2026-10-30 ペンシルベニア州立大学（Penn State）
米国ペンシルベニア州立大学などの研究チームは、地域住民や行政担当者の知見を取り入れた都市洪水シミュレーションモデルを開発し、雨水による都市型浸水の軽減策を評価した。研究では、米国ボルチモア市を対象に、住民との3年間にわたるワークショップや現地調査を通じて、浸水の発生場所、地域の課題、実行可能な対策を把握し、地形データや水文学的情報と統合したモデルを構築した。特に、河川氾濫ではなく、豪雨によって市街地に発生する内水氾濫に着目した。対策として、雨水を浸透・貯留させるレインガーデンなどのグリーンインフラ整備と、道路側溝の集水口に詰まった落ち葉やごみの清掃を検証した。その結果、両対策を組み合わせることで、一部地域の浸水深を最大55％削減できることが示された。特に集水口の清掃は、単独でも高い効果を示した。本研究は、地域住民の経験や優先事項を洪水モデルに組み込むことで、科学的な予測と地域で実行可能な防災対策を結び付ける新しい都市水害適応手法を提示した。
＜関連情報＞
地域社会の意見を取り入れた都市型降雨洪水モデリングを通じた雨水対策の共同設計
Co-designing stormwater adaptations through community-informed urban pluvial flood modeling
Ava Spangler,Antonia Hadjimichael,Carlin Blash,Mahsa Adib,Hong Wu,Mark Cameron, Claire Welty,Doris Minor-Terrell, Benjamin Zaitchik
Sustainable Cities and Society Available online: 3 August 2026
DOI:https://doi.org/10.1016/j.scs.2026.107750
Highlights
- Community-engaged SWMM model co-developed for Baltimore pluvial flooding.
- Showcases sustained, collective, and iterative engagement.
- Stakeholder-prioritized green/gray adaptations refined and simulated for feasibility.
- Inlet cleaning is most effective adaptation, but benefits vary with backflow.
- Adaptation strategies cut flood depths up to 55% in hotspots.
Abstract
The intensification of the hydrologic cycle due to climate change poses a threat to urban areas with aging and under-sized water infrastructure systems which often fail to adequately manage intense storm events. The City of Baltimore, Maryland, experiences recurrent stormwater (pluvial) flooding that overwhelms drainage infrastructure, damages housing and disrupts transportation. Adaptations are urgently needed to manage this threat; however, flood mitigation plans frequently fail to consider the objectives and preferences of residents. Engaging communities in pluvial flood modeling is often limited to hazard identification or model validation, and collaborative development of adaptation strategies is uncommon. This study presents a co-designed urban flood modeling framework in which community and technical experts directly inform flood model development and adaptation design through long-term and iterative engagement. The EPA Storm Water Management Model (SWMM) is used to integrate city-provided drainage infrastructure data, community-mapped flood locations, and local expert knowledge of local hydrologic processes. Three adaptations of interest to stakeholders, including green infrastructure, enhanced maintenance, and a combination of both, are simulated and compared across three representative rainfall scenarios. Enhanced infrastructure maintenance is found to be the most effective adaptation, reducing flood depths at priority intersections, though with spatially variable effects across the watershed. Spatially-concentrated greening provides limited benefit to the watershed as a whole. Together, these adaptations have the potential to reduce flood depths by as much as 55% in select locations, which would greatly reduce impacts on local stakeholders. This work demonstrates that co-produced flood models can serve as shared tools for learning and deliberation. Furthermore, these models can test adaptation options that are grounded in both hydrologic process and community priorities, resulting in more relevant and usable insights for communities working to prepare for climate impacts.
