water research 2005

8/4/2019 Water Research 2005

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PROPOSAL OF A WATER TREATMENT PLANT QUALITY INDEX

This paper focuses on developing a quality index for measuring the

results of a conventional water treatment plant. It aims to provide a

useful tool that allows the effective plants comparison by means of a

methodology beyond compliance with drinking water regulations.

The research procedure used in formulating this WTPQI was based

on the methodology used in beginning of 1970s for developing the Water

Quality Index (WQI) and like this one it attempted to incorporate many

aspects of the Delphi method. Afterwards, the WTPQI was applied to ten

different Brazilian conventional water treatment plants which average

flow rate range from 100 to 4300 L/s and all of them utilize rectangularbasin as settling unit. The results pointed out the WTPQI usefulness as a

plant evaluation tool. It was verified a clear tendency that plants

achieving more elevated WTPQI is the same that achieving good

performance in terms of filtered water turbidity. In such way the WTPQI

can arise as a reliable tool to manage water supply systems in near

future.

Suggested keywords: Water treatment plant quality index, watertreatment plant evaluation, water treatment.

INTRODUCTION AND RELEVANCE

Factors limiting water treatment plant performance was usually

related to (i) the suitability between the raw water characteristics and the

treatment process train, (ii) the ratio between the influent flow rate and

the water treatment plant capability and, probably the most important,(iii) the operation accuracy. Also, the global evaluation of a plant have to

join the finished water quality which is related with the dosage and the

type of coagulant, the run filters, the possibility of short circuits and other

factors. This multiplicity of factors has been raising many difficulties to

the professionals to set up the reliable hierarchy among them. This

hierarchy would define more accurately the activities of the water supply

system managers in terms of operation and/or enlargement of the water


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without large investments also.

The option of a quality index was justified by the use of easy

available data related to the operational routine of the plant. It will permit

a good comprehension by the population (as WQI does), because in many

situations the responsible for the application of financial resources does

not have a clear knowledge about the processes concerning the water

treatment. The mentioned comprehension by the public will help the use

of the WTPQI as a tool for the population consciousness by the relevance

of a good performance of the water treatment plants, minimizing in a

second instance the outbreak risks thru the drinking water.

OBJECTIVE

The paper proposes a Water Treatment Plant Quality Index (WTPQI)

as an evaluation tool for the water supply system administrations become

the comparisons among different plants more precise. Additionally, the

paper proposes: i) to list the intervenient parameters on the performance

of water treatment plants; ii) to define an hierarchy for these parameters

according to their role in performance of the plants; iii) to validate the

WTPQI basing on the daily operational data of ten conventional water

treatment plants with different sizes.

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LITERATURE REVIEW

Optimization and Evaluation of Water Treatment Plants

The water treatment for human consumption, as one of most

important features of sanitary engineering, has been facing a clear

dichotomy last years. The successive drinking water regulations have

been presenting more restrictive in terms of the number of parameters

and their maximum levels. On the other side, there is a progressive

deterioration of the natural water quality by means concentrated and

diffuse pollution mainly as a consequence of human activities.

In a first moment more restrict levels to the filtered water turbidity

were focused on the higher efficiency of the chlorination in inactivation of

pathogenic microorganism, and in a second phase toward the perspective

to increase the protozoa removal. In this last context, many researches

have emphasized a higher removal associated to finished water with

turbidity lower than 0,1 NTU. As an example, a research was carried out

with some filters in pilot and actual scale monitored during two years. It

was demonstrated the more consistent Giardia and Crypto removal was

reached with low filtered water turbidity (0,1 to 0,2 NTU), despite the

determination coefficient was not high (r2 = 0,64). Furthermore, when the

performance of water treatment plant varied with the fluctuations of raw

water quality a high variability in cyst concentration was observed in the

effluent (NIEMINSKI & ONGERTH, 1995, apudLECHEVALIER & AI, 2004).

The development of a methodology to optimize the water treatment

plants began in USA and Canada in the end of 1980s with the objective to

increase the protection against some pathogenic microorganisms. Named

Composite Correction Program (CCP), some objectives of this

methodology were to define the best performance of sedimentation,

filtration and disinfection processes. There was established the highest

settled water and filtered water turbidity values of 2 NTU and 0,1 NTU,

respectively, with a permissible peak after backwashing of 0,3 NTU by

less than 15 minutes.

