Date of Award

Spring 1-1-2011

Document Type

Thesis

Degree Name

Master of Science (MS)

First Advisor

Balaji Rajagopalan

Second Advisor

Edith Zagona

Third Advisor

Subhrendu Gangopadhyay

Abstract

The past decade has been one of unprecedented drought in the Upper Colorado River Basin (UCRB), having wide impacts on basin hydrology and management. The drought has raised many questions about the sustainability of the UCRB water supply and emphasized the need for accurate forecasts and simulations of streamflow. The UCRB is home to many of the largest reservoirs in the United States including Lake Powell. For large reservoirs such as these, the ability to forecasts on a seasonal to inter-annual time scale is particularly important for management.

The first chapter of this thesis develops a seasonal forecasting framework for generating ensembles of peak season flow at long lead times. The framework uses large scale climate predictors as well as snowpack and soil moisture conditions to produce ensemble forecasts of Lees Ferry natural flow. The natural flow forecasts are then disaggregated spatially and temporally to produce monthly forecasts at four key UCRB sites.

One question raised by the 2000-2010 drought is, how likely is it to occur again? Traditional time series models would estimate the risk of such a drought as very low. Along these lines a Hidden Markov (HM) time series model was developed that is able to capture a distinct regime switching behavior in the Lees Ferry natural flow record. The model suggests that the likelihood of a drought of the current magnitude is much more likely than suggested by traditional autoregressive methods. The HM model is also useful for ensemble forecasting. Here it is used to generate skillful inter-annual forecasts of UCRB flow.

The availability of skillful seasonal and inter-annual streamflow forecasts does not guarantee their usefulness in water supply forecasting. To evaluate this, flow sequences are used as input to the Midterm Operations Model (MTOM), a new operational water supply model for the Colorado River Basin. The MTOM was developed as part of this research in collaboration with the Bureau of Reclamation. Ensemble forecasts of reservoir operations are developed and compared along side the existing model for the region.

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