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Embedding co-production and addressing uncertainty in watershed modeling decision-support tools: Successes and challenges
Citation:
Barnhart, B., H. Golden, J. Kasprzyk, J. Pauer, C. Jones, K. Sawicz, N. Hoghooghi, M. Simon, Bob Mckane, P. Mayer, A. Piscopo, D. Ficklin, J. Halama, P. Pettus, AND B. Rashleigh. Embedding co-production and addressing uncertainty in watershed modeling decision-support tools: Successes and challenges. ENVIRONMENTAL MODELLING & SOFTWARE. Elsevier Science, New York, NY, 109:368-379, (2018). https://doi.org/10.1016/j.envsoft.2018.08.025
Impact/Purpose:
This journal article provides a roadmap for producing effective decision-support tools that utilize mechanistic watershed models. We emphasize the importance of co-production—that is, the co-development of methods, tools, and results through close interactions between technical experts and stakeholders—as well as inclusion of uncertainty. The review uses literature-based case study examples to demonstrate each step of the roadmap and highlight successes and challenges associated with current and past decision-support tools. This work will be submitted to Environmental Modelling & Software and will be generally applicable to technical experts and stakeholders that intend to produce or utilize watershed model decision-support tools.
Description:
Decision-support tools (DSTs) are often produced from collaborations between technical experts and stakeholders to address environmental problems and inform decision making. Studies in the past two decades have provided key insights on the use of DSTs and the importance of bidirectional information flows among technical experts and stakeholders – a process that is variously referred to as co-production, participatory modeling, structured decision making, or simply stakeholder participation. Many of these studies have elicited foundational insights for the broad field of water resources management; however, questions remain on approaches for balancing co-production with uncertainty specifically for watershed modeling decision support tools. In this paper, we outline a simple conceptual model that focuses on the DST development process. Then, using watershed modeling case studies found in the literature, we discuss successful outcomes and challenges associated with embedding various forms of co-production into each stage of the conceptual model. We also emphasize the “3 Cs” (i.e., characterization, calculation, communication) of uncertainty and provide evidence-based suggestions for their incorporation in the watershed modeling DST development process. We conclude by presenting a list of best practices derived from current literature for achieving effective and robust watershed modeling decision-support tools.
URLs/Downloads:
DOI: Embedding co-production and addressing uncertainty in watershed modeling decision-support tools: Successes and challenges