Date of Award

Spring 1-1-2014

Document Type

Thesis

Degree Name

Master of Science (MS)

First Advisor

Edith Zagona

Second Advisor

Balaji Rajagopalan

Third Advisor

Douglas Kenney

Abstract

Previous approaches to water resources planning under inter-annual climate variability combining skillful seasonal flow forecasts with climatology for subsequent years are not skillful for medium term (i.e. decadal scale) projections as decision makers are not able to plan adequately to avoid vulnerabilities. This research addresses this need by integrating skillful decadal scale streamflow projections into the robust decision making framework and making the probability distribution of this projection available to the decision making logic. The range of possible future hydrologic scenarios can be defined using a variety of nonparametric methods. Once defined, an ensemble projection of decadal flow scenarios is generated from a wavelet-based spectral K-nearest-neighbor resampling approach using historical and paleo-reconstructed data. This method has been shown to generate skillful medium term projections with a rich variety of natural variability. The current state of the system in combination with the probability distribution of the projected flow ensembles enables the selection of appropriate decision options. This process is repeated for each year of the planning horizon--resulting in system outcomes that can be evaluated on their performance and resiliency.

The research utilizes the RiverSMART suite of software modeling and analysis tools developed under the Bureau of Reclamation's WaterSMART initiative and built around the RiverWare modeling environment. A case study is developed for the Gunnison and Upper Colorado River Basins demonstrates the utility of the decision-making framework.

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