USGS ScienceSearch

USGS · 1015133

Simulated limnological effects of the Shasta Lake temperature control device

Abstract

We estimated the effects of a temperature control device (TCD) on a suite of thermodynamic and limnological attributes for a large storage reservoir, Shasta Lake, in northern California. Shasta Dam was constructed in 1945 with a fixed-elevation penstock. The TCD was installed in 1997 to improve downstream temperatures for endangered salmonids by releasing epilimnetic waters in the winter/spring and hypolimnetic waters in the summer/fall. We calibrated a two-dimensional hydrodynamic reservoir water quality model, CE-QUAL-W2, and applied a structured design-of-experiment simulation procedure to predict the principal limnological effects of the TCD under a variety of environmental scenarios. Calibration goodness-of-fit ranged from good to poor depending on the constituent simulated, with an R 2 of 0.9 for water temperature but 0.3 for phytoplankton. Although the chemical and thermal characteristics of the discharge changed markedly, the reservoir's characteristics remained relatively unchanged. Simulations showed the TCD causing an earlier onset and shorter duration of summer stratification, but no dramatic affect on Shasta's nutrient composition. Peak in-reservoir phytoplankton production may begin earlier and be stronger in the fall with the TCD, while outfall phytoplankton concentrations may be much greater in the spring. Many model predictions differed from our a priori expectations that had been shaped by an intensive, but limited-duration, data collection effort. Hydrologic and meteorological variables, most notably reservoir carryover storage at the beginning of the calendar year, influenced model predictions much more strongly than the TCD. Model results indicate that greater control over reservoir limnology and release quality may be gained by carefully managing reservoir volume through the year than with the TCD alone.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

J. Bartholow, R.B. Hanna, L. Saito, D. Lieberman, M. Horn. 2001. Simulated limnological effects of the Shasta Lake temperature control device. https://doi.org/10.1007/s0026702324

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

Trust-building as a keystone activity in beaver-related restoration practice

North American beavers ( Castor canadensis ) are increasingly being used to achieve restoration goals, prompting practitioners to engage with private landowners in efforts to promote beaver coexistence. Through 23 semi-structured interviews with restoration practitioners in Oregon, USA, we explored how practitioners from government agencies, non-governmental organizations (NGOs), service organizations, and private businesses communicate with private landowners about nonlethal beaver management and habitat creation. Using abductive analysis, we identified trust-building as an essential element of restoration practice. Practitioners described 60 tactics for building trust, which we organized using the Shared Foundations model of trust and distrust and the adaptive management cycle to bridge theory with field-based experience. Practitioners also reported navigating tensions between tactics and adapting their approaches to individual landowners and contexts. We argue that trust-building is a craft that can be mastered, propose a potential progression from novice to master trust-builder, and highlight the need for greater attention to trust, relationships, and trust repair in environmental management. Our findings offer a theoretically grounded yet practitioner-informed framework for understanding and improving trust-building efforts in restoration practice.

Oregon

Restoring the Florida Everglades: Insights on integrating sea level rise into decision-support tools

Although coastal ecosystems are impacted by climate change and sea-level rise, many ecological and hydrological models do not yet incorporate sea-level rise projections in their modeling outputs. Therefore, this research examined the various challenges that may prevent sea-level rise from being effectively incorporated in modeling and decision-support tools. We conducted semi-structured interviews with twenty-six professionals involved in Florida’s Everglades restoration. We applied the Diffusions of Innovations Theory to better understand factors that can impact practitioners’ adoption of newly designed decision-support tools that examine sea-level rise in the freshwater Everglades. The Diffusions of Innovations Theory provided insights into practitioners’ perceptions of these tools. We found that these practitioners have a strong interest in using dynamic decision-support tools to plan for sea-level rise impacts on Everglades restoration, particularly when they receive information at appropriate geographic and temporal scales and are given hands-on tools and training. However, challenges that prevent developing these tools include outdated data, limited organizational capacity and funding, limited use of long-term indicators, uncertainty about climate change impacts on local ecosystems, and lack of integration between hydrological and ecological models. Our research also highlights that greater availability of different types of tools can help to meet the needs of the scientific and non-scientific audiences involved in Everglades restoration.

Florida

Causal networks to inform decisions for ecological restoration

The release of contaminants into the environment can occur from anthropogenic activities, such as oil extraction and transportation, mining, and industrial processes. Remediation associated with reducing contaminant concentrations, and restoration that improves animals and supporting habitat, are often needed to restore ecosystems to their pre-release, baseline condition. We demonstrated the application of Bayesian Decision Networks (BDNs) with two Natural Resource Damage Assessment and Restoration (NRDAR) case studies. We use a stylized case study of riparian restoration following the remediation of a mine-impacted site to evaluate proposed restoration actions aimed at restoring Song Sparrow ( Melospiza melodia ) populations to baseline conditions. We then use a settled NRDAR case with implemented restoration in the Upper Arkansas River (UAR, Colorado, USA) to demonstrate the application of BDNs to evaluate and forecast restoration effectiveness for Brown Trout ( Salmo trutta ) (i.e., restoration effectiveness assessment). The riparian restoration model showed differences in the effects of restoration actions on Song Sparrow populations, with the time to reach baseline generally reduced with increased restoration costs, indicating trade-offs between costs and expected recovery. The UAR model showed recovery of Brown Trout populations (i.e., uplift) in response to improved instream habitat restoration, along with forecasted improvements. While the BDNs we developed were specific to two case studies, the structure is adaptable to a diversity of sites, resources, and actions. We suggest that causal network modeling can provide restoration practitioners with a decision advisory tool useful for a wide range of projects.

Environmental Management