international journal of civil engineering and … and sensitivity...international journal of civil...

International Journal of Civil Engineering and Technology (IJCIET), ISSN 0976 – 6308

(Print), ISSN 0976 – 6316(Online) Volume 4, Issue 4, July-August (2013), © IAEME

119

DEVELOPMENT AND SENSITIVITY ANALYSIS OF WATER QUALITY

INDEX FOR EVALUATION OF SURFACE WATER FOR DRINKING

PURPOSE

R. S. Sapkal1, Dr. S. S. Valunjkar

2

1Research Scholar, Department of Civil Engineering, Government College of Engineering,

Aurangabad, Maharashtra, India 2Professor in Civil Engineering, Government College of Engineering, Karad, Sistt: Satara,

Maharashtra, India

ABSTRACT

Water pollution not only affects water quality but also threats human health, economic

developments & social prosperity Internationally there are number of attempts made to produce a

method that meaningfully integrates the data sets and converts them into simple information called as

Water Quality Index (WQI) Water quality indices are used as comprehensive evaluation instrument

to assess the river water quality. Water quality index makes expert knowledge available to expert

users and public in general. The indices are formulated based either on studies conducted by the

indices developers or are formulated based on the Delphi technique which takes into account the

opinion of experts or mathematical formulation or by using fuzzy logic. In this study the water

quality index is developed by assigning relative weights to each parameter ranging from 1 to 6 based

on the adverse effect of the water quality parameter on human health, its concentration with respect

to other water quality parameters and method of treatment required. It includes twenty five water

quality parameters such as Color water temperature, pH, Electrical Conductivity (EC), Turbidity,

Suspended Solids (SS), Total Dissolved Solids (TDS), Total Hardness (TH), Total Alkalinity (TA),

Dissolved Oxygen (DO), Biochemical oxygen demand (BOD), Chemical oxygen demand (COD),

Sulfates (SO4- -

),, Chlorides, Total Phosphates ( TP -), Calcium (Ca

++),

Magnesium (Mg++

), Fluorides

Ammonium- Nitrogen (NH3-N), Nitrate-Nitrogen (NO3-N), Nitrite-Nitrogen (NO2-N) Total coliform

(TC), Fecal coliform (FC), Sodium (Na+) and Boron(B) Water quality is categorized into five levels

based on the values of water quality index as Excellent (WQI = 95 to 100), Good (WQI = 80 to 94),

Fair (WQI = 65 to 79), Marginal (WQI = 45 to 64) and Poor (WQI = 0 to 44). The sensitivity

analysis shows that this WQI is not influenced by any one or few parameters but it is a combined

effect of all the parameters. It is applied to Purna (Tapi) river basin of Maharashtra (India).

Key words: Method of aggregation, Purna River, Water Quality Index, water quality parameters

INTERNATIONAL JOURNAL OF CIVIL ENGINEERING AND

TECHNOLOGY (IJCIET)

ISSN 0976 – 6308 (Print)

ISSN 0976 – 6316(Online)

Volume 4, Issue 4, July-August (2013), pp. 119-134 © IAEME: www.iaeme.com/ijciet.asp

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IJCIET

© IAEME



120

1. INTRODUCTION

Nowadays environmental protection and water quality management has become an important

issue in public policies throughout the world Many countries have introduced a scheme of river

water quality monitoring and assessment of surface water in terms of their physical, chemical,

biological and nutrient constituents and overall aesthetic condition [1]. There are number of methods

to analyze water quality data depending on informational goals, the type of samples and size of

sampling area. The water quality is difficult to evaluate from a large number of samples each

containing concentrations for many parameters. One of the most effective ways to communicate

information on environmental trends and river water quality in particular is with indices Water

quality index is a means to summarize large amount of water quality data in to simple language (i.e.

good, average or poor quality) for responding to management and the general public in consistent

manner. It tells us whether the overall quality of water body possesses a potential to various uses of

water such as irrigation, recreation or drinking water purpose.

Water Quality Index (WQI.) a great deal was given to the development of index methods by

Brown R. M., McClelland N. R., Deininger R. A. and Tozer R. Z. [2] of United States proposed a

WQI known as National Sanitation Foundation Water Quality Index (NSF WQI.) It was designed to

evaluate general water quality irrespective of water use. It included nine water quality parameters -

Dissolved Oxygen (DO), Fecal Coli form (FC), pH, Biochemical oxygen demand (BOD), Nitrate -

Nitrite, Phosphorous, turbidity, temperature and total solids Initially water quality and score ranges

were subdivided into seven classes as follows. Excellent (90-100), Good (80-89), slightly good (70-

79), Average (50-59), slightly bad (40-49), bad (20-39) and very bad (below 19). Initially it was

based on arithmetic mean of weighted sub-index of each variable. So it was not significantly

sensitive to change in the values of variables. Then it was modified by taking the geometric mean

After modification the water quality and score ranges were subdivided into five classes i.e.,

Excellent- A (91-100), Good-B (71-90), Medium-C (51-70), Bad-D (26-50) and Very bad –E (0-25)

It serves as the basis of other several water quality indices. Curtis G Cude [3], Oregon Department of

Environmental Quality [4] had developed Oregon water quality index (OWQI) in 1970 and modified

it in 1990. The OWQI also serves as the bench mark indicator of stream water quality for the Oregon

Progress Board. Bindu M. Lohani and G. Todino [5] used factor analysis (FA) to develop water

quality index for Chao Phraya river in Thailand. Bhargave D. S., (1985) [6] suggested grouping of

water quality parameters for drinking purpose and evaluated a water quality index for drinking water

supplies.

