African Computational Statistics (Technology/Maths) | 26 November 2009
Methodological Evaluation and Time-Series Forecasting of Water Treatment Facilities in Ethiopia: A Risk Reduction Study
M, u, l, u, g, e, t, a, G, e, b, r, e, h, i, w, o, t, ,, Y, a, r, e, d, A, s, s, e, f, a
Abstract
Water treatment facilities in Ethiopia face challenges related to operational efficiency and risk management. A comprehensive review of existing models was conducted, followed by a predictive model based on ARIMA methodology. Uncertainty in forecasts was quantified through robust standard errors. The ARIMA model showed an average error reduction of around 15% in forecasting future water quality levels compared to baseline methods. ARIMA models provide a reliable framework for monitoring and predicting the performance of water treatment facilities, with practical applications in risk reduction strategies. Implementing ARIMA-based forecasts can help minimise operational risks by enabling proactive management decisions. water quality forecasting, ARIMA model, Ethiopian water treatment systems The maintenance outcome was modelled as $Y<em>{it}=\beta</em>0+\beta<em>1X</em>{it}+u<em>i+\varepsilon</em>{it}$, with robustness checked using heteroskedasticity-consistent errors.