Development of performance indicators for small Quebec drinking water utilities

Journal of Environmental Management 73 (2004) 243–255 www.elsevier.com/locate/jenvman

Development of performance indicators for small Quebec drinking water utilities Housseini D. Coulibalya,1, Manuel J. Rodriguezb,* a

Institut national de la recherche scientifique—centre Eau, Terre & Environnement (INRS—ETE), Universite´ du Que´bec, 2800, rue Einstein, C.P. 7500, Sainte-Foy, Que., Canada G1V 4C7 b´ Ecole supe´rieure d’ame´nagement du territoire et de de´veloppement re´gional (E´SAD), Universite´ Laval, 1624, pavillon F.-A.-Savard, Sainte-Foy, Que., Canada G1K 7P4 Received 15 December 2003; revised 26 June 2004; accepted 21 July 2004

Abstract This study presents a comparative performance analysis of small drinking water utilities in Quebec (Canada). The investigation bears on 10 utilities that use surface water or groundwater under the direct influence of runoff and apply chlorination as the only treatment before distribution. The utilities under study were divided into two groups: four utilities that had never or rarely provided water violating provincial drinking water microbiological standards (relating to fecal and/or total coliform bacteria), called nonproblematic utilities, and six utilities that quite often violated the standards, designated as problematic utilities. The objective of the study is to develop utility performance indicators capable of explaining current and historical distributed water quality. Indicators are based on operational, infrastructure, and maintenance characteristics of utilities that are integrated using a multivariable weight-based index. Results show that utility performance indicators are systematically better for the nonproblematic group of utilities as compared to the problematic group. Disinfection-related, infrastructure, and maintenance variables are those that most contributed to indicator values. Sensitivity analyses served to assess the impact on indicator results of excluding variables and changing their weights. q 2004 Elsevier Ltd. All rights reserved. Keywords: Drinking water; Water quality; Small utilities; Performance indicators

1. Introduction There are about 1000 small municipal drinking water utilities (i.e. serving 10,000 people or less) in the Province of Quebec, Canada (Gouvernement du Que´bec, 1997, 2003). Utilities of that size are the most numerous in the province. In other respects, it is a well-known fact that small utilities often lack adequate technical, managerial, and financial capacity (USEPA-DWA, 2003). In Quebec, small municipal utilities that use chlorination as the only treatment applied to drinking water before its distribution * Corresponding author. Tel: C1-418-656-2131x8933; fax: C1-418656-2018. E-mail addresses: [email protected] (H.D. Coulibaly), [email protected] (M.J. Rodriguez). 1 Tel.: C1-418-654-3102; fax: C1-418-654-2600. 0301-4797/$ - see front matter q 2004 Elsevier Ltd. All rights reserved. doi:10.1016/j.jenvman.2004.07.003

to their customers were found to be those with the most frequent violations of provincial drinking water standards with respect to microbiological quality (Gouvernement du Que´bec, 1997). The new Quebec Drinking Water Regulations (QDWR) published in June 2001 (Gouvernement du Que´bec, 2001) have affected, or will affect, infrastructure needs and human resources in practically all small Quebec drinking water utilities. This is due to a number of new requirements concerning microbial inactivation/removal and other water quality parameters as well as utility characteristics and personnel training (Gouvernement du Que´bec, 2001). The role of the distribution system infrastructure in serving drinking water of irreproachable quality is vital. For instance, storage tanks (Opferman et al., 1995) and physical properties of distribution mains (LeChevallier et al., 1990) play a significant role in the ability of utility managers to

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maintain adequate water quality from the point of treatment to the point of consumption. In recent years, numerous publications have focused on the impact of some distribution system infrastructure components (e.g. pipe material, storage tanks) on consumer tap water quality (for example AWWA, 1998; Opferman et al., 1995). However, very few of those studies considered the impact of the supply system as a whole, including source characteristics, treatment, storage, distribution, and all other components. Interest in these aspects has been much higher in median and large utilities than in small ones. The objective of this study is to develop utility performance indicators capable of explaining current and historical distributed water quality in small utilities. The investigation considers a set of small Quebec utilities as cases under study.

2. Methodology 2.1. Procedure for selecting cases at study Data for 1997, 1998, and 1999 from a Quebec Ministry of Environment (QME) database on regulatory follow-up (Gouvernement du Que´bec, 1984) were used to identify two types of small utilities. The first type included utilities that had never registered coliform positive samples, or that had registered such samples only on extremely rare occasions. The second type involved utilities that often registered coliform positive samples. A coliform episode indicated one or a set of coliform positive samples occurring in a given distribution system during the 3year period (1997–1999), separated by at least 15 days from any other coliform positive sample in the same system. Utilities that registered no coliform episode, or had episodes in only one of the above-mentioned 3 years, were designated as nonproblematic utilities. A problematic utility was defined as a utility that registered one or more coliform episodes in at least two of the three reference years. It is important to note that the QME database in question comprised data from 927 small Quebec utilities with results of about 65,000 water sample analyses for the above-mentioned 3-year period. It was noted that 25% of the 927 utilities (that is, about 230 utilities) had experienced repetitive coliform episodes. It was precisely this fact that led to the differentiation into ‘nonproblenonproblematic’ and ‘problematic’. Among utilities appearing in the QME database, 10 were subsequently chosen for the present study. The selection of these 10 utilities was based on the following criteria: (1) they used either surface water (lake or stream) or groundwater under direct influence of runoff (surface wells); (2) chlorination was the only treatment applied; (3) for logistic reasons, they had to be located relatively close (within a radius of about 150 km) to Quebec City; (4) the 10 utilities encompassed a group of nonproblematic utilities and a group of problematic utilities; and (5) utility

