Master of Science (MS)
Water Resource Management
First Committee Member
Number of Pages
Water managers at the U.S. Department of Interior, Bureau of Reclamation as well as other federal and local agencies use a monthly modeling tool called the 24-Month Study as the numerical basis of many decisions along the Lower Colorado River. It is a deterministic model and currently does not provide information about the uncertainty associated with forecasted outputs. As water resource management becomes increasingly based on technical models, managers realize the importance of the ability to understand and quantify uncertainty. This thesis contributes to efforts in this arena by accomplishing the following objectives: (1) identification of the various sources of uncertainty in predicting future states of the Lower Colorado River system; (2) characterization of the underlying structure of uncertainty in the forecast errors for key model inputs; (3) quantification of output uncertainty in the model using Monte Carlo simulations; and (4) assessment of the potential usefulness of uncertainty information to managers and other decision-makers using a case study. A multivariate Markov model with seasonality was used to characterize the structure of the input forecast uncertainty and preserve the lag-1 serial correlations and cross correlations between input variables. The Latin hypercube sampling technique was used to generate stochastic error terms, and 625 sets of model inputs were produced to import into the 24-Month Study for Monte Carlo simulation. The potential usefulness of this methodology is illustrated with an application to hydropower management, for which the quantification of forecast uncertainty associated with Hoover Dam energy forecasts is of prime interest. Having information about uncertainty influences how resource management questions are approached and how problems are resolved by providing decision-makers with a realistic range of alternatives to consider.
Analysis; Colorado; Lower; Mid; Model; Operational; River; Term; Uncertainty; Bureau of Reclamation
University of Nevada, Las Vegas
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Tighi, Shana Goffman, "Uncertainty analysis: Mid-term operational model for the Lower Colorado River" (2006). UNLV Retrospective Theses & Dissertations. 1992.