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Water Meter Billing Data and Apparent Water Loss James Fisher - JBS Associates, LLP, 3094 Candlewood Ct. Erlanger, Kentucky 41018 - E-mail: jefisher@fuse.net - Tel: (859) 342-6258, (859)380.9703 cell James B. Smith – JBS Associates, LLP, 4715 Strack Road, Suite 114, Houston, Texas 77069 – E-mail: jbsassociates@att.net - Tel: (281) 435-2780 Keywords: Unaccounted-for water, non-revenue water, apparent water loss, meter error, water billing systems, water loss management, meter management Abstract This paper introduces the importance of understanding the depth of data contained in a water meter billing system and the relation of this data to analyses of potential water and revenue loss whether it is defined as unaccounted for water (UFW), non-revenue water (NRW), revenue water or real and apparent loss. Over the past couple of years there has been interest in the U.K. based International Water Association’s (IWA) methodology for analysis of unaccounted for water. While this method presents new definitions for the various components of water loss and groups them differently than done historically in the USA, the focus is on leakage or real losses and not on metering. This is in part due to the lack of full metering in the UK, England and Wales where only approximately 25% of the customers are metered, the residential customers’ use is estimated and they pay for water based on the rated value of their property. This paper will stress the importance of understanding the meter reading and billing systems and the wealth of information gathered by metering and meter readers and contained in the customer information system (CIS) or billing software. Errors or assumptions in this data have a far-reaching impact on the determination of system accountability and lost revenue because it is a retail (or commercial) loss and not a production (or physical) loss. For most systems in the United States the economic impact of water loss associated with meter error may be anywhere from 2 to 30 times the direct cost of leakage. Meter Reading and Billing Systems Most water systems in the United States are fully metered. There are some that still use an estimated flat rate but they are few in number and getting fewer as the years go by. In order to properly account for the water that is produced by the water plants and input to a distribution system for sale, a method of measurement is required and this is a water meter, whether it is the master meters at the water plant or the customer meters at the point of use. Water meters are, by definition, performance indicators and errors and oversights in the application and use of these devices or the water billing system have a direct impact on the ability of any water system to properly account for the water distributed for sale. Errors and assumptions in these two areas can result in expenditure of capital in leak detection that does not identify the initial missing or lost water. Consequently the true cost/benefit ratio of the water that was identified as lost, is sometimes is not realized.

Water Meter Billing Data and Apparent Water Loss © 2005 JBS Associates All Rights Reserved

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Meter Reading Cycles The number of meters in the system and methods used to read the meters determine the number of meter reading cycles that occur in a year. Generally, customer meters cannot all be read at the beginning and end of a year as can production meters, so there is not an “apple to apple” comparison of water produced and water sold. There are numerous steps involved depending on the method used to read the meters as depicted in Figure No.1. Each of these steps develops information that will identify areas in this process where either potential problems develop in using these data in an engineering analysis of water loss or, valuable attribute data relating to the meters and water use are developed which aid in this analysis. Meter Reading and Billing are not engineering functions; they are revenue-generating functions and need to be recognized as such.

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Because larger cities normally read different classes of customers on different cycles, i.e. commercial, industrial, institutional read monthly and residential read quarterly, summing the customer water use on a monthly basis can actually result in the appearance that more water was sold than was produced. This is illustrated in Figure No. 2 and, the inclusion of wholesale customers whose meters are read monthly and billed quarterly in early years then changed to monthly billings in the middle of a major billing software upgrade can compound the interpretation of this data. Establishment of customer billed water use in a form comparable to water produced is additionally hampered by a term

Water Meter Billing Data and Apparent Water Loss © 2005 JBS Associates All Rights Reserved

Figure No.

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Figure No. 2

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identified in the AWWA M36 – Water Audits and Leak Detection Manual as “meter reading lag time”. This section, 2-2A states: Corrections must be made to meter use data when the source-meter reading dates and the customer meter reading dates do not coincide with the beginning and ending dates of the audit study period. The following Figure illustrates the problem.

Figure No. 3 Meter Reading Lag Time – Audit Study Period is Jan 01 2004 through Dec 31 2004

Most billing system software uses a running average daily water use for each account that is a six month average with the newest reading added and the oldest reading dropped and then re-averaged each period. When an annual report is requested, the average daily use is calculated and multiplied by 365 days to develop the annual figure and this is compared to the annual water produced at the water plants to determine the initial water loss figures.

