Seasonality and Repair Time Analysis of Water Distribution System Failures

Water distribution networks are part of critical infrastructure, and ensuring a rapid return to service after failures is vital for public health and economic resilience. While numerous studies have quantified failure rates and examined factors that influence the duration of repairs, the seasonal variability of repair time itself has received little attention. This study analyses 264 monthly observations (January 2004–December 2025) from a large urban water supply system in south-eastern Poland. We evaluate the seasonality of failure counts, average repair time per event, and the total labour hours needed to restore service. Methods include descriptive statistics, seasonal indices, non-parametric tests, kernel density estimation, parametric distribution fitting, empirical exceedance curves of monthly mean repair duration, and time-series decomposition. The results show a pronounced seasonal pattern in the number of failures and total labour hours, with peaks in winter and minima in spring, whereas the monthly mean repair duration remained stable at approximately 8 h and showed no significant seasonal variation. Among the positive-support candidate distributions, the log-normal model provided a slightly better fit than the Weibull model. Empirical exceedance analysis and non-parametric tests confirmed no significant differences in monthly mean repair duration between seasons or calendar months. Decomposition reveals a small downward trend in total repair hours after 2010. These findings provide new insights for maintenance planning and indicate that winter workload peaks are driven primarily by higher failure counts rather than by longer mean repair duration.