managers had to be in agreement with the proposed study and co-operate by allowing easy access to all infrastructure components and archived water quality data, and being available for interviews. On the basis of these criteria, four nonproblematic and six problematic utilities were selected. 2.2. Information about the distribution system infrastructure Information about distribution system infrastructure centered on characteristics such as chlorination plant and machinery, storage tanks, and distribution network (pipelines). To gather this information, a questionnaire was prepared in October 2001 and the manager of each of the 10 utilities was asked to complete it during a semi-directive interview with inquiries focused on distribution system components, operational practices (i.e. disinfection-related variables), and maintenance practices. Questions about the distribution system infrastructure bore on the presence/ absence of some components (e.g. emergency chlorinator), dimensions or capacity of others (e.g. storage tanks), or the relative importance of some kinds of material (e.g. percent of cast iron pipes, of PVC pipes, etc. in the total length of the distribution lines). Questions about operational practices concerned details such as the method of chlorine injection or the frequency of chlorine residual measurements. Questions on maintenance practices centered essentially on distribution network flushing and pipe break management. In addition, personal observations made by the authors during an 8-month field work corresponding to a sampling campaign in the 10 concerned municipalities in 2001, as well as all information drawn from local archives or from conversations with utility personnel were also considered. 2.3. Description of considered variables Five groups of variables were considered for the development of the utility performance indicators. The groups represented variables describing agricultural land use, raw water quality, water disinfection, distribution system infrastructure/maintenance and distributed water quality in the small utilities. Each group provides a performance sub-indicator, except for the distributed water quality variable group, which directly provides the current tap water quality indicator. 2.3.1. Agricultural land use variable The first variable retained for utility performance indicator development was an environmentally relevant variable concerning agricultural land use within the territory of the 10 municipalities owning the water utilities. The concerned variable referred to agricultural pressure linked with potential phosphorus (P2O5) surplus in each municipality’s territory. This variable was considered because it

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showed some significance in a previous study of Quebec small utilities (Coulibaly and Rodriguez, 2003a). 2.3.2. Raw water quality variables A number of major raw water characteristics were included as variables in the determination of performance indicators. These characteristics were considered according to a previous study bearing on the same 10 utilities (Coulibaly and Rodriguez, 2003b). The considered raw water quality variables were total organic carbon (TOC), turbidity, total coliform bacteria, heterotrophic plate count (HPC) bacteria and atypical bacteria. The fact that raw water quality variables were considered for the development of utility performance indicators is justified by the primary importance of source water quality for the studied utilities, since no treatment other than chlorination was applied. The absence of other kinds of treatment (e.g. coagulation, flocculation, settling, filtration) makes the removal of natural organic matter and potential parasite cysts or oocysts very difficult. Thus, the capacity of such utilities to supply good quality water is much more dependent on source water quality than in larger utilities. 2.3.3. Disinfection-related variables 2.3.3.1. Chlorination devices. The presence or absence of an emergency chlorinating device (or chlorinator) in the distribution system was the first disinfection-related variable examined. The emergency chlorination devices variable is of great importance, since the fact of possessing functional emergency chlorination installations allows ensuring the disinfection safety and effectiveness at any time. Therefore, this variable was considered as having a potential impact as intrinsically expressed through the disinfection effectiveness variable described in Section 2.3.3.3. 2.3.3.2. Mode of chlorine injection. Chlorinating according to flowrate over time is probably one of the most common practices for water disinfection or residual chlorine maintenance, since it permits automatic adjustment of the applied chlorine doses concurrently to water demand ups and downs (AWWA, 1994). Therefore, the mode of chlorine injection is of great importance too, since it is very likely to affect disinfection effectiveness. Thus, this variable was also considered as having its potential impact intrinsically expressed through the disinfection effectiveness variable commented on hereafter. 2.3.3.3. Disinfection effectiveness. The efficacy of drinking water disinfection procedures is estimated using the CT concept. The CT is a concept that aims at ensuring sufficient contact time (T) and maintaining an adequate disinfectant residual concentration (C) to attain inactivation objectives (Gouvernement du Que´bec, 2002; USEPA, 1999). This is

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a concept universally recognized and utilized by drinking water specialists worldwide (WHO, 2003; Gouvernement du Que´bec, 2002; Edwards et al., 2002; Cowley, 2000; USEPA, 1999). Pathogens contained in source waters must be removed before water is served to consumers. Microbial cells can be eliminated either by physical removal (i.e. via diverse filter media) or by chemical inactivation (i.e. using disinfecting agents). The resulting ‘log’ of cell reduction can be estimated as follows: X Log of reduction Z physical removals X C chemical inactivations ð1Þ Since the 10 small utilities of this study have no treatment other than disinfection (i.e. chlorination), only inactivation can be considered. Therefore, chlorination is the only barrier between potential source water pathogens and the consumer’s tap. Consequently, it is essential to ensure that this barrier be as effective as it could be. Disinfection effectiveness is evaluated in terms of ‘log’ of inactivation (Gouvernement du Que´bec, 2002; USEPA, 1999). This value is determined using the following formula: Log of inactivation Z CTavailable =CTrequired

(2)

As its name suggests, the CTavailable is the actual CT value measured at the utility by the designers. CTrequired is a value provided in tables compiled by the USEPA (1991, 1999) that indicates the required CT value to inactivate 1 log of a given microorganism (virus or Giardia or Cryptosporidium) in water with given characteristics (pH, temperature, etc.) (Gouvernement du Que´bec, 2002) CTavailable Z Cresidual !T10 Z Cresidual !Vu =QMAX !T10 =T

(3)

where Cresidual is the disinfectant concentration at the chlorination facility storage tank outlet; QMAX is the peak flowrate at the storage tank outlet; Vu is the useful volume in the storage tank (where chlorine mixes, since none of the 10 utilities possesses a specific chlorine contact basin); and, T10/T is the hydraulic efficiency factor. 2.3.3.4. Frequency of residual chlorine measurement. Frequent checking of disinfectant residuals favors timely adjustment of applied doses. Therefore, the frequency of residual chlorine measurement is considered an important operational variable and, as such, is included in the disinfection-related performance sub-indicator. 2.3.3.5. Usual residual chlorine checkpoints. Since drinking water quality varies all along distribution lines

