The peak intensity that occurs during a storm event can drive the performance of a green stormwater infrastructure (GSI), which may or may not align with the expected performance of the GSI. Both the peak intensity volume and where it occurs within an event are found to influence the GSI response. The design criteria set the expectation of how well a GSI will manage stormwater within a watershed. The Villanova University bioinfiltration rain garden (BRG) has been monitored since 2003, providing a long hydrological data record that is used to study local and observed rainfall patterns in comparison to design criteria to understand the impact of storm intensity on GSI performance. Intensities for all the storms recorded at the site were assessed at different timesteps and compared to the intensities typically used by the design storm approach in meeting regulatory criteria. There were 1482 storm events analysed and for all timesteps, the values commonly used for meeting design regulations were seen to be well above what was observed at the BRG, with 98% of the storms occurring below these values. Out of the 1482 storms, only 46 storms (3%) had effective durations longer than 10 h and no storm observed had an effective duration longer than 22 h, yet their peak intensities were still below the peak intensity associated with design regulations. This finding highlights the difference in the duration these sites are designed to manage (typically 24 h), in comparison to the ones experienced by the systems. The peak intensity analysis done at the different timesteps shows that for the storms recorded at the BRG, the intensities vary with changing time intervals and events. Of all the assessed events, only two events recorded larger intensities than the regionally specified NOAA C design storm, demonstrating the skewness of the approach. There was no trend in peak rain intensities over the 20‐year rainfall record. This study concludes that due to their dynamic performance, vegetated GSI have a natural resilience to a variety of precipitation patterns and climate changes that may be compromised when designing to a static value set through design storms.

The Schuylkill River Watershed in southeastern PA provides essential ecosystem services, including drinking water, power generation, recreation, transportation, irrigation, and habitats for aquatic life. The impact of changing climate and land use on these resources could negatively affect the ability of the watershed to continually provide these services. This study applies a hydrologic model to assess the impact of climate and land use change on water resources in the Schuylkill River Basin. A hydrologic model was created within the Structural Thinking Experiential Learning Laboratory with Animation (STELLA) modeling environment. Downscaled future climate change scenarios were generated using Localized Constructed Analogs (LOCA) from 2020 to 2040 for Representative Concentration Pathways (RCP) 4.5 and RCP 8.5 emission scenarios. Three regional land use change scenarios were developed based on historical land use and land cover change trends. The calibrated model was then run under projected climate and land use scenarios to simulate daily streamflow, reservoir water levels, and investigate the availability of water resources in the basin. Historically, the streamflow objective for the Schuylkill was met 89.8% of the time. However, the model forecasts that this will drop to 67.2–76.9% of the time, depending on the climate models used. Streamflow forecasts varied little with changes in land use. The two greenhouse gas emission scenarios considered (high and medium emissions) also produced similar predictions for the frequency with which the streamflow target is met. Barring substantial changes in global greenhouse gas emissions, the region should prepare for substantially greater frequency of low flow conditions in the Schuylkill River.

Accurately delineating both pluvial and fluvial flood risk is critical to protecting vulnerable populations in urban environments. Although there are currently models and frameworks to estimate stormwater runoff and predict urban flooding, there are often minimal observations to validate results due to the quick retreat of floodwaters from affected areas. In this research, we compare and contrast different methodologies for capturing flood extent in order to highlight the challenges inherent in current methods for urban flooding delineation. This research focuses on two Philadelphia neighborhoods, Manayunk and Eastwick, that face frequent flooding. Overall, Philadelphia, PA is a city with a large proportion of vulnerable populations and is plagued by flooding, with expectations that flood risk will increase as climate change progresses. An array of data, including remotely sensed satellite imagery after major flooding events, Federal Emergency Management Agency’s Special Flood Hazard Areas, First Street Foundation’s Flood Factor, road closures, National Flood Insurance Program claims, and community surveys, were compared for the study areas. Here we show how stakeholder surveys can illuminate the weight of firsthand and communal knowledge on local understandings of stormwater and flood risk. These surveys highlighted different impacts of flooding, depending on the most persistent flood type, pluvial or fluvial, in each area, not present in large datasets. Given the complexity of flooding, there is no single method to fully encompass the impacts on both human well-being and the environment. Through the co-creation of flood risk knowledge, community members are empowered and play a critical role in fostering resilience in their neighborhoods. Community stormwater knowledge is a powerful tool that can be used as a complement to hydrologic flood delineation techniques to overcome common limitations in urban landscapes.