Municipal water systems in Rwanda face challenges related to supply chain management, particularly in terms of cost-effectiveness and forecasting future demand. A time-series forecasting model was developed using an ARIMA (Auto-Regressive Integrated Moving Average) model. Uncertainty around the forecast was assessed through robust standard errors. The model demonstrated a 10% reduction in costs over a one-year period compared to traditional methods, with forecasts showing a consistent trend of demand increase by 5% annually. The ARIMA model proved cost-effective and reliable for predicting municipal water system demands in Rwanda. Further research should be conducted to validate these findings across different regions and scales within Rwanda's municipal water systems. Municipal Water Systems, Time-Series Forecasting, Cost-Effectiveness, ARIMA Model Model estimation used =argmin_ᵢ (yᵢ, f_ (xᵢ) ) +₂², with performance evaluated using out-of-sample error.
Kwegyirwa et al. (Sat,) studied this question.