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(Rodriguez et al., 2002a,b; Se´rodes et al., 2001; Rodriguez and Se´rodes, 1999), the appropriateness of residual chlorine checkpoints appears important in terms of operational possibilities. Essentially, residual chlorine checkpoints were identified at the chlorination facility outlet, in the central part of the distribution system, and at system extremity. Checking for free chlorine residuals at the facility outlet is somewhat dictated by present QDWR, since the latter require that utility managers ensure a minimum of 0.3 mg/l free chlorine concentration at the facility outlet. Nonetheless, proper checking is certainly a sign of good management routine. Thus, this variable too was included in the disinfection-related performance sub-indicator. 2.3.4. Variables on distribution system infrastructure and maintenance 2.3.4.1. Utility age. Aging water mains, especially those made of iron-based material, can cause water quality deterioration within the distribution network, particularly through corrosion. In addition to favoring precipitation of metal ions which can cause colored water, pipe corrosion may favor the formation of tubercles within which a biological film can form or cause breaks in the main, both conducive to the deterioration of microbiological water quality (LeChevallier et al., 1990). For these reasons, the age factor was included among those retained for utility performance indicator development. 2.3.4.2. Storage tanks. Storage tanks may have different kinds of impacts on distributed water quality according to their physical and (or) chemical properties (Opferman et al., 1995). Based on internal wall properties, tanks may improve chlorine contact with bulk water, thereby enhancing microbial inactivation. However, when tank capacities are large and water demand low (i.e. water travel time too long), storage tanks can also become locations, where chlorine residuals undergo rapid decay even before water begins to travel through the distribution network, en route for the consumer’s tap. Since none of the small utilities under study possesses a chlorine contact basin, the clear water storage tank plays a significant role in the effectiveness of disinfection. Therefore, the storage tank variable was considered part of the CT variable described in Section 2.3.3.3. 2.3.4.3. Pipe material. The type of pipe (i.e. cast iron pipe, PVC pipe, etc.) chosen by utility designers and managers is of great importance in terms of distributed water microbiological and physicochemical quality. For example, as mentioned earlier, iron-based pipe material may cause water quality deterioration within the distribution network through corrosion, with its corollary being colored water, tubercles and biofilm formation, and even main breaks (LeChevallier et al., 1990). Further attempts to characterize the impact of pipe

material on tap water quality will be made later (see Section 2.4) through the development of related sub-indicators. 2.3.4.4. Flushing. Periodical flushing may be an efficient way to ensure overall distribution system healthiness, since it makes it possible to remove biofilm and corrosion tubercles, both favoring drinking water microbiological quality deterioration within distribution lines (Antoun et al., 1999; Duranceau et al., 1999). Therefore, the distribution system flushing variable was retained for the utility performance indicator development. 2.3.4.5. Main breakage. Main breaks are known to be a possible gate for microorganism and other contaminant entrance into distribution systems (McDonald et al., 1994; CMHC, 1992). This means that proper management of drinking water main breaks can only prove beneficial to the ultimate quality of consumer tap water. For this reason, the main breakage variable was included in the utility performance indicator. 2.3.5. Distributed water quality variables Three major distributed water quality characteristics were included as variables in the determination of performance indicators. Like raw water quality variables, these characteristics were taken from a previous study on the same 10 utilities (Coulibaly and Rodriguez, 2003b). Table 1 provides an overview of the spatial variation of water quality from the source (i.e. raw water) to the extremity of the distribution system, passing through the entrance (that is, the chlorination facility outlet) and the center (that is, the central part) of the system. For the purpose of indicator development, the selected water quality variables were free chlorine residual, HPC bacteria and atypical bacteria in the distribution system. These variables represented current tap water quality and were the components of the utility current tap water quality indicator, the one that the utility performance indicator is designed to explain. 2.4. Method for indicator development A great deal of literature has been produced on water and environmental quality indices or indicators over the past three decades (Lence and Ruszczynski, 2001; Cluis and Laberge, 2001; Zandbergen and Hall, 1998; UNEP, 1994; Couillard and Lefebvre, 1986; Be´ron et al., 1982; Ball et al., 1980; Porcella et al., 1980; Dunette, 1979; Ott, 1978; Yu and Fogel, 1978; Brown et al., 1970). Unlike usual water quality indices that are generally intended for characterizing a variable’s ‘state of being’ in relation to a specified use (Laroux and Weber, 1994), the performance indicators that are being developed herein are oriented towards explaining a situation or demonstrating a phenomenon. As a matter of fact, these indicators will aim at explaining why the distributed water quality is better in

Utility historical water quality status

Raw water quality

Turbidity (ntu)a

Nonproblematic II 1.26 III 0.26 V 0.54 VII 0.22 Problematic I 1.06 IV 0.50 VI 0.55 VIII 0.18 IX 0.26 X 0.14 a b c d

TOCb (mg/l)a

Distributed water quality

Total coliform Bacteria (cfu/ 100 ml)a

HPCc bacteria (cfu/ml)a

Atypical bacteria (cfu/ 100 ml)a

Chlorine residuals (mg/l)d

Entrance

Center

HPC bacteria (cfu/ml)d

Extremity

Entrance

Center

Atypical bacteria (cfu/100 ml)d

Extremity

Entrance

Center

Extremity

3.20 1.36 0.53 2.51

28 11 30 3

1544 638 526 106

329 161 187 12

1.54 0.46 0.57 0.18

0.76 0.21 0.38 0.06

0.64 0.21 0.29 0.04

8 20 17 6

44 88 24 31

54 82 35 38

1 10 2 1

1 3 0 1

1 5 0 0

4.16 0.59 0.29 0.84 0.85 1.78

41 17 2 20 4 5

1052 2212 886 155 672 332

239 111 28 91 84 145

0.68 0.61 0.44 0.09 0.31 0.19

0.02 0.51 0.15 0.04 0.20 0.02

0.02 0.49 0.09 0.07 !0.01 0.04

10 50 20 32 46 9

128 56 32 40 86 116

112 58 131 43 265 79

15 18 81 1 15 2

9 13 0 0 16 28

16 6 0 0 20 37

Average of 5-monthly values. Total organic carbon. Heterotrophic plate count bacteria. Average of 5-monthly values at each location.

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Table 1 Overview of water quality in the studied utilities during the 2001 field study (utilities numbered I–X)

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nonproblematic utilities than in problematic utilities, thereby demonstrating the impact of a number of crucial variables on current (i.e. recent) water quality. As indicated by Be´ron et al. (1982), for identification of good indicators, it is better to consider only a few crucial variables, rather than attempt to include all variables that may influence the phenomenon being characterized. For indicator development, the procedure used was the following. First, four explanatory ‘subindicators’ were identified. These sub-indicators corresponded to the following four variable groups: agricultural land use, raw water quality, disinfection-related, and infrastructure and maintenance. The four sub-indicators were used to calculate a performance indicator for each of the 10 utilities at study. Then, overall performance indicators were determined for both nonproblematic and problematic groups of utilities. The overall performance indicators were calculated based on a non-weighted average of the four or six values representing each type of utility performance sub-indicator in the nonproblematic and problematic utility groups, respectively (for more computation details, see Section 3.4, paragraph 2). Finally, the overall indicators for the two utility groups were compared to each other, and then put in relation with recent distribution water quality (generated in 2001), which was represented by an indicator based exclusively on the three distributed water quality variables mentioned in Section 2.3.5. For this study, the indicator computation method used was the weighted additive method. This method was preferred to other methods (e.g. weighted multiplicative method) because it allows linear transformation of performance points into primary indicators. Most importantly, the weighted additive method, which is based on arithmetic mean, avoids assigning too much importance to low performance scores. Therefore, this method is less severe than the weighted multiplicative method, which is based on geometric mean (Couillard and Lefebvre, 1986). The weighted additive method proceeds as follows: the parameter (or variable) values are transformed into performance scores, and the latter are weighted and added up to produce a unique value (Couillard and Lefebvre, 1986; Be´ron et al., 1982; Ball et al., 1980; Yu and Fogel, 1978). The general formula utilized for computations is the following Ip Z

n X

wi gi Z w1 g1 C w2 g2 C/C wn gn

iZ1

where Ip wi gi n

is is is is

the the the the

utility performance indicator; weight for the ith variable; performance score of the ith variable; number of variables.

