Methodological Evaluation and Time-Series Forecasting of Water Treatment Facilities in Ethiopia: A Risk Reduction Study

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 $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.