Urban stormwater management (SWM) systems are increasingly challenged by the combined effects of climate change and urbanization, which are driving more intense rainfall, higher runoff volumes, and greater stress on aging infrastructure. Traditional stormwater approaches—largely reliant on static design storms and pipe-based conveyance—are no longer sufficient to manage compound flooding risks, water quality impacts, and system reliability under nonstationary climate conditions. This presentation synthesizes lessons learned from planning, design, and operational stormwater projects across multiple U.S. municipalities, highlighting the evolution from conventional SWM practices toward integrated, adaptive, and technology-enabled systems. The work draws upon a combination of advanced hydrologic and hydraulic (H&H) modeling, historical storm reconstruction, and real-time system optimization. Historical rainfall trends were evaluated using long-term gauge records and gauge-adjusted radar rainfall (GARR), demonstrating statistically significant increases in extreme precipitation compared to legacy design assumptions. Updated intensity-duration-frequency (IDF) relationships were developed using both full periods of record and recent 30-year subsets, illustrating the limitations of relying solely on NOAA Atlas 14, which does not reflect recent decades of intensified rainfall. Representative storm distributions were derived from observed high-impact events to better capture peak intensities and temporal variability critical to runoff generation and flood response. These refined rainfall inputs were applied within planning- and design-level H&H models to support system stress testing, identification of priority flooding locations, and evaluation of capital improvement alternatives. Beyond traditional modeling, the presentation highlights the role of cloud-based continuous monitoring and adaptive control (CMAC) systems in transforming stormwater infrastructure from passive storage assets into actively managed systems. By leveraging real-time rainfall forecasts, sensor data, and automated outlet controls, these systems dynamically optimize detention storage, draw down capacity ahead of storms, and reduce downstream peak flows. Operational case studies demonstrate measurable performance improvements over conventional approaches, including annual stormwater runoff capture rates approaching 87%, peak flow reductions on the order of 60%, and adaptive systems outperforming passive storage designs by factors exceeding two to three times. Additional benefits include increased infiltration volumes, improved compliance with regulatory water quality requirements, and reduced long-term costs for municipalities and property owners. Beyond technical outcomes, the presentation emphasizes key implementation lessons related to early integration of green infrastructure into master planning, long-term maintenance and funding strategies, cross-agency coordination, and community engagement to ensure equitable and sustainable outcomes. Collectively, these findings provide a defensible, data-driven framework for advancing stormwater management planning and design, enabling communities to transition from static infrastructure toward resilient, adaptive systems capable of responding to evolving climate and urban conditions.