A Strategy to Assess Water Meter Performance

Apparent water losses can be problematic to water companies' revenues. This type of loss is very difficult to detect and quantify and is often associated with water meter anomalies. This study was motivated by a water company's challenge that links a decrease in water consumption to water meters' malfunction. The aim is to develop a strategy to detect decreasing water usage patterns, contributing to meter performance assessment. The basis of the approach is a combination of statistical methods. First, the time series of billed water consumption is decomposed using Seasonal-Trend decomposition based on Loess. Next, breakpoint analysis is performed on the seasonally adjusted time series. After that, the Mann-Kendall test and Sen's slope estimator are used to analyze periods of progressive decrease changes in water consumption, defined by breakpoints. A quantitative indicator of this change is proposed. The strategy was successfully applied to eight-time series of water consumption from the Algarve, Portugal.

Automated summary

This study aims to address apparent water losses faced by water companies by proposing a strategy to detect decreasing water usage patterns. Statistical methods are used to analyze time series data of water consumption and identify potential issues.