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Decision-centric adaptation appraisal for water management across Colorado's Continental Divide
journal contributionposted on 2015-10-14, 11:24 authored by David N. Yates, Kathleen A. Miller, Robert WilbyRobert Wilby, Laurna Kaatz
A multi-step decision support process was developed and applied to the physically and legally complex case of water diversions from the Upper Colorado River across the Continental Divide to serve cities and farms along Colorado's Front Range. We illustrate our approach by simulating the performance of an existing drought-response measure, the Shoshone Call Relaxation Agreement (SCRA) [the adaptation measure], using the Water Evaluation and Planning (WEAP) tool [the hydrologic cycle and water systems model]; and the Statistical DownScaling Model (SDSM-DC) [the stochastic climate scenario generator]. Scenarios relevant to the decision community were analyzed and results indicate that this drought management measure would provide only a small storage benefit in offsetting the impacts of a shift to a warmer and drier future climate coupled with related environmental changes. The analysis demonstrates the importance of engaging water managers in the development of credible and computationally efficient decision support tools that accurately capture the physical, legal and contractual dimensions of their climate risk management problems.
The research was supported by the Weather and Climate Assessment Program and the Climate Science Applications Program of the National Center for Atmospheric Research (NCAR). NCAR is a supported by the National Science Foundation.
- Social Sciences
- Geography and Environment
Published inClimate Risk Management
CitationYATES, D.N. ... et al, 2015. Decision-centric adaptation appraisal for water management across Colorado's Continental Divide. Climate Risk Management, 10, pp.35-50.
Publisher© Elsevier B.V.
- VoR (Version of Record)
Publisher statementThis work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/
NotesThis article was published by Elsevier as an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).