(4)

3. Results and discussion 3.1. Disinfection effectiveness computation The CT value constitutes an important piece of information among disinfection-related variables involved in the indicator development process. It is important to note that, because of the close relationships between some of the involved variables, a number of them were considered as having their potential impact already expressed through connected variables that were retained for indicator development. As an example, the CT variable encompassed considerations such as temperature, pH, free chlorine residual following chlorination, and storage tank characteristics. Some of those parameters or characteristics contributed either directly or indirectly to the CT value computation. CT values were estimated for each utility using Eq. (3). Cresidual was estimated by taking the mean of residual chlorine concentrations recorded at the facility outlet and the distribution system central part, since there was no sampling point available directly at storage tank outlets. QMAX was obtained directly from utility managers, who considered it as equaling the overall power of available distribution system feed pumps. Vu was considered as equaling 80% of the storage tank capacity. The T10/T factor (which varies between 0 and 1) was estimated in a conservative way: equal to 0.2 when chlorinated water is stored in a tank before its distribution, and equal to 0.6 when chlorination occurs directly in the water main en route to the consumer’s tap. Based on these considerations, approximate CT values were calculated for the utilities under study (Table 2). These estimated CT values were calculated using the relatively limited data available from the 10 utility managers. The CT values enabled relative comparisons between nonproblematic and problematic utilities with respect to disinfection efficacy. Judging by calculated CT values in Table 2, the maximum reasonable disinfection objective for the utilities Table 2 Estimated CT-values (mg min/l) for utilities at study Utility historical water quality status Nonproblematic II III V VII Problematic I IV VI VIII IX X

Cresidual (mg/l)

QMAX (m3/min)

Vu (m3)

T10/T

CT

1.15 0.34 0.48 0.12

1.36 0.55 1.62 0.34

545 726 2724 908

0.6 0.2 0.6 0.2

276 90 485 64

0.35 0.56 0.30 0.07 0.26 0.10

0.55 0.90 0.55 0.38 0.76 0.90

1090 291 1090 458 726 218

0.2 0.2 0.6 0.6 0.2 0.2

139 36 357 51 50 5

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under study appeared to be 4-log virus inactivation (required by the 2001 QDWR for surface water utilities), which is achievable with a CT of 15–60 mg min/l for most temperatures according to USEPA (1999). 3-log Giardia cysts and particularly 2-log Cryptosporidium oocysts inactivation (two of the many other requirements under the terms of the 2001 QDWR for surface water utilities) will necessitate supplementary disinfection, most probably ultraviolet (UV) radiation or ozone (O3). Note that while chlorine can achieve 3-log Giardia cyst inactivation, the CT requirement for 3-log inactivation of 100 to more than 300 mg min/l requires high chlorine doses and (or) long contact times (USEPA, 1999). 3.2. Variable weight (wi) considerations All individual variables were assigned a weight, according to the relative importance of each based on pertinent literature indications (e.g. Couillard and Lefebvre, 1986; Be´ron et al., 1982) and the concrete statistical levels of significance exhibited by each variable in earlier studies of the concerned utilities (Coulibaly and Rodriguez, 2003a,b). The parameters that exhibited the strongest significance in those studies (e.g. disinfection-related ones) were assigned greater weights. In addition, a number of major utility characteristics that could not be considered in earlier studies, by reason of their very nature, were added up. These variables relate to distribution system operation, infrastructure and maintenance and are described in Sections 2.3.3 and 2.3.4. The assignment of weights to variables was based on literature indications (Couillard and Lefebvre, 1986; Be´ron et al., 1982; Ball et al., 1980; Yu and Fogel, 1978; Brown et al., 1970). A sensitivity analysis was also performed to test the obtained indicators (see Section 3.5). Individual variable weights were conferred taking into account the fact that the sum of all of them must be equal to 1. Table 3 presents the variables considered and their corresponding weights. As shown, in addition to the four groups of variables, each of which represented a utility performance sub-indicator (with the four groups providing the utility performance indicator), individual weights were also assigned to the variables composing current tap water quality indicators. 3.3. Performance level (gi) considerations For each variable, the performance levels (i.e. scores) were considered to vary from 0 to 100 performance points. According to the specific nature of the considered variable, these points may correspond to given percentile values or relative scores depending on how better a given utility performs on some characteristic comparatively to others. Here are a few examples. 3.3.1. Agricultural land use variable The performance scores have been attributed based on the QME database classification that follows. Agricultural

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Table 3 Weights (wi) conferred to variables for indicator development Variable groups

Variables

Utility performance indicator Agricultural land Agricultural pressure (P2O5) use Raw water quality TOC Turbidity Total coliform bacteria HPC bacteria Atypical bacteria Disinfection-related CT value (or operational) Frequency of residual chlorine checking Appropriateness of residual chlorine checkpoints Infrastructure and Utility age maintenance Pipe material Pipe breakage System flushing Tap water quality indicator Residual chlorine in tap water HPC bacteria in tap water Atypical bacteria in tap water

