Hindawi

Advances in Civil Engineering

Volume 2018, Article ID 3841979, 10 pages
https://doi.org/10.1155/2018/3841979

Research Article
A Parameter Classification System for Nonrevenue Water
Management in Water Distribution Networks

Dongwoo Jang
Department of Civil and Environmental Engineering, Incheon National University, Incheon 22012, Republic of Korea

Correspondence should be addressed to Dongwoo Jang; nightray@paran.com

Received 28 December 2017; Revised 22 March 2018; Accepted 10 April 2018; Published 6 May 2018

Academic Editor: Dujuan Yang

Copyright © 2018 Dongwoo Jang. This is an open access article distributed under the Creative Commons Attribution License,
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Nonrevenue water (NRW) in a water distribution network is the water lost from unbilled authorized consumption, apparent
losses, and real losses compared to the total system input volume. Nonrevenue water is an important parameter for prioritizing
water distribution network improvement intervention planning, and it is necessary to identify the affecting parameters. A factor
classification system has been developed based on the factors suggested by major institutions and researchers to propose an
effective NRW classification system in a water distribution network. The factor classifications used include physical, operational,
and socioeconomic factors that could affect NRW. Appropriate standards are required when classifying water main parameters. In
this study, three criteria were proposed to create independent factors. The first relates to the properties of the parameter. One
determines whether the parameters related to the water network are more suitable for physical, operational, or socioeconomic
factors and classifies them into one of these three parameters. Second, one considers data availability and data characteristics
taking into account the scope of the coverage area. Third, it must be possible to quantify selected parameter data. Whether the
collected data are numerically valid and whether it can be used as a standard for assessment or comparison between regions must
be examined. The quantification portion of the qualitative data in managing NRW is important and needs to be used in accordance
with reasonable standards. In this study, more factors can be used depending on those selected, and it was found that NRW
prediction that reflects regional characteristics is possible.

1. Introduction (WLTF). The WLTF has examined international best prac-

tices and developed a standardized terminology for non-
Climate change and population growth have resulted in revenue water (NRW) [5, 6].
large requirements of water in domestic, industrial, and Nonrevenue water (NRW) is one of the major issues
agricultural purposes. Water distribution networks are water utilities are facing today, especially in areas with severe
subject to deterioration over time, and this usually leads to water scarcity conditions [7, 8]. NRW includes physical
difficulties such as decreased capacity of hydraulic facilities, (pipe leaks) and commercial losses (unbilled metered water,
increased volume of water loss, service disruption, and lower unmetered public use, illegal connections, meter error, and
water quality. Additionally, the continuing increase in water for which payment is not collected) [9, 10]. The IWA
consumer water demand presents additional problems such has proposed performance indicators [11–14]. In addition, it
as low pressure in a pipe network. Migration to urban areas has been suggested to avoid the use of a percentage indicator
and rapidly growing populations in developing countries has in performance comparison, especially in target areas where
resulted in a vital need for the construction of adequate there are large differences in consumption per service
water systems to distribute water to residents [1–4]. connection [15, 16].
During the early 1990s, no standard term existed to Based on an analysis of the influence of pipe damage
express and evaluate water losses in a water supply system. on the overall pipe distribution network in determining
The International Water Association (IWA) has recognized priorities for improving a water pipeline [17], a systematic
this problem and established the Water Loss Task Force replacement and remediation plan has been developed for
2 Advances in Civil Engineering

