Date of Award:

12-2025

Document Type:

Thesis

Degree Name:

Master of Science (MS)

Department:

Civil and Environmental Engineering

Committee Chair(s)

David G. Tarboton

Committee

David G. Tarboton

Committee

Pin Shuai

Committee

Sarah Null

Abstract

Accurate seasonal streamflow forecasts are essential for managing water resources in the western United States, where much of the water supply depends on snow accumulation and melt. Water managers, farmers, and communities rely on these forecasts to plan for water use, prepare for droughts, and protect the environment. However, traditional forecasting methods often do not fully use all the available information about how water is stored in the landscape, such as in snowpacks, soil moisture, and groundwater. This can limit the accuracy of predictions and make water management more difficult.

This study aimed to improve streamflow forecasts by explicitly including multiple hydrologic storage indicators, namely, snow water equivalent (SWE), January baseflow, and soil moisture, within forecasting models for watersheds in two important basins: the Upper Colorado River Basin and the Great Salt Lake Basin. January baseflow, the streamflow that occurs during winter when there are limited water inputs, has been suggested as an indicator of groundwater storage. By testing various combinations of these indicators, the research showed that including them improves forecast accuracy, especially in the mountainous headwater areas where natural hydrologic processes remain largely undisturbed. Among the indicators tested, soil moisture was consistently the best at incrementally improving current National Weather Service seasonal water supply forecasts, highlighting its crucial role in these regions. Soil moisture also proved to be a key predictor, often providing the largest gains in forecast skill when added by itself to the official Colorado Basin River Forecast Center Most Probable forecast. This highlights the important role of antecedent soil moisture conditions in determining how much rainfall and snowmelt actually reaches rivers and streams, especially during the spring runoff season.

This research is important because more reliable streamflow forecasts help water managers make better decisions about reservoir operations, irrigation, and drought planning. Communities can better prepare for water shortages or flooding, farmers can optimize irrigation, and environmental protections can be more effectively targeted. By providing a practical way to include multiple types of water storage information, this study offers a path toward improving water forecasts and supporting sustainable water management across the interior western United States, where every drop of water counts.

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