Evaluating the Cost Effectiveness of Data Collection Techniques and Relative Improvements in Modeling Reservoir Production
Project ID: 7622
Principal Investigator: Allyn Meuleman
Research Topic: Ecosystem Needs
Priority Area Assignments: 2011 (Place Holder - Do not use)
Funded Fiscal Years: 2009, 2010 and 2011
This Science and Technology (S&T) Program research project will evaluate the relative improvement in reservoir production results based on the types of data incorporated into the hydrodynamic model. This effort will address the following question:
* How much better will model resolution and reservoir production results be characterized if taxonomic analysis is performed on the primary and secondary production components of the food base?
Typically, the more data; the better the results. This research project will focus on relative model improvements if taxonomic data, comprising the reservoir food base, are included versus using standard measured water quality constituents, obtained and processed at a lesser cost to parameterize the reservoir processes. Ultimately, this model output, under varying operational scenarios, can then be linked quantitatively to fish production using a food web model, incorporating stable isotopes to trace energy transfer from primary production in a reservoir to fish and intermediary consumers in the food web.
Need and Benefit
Development of innovative water management tools is paramount to Reclamation's ability to reliably deliver water and effectively generate power. Another component of Reclamation's mission is to understand and evaluate the impacts of its project operations and resulting implications to the surrounding ecosystem, particularly as it relates to threatened or endangered species.
Water quality and ecosystem models of varying complexity have become increasingly common in the management and study of water resources. These tools provide scientists and resource managers a means to explore ecosystem responses to actions that are a result of operational or outside system changes. In particular, mechanistic models (which explicitly represent physical, chemical, and/or biological processes) are useful for inferring effects outside of the domain within which those initial data were collected, as direct and indirect effects of reservoir operations can affect fish in complex ways. As a result, these models have become complex both in terms of data needs and system representation. The questions remain:
* To what extent does the benefit of bettering the calibrated accuracy of the model and predictive capability to represent the system response justify the additional data collection and processing costs?
* As budgets become more constrained, what are the appropriate level of data needs and subsequent system representation to quantify and describe project impacts?
It is anticipated that the results of this analysis could help inform decisions about sampling and study development costs at other Reclamation systems.
A specific test case for this research project will be Deadwood Reservoir. The U.S. Fish and Wildlife Service (USFWS) issued a Biological Opinion (BiOp) which outlines Terms and Conditions to implement. Specifically, this process will address the question of bull trout production potential in the system and its linkage to ecosystem management. The test case will use the following model and instrumentation. The ELCOM-CAEDYM model is a fully three-dimensional (3D) hydrodynamic model, capable of describing the physical and biological aspects of ecosystem responses and simulating spatial and temporal water velocity, temperature, and salinity in aquatic systems, including algorithms detailing biological processes. A Lake Diagnostic System is used to collect water column temperature and dissolved oxygen as well as meteorological data for the reservoir model. Bi-weekly reservoir profiles collect water column data including T, DO, pH, NTU, conductivity. Water samples are analyzed for NO(v2)/NO(v3), NH3, TKN, Ortho-P, TP, TOC, DOC. Chlorophyll-a and phtoplankton biomass are also collected.
Typically, a single phytoplankton group is configured in the model so that it represents the entire primary production assemblage. The model is calibrated such that seasonal succession is representative of measured biomass and water quality constituents by this simplified model construct. However, each major group of phytoplankton has its own unique characteristic of energy use and zooplankton are discriminating in their food selection. The ELCOM-CAEDYM model is capable of including up to seven phytoplankton groups and five zooplankton groups. Therefore, with the addition of taxonomic work to differentiate these groups, the biotic community can be appropriately parameterized and more precisely simulated by the model. It is anticipated that improvements in the modeled reservoir conditions will result in improved predictions of bull trout production when linked using a food web energy transfer model. This research will improve the modeling of the Deadwood system and provide a cost comparison of those improvements and sensitivities to these types of additional data relative to model output differences. This information will make informed decisions about modeling and sampling protocol for other Reclamation projects
Contact the Principal Investigator for information about these documents.
This information was last updated on April 21, 2014
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