the maintenance of the metropolitan waterworks [18]. Al- In this study, a classification system for NRW man-
though projects to improve old waterworks are being agement was suggested using survey results of researchers
continuously implemented, it is difficult to avoid economic and international institutions via an analysis of the main
losses and improve a system’s function by enhancing the parameters of water distribution systems. This study iden-
assessment and accident prevention of old pipes that depend tified parameters for NRW management in water distribution
on empirically based judgments [19]. systems. The main content of the research is summarized as
Therefore, advanced study and analysis are required of follows.
the factors affecting leaks in decision making to prioritize First, a literature survey was conducted using data from
maintenance of water distribution systems, as well as to domestic and foreign researchers. The relationship of pa-
identify the physical and operational factors affecting NRW rameters in a water distribution system and NRW, a sta-
with parameters such as leaks, hydraulic pressure, water tistical approach, and ANN studies were reviewed.
quality, and water demand volume [8]. To reduce the NRW, Second, a study of parameters related to water distri-
studies analyzing pipe networks, increasing reliability, di- bution systems was conducted. The physical, operational,
agnosing pipe network technology, and evaluating pipe and socioeconomic factors of water distribution systems
deterioration have been conducted to promote an optimal were identified and then classified using detailed charac-
water distribution system [20–22]. teristics for application to NRW management.
Leak analysis is possible by examining each factor af- Third, a parameter classification process with appro-
fecting a water distribution system. Yet a water network in priate standardization was developed avoiding duplication
a large city is complex and comprises various parameters. To of each parameter’s characteristics.
estimate the leak volume, the main water supply network The factor classification system is presented using the
parameters appropriate for the regional characteristics are aforementioned three steps. The factor classification table
selected, and an NRW calculation model, developed by was created considering additional quantification such that
statistical methods, will play an important role in operating it can be used for management and estimation of NRW.
and managing a water supply network [4].
The NRW index of a water distribution system needs to
be proven via relationship with the characteristics of the 2. Definition of NRW in Water
district metered area and quantifying the influence of related Distribution Systems
parameters. In districts with severely deteriorated pipe
networks, for example, the NRW can be considered high NRW is water that has been produced and is “lost” before
because of many leaks but their extent is not quantified. it reaches the customer. Losses can be real losses (e.g., via
Unless the correlation between regional characteristics and leaks, sometimes also referred to as physical losses) or
the NRW is properly identified, NRW management might apparent losses (e.g., via theft or metering inaccuracies)
prove unrealistic and uneconomic even if its ratio is high due [24–26]. NRW corresponds to water loss due to leaks,
to local specificity [4]. commercial problems, and nonbilled consumption such
Korea’s NRW is considered a management performance as a lack of water meter precision or mistakes in client
index of water distribution systems of waterworks operators databases. In (1), Ap is the volume of water produced per
and municipalities. It can be considered the economic unit time and Ab is the volume of billed water per unit
feasibility of a project, suitability of the operational man- time [1]:
agement, and efficiency of investment. A high NRW in terms
Ap − Ab
of economic significance means that the recovery rate NRW ratio � (%). (1)
compared to the production cost is low [23]. Ap
A reduction in NRW is thus essential to maintain sound
financial operation of a waterworks business. In operational The definition of NRW is described as the difference
management, a low NRW ratio indicates appropriate man- between the volume of water input into a water distribution
agement in water distribution systems; a high NRW usually network and the volume billed to customers. NRW has three
means problems in operational management of the facility components as follows [1].
(unmeasured quantities using water meters, leaks, and illegal Physical losses comprised of leaks from all parts of the
use). distribution network and overflows at the facility’s storage
In addition, investment and expansion of water supply tanks. They can be caused by poor operations and main-
facilities requires a huge budget and determination on ap- tenance, a lack of active leak prevention, and poor quality
propriate expectation face constraints. Making a decision is underground assets. Commercial losses are caused by under
difficult on what to prioritize when improving facilities and registration of water meters, errors in data treatment, and
operations comparing and analyzing the lack of supplied the theft of water in various forms.
water with the volume of lost tap water. In this case, NRW is Unbilled and authorized consumption contains water
expected at driving the project by determining whether to used for operational purposes or firefighting which is pro-
improve or expand the facility’s water supply operation. The vided free of charge to select consumer groups. Various
existing NRW method is based on observational data. indicators measure NRW, and essentially all have weak-
Management of leakage is difficult; thus, an analysis of nesses. The generally used indicator is NRW defined as
influencing parameters can calculate NRW. a percentage of water provided.
Advances in Civil Engineering 3

Table 1: Components of water balance [14, 15, 29].

Billed authorized Billed metered consumption (including water exported)
Revenue water
Authorized consumption Billed nonmetered consumption
consumption Unbilled authorized Unbilled metered consumption
System consumption Unbilled nonmetered consumption
input Unauthorized consumption
Apparent losses Nonrevenue
volume Metering inaccuracies
water
Water losses Leaks in transmission and/or distribution mains
Real losses Leaks and overflows at a utility’s storage tanks
Leaks in service connections to customer meters

The IWA recommends the use of alternative indices such 3. Development of Parameter
as water losses per junction and per main length and in- Classification System
frastructure leakage indices [11–13, 24–27]. The latter is
a complex index as it also measures pressure in the DMA of 3.1. Previous Research of Parameter Classification in Water
water distribution network. Distribution Systems. In previous research of the main
Collecting pressure data at junction for a utility is parameters for NRW management, Shinde et al. suggested
complicated, however, as measured pressure can vary widely reliable indicators for waterworks and stable management in
within a piped water supply system. It is thus useful as an water supply systems [7]. Performance indicators (PIs) and
index when improving the system performance but cannot quantifiable data (reflecting operational indicators in the
be easily used to evaluate network losses between utilities, as water distribution network) were used as indicators related
averaging such an index for a utility might fail to provide to those used in NRW management. The purpose of PIs is
useful data except to reflect an underlying problem [28]. not only to perform statistical analysis but also to provide
As parameters of water balance in Korea and their efficient information to support in decision making. PIs of
definitions are different from those of the IWA, they were international organizations are presented in Table 2 [7, 8].
rearranged as shown in Table 1 [14, 15, 29]. Metering and As seen in Table 2, international organizations have
under registration were recalculated, and the remaining recommended similar items. The apparent differences
amount of the recalculation was added to the ineffective shown in Table 2 are due to the various DMAs for which the
water, which was considered equivalent to the real losses of indicator system was developed. For example, the World
the IWA’s water balance. Water theft and illegal connections Health Organization (WHO) indicator is suitable for de-
are apparent losses of NRW. veloping countries and districts where costs and services are
Because of the various definitions and deficiency of well- inadequate.
documented procedures for several parameters (e.g., public The IWA components, on the other hand, cover a wide
use, supplier’s official use, and metering under registration), range of indicators to assess every aspect of the system
selected data could be inaccurate. Mean pressure and lo- across topographical boundaries and are considered major
cation of water meters were estimated using limited samples, reference sources in the global water industry [30]. Recent
possibly causing data variation [29]. studies have increasingly focused on sustainability indicators
This study focused on physical and operational pa- [31–34] and those that integrate social and economic aspects
rameters related to water distribution systems. Physical of waterworks to ensure long-term service [8, 9].
parameters were considered, and measured data such as the In Table 2, the PIs presented by the IWA include physical
number of leaks were also used for NRW management. and operational factors used in the management of NRW
Components of water balance in water distribution systems and other water resource, and personal, service quality, and
are shown in Table 1 as presented by the IWA [14, 15, 29]. economic and financial indicators were suggested.
The combined water balance in a network can be cal- For water resources, the efficiency of a water supply can
culated using real measured data but doing so in a real water be evaluated by water quality, distance from the water
distribution system can be difficult because of the uncon- source, and scale of water supply facilities. In terms of quality
structed district metered area (DMA) and design errors in of service, indicators should be included, but depending on
the water distribution system. In addition, periodic man- the service system and the water supply facilities such as the
agement is an essential element in water distribution systems reservoir, pressurization facility, water purification plant,
including identification of leaky pipes, hydraulic pressure and valve facility, a major influence on the manual supply
management, and proper pump operation. system is observed. This is an essential factor in water loss
Because Korea has a detailed standard for its volume of when managing NRW.
water, NRW calculation using more diverse parameters is Economic and financial indicators can affect NRW in-
necessary. Under the conventional NRW calculation, con- cluding the tax and water rate system according to the living
sideration of physical parameters is needed more than so- criteria of residents in the water supply area, and the re-
cioeconomic parameters. If physical parameters are only construction budget of water supply facilities. Thus, this
used to calculate NRW, it could reduce the economic cost of index is also directly related to NRW.
measuring NRW and help in selecting the maintenance of In addition to the aforementioned IWA indicators, the
DMAs in water distribution systems. main indicators suggested by the other organizations are
4 Advances in Civil Engineering