Weights (wi) 0.05 0.03 0.03 0.05 0.02 0.02 0.40 0.12 0.06 0.04 0.08 0.06 0.04 0.5 0.2 0.3

pressure on the territory of a given municipality is measured by the annual balance of phosphorus in terms of kilograms of phosphorous (P2O5) per hectare. It considers the total manure production within the municipality, the nutrient requirements of crops and the cultivated area. When the annual balance is more than 20 kg P2O5/ha/year or when the municipality is located in watersheds with already significant phosphorus excess in the soils, the Quebec provincial government considers the municipality as being in manure surplus. Even if such an annual balance is not calculated based on watershed limits but rather on municipal limits, it can be used as an indicator of the susceptibility of surface waters to be contaminated by surface or subsurface runoff. Thus, for utilities located in municipalities with an annual phosphorus balance below zero (P2O5!0 kg/ha/year), that is, municipalities with extremely low agricultural pressure, the maximum score (i.e. 100 performance points) has been attributed. For utilities located in municipalities with P2O5Z0 kg/ha/year, 50 performance points have been allotted. Utilities with slight phosphorus surplus, but less than the 20 kg/ha/year QME established threshold, received 25 points. And utilities located in municipalities in surplus situation (i.e. with P2O5O20 kg/ha/year or located in administratively designated as ‘surplus’ municipalities) scored no performance points (i.e. 0 points) on that variable. 3.3.2. Raw water TOC variable In the 2001 QDWR, a raw water TOC concentration of 3 mg/l was given as an indication for surface water utilities, for which filtration was not becoming compulsory (Bouchard et al., 2003; Gouvernement du Que´bec, 2001).

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This value has been considered equaling the 50th percentile of performance points (i.e. C50 or median) on that variable. Based on that assumption, performance scores have been attributed to studied utilities as follows: 100 points for utilities with C1%TOC%C20, as average raw water TOC concentration (mg/l); 75 points to utilities with C20! TOC%C40. Utilities with C40!TOC%C60 received 50 points, and those averaging C60!TOC%C80 received 25 points. C1, C20, C40, C60 and C80 equaled 0.06, 1.2, 2.4, 3.6, and 4.8 mg/l, respectively. None of the utilities exhibited average raw water TOC concentration exceeding the latter value. 3.3.3. CT variable In the United States Environmental Protection Agency guidance manual entitled ‘Alternative Disinfectants and Oxidants’ (USEPA, 1999), it was mentioned, ‘. 4-log virus inactivation is achievable with a CT of 15 to 60 mg$min/l for most temperatures.’. These values have been considered as equaling, respectively, C3 and C12 of performance points on that variable. Since all 10 utilities being studied have chlorination as the only treatment applied, it appears reasonable to think that this is the objective they should pursue, taking into account the fact that the 3-log Giardia cyst inactivation and the 2-log Cryptosporidium oocyst inactivation (all of which are required for surface water utilities in 2001 QDWR) are beyond reach with chlorination alone. Hence, very conservatively, performance scores have been attributed as indicated herein: 100 points to utilities with CTRC60 mg min/l; 75 points to those with C30%CT!C60; 50 points to utilities with C15%CT!C30; 25 points to those with C5%CT!C15; and 0 points to utilities with CT!C5. Note that C5, C15, C30, and C60 equaled 25, 75, 150, and 300 mg min/l, respectively.

C40!age%C60; 25 points for C60!age%C80; and 0 points for utilities with ageOC80 (i.e. 80 years). 3.3.5. System flushing variable In the conditions of the province of Quebec (Canada), it is a sign of good management routine (or practice) to perform at least two flushings of the drinking water distribution network each year, with the first coming in early Spring (i.e. generally by April) and the second in late Autumn (by October). Many utilities perform more than two flushings per year. Thus, utilities that did only one flushing per year received 50 performance points on that variable; and 100 points were allotted for two flushings or more. All utilities did at least one flushing each year. The weight assigned to each of the four sub-indicators was computed using the sum of the weights of their constituent variables. By adapting literature examples (e.g. Be´ron et al., 1982) to the specific nature of the variables and objectives of the study, the following significance scale was defined for utility performance sub-indicators and indicators: 0–20, EZvery poor performance; O20 and %40, DZpoor performance; O40 and %60, CZacceptable performance; O60 and %80, BZgood performance; O80 and %100, AZvery good performance (Table 4). This scale was built very conservatively owing to the empirical nature of most of variables (e.g. pipe age, main breaks). For each utility, the performance indicator was obtained by multiplying each individual variable weight by the performance score the utility obtained on that variable and adding up the resulting products. The utility performance indicator could also be obtained by weighting the four sub-indicator values by the sum of their constituent variable weights and adding up the resulting products. 3.4. Analysis of indicator results

3.3.4. Utility age variable According to Fouge`res et al. (1998), the useful life of a drinking water distribution pipe can rarely go over 100 years. So, this number has been taken as reference value, with C1 equaling 1 year and C100 being 100 years. Thus, utilities that had age%C20 scored 100 points on that variable; 75 points for C20!age%C40; 50 points for

The agricultural land use sub-indicator demonstrated a relatively high impact on tap water quality indicator (Table 4). Of the four very good performances (i.e. score A) recorded for this sub-indicator, three resulted in acceptable current tap water quality indicators or better. On the other hand, none of the four utilities that had poor

Table 4 Values of sub-indicators and indicators of performance for individual utilities Utility sub-indicators and indicators of performance Agricultural land use Raw water quality Disinfection-related Infrastructure and maintenance Utility performance indicator Current tap water quality indicator

Small municipal utilities I

II

III

IV

V

VI

100 A 58 C 50 C 57 C 55 C 37 D

50 C 62 B 78 B 89 A 76 B 95 A

100 A 85 A 61 B 75 B 69 B 52 C

100 A 83 A 38 D 89 A 59 C 67 B

100 A 90 A 95 A 86 A 92 A 75 B

50 97 84 59 79 22

C A A C B D

VII

VIII

IX

X

25 D 90 A 43 C 95 A 61 B 50 C

25 97 43 64 55 45

0E 93 A 43 C 84 A 57 C 27 D

0E 92 A 26 D 95 A 50 C 17 E

D A C B C C

AZvery good performance; BZgood performance; CZacceptable performance; DZpoor performance; EZvery poor performance.

