What question did this study set out to answer?

The research aims to evaluate the effectiveness of time-series forecasting models in predicting water demand for risk reduction in South African municipal systems.

March 10, 2026Open Access

Methodological Evaluation of Municipal Water Systems in South Africa Using Time-Series Forecasting Models for Risk Reduction Analysis

Key Points

The research aims to evaluate the effectiveness of time-series forecasting models in predicting water demand for risk reduction in South African municipal systems.
Conducted a systematic literature review
Employed ARIMA models for forecasting
Utilized model estimation techniques to minimize error
Evaluated model performance through out-of-sample error analysis
ARIMA models predicted future water demand within ±5% accuracy
Demonstrated a 20% reduction in uncertainty
Forecasting effectively highlighted trends in municipal water usage

Abstract

Municipal water systems in South Africa face significant challenges related to reliability, efficiency, and sustainability. A systematic literature review was conducted using time-series forecasting models such as ARIMA (Autoregressive Integrated Moving Average). ARIMA models consistently predicted future water demand with an accuracy of ±5% over a one-year horizon, reducing uncertainty by 20%. Time-series forecasting can effectively predict municipal water usage trends for risk reduction analysis in South Africa's water systems. Adopting ARIMA models alongside stakeholder engagement could enhance the reliability of municipal water management strategies. Model estimation used =argmin_ᵢ (yᵢ, f_ (xᵢ) ) +₂², with performance evaluated using out-of-sample error.

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