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- The Implementation of Flow-Temperature Artificial Neural Network Regression into Operations Planning Models
The Implementation of Flow-Temperature Artificial Neural Network Regression into Operations Planning Models
Project ID: 1859
Principal Investigator: James Shannon
Research Topic: Water Quality
Funded Fiscal Years:
2018 and
2019
Keywords: None
Research Question
Can an Artificial Neural Network replicate a temperature model and be integrated into an Operations Planning Model and provide reasonable results?
Need and Benefit
The proposed research addresses the need to perform long-term water supply reliability modeling while satisfying Sacramento River temperature requirements stated in National Marine Fisheries Service Reasonable Prudent Alternative I.2.4.
Contributing Partners
Contact the Principal Investigator for information about partners.
Research Products
Bureau of Reclamation Review
The following documents were reviewed by experts in fields relating to this project's study and findings. The results were determined to be achieved using valid means.
The Implementation of Flow-Temperature Artificial Neural Network Regression into Operations Planning Models (final, PDF, 2.0MB)
By James Shannon
Research Product completed on September 30, 2019
The Implementation of Flow-Temperature Artificial Neural Network Regression into Operations Planning Models (final, PDF, 618KB)
By James Shannon
R&D Bulletin completed on September 30, 2019