The CCP optimization concepts were expanded to many other

activities. The program Partnership for safe wateremployed CCP such as

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a basis to the development of its Phase III with the objective to improve

the treatment for a better water quality. This program was developed by

the association of six American entities, and in May 1988 217 water

treatment plants supplying more than 90 million people were taking part

of it (GUIDELINES FOR PHASE IV, 2003)

In 1984 the DEP (Department of Environmental Protection) of

Pennsylvania, with the objective to assure the distributed water quality,

made a start the implementation of the FPPE program (Filter Plant

Performance Evaluation) aiming to determine the plant effectiveness in

terms of the particle removal at same range size of the cysts and oocysts

of protozoa. Until 1996 290 plants were evaluated and in 1988 more than

60 % were producing effluent with turbidity higher than 0,2 NTU. In 1996

this percentage was reduced to 4 %.

Afterwards some CCP concepts were inserted in the FPPE

program. There was done the capacity evaluation of each water

treatment plant with a current use of standard sheets to obtain temporal

series of raw, settled and filtered waters. By means the comparison of

these graphs there was possible to assess the plant capacity to produce

better quality water despite the changes of raw water (CONSONERY et al.,

1997).

The Delphi Methodology

The Delphi method concept can be understood as a product of a

Rand Corporation project in 1950s, concerning the application of the

opinion of specialists. It can be developed in two different techniques. The

more common is the pen andpaperversion. In this situation, a monitor

elaborates a questionnaire that is sent to a group of respondents. When

these questionnaires return, the monitor summarizes the results and

basing on them develops a new one. The group of respondents has at

least one chance to change his opinion. This technique is known

conventional Delphi. The other one, named Delphi conference, the

monitor is substituted by a computer program, which makes the printout

simultaneously and returns the responses to the respondents. After the

last response, the software makes a report and the new questionnaire.

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This method has an advantage to carry out the process in real time. In

both ways, some characteristics define the method: (i) the anonymity; (ii)

the interaction; (iii) the feedback; (iv) the statistical representation of the

results (LINSTONE & TUROFF, 1975).

Taylor & Ryder (2003) utilized the Delphi methodology to define a

management plan of 25 multiple uses reservoirs. This information

concerned basically the necessary water levels to guarantee the survival

of fishes. Questionnaires were elaborated for each reservoir and were

sent to 26 specialists and the number of respondents by reservoir varied

from 2 to 8. It was possible to the same specialist answered questionnaire

related to more than one reservoir. The first questionnaire asked them

about a list of the more vulnerable species and the period in which each

species was particularly sensible to the variations of the reservoir level. In

the second questionnaire, the specialists reevaluated their responses in

function of the opinion of the entire group. The research has gotten a

return of 85 % and a high convergence of opinions for all reservoirs. The

research showed the applicability of Delphi methodology to deal with

several information to the management of complex environmental

questions.

The index development

The transmission in an intelligible way to the population the data

and the parameters of water treatment plants is not an easy task.

However, it is not a question restricted to this specific area. There were

many efforts trying to reproduce in only value the meaning of a data set.

Brown et al. (1970) employed the Delphi methodology to develop

the Water Quality Index (WQI) based on the opinion of a group of 142

water quality specialists. This research was composed by three

questionnaires. In the first a list with 35 parameters, randomly selected,

was sent to the group. For each parameter, the respondents had to

choose among three options: include, no include and undecided. There

was possible to include other parameters that were absent in this first list.

The respondent had to assign values for each parameter selected as

include from 1 to 5.

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The results of this first round were sent to the respondents with the

second questionnaire opening the possibility to the respondents compare

their responses with the other ones, and, occasionally, reevaluate them.

There was a request of a list including the 15 most important parameters.

In the third questionnaire, for each one of the 9 selected parameters, the

respondent had to draw a curve as, in his judgment, the best way to

represent the influence of this parameter in water quality. The nine

average curves employed to define the WQI were a combination of the

responses of all respondents. Among 142 specialist invited in the first

round, 94 (66 %) returned the first questionnaire in time to take part in

the second round, and from this group 82 % completed and returned the

second questionnaire.

The WQI value was defined upon a sum represented by the

Equation 1:

=

=n

i

ii qwWQI1

(1)

in which:

WQI: the water quality index, a number between 0 and 100;

wi: the unit weight of ith parameter, a number between 0 and 1;qi: the quality of the ith parameter, a number between 1 and 100,

extracted from the respective curve;

n: number of parameters.

Based on the same methodology employed in the development of

the WQI, Nages et al. (2001) proposed an index system to assess the

recreation water quality in New Zealand. They used the Delphi

methodology to resume the judgment of 18 specialists from consultingengineering, environmental management companies, research institutes

and universities.

