Streamflow Forecasting Using Trainable Neural Networks

TLDR: In this paper, the practicality of applying a backpropagation neural network to modeling watershed response characteristics is examined, and two separate tests are performed: one test involved testing the ability of a CNN to predict time to peak and peak discharge resulting from unique storms produced with spatially distributed rainfall.

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.