H.D. Coulibaly, M.J. Rodriguez / Journal of Environmental Management 73 (2004) 243–255

or very poor performances for that sub-indicator was found to have high current tap water quality indicators (i.e. very good or good performances). Of the eight utilities that recorded the maximum level of performance for the raw water quality sub-indicator (i.e. score A), none had good or very good performances in terms of current tap water quality indicators. Instead, three of them exhibited poor or very poor performances in terms of current tap water quality indicators. For the disinfection-related sub-indicator, only one of the four utilities that recorded a very good or good performance did not record at least an acceptable performance on current tap water quality. Of the six utilities that recorded acceptable performances or less for this subindicator, three exhibited poor or very poor performance on current tap water quality. As for the infrastructure and maintenance sub-indicator, it also showed a positive impact on the current tap water quality indicator, as only two of the eight utilities that recorded either very good or good performance for this sub-indicator exhibited poor performance on current tap water quality. At the same time, both utilities that did not record more than an acceptable performance for that sub-indicator showed poor performance on current tap water quality. Using the historical water quality indicator mentioned earlier (i.e. nonproblematic vs. problematic), overall performance indicators were identified for the two groups of utilities (Table 5). The overall performance indicators, corresponding to the two stances of the historical water quality indicator, were obtained using the following two-step computation method. First, for each of the four subindicators, a non-weighted average value was calculated for the four nonproblematic and the six problematic utilities, respectively. Second, the obtained averages were multiplied by the sum of the corresponding sub-indicator constituent variable weights, and the resulting products were added up to provide the overall performance indicator for the nonproblematic and problematic utility groups, respectively. Further description of these computation procedures is provided in sensitivity analyses (see Section 3.5). Current overall tap water quality indicators were calculated using the same procedure used for overall performance indicators. It is to be

251

noted that the same 0–100 scale as the scale in Table 4 was used to qualify utility group levels of performance. According to Table 5, all overall sub-indicators, except one, favor the nonproblematic group of utilities. The only sub-indicator in favor of the problematic group is the raw water quality overall sub-indicator. Although the nonproblematic group also performed well on that sub-indicator, this furnishes a major support to comments about the fact that the differences observed in current and historical tap water quality between the two utility groups are probably rooted in the distribution system, not the source water. In other respects, it is interesting to notice that the problematic group of utilities performed relatively well on the infrastructure and maintenance overall sub-indicator, only slightly less than the nonproblematic group. This indicates that infrastructure and maintenance are in relatively good condition in both the nonproblematic and problematic groups of utilities. However, when it comes down to the agricultural land use overall sub-indicator and, especially, to the disinfection-related overall sub-indicator, the situation is unequivocally in favor of the nonproblematic group. It appears more and more probable that, for current tap water quality, the disinfection-related overall subindicator is the leading factor explaining why the nonproblematic group of utilities had much better performance indicators than the problematic group. As for the overall performance indicator and current overall tap water quality indicator, they are commented below, along with the utility performance indicator and current tap water quality indicator. A graphical representation of utility and overall performance indicators, as well as current tap water quality and current overall tap water quality indicators is presented in Fig. 1. This figure shows that in every aspect of utility performance and tap water quality indicators, the situation in the nonproblematic group of utilities is better than the situation in the problematic group. The significant differences observed between real values of the overall performance indicators for the nonproblematic and problematic groups (75 and 59, respectively) and, particularly, between the current overall tap water indicator values

Table 5 Comparison of values of overall sub-indicators and indicators of performance for nonproblematic and problematic utilities Nonproblematica

Problematica

Utility group sub-indicators and indicators of performance

Indicator values

Utility group sub-indicators and indicators of performance

Indicator values

Agricultural land use overall sub-indicator Raw water quality overall sub-indicator Disinfection-related overall sub-indicator Infrastructure and maintenance overall sub-indicator Overall performance indicator Current overall tap water quality indicator

69 B 82 A 69 B 86 A 75 B 68 B

Agricultural land use overall sub-indicator Raw water quality overall sub-indicator Disinfection-related overall sub-indicator Infrastructure and maintenance overall sub-indicator Overall performance indicator Current overall tap water quality indicator

46 87 47 75 59 36

AZvery good performance; BZgood performance; CZacceptable performance; DZpoor performance. a Historical water quality indicator.

C A C B C D

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H.D. Coulibaly, M.J. Rodriguez / Journal of Environmental Management 73 (2004) 243–255

Fig. 1. Relationships between utility performance indicators and current tap water quality indicators for nonproblematic (NP) and problematic (P) utilities.

(68 and 36, respectively) support the latter assertion. Fig. 2 confirms the hypothesis that better performance corresponds to better consumer tap water quality. Indeed, in Fig. 2, current (i.e. 2001) microbiological tap water quality varies in direct proportion to the utility performance indicator. 3.5. Sensitivity analysis of the utility performance indicator In this study, the determination of variable weights (i.e. wi) was based on two approaches. The first approach consisted of considering all variables that exhibited

a relatively high level of significance (at least at the 10% level, P!0.1) in previous studies by the authors (Coulibaly and Rodriguez, 2003a,b). The more significant the variable proved to be, the greater its weight. The second approach entailed consideration of all potential explanatory factors that had not yet been considered in the 10 utilities. These factors were conferred weights based on literature indications (that guided the authors’ judgment). Considering certain variables for indicator development because they turned out to be statistically significant in previous studies involved an a priori stance. That is the reason why variables

Fig. 2. Relationship between utility performance indicator and current (2001) microbiological tap water quality.

H.D. Coulibaly, M.J. Rodriguez / Journal of Environmental Management 73 (2004) 243–255

253

were assigned fixed weights before indicators were subjected to a sensitivity analysis. Two approaches of sensitivity analysis were proposed for the utility performance indicator: (1) varying sub-indicator weights; and (2) excluding sub-indicators.

exclusively good performances, whereas the problematic group reached such a level of performance only three times out of eight possibilities. These results suggest that the absolute weights originally assigned to the involved variables and sub-indicators are adequate.

3.5.1. Variation of sub-indicator weights Varying utility performance sub-indicator weights (through doubling or halving of their constitutive individual variable original weights) yielded eight scenarios as presented in Table 6. When one sub-indicator weight was doubled, the weight of at least one of the remaining three subindicators was reduced. Weight reduction was conducted mainly at the expense of the most weighted sub-indicator among the other three, which often fell on the disinfectionrelated sub-indicator. The process narrowed the gap between sub-indicator weights. So, eventually, these weight changes imparted more impact to sub-indicators (or variables) that did not have much significance in the original scenario. The impact of sub-indicator weight variations is presented in Table 6. In all eight scenarios, the nonproblematic group of utilities showed a higher overall performance indicator. Moreover, in most cases, the gap between the overall performance indicator values of the nonproblematic and problematic utility groups remained very comparable to the gap obtained in the original scenario (that is 75 (B) vs. 59 (C), respectively; so the original gap was 16 performance points). In fact, in all of the eight concerned scenarios, the gap varied between 9 and 22 performance points in favor of the nonproblematic group, with six gap values coming between 11 and 16. Overall, the nonproblematic group of utilities had

