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Submitter's Name |
Kenneth Friedman |
Session Name |
Posters - Water Conservation and Use 1 |
Category |
Water Conservation and Use |
Poster Number |
72 |
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Author(s) |
Kenneth Friedman, University of Florida (Presenting Author) |
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James Heaney,
University of Florida |
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Data Validation Methodologies for Water Audits in Florida |
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This presentation focuses on data validation methodologies for water audits in Florida as part of a water conservation plan. Current procedures for estimating water losses in Florida are not uniform and the accuracy of the reported estimates of water loss is questionable. The quality of the water audit is directly dependent upon the quality of the input data. Friedman and Heaney (2009) evaluated the new third edition of the AWWA M36 manual titled Water Audits and Loss Control Programs (AWWA 2009a) and associated free software for evaluating water losses (AWWA 2009b). They recommend that Florida water utilities adopt the water audit and loss control procedures that are described in M36 including the water audit procedures outlined in Chapter 2. They also recommend using Version 4.0 of the AWWA Free Water Audit Software, which offers a top down method to compile water audit data and analyze loss levels and cost impacts.
The AWWA software requires that the user input estimates of up to 18 parameters. The reliability of these estimates ranges from excellent for measured water uses with accurate meters to poor for unsupported estimates of unmetered quantities. The AWWA software addresses the question of the validity of the data using a weighted scoring system that provides a normalized score ranging from 0 to 100 based on the user’s estimates of the quality of the data.
Based on a detailed review of the 2009 AWWA M36 Manual on water audits and water loss, and the associated Version 4.0 software, we recommend estimating the validity of the water audit based on the percentage of metered water supplied and used for a relative importance metric, and the gallons per capita per day of unmetered water for an absolute metric of importance.
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