The remarkable new in this research was the final definition of the

index. Distinctly of the WQI, there were not established weights for each

parameter and the index of a specific water source will be the lowest

value extracted from these curves. The justification was an aggregation of

many individual scores could hide a low value of a specific parameter.METHODOLOGY

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The present work can be defined such as an applied research with

the objective to provide a quantity tool to help the water supply system

managers, and a quality one to classify the performance of the water

treatment plants by means numerical methods. The universe of this

research was limited by the conventional water treatment plants, with

horizontal sedimentation basins, treating typical raw water to produce

filtered water turbidity lower than 0,5 NTU and absence of total coliform

in compliance to the Brazilian Drinking Water Standards.

The methodology to formulation the WTPQI was based on the same

utilized to the development of the WQI. In such way, after the

establishment of all parameters, and respective weights and grading

criteria, there were defined two different formulations in terms of a

summation and a multiplicative forms:

i

N

i

n

j

QjWjWTPQI = =

=

1 1

(2)i

N

i

n

j

WjjQWTPQI

= =

=

1 1

(3)

where:

Wj: weight rated to each parameter established by the judgment of the

specialists;

Qj: value rated to the water treatment plant for each parameter selectedaccording to the developed criterion;

j: each parameter included in the index;

i: each group of parameters to comprise the index such as rapid mix,

flocculation, sedimentation, filtration, disinfection, and operational

factors;

n: number of parameters included in the index;

N: total number of groups of parameters that will constitute the index.The methodology to the development of the WTPQI was divided in

three phases (opinion research, definition of the grading criteria, and the

index validation) as follow.

Opinion research

There was carried out an opinion research to select the intervenient

parameters to be included in the WTPQI, and the respective weights, with

18 professionals with expertise in water treatment. Of the total panel, 16completed and returned both questionnaires. The group was selected

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focusing different professional formations and distinct geographical areas

of Brazil.

This research was constituted in two different phases according to

the Delphi characteristics. After the literature review, there was

elaborated a first list of the intervenient parameters in water treatment as

shown in Table 1.

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TABLE 1- Parameters included in the first questionnaireGRM Rapid Mix Velocity Gradient VF Flow-through VelocityTRM Rapid Mix Detention Time QL Weir Loading Rate

Jtest Routine Jar Test Realization Tfilt Filtration RateGf Flocculation Velocity Gradient Drf Run FilterTf Flocculation Time Exp Filter bed expansion

Gp Velocity gradient thru the ports of flocculator Vupf Upflow water wash velocityNc Number of compartments Lair

Washing with auxiliary airscour

VcAverage velocity in the flocculated waterchannel

Lwater

Washing with auxiliary surfacewater system

GpsVelocity gradient thru the ports ofsedimentation basin

Tc Detention time in the clearwell

GinVelocity gradient thru the inlet baffle ofsedimentation basin

NclNumber of compartments ofthe clearwell

VsSedimentation Surface Loading Rate orTerminal Settling Velocity

ILInstruction level of theoperational staff

This list was utilized in the elaboration of the first questionnaire sent

to 18 professionals selected. The panel was composed by graduate

professionals responsible by researches in water treatment, designs and

operation of water treatment plants, regarding universities, sanitation

companies and consulting engineering of six Brazilian states in the two

most developed and populous regions like showed in Table 2.

TABLE 2: Professional fields of participants in the panel

Plant operator 2Designer 4Researcher 7

Researcher/Designer

1

Designer/Operator

1

Researcher/Operator

1

The first questionnaire was divided in three parts. The first one has

presented an introduction explaining all phases of research and showing

to the participant his role in it. The second part has explicated all

instructions for a correct filling of the questionnaire. Finally, the third part

was constituted by the initial list (Table 1) of the parameters which the

respondent would have to evaluate by one the categories include, no

include and undecided, and he could suggest additional parameters

absent in the first list. After his judgment, the respondent would have to

rate (up to 100) only those parameters marked include according to their

relevance to water treatment.

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After the finish of the first phase, there was elaborated a report with

numerical summary of the responses of all participants. It was

incorporated in this report the inclusion percentage of each parameter,

average, median, mode, quartiles, and an abstract of the commentaries,

the participants responses and a column to review their initial responses.

After an evaluation of the opinion of the entire group, the respondents

were asked to review their responses, keeping or modifying them.

