Date of Award

Spring 1-1-2013

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

First Advisor

Balaji Rajagopalan

Second Advisor

Edith Zagona

Third Advisor

Harihar Rajaram

Fourth Advisor

Subhrendu Gangopadhyay

Fifth Advisor

Barry Eakins

Abstract

Increasing demands on the limited and variable water supply across the West can result in insufficient streamflow to sustain healthy fish habitat. In addition, construction of dams and diversions along rivers for the purpose of storing and distributing the limited supply of water can further deteriorate natural flow regimes and, often, obstruct important migratory pathways for cold water fish reproduction and development. The thermal impacts on the ecology of river ecosystems have been well documented, yet there is no comprehensive modeling framework in place for skillfully modeling climate-related impacts. In regulated systems, such as the Sacramento River system, these impacts are an interaction of volume and temperature of water release from the reservoir and the subsequent exchange with the environment downstream.

We develop an integrated framework for modeling and mitigating water temperature impacts and demonstrate it on the Sacramento River system. The approach has four broad components that can be coupled to produce decision tools towards efficient management of water resources for stream temperature mitigation: (i) a suite of statistical models for modeling stream temperature attributes using hydrology and climate variables of critical importance to fish habitat; (ii) a reservoir thermal model for modeling the thermal structure and, consequently, the water release temperature, (iii) a stochastic weather generator to simulate weather sequences consistent with long-range (e.g., seasonal) outlooks; and, (iv) a set of decision rules (i.e., rubric) for reservoir water releases in response to outputs from the above components.

The statistical stream temperature models and stochastic weather generators are coupled to the reservoir thermal model and validated for their ability to reproduce observed stream temperature variability along with characterizing the uncertainty at a compliance point downstream. We develop and validate a Decision Support Tool (DST) developed by coupling the stream temperature forecast model with the stochastic weather generator to the decision rubric. The DST incorporates forecast uncertainties and reservoir operating options to help mitigate stream temperature impacts for fish habitat, while efficiently using the reservoir water supply and cold pool storage. The use of these coupled tools in simulating impacts of future climate on stream temperature variability is also demonstrated.

Share

COinS