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Connectivity in urbanscapes can cause unintended flood impacts from stormwater systems

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Abstract

Urban flooding is intensifying worldwide, presenting growing challenges to urban communities. We posit that most of the flood management solutions currently employed are local in nature and fail to account for ways in which the space–time connectivity of floods is exacerbated by built infrastructure. We examine the 2014 flood in Southeast Michigan to identify key factors contributing to urban flooding and explore the implications of design choices on inundation. Findings reveal that stormwater infrastructure that neglects flood spatial connectivity can be ineffective in mitigating floods, leading to inundation even in the absence of local rainfall. Different configurations of network connections—including interfaces with natural channels—can significantly impact upstream surcharge, overflowing manholes and inundation conditions. These results emphasize the need to consider interconnectedness of flood processes in urban watershed systems to mitigate limitations inherent in the design of flood control and warning systems, to enhance urban flood resilience.

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Fig. 1: Illustration of key urban flooding concepts.
Fig. 2: Flood maps of Warren, Michigan for the STORM2014 (11 August 2014) event.
Fig. 3: Simulated water levels and flow rates at the outfalls and surcharged manholes for STORM2014.
Fig. 4: Relationship between flood inundation and flooded area.

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Data availability

The land use cover was obtained from the National Land Cover Database 2019 (https://www.mrlc.gov). High-resolution elevation data were provided by the USGS (https://apps.nationalmap.gov/downloader/). The building footprint data were obtained from the Southeast Michigan Council of Governments (https://maps.semcog.org/BuildingFootprints). Data on the stormwater system, including manholes, outfalls and pipes, were collected and compiled in collaboration with Macomb and Oakland Counties. The rainfall data were from the Automated Surface Observing Systems network (https://www.weather.gov/asos/). The simulation dataset (~600 gigabytes) archived on the Globus Cloud is available upon written request to the authors. Source data are provided with this paper.

Code availability

Data processing and analysis were performed using MATLAB 2022b (standard version). The source code is publicly accessible via GitHub at https://github.com/vinhngoctran/RedRun_processing.

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Acknowledgements

V.N.T. and V.Y.I. acknowledge the support of the US National Science Foundation CMMI program award no. 2053429 and the Department of Defense, Department of the Navy, the Office of Naval Research award no. N00014-23-1-2735, Environmental Protection Agency grant #2020‐2509. J. Kim was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT)(NRF-2022R1A2C2008584. D.B. Wright and G.A. Alexander acknowledge the support of the U.S. National Science Foundation CMMI program award #2053358. We acknowledge informative discussions with P. Seelbach, B. Kerkez, J. Bednar, G. O’Neil, C. Brown, C. Purdy, A. Asher, M. Thomas and S. Bergt that assisted this study.

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Authors and Affiliations

  1. Department of Civil and Environmental Engineering, University of Michigan, Ann Arbor, MI, USA

    Vinh Ngoc Tran, Valeriy Y. Ivanov, Weichen Huang, Kevin Murphy & Fariborz Daneshvar

  2. Macomb County Public Works Commissioner Candice S. Miller, Clinton Township, MI, USA

    Jeff H. Bednar

  3. Department of Civil and Environmental Engineering, University of Wisconsin-Madison, Madison, WI, USA

    G. Aaron Alexander & Daniel B. Wright

  4. School of Civil and Environmental Engineering, University of Ulsan, Ulsan, South Korea

    Jongho Kim

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Contributions

V.N.T. and V.Y.I. designed the study. V.N.T., W.H., K.M. and F.D. collected the data. V.N.T. conducted the experiments. V.N.T. and V.Y.I. analyzed the data and wrote and revised the paper with inputs from all co-authors. All authors contributed to the interpretation of results, writing and revision of the paper.

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Correspondence to Valeriy Y. Ivanov.

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Nature Cities thanks Matt Bartos and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Source data

Source Data Fig. 2

Inundation depth and the locations of surcharged manholes.

Source Data Fig. 3

Simulated water levels and flow rates at the outfalls and surcharged manholes for STORM2014.

Source Data Fig. 4

A relationship between flood inundation and flooded area.

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Tran, V.N., Ivanov, V.Y., Huang, W. et al. Connectivity in urbanscapes can cause unintended flood impacts from stormwater systems. Nat Cities (2024). https://doi.org/10.1038/s44284-024-00116-7

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