Date of Award

Spring 1-1-2012

Document Type

Thesis

Degree Name

Master of Science (MS)

First Advisor

Balaji Rajagopalan

Second Advisor

Edith A. Zagona

Third Advisor

Subhrendu Gangopadhyay

Abstract

Dworshak Reservoir in Idaho is on the snowmelt dominated Clearwater River and provides flood control and conservation for the Snake River and Columbia River basins. During dry years in which the spring inflow forecast is decreasing, problems have occurred with trapped storage and minimum outflow requirements. To mitigate these impacts, and to provide a spring freshet for fish, an modification to the flood control curve may be used, known as the shift policy. In years that end up being wetter than forecast, the resulting operation may cause the reservoir to violate environmental and flood control limits. An improved forecast for pre-season planning is needed to better predict which years the shift is appropriate.

A linked decision support system and statistical forecast is used to try to predict the decision variable of whether or not the shift policy should be implemented. The decision support system analyzes the difference in impacts of the shift policy compared with the default policy. From the output, a binary sequence of the preferred policy for each year is created and predicted by a logistic regression model, with climate and hydrologic variables as predictors. The operational model then uses this forecast to see the impacts of the forecast on the operational policy and the resulting risks.

For seasonal planning, the forecast for years in which the shift is allowed by any rule is shown to be more skillful than a baseline model in January, with a Brier Skill Score of 0.11. For particular reservoir constraints, the model performance varies, with less skill for those which are rarely violated by shifting, and significant skill for more frequent violations by a shift policy, such as environmental flow limits. Using the forecast to inform the fraction of the shift does not result in the shift achieving it's objectives as effectively, but does result in less violations. The model also has applications for long-term studies of the effectiveness of the shift policy and impacts of non-stationary climate variables on the shift policy.

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