Table 2: PI themes recommended by international organizations [7, 8].

IWA (2006) IBNET (2005) WHO (2000) WB (1999)
(i) Service coverage
(i) Coverage
(ii) Water consumption and production
(ii) Water consumption and
(iii) NRW (i) User satisfaction
(i) Water resources production
(iv) Metering practices (ii) Community management
(ii) Personnel (iii) Water unaccounted for
(v) Pipe network performance (iii) Financial
(iii) Physical (iv) Metering practices
(vi) Cost and staffing (iv) Level of service
(iv) Operational (v) Pipe network performance
(vii) Quality of service (v) Materials
(v) Quality of service (vi) Cost and staffing
(viii) Billing and collection (vi) Personnel
(vi) Economic and (vii) Quality of service
(ix) Financial performance (vii) Equipment
financial (viii) Billing and collection
(x) Assets (viii) Work control
(ix) Financial performance
(xi) Affordability
(x) Capital investment
(xii) Process indicators

reviewed. NRW is included as an indicator from the In- related to the pipe length and unit of time (usually
ternational Benchmarking Network for Water and Sanita- the number of failures per km per year) and the
tion Utilities (IBNET) including service convergence, dynamics of failures. This study suggests the number
metering practices, cost and staffing, quality of service, and of leaks as the main parameter [35, 36].
assets. These are more detailed than the IWA indicators and (c) Water losses. A number of factors are used to evaluate
easier for the user to understand. the water losses, but not all include the effect of
WHO has provided indices that take account into a network’s technical condition. For estimating the
customer level rather than user satisfaction and community technical condition of a water distribution network,
management. The World Bank provides economic and fi- recommended indicators include the unit leakage,
nancial indicators with a weighting factor such as those of infrastructure leakage index (ILI), and economic
water production, water consumption, and water un- leakage index (ELI). This study considered water
accounted for; billing and collection; and capital investment. losses using the number of leaks in each DMA.
The fundamental concept of NRW comprises real (d) Pressure in pipe network. From the perspective of the
(quantity of leaks) or apparent losses (inaccurate metering effect of operational pressure on the network’s
and illegal use). These losses are direct physical losses, and technical condition, a general observation is that
their management is needed to accurately measure water a high value of operating pressure is undesirable.
using meters installed in water distribution systems. Even less desirable is rapid deviation in hydrody-
When approximating the technical circumstance of water namic pressure each day. The operating pressure
distribution networks, a qualified analysis of the network’s value also affects other indicators for evaluating the
individual components (e.g., separate water pipelines, pres- network’s technical condition: water losses, failure
sure zones, or measurement districts) is conducted using rate, and theoretical service life of the pipe material.
physical indicators. In terms of the scope and availability of Water losses caused by leakage, pipe failure, and
the required supporting analysis, the following physical and higher pipe hydraulic pressure can affect energy
operational indicators are recommended [35]: demands at each junction of a water distribution
(a) Pipe age. The service life of a pipe depends on many network. Thus, energy demand is an important
factors. For each pipe material in the evaluated parameter explaining the hydraulic pressure of
portion of a water distribution network (pressure a water distribution system [4, 38].
zone and water pipeline), consideration of the DMA (e) Reliability. Using qualitative and quantitative re-
region in operational experience, as well as an as- liability factors allows identification of the network’s
sessment of the theoretical service life of the pipe critical facilities and their prioritization in re-
materials and a comparison to the structure and age construction planning. For each indicator, it is
of the operated network, is needed. This study possible to define the processes for its determination,
chooses the deteriorated pipe ratio for the pipe age physical dimension, and method of presentation.
indicator. In addition, each DMA network’s calcu- Each indicator is also a means of monitoring the
lated age of pipes, and its ratio of network data were technical condition of the evaluated distribution
considered. network.
(b) Failure fate. Failure evaluation is an important factor In Korea, the Ministry of Environment (MOE) has
for the operational maintenance, repair, and re- established the country’s main indicators and the classifi-
construction planning of a water distribution net- cation of water distribution systems. In the assessment of
work. The main indicator for failure analysis in terms aging and DMAs, factors are classified based on the physical
of the needs of an evaluated technical circumstance parameters of a water distribution network, and scoring is
is the failure rate expressed as a number of failures completed according to weights. According to the Water
Advances in Civil Engineering 5

Table 3: MOE’s evaluation index for deteriorated pipes.

