A TIME SERIES ANALYSIS OF THE MONTHLY DISTRIBUTION OF RAINFALL IN ENUGU METROPOLIS.
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It is widely accepted that water supply will be a pressing issue in this century. Thus, position of adequate rainfall in the development of human and natural resources is a worthwhile research work. The data used in this project work was monthly amount of rainfall in Enugu city within the period of (2000- 2012).A preliminary inspection on the data revealed that the data has no trend but consist of multiplicative seasonal movements. Furthermore, the monthly data was also found to be stationary and serially uncorrelated by the Augmented Dickey Fuller test of unit root and the Autocorrelation test for serial correlation of the error term respectively. The exponential smoothing procedures were adopted for the construction of the best fit model for the prediction of future rainfall pattern in Enugu. This was achieved by algorithms aimed at smoothing out all irregular components inherent in the series. The best fit model parameters were used to predict monthly rainfall distribution for 2013. The result suggested heavy rainfall in general for the year in question with its amplitude in the month of October.
It is widely accepted that water supply will be a pressing issue in this century. Thus, position of adequate rainfall in the development of human and natural resources is a worthwhile research work. The data used in this project work was monthly amount of rainfall in Enugu city within the period of (2000- 2012).A preliminary inspection on the data revealed that the data has no trend but consist of multiplicative seasonal movements. Furthermore, the monthly data was also found to be stationary and serially uncorrelated by the Augmented Dickey Fuller test of unit root and the Autocorrelation test for serial correlation of the error term respectively. The exponential smoothing procedures were adopted for the construction of the best fit model for the prediction of future rainfall pattern in Enugu. This was achieved by algorithms aimed at smoothing out all irregular components inherent in the series. The best fit model parameters were used to predict monthly rainfall distribution for 2013. The result suggested heavy rainfall in general for the year in question with its amplitude in the month of October.
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