Senior Hydrologic Scientist
Lynker Technologies, LLC has an exciting opportunity for a Senior Hydrologic Scientist located in Tuscaloosa, AL.
The NOAA National Water Model (NWM) provides operational analyses and assessments of the full range of water cycle components across the United States, with an emphasis on streamflow. Accurate simulation of these elements entails proper representation of all relevant physical processes and anthropogenic influences that impact the flow of water. While natural factors work in a complex and interwoven fashion to affect streamflow, reservoirs, which are operated in ways that are governed by a mixture of natural forcing and water law, add yet another layer of complexity. Reservoirs can be operated for flood control, water supply, energy production, and water storage purposes, with each purpose having unique governing requirements. Over 1,000 reservoirs are represented in the current version of the NWM. However, the current representation is rudimentary, with each reservoir modeled in a passive level-pool fashion. In this approach, the spillway length and height are prescribed in the model, which then governs discharge in the model. While this method provides a solid foundation for representation of reservoir operations within the model, improvements need to be made in order to more accurately represent how reservoirs are governed in light of competing purposes, especially in critical water supply areas.
While the current version of the NWM includes basic representation of reservoirs, the ability of the NWM to simulate the behavior of reservoirs with and without existing operating rules needs to be improved in order to increase the accuracy of streamflow analyses and predictions. Enhancements to representation of reservoirs in the NWM will need to take into account the wide variety of factors that influence operations over the course of each water year. For reservoirs that feature an existing set of operating rules, this may simply involve integrating those rules into the NWM via a new module. However, for the majority of reservoirs where operating rules do not exist, a different approach will be needed. One of the promising techniques for doing this is through machine learning. This technique has the potential to intelligently integrate a wide variety of factors, from water law to antecedent/forecast conditions, to past behavior, and form a new set of rules by which to model reservoir operations within the NWM.
This position will work with a ML/AI expert to design, construct, integrate and test new NWM modules necessary to achieve this enhanced capability in particular it will replicate the behavior of reservoir managers in order to accurately simulate reservoir releases within the NWM framework. By the completion of the task order it is expected that an enhanced instance of the NWM will successfully run in a retrospective non-operational mode with the new module governing flow at two reservoirs, one with existing operating rules and one without existing rules, and the existing NWM scheme governing flow at the remaining reservoirs in the development domain. The position will develop documentation and code to accomplish the reservoir modeling improvements outlined above. They will be responsible for integrating the code into the current version of the NWM.
Closing Date: 30th September 2017
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