Indirect evaluation (10 items, 100 points) Direct evaluation (12 items, 100 points)
Pipe diameter (27.3) Thickness of sediment (14.9)
Pipe type (15) Soil type (7)
Pipe thickness (12.4) Pipe internal corrosion depth (3.4)
Pipe diameter (3) Surrounding road (3)
Coating thickness (8.5) Internal corrosion circumference (3.2)
Inner pipe coating type (12) Connection method (5)
Pipe external corrosion depth (3.2) Internal coating management (7.6)
Outer pipe coating type (4) Number of leaks (7)
External corrosion circumference (2.8) Thickness of scale (7.3)
Elapsed years (37) Water quality (7)
External surface coating anagement (4.4) Hydraulic pressure (5.0)
Source: Waterworks Network Diagnosis Manual [39].

Table 4: Classification of main parameters in water distribution systems [4, 8, 36–38].

Provider Purpose Parameter
Water supply pipe Pipe material, pipe type, inner and outer pipe coating types, elapsed years, soil type,
Waterworks
(property data), number of complaints of leaks and water quality, pipe diameter, thickness and external
Network Diagnosis
deteriorated ratio corrosion depth, external corrosion circumference, thickness of scale, and others
Manual (2007,
Size configuration (loop or resin type), internal and external stagnation parts of DMA,
Ministry of Evaluation of small
occurrence of rust, scale attachment of pipe, hydraulic pressure and measurement
Environment) [38] DMA
facility in DMA, leak measurement management, and number of leaks
Fiscal self-reliance ratio, reservoir capacity, water supply population, water price cost
Leak evaluation
recovery rates, water meter (13 mm) installation rate, amount of daily water supply per
index
person, and length of deteriorated (more than 20 years) and water supply pipe
Scale of water supply (population growth rate, population of water supply per number
of demand junctions, and water supply rate), facility scale (total pipe length of DMA,
Park, IWA [23] administrative area, number and capacity of reservoirs, and water meter (13 mm)
Effective parameter
installation rate), financial condition (fiscal self-reliance ratio, investment ratios of
of revenue water
maintenance cost compared to expenditures and facility improvement cost compared
ratio
to expenditures, replacement rate of DMA pipes per year, and water price cost recovery
rates), and deteriorated facility (length of deteriorated pipe, new installation per year,
and number of leaks per number of demand junctions)
Effective parameter
Number of leaks and demand junctions, pipe age, hydraulic pressure, and nightly
Jang [40] of revenue water
minimum flow
ratio
Rise in revenue
Lee [41] Replacement rates of DMA, inlet pipe and water meter, and recovery rate of leaks
water ratio
Effective parameter
Population per pipe length in DMA, percentage of homes older than 21 years, ratio of
Chung et al. [42] of revenue water
apartment units, and installation rate of 13 mm for water meter
ratio

Supply Network Diagnosis Manual [39], the index of the 3.2. Establishment of a Parameter Classification System. Ad-
deteriorated pipe is as shown in Table 3. equate standards are mandatory when classifying the pa-
To assess the deterioration of a pipe, distinguishing in- rameters of a water distribution network selected from
direct evaluation items is possible considering design pa- among organizations and researchers. In this study, three
rameters and numerical data and direct assessment items criteria were proposed to create independent factors.
from measured values via pipeline inspection. Indirect as- The factor classification system was based on the in-
sessment includes physical property elements such as pipe herent properties of parameters. This study suggested if the
diameter, type, and external observation components such as parameters related to the water distribution network were
the number of complaints regarding leaks and water quality. more suitable for physical, operational, or socioeconomic
Direct evaluation objects include pipe data such as pipe parameters and classified them into one of these three
thickness, corrosion status, and sediment thickness in the groups.
pipeline and hydraulic pressure data generated from the dis- The scope of coverage, data availability, and data
tribution network. The assessment index of the deteriorated characteristics were considered. When data were acquired,
pipe ratio is composed of the physical components of pipelines regional characteristics could be identified according to
and includes operational components such as hydraulic whether the boundary data were divided into administra-
pressure, which is an appropriate classification system for tions or DMAs.
examining a water distribution system. Quantification of the data for the selection parameters
Table 4 lists a classification of the parameters in a water was possible. Whether the collected data were numerically
distribution system as proposed by the MOE and major valid and could be used as a standard for comparison or
domestic studies. assessment of regions was examined. If the designated
6 Advances in Civil Engineering

Table 5: Classification of effective parameters suggested for NRW management [4, 8, 36–38].
Primary Secondary Tertiary
Pipe material, mean pipe
Pipe material, type, inner or outer coating type, elapsed years, mean pipe
Pipe property diameter, length of water
diameter, pipe thickness, length of water supply pipe, and metal pipe ratio
supply pipe, and elapsed years
Amount of daily water supply per person, water supply rate, number
Water supply Amount of water supply per
of demand junctions, and reservoir capacity per pipe length of water
scale number of demand junctions
distribution systems
Physical Reservoir capacity, size, configuration (loop or resin type) and pipe Size and configuration (loop
parameters Facility scale length of DMA, area of administrative district, and number of or resin type) and pipe length
reservoirs of DMA
Evaluation, ratio and length of deteriorated pipe (age older than 20 years),
Facility Ratio and evaluation of
external corrosion depth and circumference of pipe, internal corrosion
deterioration deteriorated pipe
depth of pipe and circumference, and new pipe installation per year
∗
Included in evaluation of
Others Soil type (chemical classification)
deteriorated pipe
Leak measurement facility in DMA and management, number of
Leaks Number of leaks (10 km)
leaks (10 km), nightly minimum flow, and leak recovery rate
Hydraulic
Operational Hydraulic pressure and stagnant part of DMA Demand energy ratio
pressure
parameters
Number of complaints over water quality, self-production rate of tap ∗
Included in evaluation of
Others water, replacement rates of inlet and DMA pipe, water meter and water
deteriorated pipe
distribution pipe per year, and installation rate of 13 mm water meter
Population of water supply
Population of water supply per pipe length of water distribution
per number of demand
Population systems, population growth rate, population of water supply per
junctions and population
number of demand junctions
Socioeconomic growth rate
parameters Fiscal self-reliance ratio, water price cost recovery rates, and Fiscal self-reliance ratio and
Financial
investment ratio of maintenance cost compared to expenditures and water price cost recovery
condition
that of facility improvement cost compared to expenditures rates
Others Percentage of homes older than 21 years and ratio of apartment units —
Other
— User satisfaction —
parameters

