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Optimal Selection of Short- and Long-Term Mitigation Strategies for Buildings within Communities under Flooding Hazard

Author

Listed:
  • Himadri Sen Gupta

    (School of Industrial and Systems Engineering, University of Oklahoma, Norman, OK 73019, USA)

  • Omar M. Nofal

    (Department of Civil and Environmental Engineering, Colorado State University, Fort Collins, CO 80523, USA)

  • Andrés D. González

    (School of Industrial and Systems Engineering, University of Oklahoma, Norman, OK 73019, USA)

  • Charles D. Nicholson

    (School of Industrial and Systems Engineering, University of Oklahoma, Norman, OK 73019, USA)

  • John W. van de Lindt

    (Department of Civil and Environmental Engineering, Colorado State University, Fort Collins, CO 80523, USA)

Abstract

Every year, floods cause substantial economic losses worldwide with devastating impacts on buildings and physical infrastructures throughout communities. Techniques are available to mitigate flood damage and subsequent losses, but the ability to weigh such strategies with respect to their benefits from a community resilience perspective is limited in the literature. Investing in flood mitigation is critical for communities to protect the physical and socioeconomic systems that depend on them. While there are multiple mitigation options to implement at the building level, this paper focuses on determining the optimal flood mitigation strategy for buildings to minimize flood losses within a community. In this research, a mixed integer linear programming model is proposed for studying the effects and trade-offs associated with pre-event short-term and long-term mitigation strategies to minimize the expected economic losses associated with floods. The capabilities of the proposed model are illustrated for Lumberton, North Carolina (NC), a small, socially diverse inland community on the Lumber River. The mathematically optimal building-level flood mitigation plan is provided based on the available budget, which can significantly minimize the total expected direct economic loss of the community. The results reveal important correlations among investment quantity, building-level short- and long-term mitigation measures, flood depths of various locations, and buildings’ structure. Additionally, this study shows the trade-offs between short- and long-term mitigation measures based on available budget by providing decision support to building owners regarding mitigation measures for their buildings.

Suggested Citation

  • Himadri Sen Gupta & Omar M. Nofal & Andrés D. González & Charles D. Nicholson & John W. van de Lindt, 2022. "Optimal Selection of Short- and Long-Term Mitigation Strategies for Buildings within Communities under Flooding Hazard," Sustainability, MDPI, vol. 14(16), pages 1-20, August.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:16:p:9812-:d:883859
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    References listed on IDEAS

    as
    1. Nozhati, Saeed & Sarkale, Yugandhar & Ellingwood, Bruce & K.P. Chong, Edwin & Mahmoud, Hussam, 2019. "Near-optimal planning using approximate dynamic programming to enhance post-hazard community resilience management," Reliability Engineering and System Safety, Elsevier, vol. 181(C), pages 116-126.
    2. Mrinal Kanti Sen & Subhrajit Dutta & Golam Kabir, 2021. "Flood Resilience of Housing Infrastructure Modeling and Quantification Using a Bayesian Belief Network," Sustainability, MDPI, vol. 13(3), pages 1-24, January.
    3. Tsai-Yun Liao & Ta-Yin Hu & Yi-No Ko, 2018. "A resilience optimization model for transportation networks under disasters," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 93(1), pages 469-489, August.
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    5. Morteza T. Marvi, 2020. "A review of flood damage analysis for a building structure and contents," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 102(3), pages 967-995, July.
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