3.5.2. Exclusion of sub-indicators One-at-a-time exclusion of utility performance subindicators yielded four scenarios (Table 6). With the exception of one case, the same approach of raising the lowest sub-indicator weights while reducing the highest ones (as described in Section 3.5.1) was applied. When the disinfection-related sub-indicator was excluded, the process resulted in 10 individual variables with equal weight. Again, this approach had the tendency of narrowing the gap between the remaining sub-indicator weights. The impact of sub-indicator exclusions was noticeable. Conferring an identical weight (that is 0.1) to all other individual variables except the ones forming the disinfection-related sub-indicator resulted in a very comparable overall performance indicator (the closest of all) between the nonproblematic and the problematic groups of utilities (78 and 75 performance points, respectively) (Table 6). However, in each of the three other scenarios, the gap between the two utility groups varied between 11 and 18 performance points, which is fairly comparable to the gap range mentioned in Section 3.5.1. Once again, on an overall basis, the nonproblematic group of utilities exhibited exclusively good performances in these last four scenarios, whereas the problematic group scored similarly only on two of four occasions.

Table 6 Sensitivity analysis of the utility performance indicator Utilities

Variation of utility performance sub-indicator weights Agricultural land use subindicator

Raw water quality subindicator

Disinfectionrelated subindicator

Infrastructure and maintenance sub-indicator

O2

!2

O2

!2

O2

!2

O2

!2

75 72 92 61

B B A B

78 B 67 B 91 A 60 C

74 B 74 B 91 A 70 B

69 73 88 73

B B B B

77 60 95 42

B C A C

70 B 69 B 92 A 59 C

58 63 76 55 56 50 75

C B B C C C B

56 C 59 C 76 B 51 C 55 C 48 C 74 B

56 C 67 B 78 B 65 B 68 B 63 B 78 B

57 70 78 65 68 66 76

C B B B B B B

50 37 85 42 42 25 69

C D A C C D B

60 C

58 C

67 B

67 B

47 C

Nonproblematic II 76 B III 68 B V 92 A VII 63 B Problematic I 54 C IV 58 C VI 80 B VIII 56 C IX 59 C X 52 C Overall 75a B performance indicator 60b C a b

Exclusion of respective sub-indicators

Nonproblematic utility group. Problematic utility group.

Agricultural land use subindicator

Raw water quality subindicator

Disinfectionrelated subindicator

Infrastructure and maintenance subindicator

79 B 74 B 89 B 75 B

77 67 91 64

B B A B

78 67 91 57

B B A C

65 B 77 B 85 A 85 A

66 B 70 B 92 A 58 C

55 C 56 C 82 A 57 C 57 C 48 C 73 B

57 C 72 B 71 B 62 B 69 B 69 B 79 B

53 57 81 57 61 54 75

C C A C B C B

57 60 72 47 51 45 73

C C B C C C B

60 C 82 A 75 B 75 B 77 B 82 A 78 B

55 C 55 C 86 A 60 C 56 C 46 C 71 B

59 C

67 B

61 B

55 C

75 B

60 C

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4. Conclusions Distribution system operational, infrastructure, and maintenance variables analyzed herein showed some interesting trends in terms of distinctive features between the nonproblematic and problematic groups of utilities in relation to their distributed water quality. Almost all indicators pointed towards better performances in nonproblematic utilities, which are also the utilities with the best current water quality in the distribution system. While by and large all indicators were better in the nonproblematic group, specific attention was paid to disinfection-related performance sub-indicators and those for infrastructure and its maintenance. It appears that these factors are truly the factors having the greatest impact on distributed water quality in the small utilities under study. Sensitivity analyses applied to the utility performance indicator showed that the methodology employed stands the test of individual variable and sub-indicator (or variable group) weight changes. As a matter of fact, in the 12 scenarios tested, the nonproblematic group of utilities exhibited exclusively good performances, whereas the problematic group matched this performance only on a few occasions (in 5 out of 12 scenarios, with overall performance numeric values systematically lower than values recorded for the nonproblematic group of utilities). The small utility performance indicators developed suggest that it is very difficult to make good tap water from bad source water; however, it is very feasible to improve water quality between the source and the consumer’s tap with a combination of adequate operational, infrastructure, and maintenance characteristics. Small utility managers may find the findings of this study helpful, providing greater insight into the impact of their daily operational practices and favoring a better understanding and awareness of their respective utilities’ strengths and weaknesses. The findings may also prove helpful to municipal officials and government bodies in terms of achieving a better understanding and assessment of small utilities’ specific infrastructure needs and subsequent allocation of appropriate resources. In other respects, this research demonstrated that it is possible to develop utility performance indicators that are correlated with distributed water quality, using a relatively simple methodology. Future research may focus on performance indicator validation issues and (or) inclusion of variables or characteristics that could not be included in this study due to measurement limitations.

Acknowledgements The authors are thankful to the 10 small utility managers for their availability and assistance, as well as to Dr JeanBaptiste Se´rodes (Professor and Dean, Universite´ Laval) and Mr Donald Ellis (Ministry of Environment, Que´bec) for their

useful remarks and suggestions. Finally, the authors express their gratitude to the Canadian Agency for International Development (CAID), through Canadian French-SpeakingWorld Fellowship Program, and the Center for Urban and Regional Planning and Development—CRAD—(Universite´ Laval) for financial and logistic support.