parameters express only qualitative characteristics that parameters was also based on data collection considering the
cannot be quantified, using them in NRW management is data characteristics of selected parameters. Quantitative
difficult. parameters must be converted by using data quantification
The parameter classification system is objectively de- standards for each DMA or country.
veloped according to the characteristics of each parameter,
and this made it possible to consider all the parameters of
water distribution networks previously suggested by think 3.3.1. Direct Factors. Physical factors such as mean pipe
tanks and researchers. Parameters related to NRW are ex- diameter, pipe length, number of demand junctions, pipe
amined in regard to physical, operational, and socioeco- length per demand junction, amount of water supply per
nomic parameters. The effective parameters to NRW are demand junction, and deteriorated pipe ratio have been used
selected according to the developed classification system of in previous studies. If used for NRW management, then the
main parameters. amount of water supply and deteriorated pipe ratio were
Based on these three standards for classification, NRW chosen.
affecting parameters are classified as listed in Table 5 by using To apply physical parameters to the test bed, a pipe
three classifications with no integration or redundancy. material can be selected an additional parameter as it can
affect pipe breakage, pipe leaking, and rehabilitation that will
influence the prediction results. Selection of data is necessary
3.3. Parameter Classification per Data Quantification. Figure 1 such that rehabilitation can be connected to the deteriorated
shows selected parameters from Table 5 further considering pipe ratio.
effective NRW parameters from international studies. As Pipe materials such as cast iron and polyvinyl chloride
shown in Figure 1, the representative parameters for NRW (PVC) can affect the shape and scale in the pipe. Thus, when
management can be classified as either direct or indirect using a pipe material, a typical classification of the pipe
factors. material is required. In a general distribution network
Direct factors are physical and operational parameters, system, however, iron pipes such as cast iron or steel pipes
and indirect factors are socioeconomic parameters and are often used, so their use as categorized components can
others. Classification between quantitative and qualitative prove difficult depending on the region.
Advances in Civil Engineering 7

Quantitative parameters Qualitative parameters

Direct factor Indirect factor

Operational Socioeconomic
Physical parameter Others
parameter parameter
Pipe length per Number of leakage
Personnel User satisfaction
demand junction accidents
Water supply quantity
Demand energy ratio Billing and collection
per demand junction

Mean pipe diameter Metering practices Cost and staffing

Deteriorated pipe Economic and

Quality of service
ratio financial
Deteriorated pipe
Work control Financial performance
evaluation score

Pipe materials Service coverage

Pipe network
performance

Figure 1: Classification of leading parameters for NRW management [4].

Among the direct factors, data on the number of leaks are measurements, but the measured data differ by the type of
collected through complaints from residents, thus obtaining water meter.
reliable data for a specific area can be difficult. The demand Given its economic efficiency, a mechanical water meter
energy ratio is a parameter that represents the hydraulic is the most commonly used in Korea. Water meters include
pressure of water distribution networks. It is closely associated dry and wet types. Recently, digital ultrasonic water meters
with the number of leaks; if high hydraulic pressure is used to improve accuracy but are more costly than analog
maintained in a water distribution network, the number of types and can have power supply problems.
leaks will be increased. If the parameters of water meter accuracy, periodic mea-
The quality of water service, work control, metering surement, and demand analysis are combined, investigation of
practices, service coverage, and pipe network performance NRW characteristics of a target area might become more
are PI factors serving as operational parameters. The quality advantageous. Another crucial task is managing measurement
of service indicates whether the entire procedure of water data such that the values measured via a water meter are
supply is systematically well established, such as if the water transformed into a database and a detail analysis can follow.
supply system is worked well or the frequency of accidents is The factors of work control, pipe network performance,
low. These conditions can also contain the operation of and service coverage are related to the necessary conditions
physical factors such as valve-operating settings, pressuri- to ensure that the hydraulic pressure in a water network is
zation facilities, optimal maintenance of residual chlorine, properly regulated to provide a stable water supply.
and prevention of water quality problems. Water supply system’s managers and operators can
When calculating NRW, stable water supply assures moderate the occurrence of leaks by improving the opera-
water quality, but measures are required when water quality tion of the pipe network. For example, if the hydraulic
is difficult to maintain. One proposal seeks to preserve re- pressure is high at a junction, the volume of leaked water in
sidual chlorine concentration by reducing the residence time the water distribution network increases due to the pressure
in the pipeline in which residual chlorine concentration is energy, which leads to a higher NRW.
not maintained compared to regional water-quality criteria. To maintain an optimal junction pressure, optimal valve
In urban areas, water quality is not included as a pa- operation in the water distribution network and that of the
rameter because of the short residence time, but re- pressurization facility can lower the NRW. Thus, the wa-
habilitation time is longer in a rural area because pipe terworks operator needs to establish an optimal operating
lengths for water supply are relatively long and the demand system based on real measurement data. Service coverage
is lower than that in an urban area; rural areas are partic- varies between densely populated urban areas and rural
ularly sensitive to water quality parameters such as residual areas. The network operator must devise an operating plan
chlorine concentration. In that case, service quality con- in which the area of the DMA system should be installed to
sidering water quality parameters can affect NRW. maintain optimal supply pressure.
Metering practice means periodic measurement and Developed artificial neural network (ANN) and multiple
accuracy of water meters. Water meter provides physical regression analysis models based on data of an area where
8 Advances in Civil Engineering

