Streamflow Forecasting Using Trainable Neural Networks

by Jason Smith, West Virginia Univ, Morgantown, United States,
Robert N. Eli, West Virginia Univ, Morgantown, United States,



Document Type: Proceeding Paper

Part of: Water Resources Planning and Management: Saving a Threatened Resource—In Search of Solutions

Abstract:

In this investigation the practicality of applying a backpropagation neural network to modeling watershed response characteristics is examined. Two separate tests were performed. One test involved testing the ability of a neural network to predict time to peak and peak discharge resulting from unique storms produced with spatially distributed rainfall. The other test involved training a neural network to predict volumetric discharge from a time series of rainfall.



Subject Headings: Neural networks | Mathematical models | Watersheds | Rain water | Time series analysis | Rainfall | Network analysis

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