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Developing dynamic adaptive policy pathways: a computer-assisted approach for developing adaptive strategies for a deeply uncertain world

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  • Jan Kwakkel
  • Marjolijn Haasnoot
  • Warren Walker

Abstract

Sustainable water management in a changing environment full of uncertainty is profoundly challenging. To deal with these uncertainties, dynamic adaptive policies that can be changed over time are suggested. This paper presents a model-driven approach supporting the development of promising adaptation pathways, and illustrates the approach using a hypothetical case. We use robust optimization over uncertainties related to climate change, land use, cause-effect relations, and policy efficacy, to identify the most promising pathways. For this purpose, we generate an ensemble of possible futures and evaluate candidate pathways over this ensemble using an Integrated Assessment Meta Model. We understand ‘most promising’ in terms of the robustness of the performance of the candidate pathways on multiple objectives, and use a multi-objective evolutionary algorithm to find the set of most promising pathways. This results in an adaptation map showing the set of most promising adaptation pathways and options for transferring from one pathway to another. Given the pathways and signposts, decision-makers can make an informed decision on a dynamic adaptive plan in a changing environment that is able to achieve their intended objectives despite the myriad of uncertainties. Copyright The Author(s) 2015

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  • Jan Kwakkel & Marjolijn Haasnoot & Warren Walker, 2015. "Developing dynamic adaptive policy pathways: a computer-assisted approach for developing adaptive strategies for a deeply uncertain world," Climatic Change, Springer, vol. 132(3), pages 373-386, October.
  • Handle: RePEc:spr:climat:v:132:y:2015:i:3:p:373-386
    DOI: 10.1007/s10584-014-1210-4
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    Cited by:

    1. Steinmann, Patrick & Auping, Willem L. & Kwakkel, Jan H., 2020. "Behavior-based scenario discovery using time series clustering," Technological Forecasting and Social Change, Elsevier, vol. 156(C).
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    3. Tiago Capela Lourenço & Ana Rovisco & Suraje Dessai & Richard Moss & Arthur Petersen, 2015. "Editorial introduction to the special issue on Uncertainty and Climate Change Adaptation," Climatic Change, Springer, vol. 132(3), pages 369-372, October.
    4. Moallemi, Enayat A. & Elsawah, Sondoss & Ryan, Michael J., 2020. "Strengthening ‘good’ modelling practices in robust decision support: A reporting guideline for combining multiple model-based methods," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 175(C), pages 3-24.
    5. Moallemi, Enayat A. & Elsawah, Sondoss & Ryan, Michael J., 2020. "Robust decision making and Epoch–Era analysis: A comparison of two robustness frameworks for decision-making under uncertainty," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    6. Tina Comes & Bartel Van de Walle & Luk Van Wassenhove, 2020. "The Coordination‐Information Bubble in Humanitarian Response: Theoretical Foundations and Empirical Investigations," Production and Operations Management, Production and Operations Management Society, vol. 29(11), pages 2484-2507, November.
    7. William Ascher, 2021. "Coping with intelligence deficits in poverty-alleviation policies in low-income countries," Policy Sciences, Springer;Society of Policy Sciences, vol. 54(2), pages 345-370, June.
    8. Mohanasundar Radhakrishnan & Hong Quan Nguyen & Berry Gersonius & Assela Pathirana & Ky Quang Vinh & Richard M. Ashley & Chris Zevenbergen, 2018. "Coping capacities for improving adaptation pathways for flood protection in Can Tho, Vietnam," Climatic Change, Springer, vol. 149(1), pages 29-41, July.
    9. Vizinho, André & Avelar, David & Fonseca, Ana Lúcia & Carvalho, Silvia & Sucena-Paiva, Leonor & Pinho, Pedro & Nunes, Alice & Branquinho, Cristina & Vasconcelos, Ana Cátia & Santos, Filipe Duarte & Ro, 2021. "Framing the application of Adaptation Pathways for agroforestry in Mediterranean drylands," Land Use Policy, Elsevier, vol. 104(C).
    10. Paredes-Vergara, Matías & Palma-Behnke, Rodrigo & Haas, Jannik, 2024. "Characterizing decision making under deep uncertainty for model-based energy transitions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).
    11. Julia Reis & Julie Shortridge, 2022. "Robust decision outcomes with induced correlations in climatic and economic parameters," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 27(1), pages 1-23, January.
    12. James Derbyshire, 2020. "Answers to questions on uncertainty in geography: Old lessons and new scenario tools," Environment and Planning A, , vol. 52(4), pages 710-727, June.
    13. Klerk, Wouter Jan & Kanning, Wim & Kok, Matthijs & Wolfert, Rogier, 2021. "Optimal planning of flood defence system reinforcements using a greedy search algorithm," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    14. Jayne F. Knott & Jennifer M. Jacobs & Jo E. Sias & Paul Kirshen & Eshan V. Dave, 2019. "A Framework for Introducing Climate-Change Adaptation in Pavement Management," Sustainability, MDPI, vol. 11(16), pages 1-23, August.
    15. Dana Cordell & Elsa Dominish & Mohamed Esham & Brent Jacobs & Madhuri Nanda, 2021. "Adapting food systems to the twin challenges of phosphorus and climate vulnerability: the case of Sri Lanka," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 13(2), pages 477-492, April.
    16. Tom Roach & Zoran Kapelan & Ralph Ledbetter, 2018. "A Resilience-Based Methodology for Improved Water Resources Adaptation Planning under Deep Uncertainty with Real World Application," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(6), pages 2013-2031, April.
    17. Christoffer Carstens & Karin Mossberg Sonnek & Riitta Räty & Per Wikman-Svahn & Annika Carlsson-Kanyama & Jonathan Metzger, 2019. "Insights from Testing a Modified Dynamic Adaptive Policy Pathways Approach for Spatial Planning at the Municipal Level," Sustainability, MDPI, vol. 11(2), pages 1-16, January.
    18. Robert L. Ceres & Chris E. Forest & Klaus Keller, 2017. "Understanding the detectability of potential changes to the 100-year peak storm surge," Climatic Change, Springer, vol. 145(1), pages 221-235, November.
    19. Bethany Robinson & Jonathan D. Herman, 2019. "A framework for testing dynamic classification of vulnerable scenarios in ensemble water supply projections," Climatic Change, Springer, vol. 152(3), pages 431-448, March.
    20. Kwakkel, J.H. & Cunningham, S.C., 2016. "Improving scenario discovery by bagging random boxes," Technological Forecasting and Social Change, Elsevier, vol. 111(C), pages 124-134.
    21. Anne van Bruggen & Igor Nikolic & Jan Kwakkel, 2019. "Modeling with Stakeholders for Transformative Change," Sustainability, MDPI, vol. 11(3), pages 1-21, February.
    22. Jan H. Kwakkel, 2019. "A generalized many‐objective optimization approach for scenario discovery," Futures & Foresight Science, John Wiley & Sons, vol. 1(2), June.

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