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Development of EC Forecasting Tool with ANN for Flow-Salinity Linearization in CalSim-II/CalSim-III

This paper discusses the development of an EC (Electrical Conductivity) forecasting tool with Artificial Neural Network (ANN) for flow-salinity linearization in CalSim-II/CalSim-III. The tool aims to improve the representation of nonlinear flow-salinity relationships in CalSim by providing an easy-to-use and efficient method for calculating EC contour and answering what-if scenarios about salinity. The tool is implemented in Microsoft Excel with features for data input, visualization, and updating.

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Development of EC Forecasting Tool with ANN for Flow-Salinity Linearization in CalSim-II/CalSim-III

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  1. Updated Delta-Flow Salinity ANN module in CalSim-II/CalSim-III and its Application as a Forecasting Tool California Water and Environmental Modeling Forum Asilomar Conference Center, California February 26 – February 28, 2007 Shengjun Wu and Sanjaya Seneviratne California Department of Water Resources

  2. Outline • Flow-salinity linearization module improvement • Introduction of EC forecasting tool with ANN

  3. Objective of Linearization Module • CalSim can only take linear equations • representing nonlinear flow-salinity relationship requiring linearization • Existing module failed some time during flood season in representing ANN EC

  4. Linearization method before update

  5. Dynamic Linearization Sample Rock Slough Linearization

  6. Why developing EC Forecasting Tool with ANN? • Current ANN is embedded in Calsim and is not easy for access • Easy for use and much faster comparing with a numerical model • Make calculating EC contour of flow-salinity relationship economical • Can answer some what-if scenario about the salinity

  7. What the Tool looks like • Microsoft Excel Spreadsheet • Easy upgrading • Provided universal definition of ANN inputs, including DSS file reading tool. • Provided basic charting tools • Applicable time range: 1/1/1921-12/31/2003

  8. What can be done to improve the tool • Provide EC contour • Provide automatic updating on all the input data (reading local DSS file, web server data, etc.) • Provide automatic adjustment on the forecasted EC based on trend in the historical data verification • Provide ANNs specifically designed for forecasting EC. Such as the ANN trained with historical data, or the ANN trained on lagged EC and hydrology

  9. Sample Trend adjustment Scenario

  10. What Computer Source Needed • Microsoft Excel 2003 • Ford HEC-DSS

  11. Sample Distribution • I have some copies of the installation CDs HERE

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