Figure No. 4 Calculated Annual Water Use

Database software allows the development of software routines that can calculate the water use that occurs at year splits and assigns the use to the appropriate year. Figure No.4 illustrates this. The Blue boxed figures are averaged annual figures, Red is calculated on the actual days of water use for the specific year and Green figures show the difference between the two.

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The difference in the annual water use is not a physical loss (leakage) or an apparent loss (meter error); the city did receive revenue for the water that was measured, part of it just occurred in a different year. When comparing the fixed days of the production water to the varying days in the meter reading system, this must be taken into consideration. It is an adjustment that can account for 3-5% on the initial “unmetered ratio” or “UFW” depending on the system size and the meter reading methods. Meter Reading Attribute Codes Generally, water meters are not just read and figures input to a storage device or book, there are numerous other descriptive data entered by either the meter reader or the Customer Service representatives that provide detail into the daily workings of these instruments. Depending on the software used in the billing system and the computerized maintenance management system (CMMS) there can be literally 100’s of codes that are referenced to specific actions relating to the meters or the customers. The following table illustrates these codes from a larger billing software system.

Table No. 1 Meter Reading Reason Codes

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The descriptors for these codes are normally contained in the manuals for the software and many of these are extremely useful in identifying trends in the historical meter readings and water use that have a direct impact on analyzing the accuracy of the meters and the potential loss of revenue or UFW. The following table illustrates some of these descriptors.

Table No. 2 Read Reason Descriptors

Water meters and the remote recording device, if any, are mechanical or electronic devices and will fail or become inaccurate over time. When meters are changed out either because of a scheduled replacement program or from work orders developed from the meter reading and billing process, this information can be used to analyze other meters of the same age, size, type and brand still in the system. These types of analyses can results in identification of potentially unrecorded or under-recorded water use and revenue. The figures generated from these analyses also aid in plugging the holes in any water auditing methods where a general meter inaccuracy figure is used to identify “unaccounted for” or “apparent” water loss. Additionally, errors and losses identified in the water meters are valued at the retail rate of the water rate structure as compared to system leakage, which is valued at the production cost (chemical and electrical) of the water only. Meter Change-Out Programs At some time, all cities initiate a change out program for the water meters in the system. The life of the water meter depends on the aggressiveness of the water in a particular system, the water quality, rates where the water is being used by the customer and the age of the meter. Water Meter Billing Data and Apparent Water Loss © 2005 JBS Associates All Rights Reserved

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Each city must determine the optimum time for replacement and the rate structure is the key driver in determining the acceptable amount of loss due to meter error. As meters are pulled from the system either from, individual work orders or for a change-out program, the accuracy of the meters should be checked. This can be accomplished either on-site or with a test bench. Once these accuracies are identified, the results can be extrapolated to other meters in the system of the same age or brand to aid in determining the potential water and revenue loss from similar groups. Using geographic information software (GIS) and either the physical address of the customer, parcel ID or structure address these customers can be geocoded for detailed analysis of water loss by specific pressure districts, meter reading routes or district metered areas (DMA). The following Figure illustrates meters that had been included in a meter change out program.

Figure No. 5 5/8 and ‘3/4 inch Meter in a Change Out Program

This city had 17 Service Areas and 107 “pitometer districts”, called DMA’s in the UK approach, where the results of the meter change out analysis could be applied. The results of the analysis aided in determining if the initial water loss identified by, comparing the water measured into a district and the summed metered water use in each district, were attributable more to leakage than to potential meter error. The figure on the right illustrates one of the 107 districts in this system. The boundaries of the districts are defined by natural boundaries such as highways, railroads, rivers or streams and by pressure regulating valves, or valves arraignments defined at the time of a measurement. The measurement instrument is a “Cole pitometer pito rod, a pipe caliper and a differential pressure transmitter and recorder.

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With enough meter reading and billing history, the annual water use before and after the change out can be analyzed to determine the benefits in both increased recorded use and revenue. Not all meters will show an increase in water use. Often the customer type has a lot to due with this since some multi-unit family dwellings may not have been occupied for a full year or the customer may have initiated water conservation efforts or fixed internal plumbing leaks. The following table illustrates some of this analysis.

