Models, Assumptions, and Stakeholders: Planning for Water Supply Variability in the Colorado River Basin1


  • Dustin Garrick,

    1. Respectively, PhD Candidate, Geography and Regional Development, University of Arizona, Harvill #2, Tucson, Arizona 85721
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  • Katharine Jacobs,

    1. Executive Director, Arizona Water Institute, Marshall Building, 5th Floor, 845 N Park Ave, Tucson, Arizona 85721
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  • Gregg Garfin

    1. Program Manager, Climate Assessment for the Southwest, Institute for the Study of Planet Earth, University of Arizona, 715 N. Park Ave., 2nd Fl., Tucson, Arizona 85721-0156
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  • 1

    Paper No. J06041 of the Journal of the American Water Resources Association (JAWRA). Discussions are open until August 1, 2008.



Abstract:  Declining reservoir storage has raised the specter of the first water shortage on the Lower Colorado River since the completion of Glen Canyon and Hoover Dams. This focusing event spurred modeling efforts to frame alternatives for managing the reservoir system during prolonged droughts. This paper addresses the management challenges that arise when using modeling tools to manage water scarcity under variable hydroclimatology, shifting use patterns, and institutional complexity. Assumptions specified in modeling simulations are an integral feature of public processes. The policymaking and management implications of assumptions are examined by analyzing four interacting sources of physical and institutional uncertainty: inflow (runoff), depletion (water use), operating rules, and initial reservoir conditions. A review of planning documents and model reports generated during two recent processes to plan for surplus and shortage in the Colorado River demonstrates that modeling tools become useful to stakeholders by clarifying the impacts of modeling assumptions at several temporal and spatial scales. A high reservoir storage-to-runoff ratio elevates the importance of assumptions regarding initial reservoir conditions over the three-year outlook used to assess the likelihood of reaching surplus and shortage triggers. An ensemble of initial condition predictions can provide more robust initial conditions estimates. This paper concludes that water managers require model outputs that encompass a full range of future potential outcomes, including best and worst cases. Further research into methods of representing and communicating about hydrologic and institutional uncertainty in model outputs will help water managers and other stakeholders to assess tradeoffs when planning for water supply variability.