Seasonal effects on process stability in potable water production: operational insights from statistical process control

Diagram showing workflow from routine drinking water monitoring through SPC analysis, seasonal stratification (wet vs dry), and season-aware interpretation leading to improved operational decision-making. Routine drinking water monitoring programmes are designed to demonstrate compliance with regulatory standards; however, compliance alone does not indicate whether treatment processes are statistically stable or predictable. Seasonal hydrological variability further complicates interpretation by introducing structured, non-random variation into routine monitoring data. This study applies Statistical Process Control (SPC) to examine how seasonal conditions influence process stability in potable water production and to evaluate the operational value of season-aware SPC interpretation. Secondary operational monitoring data comprising weekly physicochemical measurements were analysed using Individuals-Moving Range (I-MR) control charts. The dataset was stratified by wet and dry seasons to compare process behaviour and the distribution of instability signals. Results show clear seasonal structuring of instability. Wet-season conditions were associated with greater variability and more frequent control-chart violations, particularly for turbidity, conductivity, and hardness-related parameters. Dry-season periods exhibited tighter statistical control despite continued regulatory compliance. These findings indicate that apparent instability is often seasonally driven rather than evidence of operational failure. A Season-Aware SPC Interpretation Framework is proposed to support context-sensitive interpretation, proportionate response, and improved prioritisation of season-sensitive parameters under routine monitoring conditions.