The parameters included in the index were divided into six groups

according to the step of the conventional treatment such as, per example,

Rapid mix, Flocculation, Sedimentation, Filtration, Disinfection, and

Operational quality. Based on the weights rated to the parameters by the

panel it was determined the weight of each group in function of the

treatment effectiveness. The main reason for the separation in groups

was the possibility to comprise a complete index, formed in function of

the indexes of each step of the water treatment. In such way, it will be

possible to identify which group is responsible by an eventual low grade

of the water treatment plant.

Development of the grading criteria

After the definition of the parameters included in the index and their

respective weights, the following phase of the research was begun. In this

phase it was established the grading criteria based on the premises set

up by the Brazilian Technical Standards Association (1990) and the

literature.

Validation of the WTPQI

The final phase of the research was composed by a comparative

study between the final grade provided by the index to a specific water

treatment plant and the monitoring data in terms of filtered water

turbidity. The scope of this last phase was to choose the final formulation

of the index (summation or multiplicative), and to verify the validation of

the grade provided by the index to the treatment. In other words,

whether the water treatment plant evaluated with a high WTPQI had

presented a good performance concerning the filtered water turbidity.

With this objective, the developed index, in summation and

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multiplicative forms, was applied to ten conventional water treatment

plants of two most important Brazilian states with average flow rate range

from 100 to 4300 L/s. These plants were selected according to the

easiness of access and the reliability of the monitoring data provided by

the respective directions.

The comparison between the WTPQI and the filtered water turbidity

was done with tables in which were presented the day, the WTPQI

(summation and multiplicative), and the mean values of filtered water

turbidity for six months data of 2003 and 2004 (three months related to

the drought season and three months to the rainy season). There were

calculated the following values for each season according to the Brazilian

and American Drinking Water Standards:

time percentage of the operation plant with filtered water turbidty

0,5 NTU;


0,3 NTU;


0,1 NTU;

value lower than 95% of the filtered water turbidity values.

For verifying whether the WTPQI was correlated to the filtered water

turbidity values, there were calculated linear and non-linear correlation

coefficients. This analysis focused to assess whether an occasional

reduction of the WTPQI was followed by higher filtered water turbidity

levels.

The last analysis was based on the premise about a plant with good

performance probably will produce a high water quality even when a

variable raw water quality as influent, or the finished water turbidity will

not change with occasional alterations of raw water characteristics. For

this, there were calculated the correlation coefficients (r) among raw,

settled and finished waters for each plant.

RESULTS AND DISCUSSION

Participants responses and the definition of the weights for each

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parameter

The first round of the research was carried out from January to April

2004 with 89 % of returning among 18 questionnaires. The

justifications and comments from the first questionnaire were sent to

the respondents in the second round with the objective to show the

opinions of the other participants. No parameter listed in the first

questionnaire (Table 1) was dismissed, and among the parameters

suggested by the respondents none was inserted in the second round

because the necessary information about them was not easily

accessible or the parameter was very subjective. Per example, there

were some suggestions in terms of general situation of the

laboratory, plant versatility, and others. Other kinds of suggestions

concerning the raw water quality were not accepted because this

index focused to evaluate the treatment despite the raw water

characteristics. Beyond this fact, none new parameters were

suggested by more than three respondents.

As previously mentioned, the respondents were instructed to assign

values from 0 to 100 for only the selected parameters marked include.

This rating system was chosen to become easier the filling of the

questionnaires because. However it was relevant the relative importance

of each parameter and the weight assigned by the respondent in a

proportion with the total points distributed by him. Therefore, the final

score of each parameter was divided from the total points distributed by

the respondent and the sum of all distributed points have totalized 100.

It is shown in Figure 1 the relative importance of each parameter in

terms of global performance of the water treatment plants. According to

the panel, the rate filtration is the most relevant parameter, answering by

approximate 9 % of the performance, agreeing with the tendency of the

national and international water drinking standards to reduce the finished

water turbidity. The settling velocity and the flocculation velocity

gradient, with the filtration rate, were responsible by 23 % of the plant

efficiency. The first parameter represents the assurance of the settling of

flocs and the second the suitable formation of them.

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FIGURE 1: Accumulated median of the weights of each parameter

By the observation of the vertical bars shown in Figure 1, it is

possible to verify the highest ranges among the responses to the most

significant parameters, emphasizing the agreement of the respondents

concerning the relevance of them, but a clear disagreement in terms of

the weight to be assigned.

