Abstract

This study intensively examined the monthly water consumption forecasting performance using advanced time series (ARIMA) models. Thus, this study intends to identify the appropriate ARIMA models to best fit the water consumption data in Southwestern Ethiopia Tepi town and forecast water consumption effectively in the city. The data used for this study was the monthly water consumption in Tepi town from January 2016 to December 2021.The data were converted to returns to enhance their statistical properties and the returns were used to fit a mean equation. The monthly average water consumption in Tepi Town is 77227.8 meters cubic. Both original and transformed data show the trend of water consumption is increasing over time. Several ARIMA models were fitted to the data, and it emerged that the most adequate model for the data was ARIMA (1, 1, 1) based on the model selection criterion. The parameters for ARIMA models were estimated using the Ordinary Least Squares Estimation (OLS) method. The model was used to forecast the consumption for the next ten months and to advise Tepi town Water Company Limited in the city to meet the demand of the people. Conclusion. The consumption of water is increasing from December to September.

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