Understanding the Impact of Reservoir Operations on Temperature Hydrodynamics at Shasta Lake through 2D and 3D Modeling
Abstract
Stress on California's salmon fisheries as a result of recent drought highlights a need for effective temperature management in the Sacramento River. Cool temperatures are required for Chinook salmon spawning and rearing. At Shasta Dam in northern California, managers use selective reservoir withdrawals to meet downstream temperature thresholds set for Chinook salmon populations. Shasta Dam is equipped with a temperature control device (TCD) that allows for water withdrawals at different reservoir depths. A two-dimensional CE-QUAL-W2 (W2) model of Shasta Reservoir has been used to understand the impacts of TCD operations on reservoir and discharge dynamics at Shasta. W2 models the entire reservoir based on hydrologic and meteorological inputs, and therefore can be used to simulate various hydroclimatic conditions, reservoir operations, and resulting reservoir conditions. A limitation of the W2 model is that it only captures reservoir conditions in two dimensions (length and depth), which may not represent local hydrodynamic effects of TCD operations that could affect simulation of discharge temperatures. Thus, a three-dimensional (3D) model of the TCD and the immediately adjacent upstream reservoir has been constructed using computational fluid dynamics (CFD) in ANSYS Fluent. This 3D model provides additional insight into the mixing effects of different TCD operations, and resulting reservoir outflow temperatures. The drought conditions of 2015 provide a valuable dataset for assessing the efficacy of modeling the temperature profile of Shasta Reservoir under very low inflow volumes, so the W2 and CFD models are compared for model performance in late 2015. To assist with this assessment, data from a distributed temperature sensing (DTS) deployment at Shasta Lake since August 2015 are used. This presentation describes model results from both W2 as well as the CFD model runs during late 2015, and discuss their efficacy for modeling drought conditions.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2016
- Bibcode:
- 2016AGUFM.H41B1328H
- Keywords:
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- 1805 Computational hydrology;
- HYDROLOGYDE: 1819 Geographic Information Systems (GIS);
- HYDROLOGYDE: 1916 Data and information discovery;
- INFORMATICSDE: 1920 Emerging informatics technologies;
- INFORMATICS