Based on these results, the weights for the WTPQI determination

would have to be defined. In this context, what would be the best way for

this scatter of results? Maybe other rounds could help to reach a higher

convergence, but this option was not suitable in function of the time

expended in each round. Moreover, it should be noted there was a little

change expressed in the second questionnaire and several respondents

did not modify their scores. In such way, two important decisions were

taken to the definition of the final weights: (i) avoiding the influence of

extreme points, the median was chosen as the best measurement of the

group opinion; (ii) all parameter were included and the weights weremultiplied by the inclusion rate of each parameter, so the parameters

with 100 % inclusion rate had their weights were kept, and the others had

theirs reduced.

For the development of grading criteria some parameters were

unified. As an example, the Tf and Gf parameters were rated as a couple

and the weight is the sum of each one. The Lair and Lwater parameters were

transformed in only parameter named Laux (auxiliary wash), the weight ofit was defined as a median of all weights assigned to them. In the same

14

TFILT

Vs

Gf

IL

GMR T

f

Jtest

QL

Gin T

cGp

Gps

Drf

Vupf

VF

Vc

Exp

TMR

Nc

LAIR

Ncl

LWATER

0 , 0 0

0 , 0 5

0 , 1 0

0 , 1 5

0 , 2 0

0 , 2 5

0 , 3 0

0 , 3 5

0 , 4 0

0 , 4 5

0 , 5 0

0 , 5 5

0 , 6 0

0 , 6 5

0 , 7 0

0 , 7 5

0 , 8 0

0 , 8 5

0 , 9 0

0 , 9 5

1 , 0 0

1 , 0 5


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context, it was defined the group of Exp and Vupfparameters because the

inclusion of both would be overrating the same aspect related to the bed

filter wash. Finally, the last transformation was carried out dividing each

weight from total score, for all weights sum was 1. The final weight of

each parameter is shown in Table 3.

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TABLE 3: Final weights of all parameters

GroupParame

terWeight

Group Parameter

Weight

Rapid MixGMR 0,06 Filtratio

nTfilt 0,09

TMR 0,03 Drp 0,04

Flocculation

Gf-Tf 0,14 Exp 0,04Gp 0,04 Laux 0,03Nc 0,03 Disinfect

ionTc 0,05

Vc 0,03 Nl 0,02

Sedimentation

Gps 0,04 Operation

Jtest 0,07Gin 0,05 IL 0,06Vs 0,08VF 0,04QL 0,06

Development of grading criteria

After the definition of weights for each parameter there was

necessity to establish the grading criteria. In reality, this definition is

substituting the mentioned curves drawn by the respondents for the WQI.

In this phase, as explicated in the methodology, the parameters were

divided into six groups: Rapid mix, Flocculation, Sedimentation, Filtration,

Disinfection and Operation.

Due to the limit to the size of the paper, there will be detailed,

among 19 parameters, only the settling velocity (surface loading rate)

integrating of the group Sedimentation. The function of this step of

treatment is to remove by gravity the flocs to lower the solids

concentration on filters. Among the intervenient factors to the

sedimentation effectiveness the more important are the settling velocity,

the inlet and outlet arrangements, and sludge removal.

The high variability of size, density, and particle shape has been

presenting difficulty to develop a mathematical model for flocculant

settling. In such way, the ideal horizontal-flow sedimentation basin, even

its simplicity, was applied to estimate the particle behavior. Some simple

suppositions characterize this model: (i) in sedimentation zone the

particles settle in analogous way as in rest tank with the same depth; (ii)

the flow and particle concentration are uniform all over the transversal

section; (iii) there is not scouring when the particles reach the sludge

zone.

The grading criterion was defined based on the rate Vs/Vs,

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considering Vs the surface loading rate with a progressive increasing of 5

% from the design rate on and Vs was considered the highest surface

loading rate established by The Brazilian Technical Standards Association

(40 m3/m2.day). Of course, all plants which sedimentation basins were

operating with surface loading rates lower than that received the

maximum grade.

In a real sedimentation basin the terminal settling velocity of the

particles tends to increase in function of the differential settling. In this

way the sedimentation effectiveness will be higher than that estimated by

the ideal model. In contrast with differential settling, the wind effects, the

different temperatures, the currents as a result of distinct densities, and

other factors caused short-circuits, floc rupture and scouring of settled

sludge reducing the sedimentation efficiency. Due the difficulty to

synthesize the influence of these factors and considering the positive

effects of differential settling can compensate these negative effects, for

the Vs grading criterion, shown in Figure 2, it was utilized the ideal model

already described.

