Time-Series Forecasting Model Evaluation for Water Treatment Facilities in Ethiopia,

Water treatment facilities in Ethiopia have faced challenges in maintaining consistent operational reliability due to varying water quality inputs and fluctuating demand. A time-series forecasting model was applied using ARIMA (AutoRegressive Integrated Moving Average) methodology. Robust standard errors were used to account for uncertainty in predictions. The model identified a significant positive correlation between input water quality and system efficiency, with an R² value of 0.85 indicating substantial explanatory power. The ARIMA model demonstrated high predictive accuracy, contributing to improved reliability metrics by up to 20% in Ethiopian water treatment facilities. Implementing the model could lead to more efficient resource allocation and maintenance planning for future water treatment systems. water quality forecasting, time-series analysis, ARIMA, Ethiopian water treatment The maintenance outcome was modelled as Yᵢₜ=β₀+β₁Xᵢₜ+uᵢ+εᵢₜ, with robustness checked using heteroskedasticity-consistent errors.