a DMA system has been built can be utilized under a con- Table 6: Final selected parameters for NRW management
dition in which physical and operational element data are [4, 8, 36–38].
collected. Physical parameters are the components that have Application
the greatest influence on distribution network design. Water Classification Parameters
area
service convergence is a key element in establishing and (i) Pipe material
operating a network system and can be used for district (ii) Mean pipe diameter
determination in establishing DMA systems for operational (iii) Pipe length per number
planning and effective NRW forecasting. Physical of demand junctions
(iv) Amount of water supply Administrative
per number of demand junction area, DMA
3.3.2. Indirect Factors. In this section, we analyzed the in- (v) Deteriorated pipe ratio
direct factors related to social and economic factors. Because (vi) Number of leaks
NRW is estimated based on measured data, it is difficult to Operational (vii) Leak recovery ratio
(viii) Demand energy ratio
expect and introduce social and economic parameters. The
determination of NRW and physical and operational pa- (ix) Water price cost
recovery rates
rameters is influenced by socioeconomic parameters; thus,
(x) Investment ratio of
regional characteristics and socioeconomic factors should be maintenance cost to
considered when evaluating operational data. This can expenditures
support the analytical result of NRW. (xi) Investment ratio of Administrative
Indirect factors are classified as socioeconomic factors Socioeconomic
facility improvement area
and others. Socioeconomic factors have a social element cost to expenditures
representing the population density of a district and can be (xii) Population of water
used to consider the characteristics of urban and rural areas. supply per number of
These parameters differ depending on the grade of urban demand junctions
development. Densely populated areas tend to have shorter (xiii) Fiscal self-reliance ratio
water pipe lengths and a lower NRW because of the higher
probability of preventing water leaks. by users and operators. Waterworks system should be de-
Financial and economic factors indicate the financial veloped to quantify user opinions.
strength of a city and the economic life of residents. De-
veloped economies have higher budgets for social in- 4. Final Parameter Selection for
frastructure than those of developing economies, and quality NRW Management
control is performed periodically. Developed economies also
are highly likely to use high technology in the operation and The final selected parameters via the classification system
management of water distribution systems. These financial described in Section 3 are shown in Table 6. The selected
and economic factors help us to reduce leaks by reducing parameters are determined based on parameters that can be
their occurrence and optimizing a pipe network’s operation. quantified. Qualitative parameters are classified according to
Financial performance parameters can be connected as local characteristics. If parameter quantification is possible,
an extension of the secondary factor of economic and fi- qualitative parameters can be used via an additional data
nancial components. An efficient financial system leads to conversion process. Based on the parameters selected via the
better financial performance that in turn leads to long-term factorization scheme described in Section 3, parameters
investment and management of water infrastructure and including subcategorization based on quantifiability were
holds an advantage in designing projects such as increasing selected.
the revenue/water ratio. Cost and staffing are parameters Among the all parameters described in Section 3.2, the
related to staff works, recruitment, and management fees for selected physical parameters are mean pipe diameter, pipe
waterworks operations. Optimal cost management and staff material, amount of water supply per number of demand
operations are expected to decrease the occurrence of leaks. junctions, pipe length per number of demand junctions, and
Billing and collection include a factor that determines deteriorated pipe ratio. Operational parameters include the
whether billing is regularly collected. A higher water rate number of leaks and the ratio of energy demand and leak
results in a greater advantage, and billing and collection recovery.
helps in managing infrastructure. Funding is essential for the Among the socioeconomic parameters, parameter clas-
periodic rehabilitation of existing facilities and introduction sifications and qualitative parameters are selected. As so-
of new equipment. In addition, appropriate collection of cioeconomic parameters, the population of the water supply
water fees can be used to invest in water infrastructure. per the number of demand junctions, fiscal self-reliance ratio,
Among indirect factors, user satisfaction shows the grade of water price cost recovery rates, and the investment ratio of
optimization in efficient restoration and minimization of maintenance costs for facility improvement to total expen-
operational problems from accidental parameters that can ditures were determined.
occur in the water distribution networks such as pipeline Data acquisition from DMAs and socioeconomic
breakage and leaks. A key task is realizing the indicators parameters is difficult while physical and operational
because of the potential for personal opinions to be reflected parameters are applicable in DMAs and administrative
Advances in Civil Engineering 9