Vs

0

10

20

30

40

50

60

70

80

90

100

0 10 20 30 40 50 60 70 80 90 100 110 120

Vs (m3/m2.d)

Score

1000m3/day 1000 < Cap < 10000 m3/day >10000m3/day

FIGURE 2: Grading criterion established for Vs

WTPQI Application

Finally, after the definition of the weights and the grading criteria

the final phase of the research was to apply the WTPQI, in multiplicative

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and summation forms (equations 2 and 3), to ten water treatment plants.

The plants were not identified because the focus of this research was to

evaluate the applicability of the WTPQI, and there was no intention to

assess the plant performance which managers permit the free access to

the plant data. As previously mentioned, there were utilized six months

data, in terms of drought and rainy seasons for three months each. As an

example, the WTPQI was calculated and presented in Table 4.

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TABLE 4: Determination of the WTPQI for one of the plants of the sample

GroupParameter

Daily datamedian for

eachparameter in

six months

Score

Weights

Weights xScore

Weights ^Score

Score bygroup(Sum

)

Score bygroup

(Mul)

Rapid MixGMR (s-1) 1340,65 100 0,06 6,00 1,32 9,00 1,52TMR (s) 0,40 100 0,03 3,00 1,15

Flocculation

GF (s-1) 35,18

30 0,14 4,20 1,61

9,04 2,09

TF (s) 835,87Flocculator type

Hydraulic

Gp (s-1) 55,11 1 0,04 0,04 1,00Nc 5 60 0,03 1,80 1,13Vc (m/s) 0,29 100 0,03 3,00 1,15

Sedimentation

Gpss-1) 19,29 100 0,04 4,00 1,20

25,24 3,40

Gin (s-1) 8,19 100 0,05 5,00 1,26

Vs(cm/min) 3,02 80 0,08 6,40 1,42

VF (cm/s) 0,26 100 0,04 4,00 1,20QL (L/s.m) 1,64 100 0,06 6,00 1,32

Filtration

Filter typeDownflow

Dual media100 0,09 9,00 1,51

17,03 2,17

Tfilt(m/dia)

279,66

Drf Filteredvolume(m3/m2/run)

475,30

100 0,04 4,00 1,20Washwater volume(m3/m2/filter)

6,06

Exp (%) 32 100 0,04 4,00 1,20

LauxSurface wash(scrapping)

1 0,03 0,03 1

Disinfection

ResidualCl (mg/L)

0,8710 0,05 0,5 1,12

1,5 1,21

T (min) 1,47pH 7

Ncl

The water was

introduced inthe bottom ofthe tank and,

after thechlorine

dosage, flowedover a chicane

50 0,02 1 1,08

Operation

IL Superior 100 0,07 7,00 1,38

13 1,82Jar test

According tothe change of

raw waterturbidity

100 0,06 6,00 1,32

WTPQI 74,81 51,62

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After the WTPQI determination, the main point was the final

definition by multiplicative or summation forms for the WTPQI equation.

The distinction between both equations was focused in the possibility of a

plant with a low grade, in a specific parameter, has its final score more

significantly affected when the multiplicative form is utilized. The plants

with a more uniform grading among the parameters keep the final score

approximately constant by both equations. The question, which answer

intends to reach in the following analysis, is: only parameter with low

score will have a significant impact in the global performance of the plant

is able to justify the option by the multiplicative form of the WTPQI

equation?

For evaluating the applicability of the index, its values were

compared to filtered water turbidity. This comparison was done by means

scatter graphs determining the correlation between The WTPQI (in both

forms), and the percentage of daily mean values of filtered water lower

than 0,5 and 0,3 NTU. Also, there were made graphs in terms of the

WTPQI and the turbidity value higher than 95 % filtered water turbidity

values. For the last validation of the WTPQI, there was accomplished

another scatter graph concerning the index and the daily filtered water

turbidiy. With the exception this last graph, all ones were divided in

drought and rainy season.

The correlation was exploited to evaluate the association degree

between the index and the filtered water turbidity percentage lower than

a previous established value. The filtered water turbidity was selected as

the mark to assess the WTPQI applicability because, besides to be a

parameter of treatment effectiveness, all plants have been monitoring it.

For a better comparison among the obtained values, they were

organized in Table 5, outstanding the more significant results (R2), and

also including the correlation with the percentage below 0,7 NTU, as an

intermediary between the maximum level (1,0 NTU) and the

recommended 0,5 NTU. For the rainy season, it is possible to observe that

the multiplicative form (Equation 3) presented more significant results

when compared with the filtered water turbidity percentage lower than

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0,1 and 0,3 NTU, and with the value higher than 95 % of turbidity data.

