Abstract:
An artificial neural network model developed to forecast river flow/discharge is presented. The
model is based on the feed-forward, back-propagation network architecture optimized through a
conjugated training algorithm. The observations of daily mean river discharge and daily mean
rainfall data during the period 2002 to 2005 were used to train the model and verify the model
predictions. The Hanwella station downstream of the Kelani river basin was chosen as the
target station where the discharge was to be predicted. The river discharge at the Glencourse,
Deraniyagala, Holombuwa and Kithulgala stations upstream of the target station were selected
as the main inputs to the model. The contribution of inputs to the model output was determined
by studying the correlation between the predicted and the actual discharge values. The best
correlation coefficients between the forecasted and observed discharge for the Hanwella station
are 0.95, 0.86 and 0.68 for the same day, one day ahead and two days ahead forecasting
respectively
