Analysis of ILI Value Variance Based on Data from an AMI Water Meter Reading System

This study presents an analysis of the Infrastructure Leakage Index (ILI) variability for two District Metered Areas (DMAs) in the Silesian Region (Poland), based on 2024 data. The objective was to assess the suitability of the ILI for short-term leakage evaluation and its potential to support operational decision-making. ILI values were calculated for daily, weekly, and monthly intervals using synchronized hourly data from an Advanced Me-tering Infrastructure (AMI) system and water network monitoring platforms. A key ad-vantage of the dataset was the temporal alignment of inflow, outflow, and consumption data at the DMA level. The study applied statistical measures of variability (standard deviation, variance, coeffi-cient of variation) and graphical methods (histograms, boxplots) to evaluate ILI behavior across time resolutions. The two DMAs were compared to explore the differences in ILI dynamics, range, and identify operational factors influencing leakage levels. The results confirm that ILI interpretation is highly dependent on temporal resolution. Daily data is more responsive to anomalies and operational events, while monthly data provides more stable values suitable for benchmarking. Despite the aggregation smooth-ing the variability, notable differences in system performance between zones persist. High-frequency AMI data enhances the precision and operational value of ILI analyses.