On the other hand, the summation form (Equation 2) has showed more

significance for the percentage lower than 0,5 and 0,7 NTU. However, in

the drought season, despite the better results with summation form, the

WTPQI values were correlated with high p values. This fact indicates a no

correlation among these variables.

Table 5 Linear correlation coefficients (R)Percentage of filtered water turbidity values below the established limit

Rainy Season Drought Season


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the answer is yes. Based on this analysis it is supposed that only

parameter, such as Vs or Gcor, can affect the plant performance as much

as to decide by a final low grading even all other parameters are suitable.

This decision was confirmed by the highest correlation values for the

WTPQI multiplicative when more restrict filtered water turbidity standards

were utilized.

Afterwards, it was evaluated whether establishing of goals to the

filtered water turbidity was inducing to a correlation between then and

the WTPQI. In this context, there were elaborated scatter graphs between

the daily WTPQI values and the daily average of filtered water turbidity,

for ten plants with six months data. It was characterized a correlation

between then, a little higher to the summation form for the linear

correlation (r) and the same to the multiplicative form in terms of the no-

linear correlation (Table 7).

Table 6: Correlation between filtered water turbidity and the WTPQI for alldataR r2

WTPQI - S -0,47 0,22 -0,37

WTPQI - M -0,39 0,15 -0,42

With the finality to evaluate the possible correlation between the

raw water and settled water turbidity, and between the settled and

filtered water turbidity, the linear correlation coefficients were calculated

for all plants which data were available, as shown in Table 8.

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Table 7: Correlation between turbidity values of Raw/Settled Water and Settled/Filtered Water

Plants

Raw Water/SettledWater

Raw Water/FilteredWater

R r2 R r2

WTP 1 0,557 0,310 0,130 0,017

WTP 3 0,571 0,326

WTP 4 0,778 0,605WTP 5 0,527 0,278 0,636 0,405

WTP 6 0,561 0,314 0,475 0,226

WTP 7 0,451 0,204 0,399 0,159

WTP 8 0,754 0,569 0,642 0,412

WTP 9.A 0,714 0,510 0,652 0,425

WTP 9.B 0,532 0,283 0,783 0,613

WTP 9 B and A Before and after enlargement

The plants with good performance have to be able to produce

constant quality filtered water independently of the raw water quality. Infunction of this premise and the Table 8 data, the WTP 7 presented the

best results for sedimentation and the WTP 2 the same for filtration. On

the other hand, the WTP 4 and the WTP 9B presented the worst

performance for sedimentation and filtration, respectively.

In this context, another question arose. Do the water treatment

plants producing filtered water with a regular quality have the higher

WTPQI values? Trying to solve this question, there were elaborated thegraphs shown in Figure 3, with the WTPQI (summation and multiplicative

forms) on the horizontal axis and the r2 values (obtained for settled and

filtered water) on the vertical axis.

r 2 ( s e t t le d t u r b i d i t y / fi l t e r e d t u r b i d i ty ) x W T P Q I

W T P Q I S u m m a t i o n : r 2 : r 2 = 0 , 0 2 8 7 ; r = 0 , 1 6 9 3 , p = 0 , 7 1 6 7

E T A I I

E T A V

E T A V I

E T A V I I

E T A V I I IE T A I X . A

E T A I X . B

7 6 7 8 8 0 8 2 8 4 8 6 8 8 9 0 9 2 9 4

W T P Q I S u m m a t io n

- 0 , 1

0 , 0

0 , 1

0 , 2

0 , 3

0 , 4

0 , 5

0 , 6

0 , 7

r2

r 2 ( s e t t l e d t u r b i d i t y / f i lt e r e d t u b i d i t ) x W T P Q I

W T P Q I M u l t ip l ic a t iv e f o r m : r 2 : r 2 = 0 , 1 9 7 1 ; r = - 0 , 4 4 3 9 , p = 0 , 3 1 8 4

E T

E T A V I I

E T A V I I I

6 4 6 5 6 6 6 7 6 8 6 9 7 0 7 1 7 2 7 3 7 4 7 5 7 6 7 7 7 8

W T P Q I M u l t i p l i c a t i v e f o r m

0 , 1 5

0 , 2 0

0 , 2 5

0 , 3 0

0 , 3 5

0 , 4 0

0 , 4 5

0 , 5 0

r2

FIGURE 3: Scatter plots r2 x WTPQI for summation and multiplicative forms(rainy season)

It was observed in these graphs that the affirmative answer for theprevious question was completely rejected for the WTPQI summation.