districts. To apply socioeconomic parameters, the acqui- References

sition of statistical data is required and is completed by
subdividing DMA data into administrative districts because [1] J. G. Saldarriaga, S. Ochoa, M. E. Moreno, N. Romero, and
it depends on measured data classified into administrative O. J. Cortes, “Prioritized rehabilitation of water distribution
networks using dissipated power concept to reduce non-
districts. Thus, analyses of the specific region where water-
revenue water,” Urban Water Journal, vol. 7, pp. 121–140,
works statistics data are available are necessary for the data 2010.
collection on physical, operational, and socioeconomic [2] A. Ercumen, J. S. Gruber, and J. M. Colford, “Water distri-
parameters. bution system deficiencies and gastrointestinal illness: a sys-
tematic review and meta-analysis,” Environ Health Perspect,
vol. 122, pp. 651–660, 2014.
5. Conclusions [3] J. L. Ellen and J. S. Kellogg, “Deficiencies in drinking water
distribution systems in developing countries,” Journal of
A parameter classification process for NRW management Water Health, vol. 3, pp. 109–27, 2005.
was suggested for water distribution systems. For this [4] D. W. Jang, Estimation of Non-Revenue Water Ratio Using
purpose, the major water leakage parameters and the factors PCA and ANN in Water Distribution Systems, Ph.D. thesis,
related to NRW in a water distribution network were in- Incheon National University, Incheon, Republic of Korea,
vestigated. In particular, the process was classified according 2017.
to the characteristics of the parameters, and quantitative and [5] M. Malcolm Farley, “Non revenue water–international best
qualitative parameters were classified to help in NRW practice for assessment, monitoring and control,” in Pro-
management using statistical analysis. ceedings of the 12th Annual CWWA Water, Wastewater and
The generation of the parameter classification process Solid Waste Conference, Atlantis, Paradise Island, Bahamas,
was based on the physical, operational, and socioeconomic September–October 2003.
[6] R. Frauendorfer and R. Liemberger, The Issues and Challenges
parameters that can use for NRW analysis. This classification
of Reducing Non-Revenue Water, Asian Development Bank,
system can be applied to NRW management using the
Mandaluyong, Philippines, 2010.
quantified data of selected parameters. The study determined [7] V. R. Shinde, N. Hirayama, A. Mugita, and S. Itoh, “Revising
if the parameters related to a water distribution system were the existing performance indicator system for small water
more appropriate for physical, operational, or socioeco- supply utilities in Japan,” Urban Water Journal, vol. 10, no. 6,
nomic factors and classified them into one of these three pp. 377–393, 2013.
categories. [8] V. Kanakoudis, S. Tsitsifli, and A. I. Zouboulis, “WATERLOSS
To increase the accuracy of NRW management, socio- project: developing from theory to practice an integrated
economic parameters such as fiscal self-reliance ratio, approach towards NRW reduction in urban water systems,”
population of water supply per demand junction, water price Desalination and Water Treatment, vol. 54, no. 8, pp. 2147–
cost recovery rates, investment ratio of facility improve- 2157, 2015.
ment cost to expenditures, and investment ratio of main- [9] A. S. Wyatt, Non-Revenue Water: Financial Model for Optimal
Management in Developing Countries, RTI Press, Amman,
tenance cost to expenditures are required. It is anticipated
Jordan, 2010.
that the NRW accuracy will be improved if additional so-
[10] D. W. Jang and G. W. Choi, “Estimation of non-revenue water
cioeconomic factors can be expressed by physical and op- ratio for sustainable management using artificial neural
erational parameters. network and z-score in Incheon, Republic of Korea,” Sus-
If the accuracy of NRW prediction is low using the direct tainability, vol. 9, no. 11, pp. 1–15, 2017.
factors, it is recommended that NRW prediction be applied [11] H. Alegre, W. Hirner, J. M. Baptista, and R. Parena, Perfor-
using socioeconomic factors. Socioeconomic factors are mance Indicators for Water Supply Services, IWA Publishing,
considered to be helpful in explaining complex NRW London, UK, 2000.
phenomena that have limited data acquisition such as ad- [12] H. Alegre, W. Hirner, J. M. Baptista et al., Performance In-
ministrative districts and DMAs but cannot be explained by dicators for Water Supply Services, IWA Publishing, London,
physical factors. UK, 2nd edition, 2006.
Because socioeconomic parameter data in water distri- [13] H. Alegre, W. Hirner, J. M. Baptista et al., Performance In-
dicators for Water Supply Services, IWA Publishing, London,
bution networks are acquired from administrative districts,
UK, 3rd edition, 2017.
a disadvantage is that data acquisition for a DMA is difficult. [14] A. O. Lambert and W. H. Hirner, Losses from Water Supply
Thus, one solution for NRW management is a data utili- System: Standard Terminology and Performance Measure,
zation system for data collection and research that can IWA the Blue Pages, International Water Association,
quantify the classification system of the unquantified data. It London, UK, 2000.
is expected that more accurate NRW management will be [15] A. O. Lambert, International Report on Water Losses Man-
possible if a data utilization system is activated. In addition, agement and Techniques, Water Science and Technology:
cooperation among administrative districts for data pro- Water Supply, Vol. 2, IWA Publishing, London, UK, 2002.
vision should be implemented. [16] R. Liemberger, “Do you know how misleading the use of
wrong performance indicators can be?,” in Proceedings of
the IWA Managing Leakage Conference, Lemesos, Cyprus,
Conflicts of Interest November 2002.
[17] S. W. Park, T. Y. Kim, K. Y. Lim, and H. D. Jun, “Fuzzy
The authors declare that they have no conflicts of interest. techniques to establish improvement priorities of water
10 Advances in Civil Engineering