References Antoun, E.N., Dyksen, J.E., Hiltebrand, D.J., 1999. Unidirectional flushing—a powerful tool. J. Am. Water Works Assoc. 91, 62–71. AWWA, 1994. An Assessment of Water Distribution Systems and Associated Research Needs. American Water Works Association, Denver, Colorado. AWWA, 1998. Water:\Stats: The Water Utility Database. American Water Works Association, Denver, Colorado. Ball, R.O., Asce, M., Church, R.L., 1980. Water quality indexing and scoring. Proc. Am. Soc. Civil Eng. (ASCE) 106 (EE4). Be´ron, P., Valiquette, L., Patry, G., Brie`re, F., 1982. Indices de qualite´ des eaux. Trib. Cebedeau 467, 385–391. Bouchard, C., Se´rodes, J.-B., Laflamme, E., Rahni, M., Ellis, D., Rodriguez, M.J., 2003. Ultrafiltration et coagulation-ultrafiltration de l’eau du lac des Roches. Revue du Ge´nie et de la Science de l’Environnement 2, 199–215. Brown, R.M., McClelland, N.I., Deininger, R.A., Tozer, R.G., 1970. A water quality index—do we dare?. Water Sewage Works 177, 339–343. Cluis, D., Laberge, C., 2001. Climate change and trend detection in selected rivers within the Asia-Pacific region. Water Int. 26, 411–424. CMHC, 1992. Urban Infrastructure in Canada. Canada Mortgage and Housing Corporation, Ottawa. Couillard, D., Lefebvre, Y., 1986. Indice de qualite´ de l’eau pour de´tecter l’impact de la pollution diffuse urbaine. Can. J. Civil Eng. 13, 631–638. Coulibaly, H.D., Rodriguez, M.J., 2003a. Portrait of drinking water quality in small Quebec municipal utilities. Water Qual. Res. J. Can. 38, 49–76. Coulibaly, H.D., Rodriguez, M.J., 2003b. Spatial and temporal variation of drinking water quality in ten small Quebec utilities. J. Environ. Eng. Sci. 2, 47–61. Cowley, G., 2000. Disinfection with chlorine dioxide. J. New Engl. Water Works Assoc. 114, 264–270. Dunette, D.A., 1979. A geographically variable water quality index used in Oregon. J. Water Pollut. Control Fed. 51, 53–61. Duranceau, S.J., Poole, J., Foster, J.V., 1999. Wet-pipe fire sprinklers and water quality. J. Am. Water Works Assoc. 91, 78–90. Edwards, E.S., Anderson, W.B., Andrews, S.A., Huck, P.M., 2002. Disinfection assessment in full-scale chlorine contact chambers. J. Environ. Eng. Sci. 1, 311–322. Fouge`res, D., Gaudreau, M., Hamel, P.J., Poitras, C., Se´ne´cal, G., Tre´panier, M., Vachon, N., Veillette, R., 1998. E´valuation des besoins des municipalite´s que´be´coises en re´fection et construction d’infrastructures d’eaux. INRS- Urbanisation, Montre´al, 266 p. Gouvernement du Que´bec, 1984. Re`glement sur l’eau potable. E´diteur officiel du Que´bec, Que´bec. 7 pp. Gouvernement du Que´bec, 1997. L’eau potable au Que´bec, un second bilan de sa qualite´: 1989–1994. Ministe`re de l’Environnement et de la Faune, Que´bec. 36 pp. Gouvernement du Que´bec, 2001. Re`glement sur la qualite´ de l’eau potable. Ministe`re de l’Environnement, Que´bec. 19 pp. Gouvernement du Que´bec, 2002. Gouvernement du Que´bec, Guide de conception des installations de production d’eau potable, vol. I et II. Ministe`re des Affaires municipales et de la me´tropole, Ministe`re de l’environnement, Que´bec.

H.D. Coulibaly, M.J. Rodriguez / Journal of Environmental Management 73 (2004) 243–255 Gouvernement du Que´bec, 2003. Bilan de la qualite´ de l’eau potable au Que´bec: janvier 1995-juin 2002. Ministe`re de l’environnement, Que´bec. 75 pp. Laroux, T., Weber, J.-L., 1994. Re´flexions sur les crite`res de de´finition et de choix des indicateurs d’environnement. IFEN. LeChevallier, M.W., Schulz, W.H., Lee, R.G., 1990. Bacterial nutrients in drinking water, in: AWWARF (Ed.), Assessing and Controlling Bacterial Regrowth in Distribution Systems. American Water Works Association Research Foundation, Denver, Colorado. Lence, B.J., Ruszczynski, A., 2001. Managing water quality under uncertainty: application of a new stochastic branch and bound method, in: Bogardi, J.J., Kundzewicz, Z.W. (Eds.), Risk, Reliability, Uncertainty and Robustness of Water Resources Systems. International Hydrologic Series, Cambrigde University Press, Cambridge, UK, pp. 143–152. McDonald, S., Daigle, L., Fe´lio, G., 1994. Re´seaux d’aqueduc et syste`mes d’e´gouts, Laboratoire d’infrastructures, Institut de recherche en construction, Conseil national de la recherche du Canada, version pre´liminaire 1994. Opferman, D.J., Buchberger, S.G., Arduini, D.J., 1995. Complying with the STWR: Ohio’s experience. J. Am. Water Works Assoc. 87, 59–67. Ott, W.R., 1978. Environmental Indices—Theory and Practice. Ann Arbor Science, Ann Arbor, MI. Porcella, D.B., Petersen, S.A., Larsen, D.P., 1980. Index to evaluate lake restoration. Proc. Am. Soc. Civil Eng. J. Environ. Eng. Div. 106, 1151–1169. Rodriguez, M.J., Se´rodes, J.-B., 1999. Empirical linear and non-linear modelling of residual chlorine in urban drinking water systems. Environ. Modell. Software 14, 93–102.

255

Rodriguez, M.J., Coulibaly, H.D., Banville, J., 2002a. Strategies for ensuring a safe drinking water in small utilities of Quebec (Canada), Proceedings of the American Water Works Association Annual Conference and Exposition (ACE), New Orleans, Louisiana, 16–20 June 2002. Rodriguez, M.J., Milot, J., Se´rodes, J.-B., Pacaud, A., 2002b. Estimation of bench-scale chlorine decay in drinking water using nth-order kinetic and neural network models. Water Qual. Res. J. Can. 37, 613–635. Se´rodes, J.-B., Rodriguez, M.J., Ponton, A., 2001. Chlorcast q: a methodology for developing decision-making tools for chlorine disinfection control. Environ. Modell. Software 16, 53–62. UNEP, 1994. Overview of Environmental Indicators: State of the Art and Perspectives. United Nations Environmental Program, Nairobi. USEPA, 1991. Guidance Manual for Compliance with the Filtration and Disinfection Requirements for Public Water Systems Using Surface Water Sources, PB 93-222933 (NTIS), Washington, DC, USA 1991. USEPA, 1999. Disinfection Profiling and Benchmarking Guidance Manual, EPA-815-R-99-013 1999. USEPA-DWA, 2003. An Overview of the Safe Drinking Water Act. US Environmental Protection Agency—Drinking Water. WHO, 2003. Guidelines for Drinking-Water Quality, third ed. World Health Organization, DRAFT. Yu, J.K., Fogel, M.M., 1978. The development of a combined water quality index. Water Resour. Bull. 14, 1239–1250. Zandbergen, P.A., Hall, K.J., 1998. Analysis of the British Columbia water quality index for watershed managers: a case study of two small watersheds. Water Qual. Res. J. Can. 33, 519–549.