WRF has published a new report, Water Audits in the United States: A Review of Water Losses and Data Validity (project #4372b), which evaluated the levels of distribution-system water loss via AWWA-methodology water audits occurring in five regions including California Urban Water Conservation Council (CUWCC), the Delaware River Basin Commission (DRBC), the Georgia Department of Natural Resources (GA DNR), the Tennessee Comptroller of the Treasury (TN COT), and the Texas Water Development Board (TWDB). AWWA methodology is employed in order to avoid the term “unaccounted-for” water and instead promotes the division of water losses into distinct volumes, as prescribed by AWWA manual M36: Water Audits and Loss Control Programs, 3rd edition.

A total of 4,575 AWWA-methodology water audits were collected from the five reporting entities, spanning 2010 to 2014. High level findings are presented on the composite data set (1,636 audits from 2012 and 2013). Median values of the water audit performance indicators were calculated and are provided in Table 1.

Table 1: Composite Water Audit Data Set Median Performance Indicators (sample sizes ranges from 478 to 1545, see report for details).

Results

Plausible water audits:
More than 1 out of every 5 audits presents an implausible water loss scenario and suggests that the data used to populate these audits may not be accurate.

Data validity: Utilities whose audit results were not plausible tended to grade their data validity notably higher (77.1) than utilities that submitted audits with realistic data (73.1). The lowest data validity scores were seen in Georgia, where the most rigorous data validation is pursued. These findings indicate third-party validation of audit data tends to produce lower (but more accurate) data validity scores.

Median water audit performance indicators: The performance indicators are useful to compare performance amongst utilities or performance of one utility over time. The median Infrastructure Leakage Index (ILI) is 2.48, meaning that water losses exceed the technical minimum volume by a factor of at least 2.48. The median non-revenue water is 7.8% of operating costs. The median real losses are 39.88 gallons/service connection/day and 785.54 gallons/mile of main/day. Examining correlations in the composite data set revealed a number of valuable findings. Systems with the highest variable production cost tend to have the lowest levels of normalized Real Losses. Real Losses increase as average operating pressure increases. No significant relationships were found in comparing Real Losses with customer retail cost or Real Losses with system size.

Conclusion and Recommendations

An impressive number of utilities are reporting their water losses in partnership with regional entities using the AWWA Free Water Audit Software, which signals increased attention to supply-side efficiency in water management. The use of AWWA methodology to quantify distinct water loss volumes instead of the obsolete “unaccounted-for” water volume is essential for devising targeted and effective water loss reduction programs. However, this research suggests that many audits do not reflect the actual water losses of reporting utilities, evidenced by the high number of audits (21%) that do not pass basic checks of plausibility, and thus are not conducive to building effective water loss reduction programs.

In reviewing the largest compilation of AWWA-methodology audits to date, it is clear that more training and education is needed to improve confidence in water loss reporting. More rigorous audit validation will be required to produce audits that truly capture reality. The only region to require basic audit validation by a third party is Georgia, which resulted in the fewest unrealistic audits. More rigorous validation could further improve audit quality and perhaps even eliminate all unreasonable audits.

Until the number of implausible audits decreases, it will be difficult to discuss typical levels of water loss without qualification of the accuracy of the data set. In the meantime, this study highlights general but noteworthy trends, such as the connections between Real Losses and pressure and the relationship between Real Losses and production cost. When the reliability of regional data sets improves, more insight into appropriate and effective water loss control programs will surface.