Water treatment facilities in South Africa face challenges in maintaining consistent yield due to variable input parameters such as raw water quality and operational conditions. The study employs a hybrid ARIMA (AutoRegressive Integrated Moving Average) model with robust standard errors to forecast yield improvements based on historical data from selected facilities. A significant improvement in predicted yield was observed when using the ARIMA model, particularly for raw water quality fluctuations up to ±20%. The hybrid ARIMA model demonstrated its potential in forecasting and enhancing yield stability of South African water treatment facilities, offering a practical tool for policy-makers. Policy recommendations include pilot testing the model across different regions and incorporating feedback loops into facility management protocols. The maintenance outcome was modelled as Y₈ₓ=₀+₁X₈ₓ+uᵢ+₈ₓ, with robustness checked using heteroskedasticity-consistent errors.
Sipho Motshegoana (Wed,) studied this question.