Date of Award:

5-2022

Document Type:

Dissertation

Degree Name:

Doctor of Philosophy (PhD)

Department:

Civil and Environmental Engineering

Committee Chair(s)

Bethany T. Neilson

Committee

Bethany T. Neilson

Committee

Charles B. Yackulic

Committee

Caleb A. Buahin

Committee

David G. Tarboton

Committee

John C. Schmidt

Abstract

River temperatures play a key role in determining the suitability of habitat for aquatic ecosystems. While thermal regimes are influenced by many factors, flow and temperature patterns in large rivers are often shaped by water development. As such, water management associated with large reservoirs and diversions have also altered aquatic ecosystems. As climate change introduces new climate and hydrologic patterns, the decisions water managers make to address changes in runoff may further impact aquatic ecosystems. This calls for robust modeling tools that can predict river and reservoir temperature responses to water management decisions over large regions. However, highly variable topography and data limitations that are inherent over large spatial scales complicate our understanding of river temperature controls. Further, differences among modeling frameworks need to be overcome in order to holistically understand ecosystem responses to water management decisions. This dissertation addresses these limitations by adapting mechanistic river temperature models to account for topographic shading and spatially varying weather information and describing methods for linking temperature responses to water management decisions. The Colorado River basin was used to evaluate these methods because it experiences significant flow regulation, remote river sections, and highly variable terrain. The findings here show that discharge and release temperatures from large reservoirs, particularly Lake Powell and Flaming Gorge, influence river temperatures over significant distances, while topographic shading increases the relative importance of heat fluxes, other than solar radiation, that require representative weather data for estimation. Spatially varying weather information from a climate reanalysis dataset, combined with elevation corrections, was tested in different modeling domains and found to significantly improve temperature predictions when compared to models using sparsely distributed ground-based weather stations. With the advances in modeling over topographically complex regions, water management models were linked to river temperature responses so that ecosystem indicators could be evaluated. Using an existing water management model for flow information and strategic resampling of weather and water temperature information, river temperatures were forecasted over more than 1000 km of river. The work presented here provides the foundational tools for evaluating climate and water management impacts on aquatic ecosystems in large managed basins.

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