pipes,” Journal of Korea Water Resources Association, vol. 44, study for Tel Aviv,” Urban Water Journal, vol. 8, no. 2,
no. 11, pp. 903–913, 2011. pp. 103–118, 2011.
[18] C. S. Park, A Case Study on Establishment of Block System for [34] A. Milman and A. Short, “Incorporating resilience into
the Increase of Revenue Water in Distribution Systems, sustainability indicators: an example for the urban water
Master’s thesis, Chonnam National University, Gwangju, sector,” Global Environmental Change, vol. 18, no. 4,
Republic of Korea, 2014. pp. 758–767, 2008.
[19] I. C. Park, K. W. Kwon, W. C. Cho, and K. H. Cho, “Study on [35] L. Tuhovčák, M. Svoboda, Z. Sviták, and K. Tothova, The
the decision priority of rehabilitation for water distribution Technical Audit of Water Distribution Network Using the
network based on prediction of pipe deterioration,” in Different Leakage Indicators, IWA Leakage, London, UK,
Proceedings of the Korea Water Resources Association 2005.
Conference, pp. 1391–1394, Daejeon, Republic of Korea, May [36] V. K. Kanakoudis and D. K. Tolikas, “The role of leaks and
2006. breaks in water networks-technical and economical solu-
[20] D. W. Jang, H. S. Park, and G. W. Choi, “Estimation of leakage tions,” Aqua, vol. 50, pp. 301–311, 2001.
ratio using principal component analysis and artificial neural [37] V. K. Kanakoudis, “A troubleshooting manual for handling
network in water distribution systems,” Sustainability, vol. 10, operational problems in water pipe networks,” Aqua, vol. 53,
no. 3, pp. 1–13, 2018. pp. 109–124, 2004.
[21] H. G. Jo, Study on Influence Factors of Non-Revenue Water for [38] S. Tsitsifli, V. Kanakoudis, C. Kouziakis, G. Demetriou, and
Sustainable Management of Water Distribution Networks, S. Lappos, “Reducing non-revenue water in urban water
Ph.D. thesis, Incheon National University, Incheon, Korea, in distribution networks using DSS tools,” Water Utility, vol. 16,
Korean, 2017. pp. 25–37, 2017.
[22] H. G. Jo, G. W. Choi, and D. W. Jang, “Development of the [39] Ministry of Environment, Waterworks Network Diagnosis
non-revenue water analysis equation through the statistical Manual, Ministry of Environment, Sejong City, Republic of
analysis of main parameter in waterworks system in Incheon Korea, 2007.
city,” Crisis and Emergency Management, vol. 12, no. 11, [40] J. K. Jang, “A Study on Priority Estimation Model of Water
pp. 63–75, 2016, in Korean. Distribution System Maintenance Using the Non Revenue
[23] H. S. Park, Study on Korean-ILI Estimation Using the Revenue Water Reduction Factors,” Master’s thesis, University of
Water Rate, Master’s thesis, Chungbuk National University, Seoul, Republic of Korea, 2012, in Korean.
Cheongju, Republic of Korea, 2014. [41] J. M. Lee, “A Study on Cost Benefit Analysis and Leakage
[24] H. E. Mutikanga, S. K. Sharma, and K. Vairavamoorthy, Reduction Prediction Model for Revenue Water Ratio En-
“Assessment of apparent losses in urban water systems,” hancement Project,” Master’s thesis, University of Seoul,
Water and Environment Journal, vol. 25, no. 3, pp. 327–335, Republic of Korea, 2013, in Korean.
2011. [42] S. H. Chung, H. K. Lee, J. Y. Koo, and M. J. Yu, “Charac-
[25] Wikipedia, Non-Revenue Water, 2018, https://en.wikipedia. terization of the Ratio of Revenue Water in the 79 Cities by
org/wiki/Non-revenue_water. Principal Component Analysis and Clustering Analysis,” in
[26] M. Farley, G. Wteth, Z. B. M. Ghazali, A. Istandar, and Proceedings of Korean Society of Water & Wastewater,
S. Singh, The Manager’s Non-revenue Water Handbook: A Daejeon, Republic of Korea, 2014, in Korean.
Guide to Understanding Water Loses, United States Agency
for International Development, Bangkok, Thailand, 2008.
[27] W. Winarni, “Infrastructure leakage index (ILI) as water
losses indicator,” Civil Engineering Dimension, vol. 11,
pp. 126–134, 2009.
[28] C. Van den Berg, The Drivers of Non-revenue Water: How
Effective are Non-Revenue Water Reduction Programs?, Policy
Research Working Paper Series 6997, The World Bank,
Washington, DC, USA, 2014.
[29] S. H. Chung, H. K. Lee, J. Y. Koo, and M. J. Yu, “Charac-
terization of the ratio of revenue water in the 79 cities by
principal component analysis and clustering analysis,” in Joint
Conference of KSWQ and KSWW (The Korean Society of
Water and Wastewater and Korean Society of Water and
Wastewater), pp. 133–142, February 2004.
[30] V. Kanakoudis and S. Tsitsifli, “Results of an urban water
distribution network performance evaluation attempt in
Greece,” Urban Water Journal, vol. 7, no. 5, pp. 267–285, 2010.
[31] A. A. R. Ioris, C. Hunter, and S. Walker, “The development
and application of water management sustainability in-
dicators in Brazil and Scotland,” Journal of Environmental
Management, vol. 88, no. 4, pp. 1190–1201, 2008.
[32] U. Palme and A. M. Tillman, “Sustainable development in-
dicators: how are they used in Swedish water utilities?,”
Journal of Cleaner Production, vol. 16, no. 13, pp. 1346–1357,
2008.
[33] T. T. H. Duong, “Urban water management strategies based
on a total urban water cycle model and energy aspects–case
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