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Optimal life-cycle adaptation of coastal infrastructure under climate change

Author

Listed:
  • Ashmita Bhattacharya

    (The Pennsylvania State University)

  • Konstantinos G. Papakonstantinou

    (The Pennsylvania State University)

  • Gordon P. Warn

    (The Pennsylvania State University)

  • Lauren McPhillips

    (The Pennsylvania State University)

  • Melissa M. Bilec

    (University of Pittsburgh)

  • Chris E. Forest

    (The Pennsylvania State University)

  • Rahaf Hasan

    (University of Pittsburgh)

  • Digant Chavda

    (The Pennsylvania State University)

Abstract

Climate change-related risk mitigation is typically addressed using cost-benefit analysis that evaluates mitigation strategies against a wide range of simulated scenarios and identifies a static policy to be implemented, without considering future observations. Due to the substantial uncertainties inherent in climate projections, this identified policy will likely be sub-optimal with respect to the actual climate trajectory that evolves in time. In this work, we thus formulate climate risk management as a dynamic decision-making problem based on Markov Decision Processes (MDPs) and Partially Observable MDPs (POMDPs), taking real-time data into account for evaluating the evolving conditions and related model uncertainties, in order to select the best possible life-cycle actions in time, with global optimality guarantees for the formulated optimization problem. The framework is developed for coastal adaptation applications, considering a wide variety of possible action types, including various forms of nature-based infrastructure. Related environmental impacts of carbon emissions and uptake are also incorporated, and social cost of carbon implications are discussed, together with several future directions and supported features.

Suggested Citation

  • Ashmita Bhattacharya & Konstantinos G. Papakonstantinou & Gordon P. Warn & Lauren McPhillips & Melissa M. Bilec & Chris E. Forest & Rahaf Hasan & Digant Chavda, 2025. "Optimal life-cycle adaptation of coastal infrastructure under climate change," Nature Communications, Nature, vol. 16(1), pages 1-18, December.
  • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-024-55679-9
    DOI: 10.1038/s41467-024-55679-9
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    References listed on IDEAS

    as
    1. Klaus Desmet & Robert E. Kopp & Scott A. Kulp & Dávid Krisztián Nagy & Michael Oppenheimer & Esteban Rossi-Hansberg & Benjamin H. Strauss, 2021. "Evaluating the Economic Cost of Coastal Flooding," American Economic Journal: Macroeconomics, American Economic Association, vol. 13(2), pages 444-486, April.
    2. Robert Lempert, 2013. "Scenarios that illuminate vulnerabilities and robust responses," Climatic Change, Springer, vol. 117(4), pages 627-646, April.
    3. Anita Wreford & Ruth Dittrich & Thomas D. van der Pol, 2020. "The added value of real options analysis for climate change adaptation," Wiley Interdisciplinary Reviews: Climate Change, John Wiley & Sons, vol. 11(3), May.
    4. Andriotis, C.P. & Papakonstantinou, K.G., 2019. "Managing engineering systems with large state and action spaces through deep reinforcement learning," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    5. Yuki Miura & Huda Qureshi & Chanyang Ryoo & Philip C. Dinenis & Jiao Li & Kyle T. Mandli & George Deodatis & Daniel Bienstock & Heather Lazrus & Rebecca Morss, 2021. "A methodological framework for determining an optimal coastal protection strategy against storm surges and sea level rise," 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. 107(2), pages 1821-1843, June.
    6. Papakonstantinou, K.G. & Shinozuka, M., 2014. "Planning structural inspection and maintenance policies via dynamic programming and Markov processes. Part II: POMDP implementation," Reliability Engineering and System Safety, Elsevier, vol. 130(C), pages 214-224.
    7. Andriotis, C.P. & Papakonstantinou, K.G., 2021. "Deep reinforcement learning driven inspection and maintenance planning under incomplete information and constraints," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
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