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沿岸管理モデルは潮の満ち引きに対して長期戦を演じる(Coastal management model plays the long game against the rising tides)

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2025-04-17 ペンシルベニア州立大学(PennState)

ペンシルベニア州立大学とピッツバーグ大学の研究チームは、気候変動による海面上昇に対応するため、将来の不確実性を考慮した動的意思決定モデルを開発した。このモデルは「マルコフ決定過程」に基づき、気象データを随時更新しながら最適な防災インフラ整備のタイミングと規模を提案する。従来型の静的コスト便益分析に比べて、損害、建設コスト、環境負荷を大幅に削減できることを実証。コンクリート防波堤に加え、カキ礁や塩性湿地などの自然ベースの対策も含む。今後は政府や保険制度との連携も視野に入れて拡張を計画している。

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気候変動下における沿岸インフラの最適なライフサイクル適応 Optimal life-cycle adaptation of coastal infrastructure under climate change

Ashmita Bhattacharya,Konstantinos G. Papakonstantinou,Gordon P. Warn,Lauren McPhillips,Melissa M. Bilec,Chris E. Forest,Rahaf Hasan & Digant Chavda
Nature Communications  Published:27 January 2025
DOI:https://doi.org/10.1038/s41467-024-55679-9

沿岸管理モデルは潮の満ち引きに対して長期戦を演じる(Coastal management model plays the long game against the rising tides)

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.

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