Assessment of Dissolved Oxygen Mitigation at Hydropower Dams Using an Integrated Hydrodynamic/Water Quality/Fish Growth Model

摘要

Dissolved oxygen (DO) in rivers is a common environmental problem associated with hydropower projects. Approximately 40% of all FERC-licensed projects have requirements to monitor and/or mitigate downstream DO conditions. Most forms of mitigation for increasing DO in dam tailwaters are fairly expensive. One area of research of the Department of Energy's Hydropower Program is the development of advanced turbines that improve downstream water quality and have other environmental benefits. There is great interest in being able to predict the benefits of these modifications prior to committing to the cost of new equipment. In the case of turbine replacement or modification, there is a need for methods that allow us to accurately extrapolate the benefits derived from one or two turbines with better design to the replacement or modification of all turbines at a site. The main objective of our study was to demonstrate a modeling approach that integrates the effects of flow and water quality dynamics with fish bioenergetics to predict DO mitigation effectiveness over long river segments downstream of hydropower dams. We were particularly interested in demonstrating the incremental value of including a fish growth model as a measure of biological response. The models applied are a suite of tools (RMS4 modeling system) originally developed by the Tennessee Valley Authority for simulating hydrodynamics (ADYN model), water quality (RQUAL model), and fish growth (FISH model) as influenced by DO, temperature, and available food base. We parameterized a model for a 26-mile reach of the Caney Fork River (Tennessee) below Center Hill Dam to assess how improvements in DO at the dam discharge would affect water quality and fish growth throughout the river. We simulated different types of mitigation (i.e., at the turbine and in the reservoir forebay) and different levels of improvement. The model application successfully demonstrates how a modeling approach like this one can be used to assess whether a prescribed mitigation is likely to meet intended objectives from both a water quality and a biological resource perspective. These techniques can be used to assess the tradeoffs between hydropower operations, power generation, and environmental quality.