Table No. 3 Meter Change Out Program – Before and After

Stuck or Failed Remote Reading Device Each component in the meter reading and billing process has the possibility of error or failure and diligence in monitoring these components will reduce the impacts of these errors and failures. Identification of these errors and the geographic location of the meters where this is occurring can aid in the determination of whether any initial UFW is related to leakage or “real losses” or metering error “apparent losses”. Early identification of metering errors can eliminate un-needed expense in leak detection and return larger financial benefits to the city. The following figure illustrates the identification of stuck generators and/or remotes for one city. Water Meter Billing Data and Apparent Water Loss © 2005 JBS Associates All Rights Reserved

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Figure No. 6 Stuck Generators and/or Remote

By geocoding the occurrence of the accounts identified with this problem, detailed analyses can be completed to aid in determining which specific areas or districts may be affected more by meter error than by leakage. Tracking these occurrences can also aid in asset management and replacement programs to accelerate the removal of failing equipment. The figure and table illustrate the identification of this type of error.

Table No. 4 Stuck Generators and/or Remotes

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Low Use and Zero Use Accounts Figure No. 7 A detailed Historical Consumption Analysis can identify accounts whose annual water use may be low when compared to the average annual water use of other meters of the same age. Accounts with zero use can also be identified. While this occurrence may be attributable to vacant properties or intermittent occupancy, it may also indicate failing meters in a particular geographic area or age group. Geographically locating the water meters allows the results of numerous other analyses to be tied to specific locations of districts within a city. Historical Test Results Figure No. 8 Depending on the billing software used, there may be the capability to tag metered accounts where the accuracy of the meters has been determined by annual testing and repair programs. Identification of these accounts allows detailed analyses of meter accuracy, age and decreasing water use in a historical context. In addition, the development of a large meter asset database will aid in meter repair/replacement analysis and testing frequency determinations. Large meter inspections, photo database development and testing and repair database development should be included in this type of asset database. The following table illustrates the summary results of several large meter tests completed in one city. More detail concerning parts replacement and costs should be maintained in these types of databases.

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Table No. 5

Large Meter Test Results

Metered Ratio’s can be Masked by Large Meters

In some water systems it is not uncommon to see 1% or 2% of the customers consuming over 50% of the usage. Large meter usage can mask the metered ratio and provide false security to a utility. One City where this is true has about 14,000 metered customers. One customer consumes over 60% of the water. The metered ratio of this city exceeded 91% which is considered excellent. However, when the usage of this one account is taken out of the “production/sales” equation, the metered ratio drops to 70% reflecting a 30% loss. Percentages can be very misleading, and volume of loss is more important, since a monetary value can be established.

The following graph shows the distribution of usage for another City where about 1% of the customers consume 60% of the water. In this particular example, the cost analysis showed that meter error had a 39 times greater value than the direct cost of leakage. Large meter accounts need to be monitored closely.

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Figure No.9

Distribution of Usage - All Accounts

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Figure No. 10 Initial Metered Ratio

When a customer billing system is used in conjunction with a GIS system, identification of selective areas where the Initial Meter Ratio is low can easily be identified. The addition of selective attribute data relating to the type of custom, meter size and type, meter reading and work order attributes, meter test accuracy and historical leakage analysis records, will allow the identification of which components are causing the high initial UFW whether it is defined as Real or Apparent losses. In parts of the world that are fully metered, accurate metering, becomes the barometer for utilities to gauge their operational and financial performance. It is also important to point out that not all leak detection efforts are successful and not all meter replacement programs support water conservation programs or generate revenue. Water Meter Billing Data and Apparent Water Loss © 2005 JBS Associates All Rights Reserved

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The following figure presents a trend line graph that illustrates the cost of leakage compared to

eter error based on a combined water/sewer rate of $4.37 per 1,000 gallons. The annual

e

Figure No. 11 Leakage – v – Meter Error Cost of Unaccounted for Water

moutput from the water plant is 4.8 billion gallons per year with a 15% system wide loss or initial UFW. If 90% of the loss were due to leakage and 10% due to meter error, the annual revenuloss would be approximately $3.2 million dollars per year. On the other end of the scale, if 60% of the loss were due to leakage and 40% due to meter error, the annual revenue loss would be $$9.0 million per year.

ESTIMATED COSTS OF UNACCOUNTED FOR WATER Example of US City - Based on 2003 data

$3,000,000

$4,000,000

$5,000,000

$6,000,000

$7,000,000

$8,000,000

$9,000,000

$10,000,000

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RATIO: LEAKS TO METER ERROR IN PERCENT

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