Developing a Structured Decision-Making Model to Facilitate Adaptive Dam ManagementBy:
December 21, 2017 New!
Phillip W. Bettoli
Professor and Assistant Unit Leader
Colin P. Shea
Postdoctoral Research Fellow
Researchers at the Tennessee Cooperative Fishery Research Unit and Tennessee Tech are developing a structured decision-making model to guide adaptive dam management at the Tims Ford Dam on the Elk River in Tennessee. This model will help optimize dam operations to mitigate negative effects of cold reservoir water release on downstream native aquatic species and sport fish while maintaining human flood protection and hydropower generation opportunities. If successful, this pilot study will facilitate the creation of similar models for dams elsewhere in the state, and lay the foundation for incorporating climate information into future model updates to enhance overall management resilience.
The rivers and streams of Tennessee harbor a highly diverse population of freshwater mussels and aquatic species, as well as support a large sport fishing industry for species such as bass and non-native trout. However, many of Tennessee’s rivers are extensively dammed to provide hydropower generation, water supply, and flood protection for communities in this water-rich state. Dam-induced habitat fragmentation, as well as cold-water release from storage reservoirs above these dams, are threatening many native aquatic fauna that are adapted to warm water temperatures, leading to numerous imperiled and endangered species listings. In addition, cold-water releases are affecting economically important sport fishing species.
In an attempt to find a balance between hydropower, flood protection, and aquatic species needs, the U.S. Fish and Wildlife Service, Tennessee Valley Authority, and the Tennessee Wildlife Resources Agency approached the Tennessee Cooperative Fishery Research Unit for help. Using a combination of grant and state funding totaling close to $280,000, the Tennessee Cooperative Fishery Research Unit, in collaboration with Tennessee Tech, is developing, implementing, and optimizing a structured decision-making model for Tims Ford Dam on the Elk River in south-central Tennessee. This model is designed to serve as a management guide to improve dam operations to optimize conditions for downstream fish species such as the endangered Boulder Darter and expand their distribution while maintaining flood protection and hydropower opportunities.
To guide development of the structured decision-making model (SDMM), researchers first collected a variety of ecological and hydrological field data. Researchers from the Fisheries Unit and Tennessee Tech were able to obtain water flow and quality data from the Tennessee Valley Authority. However, gathering ecological data proved to be much more time consuming. To generate an accurate SDMM, researchers had to gather ecological information on focal species’ occupancy, life history, and current range. Limited monitoring data was previously available, so the research team had to generate and test different species detection techniques and survey protocols, and create species occupancy models. Although gathering this field data took a long time, it was a critical part of the process. The information and protocols generated from this pilot study can likely be applied to other areas, and will be used to monitor adaptive dam management impacts on Elk River fauna.
Researchers also gathered information related to current dam management. They talked with dam operators to identify hydropower needs, flood protection and flood period requirements, and to better understand current operating procedures. By identifying current management parameters, researchers were able to identify opportunities for altered flow management that still meet operational requirements.
Hydrological, ecological, and management data are being incorporated into a final structured decision-making model. This particular SDMM will take the form of a “Look Up” table. Given observed environmental conditions (i.e., season, month, day, weather), management needs (e.g., power release, flood protection), and the current occupancy status of aquatic species, the table provides specific dam operation instructions. For example, the table will give instructions on how much water to release during that day, and in what fashion (i.e., from the top, bottom, or middle of the dam, or through turbines, which may influence water temperatures and turbidity). Management directives will change daily and seasonally, essentially providing guidance for all potential scenarios on the river in a given day. Short-term modeling simulations indicate that adaptive dam management guided by the SDMM will benefit both ecological and human communities.
Project Outcomes and Conclusions
In early 2016, the Fisheries Unit was in the last stages of model finalization, with plans to present the model to state wildlife and TVA officials in the spring of 2016, along with different species detection and survey protocols. If accepted, the TVA and state wildlife agency will implement the SDMM and monitor downstream species to see if adaptive dam management, guided by the SDMM, helps improve species persistence, dispersal, and colonization. If successful, this project could lead to the creation of a structured decision-making model for many, most or all dams in Tennessee, which would not only benefit native and sport fishing species but help mitigate conflicts between various water users. However, developing individual SDMMs will likely require extensive ecological surveying and monitoring to provide the baseline ecological data needed to generate a robust, basin-specific SDMM.
In future refinements of this and other models, Fisheries Unit researchers hope to integrate climate change data (e.g., changing hydrologic flow regimes) to help reduce the vulnerability of native species and human communities to climatic events, such as floods and droughts. Ideally, the SDMM could outline specific dam-management protocols for drought years, 100- and 500-year flood events, and be adjusted to accommodate annual climate variability (e.g., wet/cool years vs. dry/warm years). To successfully incorporate this type of information into the SDMM, researchers believe they will need more available and accessible data related to climate trends and projections, particularly floods and droughts.
Reynier, W. (2017). Developing a Structured Decision-Making Model to Facilitate Adaptive Dam Management [Case study on a project by the USGS Tennessee Cooperative Fishery Research Unit]. Product of EcoAdapt's State of Adaptation Program. Retrieved from CAKE: http://www.cakex.org/case-studies/developing-structured-decision-making-... (Last updated December 2017)