FORECASTING RIVER KADUNA DISCHARGE USING HYBRID MOVING AVERAGES AND SMOOTHING EXPONENTIAL METHODS.

J. O. Folorunsho

This paper explores the use of hybrid moving averages and smoothing exponential (HMAs & SE) methods for river flow forecasting. In this study, four major variables for river discharge (rainfall, temperature, relative humidity and stage height), and the discharge values of River Kaduna drainage basin for the period 1993-2004 (Apr-Oct) was used. The variables were used as the input data while the discharge values were used as the output data for the model. The modeling tool was applied to the initial data in order to predict new sets of input values for the period 2005-2015, and subsequently used to generate the output for the same period. The efficiency and accuracy of the HMAs & SE was measured based on the comparison of the initial discharge values (1993-2004) and the forecasted discharge values for the period 2005-2015. From the result using a plot, it was shown that the model provided the best fit and the forecasted discharge trend followed the observed data closely. These result shows that Hybrid Moving Averages and Smoothing Exponential Methods is an effective tool in forecasting river discharge.

Key words: River Discharge, Hybrid Moving Averages and Smoothing Exponential Methods, River Kaduna.