% relative importance), while freshwater delivery through creek discharge (2.2%) and rainfall (2.6%) showed small but measurable contributions, along with groundwater elevation (2.4%) reflecting regional hydrologic conditions.