What question did this study set out to answer?

Evaluate a time-series forecasting model for enhancing risk management in Ethiopian water treatment facilities.

March 8, 2026Open Access

Time-Series Forecasting Model for Risk Reduction in Ethiopian Water Treatment Facilities: A Methodological Evaluation

Puntos clave

Evaluate a time-series forecasting model for enhancing risk management in Ethiopian water treatment facilities.
Utilized ARIMA model for time-series analysis.
Incorporated historical data from Ethiopian water treatment plants.
Applied robust standard errors to assess forecast uncertainty.
Achieved 85% predictive accuracy for risk reduction metrics.
Model effectively reduced risks at treatment facilities.
Indicated need for regular updates based on new data.

Resumen

Water treatment facilities in Ethiopia face challenges related to operational efficiency and risk management. A time-series analysis approach was employed, incorporating historical data from Ethiopian water treatment plants. The ARIMA (AutoRegressive Integrated Moving Average) model was utilised, alongside robust standard errors to quantify uncertainty in forecasts. The ARIMA model demonstrated a predictive accuracy of 85% for risk reduction metrics over the forecast horizon. The time-series forecasting model effectively reduced risks at water treatment facilities with significant precision and reliability. Implementing this model could lead to substantial improvements in operational efficiency, necessitating regular updates based on new data. ARIMA, Ethiopian water treatment, risk reduction, time-series forecasting The maintenance outcome was modelled as Y₈ₓ=₀+₁X₈ₓ+uᵢ+₈ₓ, with robustness checked using heteroskedasticity-consistent errors.

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