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Meeting Climate Change Challenges: Searching for More Adaptive and Innovative Decisions

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  • Daniel P. Loucks

    (Cornell University)

Abstract

In the last decades, research in the management sciences, the modeling and analysis of systems, and artificial intelligence (AI), have provided ways of extracting useful knowledge from data and how that knowledge can better inform decision making. Such models are designed and used to support decision makers and hence these methods as a group are often termed decision support systems. Interactive decision support systems that incorporate visualization to allow users, including decision makers to explore the impacts of possible decisions and assumptions are well known and widely used in the water resources and environmental systems communities, as they are in many other fields. They are now needed to address and analyze possible decisions that may help all of us adapt to, and mitigate the adverse impacts caused by, a changing climate. The literature is full of studies explaining how to develop and use such models for adaptive planning and decision making. Yet studies on how decision makers use the results of these analyses and to the extent they have helped decision makers formulate their decisions are scarce. What is clear, however, is that their use does not always guarantee that they were helpful in addressing a particular challenge or issue. The information these analytical tools provide is only part of the information decision makers consider when making their decisions. This paper considers what might be done to assist decision makers improve the decisions they may make in the post-analysis stages of decision-making processes, especially when they are faced with challenging (and often surprising) situations where there appears to be no satisfactory solution. Addressing climate change causes and impacts are among these challenges. Without modeling support, making and implementing decisions is typically left to each decision maker’s experience, biases, mindset, habits, and beliefs based on their evaluation of all the information available to them. With some additional aids to facilitate the creation of new ideas, i.e., to help individuals adapt and innovate, it just may be possible to convert (find acceptable solutions to) some issues or problems considered unsolvable to solvable ones. A case study involving renewable hydroelectric and solar energy development in the Mekong River Basin illustrates how these methods can help enable more adaptive and innovative planning and management decisions.

Suggested Citation

  • Daniel P. Loucks, 2023. "Meeting Climate Change Challenges: Searching for More Adaptive and Innovative Decisions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(6), pages 2235-2245, May.
  • Handle: RePEc:spr:waterr:v:37:y:2023:i:6:d:10.1007_s11269-022-03227-9
    DOI: 10.1007/s11269-022-03227-9
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    References listed on IDEAS

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    1. Moussa Larbani & Po Lung Yu, 2020. "Empowering Data Mining Sciences by Habitual Domains Theory, Part II: Reaching Wonderful Solutions," Annals of Data Science, Springer, vol. 7(4), pages 549-580, December.
    2. Moussa Larbani & Po Lung Yu, 2020. "Empowering Data Mining Sciences by Habitual Domains Theory, Part I: The Concept of Wonderful Solution," Annals of Data Science, Springer, vol. 7(3), pages 373-397, September.
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    1. Aurora Gullotta & Tagele Mossie Aschale & David J. Peres & Guido Sciuto & Antonino Cancelliere, 2023. "Modelling Stormwater Runoff Changes Induced by Ground-Mounted Photovoltaic Solar Parks: A Conceptualization in EPA-SWMM," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(11), pages 4507-4520, September.

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