EGU26-8336, updated on 14 Mar 2026
https://doi.org/10.5194/egusphere-egu26-8336
EGU General Assembly 2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Poster | Friday, 08 May, 14:00–15:45 (CEST), Display time Friday, 08 May, 14:00–18:00
 
Hall X3, X3.71
Community-Informed Urban Flood Modeling for Impact Mitigation
Ava Spangler1,2 and Antonia Hadjimichael1,2
Ava Spangler and Antonia Hadjimichael
  • 1Department of Geosciences, The Pennsylvania State University, State College, USA.
  • 2Earth and Environmental Systems Institute, The Pennsylvania State University, State College, USA.

Climate change is intensifying the hydrologic cycle, leading to more frequent and severe rainfall-driven (pluvial) flooding in urban areas. In the mid-Atlantic US cities, aging and under-designed stormwater infrastructure is increasingly strained by these events, resulting in recurring damage to property and disruptions to transportation networks. In this study, we combine community engagement with hydrologic modeling to develop and evaluate potential urban flood adaptation strategies. Over a three-year period, local technical experts and community representatives met regularly to discuss flooding concerns, identify priorities, and co-develop adaptation strategies. These discussions informed the development of an urban flooding model (EPA Storm Water Management Model) for the Baltimore Harbor watershed, the focus location of this study. The flooding model integrates complex surface and subsurface stormwater infrastructure data, local expert knowledge, and community insights. We simulate stakeholder-prioritized adaptations, such as green and gray infrastructure strategies. Model results demonstrate that enhanced infrastructure maintenance is the most effective adaptation for reducing flood depths, but has varied effects across the watershed, and can increase flooding in some locations. Spatially concentrated greening provides limited benefit to the watershed as a whole, but moderate benefit in community priority areas. Together, these adaptations have the potential to reduce flood depths by as much as 58% in some locations, greatly reducing property damage and mobility impacts, primary concerns of stakeholders. Future work will implement robust optimization tools to search for adaptations which meet stakeholder objectives and perform highly under varied future climate conditions. This work contributes to the expanding literature on collaborative modeling and demonstrates that community-engaged approaches can enhance model credibility and generate more actionable insights for communities seeking to strengthen climate resilience.

How to cite: Spangler, A. and Hadjimichael, A.: Community-Informed Urban Flood Modeling for Impact Mitigation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8336, https://doi.org/10.5194/egusphere-egu26-8336, 2026.