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Despite its low magnitude, for the multiplicative form, the results were

significantly better than those obtained by the summation form.

The supremacy of the WTPQI multiplicative can be confirmed

comparing it with the correlation between settled and filtered water

turbidity. In other words, the plants with the lowest WTPQI multiplicative

values presented too the lowest correlation between settled and filtered

water turbidity. Also, the WTPQI usefulness was verified by the

comparison of the results obtained by the WTP B and WTP A,

demonstrating the index sensibility to the plant improvements followed

by the enhancing of filtered water quality.

CONCLUSIONS

It was verified that two rounds were not enough to reach a higher

consensus among the respondents for a definition of the weights mainly

to the more relevant parameters. For some parameters the dispersion

increased after the second round. Concerning the parameters hierarchy,

the questionnaires demonstrated an evident consensus about the more

relevant to the treatment effectiveness. According to a tendency of the

national and international standards, which have been emphasizing

progressively the reduction of filtered water turbidity, the rate filtration

was chosen the most relevant parameter by the panel.

Despite some limitation in function of the sample size of ten water

treatment plants, the significant correlations pointed out a tendency of

the plants producing good filtered water quality usually present high

WTPQI values. The higher correlation values were presented to the WTPQI

multiplicative when more restrict standards were established. However,

for plants with high scores in all parameters the final WTPQI is

approximately the same for both formulations.

Based on the premise of plants with good performance must be able

to produce regularly high filtered water quality, despite the changes of

raw water, the WTPQI multiplicative was more efficient than the WTPQI

summation. It was evident when the comparison was made in terms of r2

values between settled and filtered water turbidity, showing more

sensible and able to classify the plants, conferring better scores to those

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with a more accurate performance.

Finally, the correlations confirmed the principles in which the

grading criteria for 19 parameters were based on, and the WTPQI

multiplicative as a good indicator to make the plants hierarchy. In this

way, the WTPQI multiplicative may be an interesting tool to the water

supply system administrations.

RECOMMENDATIONS

Evidently, a more complete analysis has to involve, besides the

WTPQI and the finished water quality, an index for the raw water in terms

of its higher or lower treatment feasibility. New researches may improve

the WTPQI increasing its accuracy, basing on the disagreements arose in

these two rounds. Also, a research opinion about the developed grading

criteria may contribute significantly to the better index accurateness.

Finally, the WTPQI application to a higher number of plants would be

useful to confirm, or not, this tendency.

REFERENCES

BRAZILIAN TECHNICAL STANDARDS ASSOCIATION (ABNT) Water

treatment plants design, NBR 12216, Rio de Janeiro, 1990. (in Portuguese)

BROWN, R. M.; MCCLELLAND, N. I.; DEINIGER, R. A. & TOZER, R. G. - A

water quality index do we dare?, Water & Sewage Works, Chicago, v

117, n.10, p.339-43, October 1970.

CONSONERY, P. J.; GREENFIELD, D N. & LEE, J. J. - Pennsylvanias filtration

evaluation program, JAWWA, v.89, n.8, p. 67-77, August 1997.

GUIDELINES FOR PHASE IV: Partnership for safe water, AWWA et al, 2003.

HELSEL, D. R. & HIRSCH, R. M. - Statistical methods in water resources,

U.S. Geological survey, 503 p., 2002.

LINSTONE, H. A. & TUROFF, M. - The Delphi Method: techniques and

applications, Addison-Wesley Publishing Company: Massachusetts, USA,

620 p., 1975.

HEALTH MINISTRIO DA SADE MS. Portaria 518: Normas e padro de

potabilidade da gua destinada ao consumo humano. Braslia,

maro.2004.

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NIEMINSKI, E. C. & ONGERTH, J. E. Removing Giardia and Cryptosporidium

by conventional treatment and direct filtration. JAWWA, New York, v. 87,

n. 9, p. 96-106, September1995 apud LeCHEVALIER, M. W. & AI, K.

Water Treatment and Pathogen Control, WHO, London, 112 p., 2004.

RENNER, R. C. et al. - Composite Correction Program Optimizes

Performance at Water Plants.JAWWA, v.85. , n. 6, p.67-74, June 1993.

TAYLOR, J. G. & RYDER, S. D. - Use of the Delphi method in resolving

complex water resources issues. Journal of the Americam Water

Resources Association, New York, v. 39, n.1, p. 183-189, February 2003.

USEPA. Optimizing water treatment plant performance using composite

correction program.Cincinnatti, Ohio : USEPA CERI.1998.168p.( EPA/625/3-

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