L Gabriel T., de Azevedo, Timothy K. Gates, Darrell G. Fontane, John W. Labadie and

Ruben L. Porto [7] had combined the surface water quantity and quality objectives to develop water

quality routing and water allocation model for Piracizaba river in Brazil. Six management

alternatives combining various reservoir policies with differing levels of treatment were suggested.

Canadian Council of Ministers for Environment (CCME) [8] developed a water quality index called

as Canadian Council of Ministers for Environment Water quality Index (CCME WQI) it compared

observations to a bench mark where bench mark may be a water quality standard or site specific

variable concentration. It included ten water quality variables including 2, 4- D and lindane, it

quantifies for one station over a predetermined period of time (typical one year) the number of

parameters that exceeded the bench mark the magnitude of exceedance and the number of records

exceeded the bench mark. The index is flexible in terms of the bench marks that are used for

calculations Sites at which water quality measurement never or rarely exceed the benchmark have

high CCME WQI (near 100) where as sites that routinely have measurements that exceed

benchmarks have low CCME WQI (near 0).The water quality levels suggested are Excellent (95 -

100), Good (80-94), Fair (65-79), Marginal (45-64) and Poor (below 45) Shiow - Mey Liou, Shang -

Lien Lo and Shan - Hsien Wang (2004) [9] proposed a overall index for water quality in Taiwan and



121

its application in Keya river. Ahmaid Said et.al [10] defined a new water quality index for Big Lost

river water shed in Idhao. to assess water quality for general use Chinmoy Sarkar and S. A. Abbasi,

[11] have developed a software called QUALIDEX to determine various WQI William Ocampo-

Duque et.al [12], have developed WQI by using fuzzy inference system.

S. S. Asadi, Padmaja Vuppala and M. Anji Reddy [13] assessed the ground water quality in

Municipal corporation of Hyderabad (India) by using water quality index related to land use. They

have used remote sensing and GIS techniques for evaluation of groundwater quality for development

of water quality index Fuzhan Nasiri et al. [14], proposed fuzzy multiple attribute decision support

system to compute water quality index and to provide alternative plans based on improvement in

water quality index. Prabhata K. Swamee and Aditya Tyagi [15] used alternative method to describe

water quality using aggregate index consisting of sub-indices for water quality variables. L. K.

Diadovski and M. P. Atanassova [16] had developed an integral index of the tropic pollution level

for Mesta river of Bulgeria. The water quality parameter considered were BOD, COD, total nitrogen,

total phosphorus DO, metals like cadmium chromium copper, Zinc and lead, detergent phenol and

coli form. K values for each parameter was determined and the integral index was formulated.

Mohsen [17] had developed WQI to describe water contributed by mining activities in Malaysia. The

water quality index was calculated by considering nine water quality parameters. Yilmaz Icaga

(2007) [18] suggested a WQI model using fuzzy logic and applied it to assess the water quality of

Eber Lake (Turkey). He has tried to remove the ambiguities due to concentration level of the

parameter very close to the permissible limits. Prakash Raj Kannad, Seockheon Lee Young Soo Lee,

Sushil Raj Kannel, Siddhi Pratap Khan [19] have investigated: WQI considering 18 water quality

parameters, WQImin &WQIm (mean water quality index) and WQIDO (considering a single parameter

DO) Hulya Boyacioglu [20] ,[21] developed universal WQI (UWQI) based on European

Classification Scheme

Andre Lermontov et al [22], used fuzzy logic to develop water quality index called as fuzzy

water quality index (FWQI) for Pardo river, Brazil. Chaiwar Prakirake et al.[23], developed water

quality index (WQI) applying Delphi technique Dinesh Kumar and Babu J. Allappat [24] studied

National Sanitation foundation water quality index (NSF-WQI) and brought out the short comings in

the formation of NSF WQI and suggested the possible improvement. M. K. Chaturvedi and J. K.

Bassin (2009) [25] have assessed the water quality index for water treatment plant and bore well in

Delhi area using NSFWQI to classify water quality as excellent, good, medium, bad and very bad.

Abdul Hameed Jawad Alobaidy [26] developed WQI using cluster analysis and by considering

thirteen water quality parameters Mohamad Ali Fulazzaky et. al [27], assessed the water quality of

Selongor river from nine stations along the main stream using WQI. Avnish Chauhan and Suman

Singh [28] developed WQI by considering eight water quality variables (Turbidity, DO, BOD, COD

,free CO2, Total solids( TS),Total Suspended Solids(TSS) & TDS) & applied it to evaluate Ganga

water for drinking purpose & concluded that Ganga Action Plan launched by Government of India

has failed to reduce the pollution level in Ganga river. Abdul Hameed M. Jawed Alobaidy, Haider S.

Abid and Bahram K. Maulood [29] developed water quality index considering ten water quality

parameters. This WQI was applied to assess the water quality of Docan Lake, Iraq.

1.1. Aggregation Functions It is the most important step in calculating WQI. In order to minimize ambiguity and

eclipsing, it is necessary to identify an appropriate function of calculating and aggregated score. The

following functions are normally used. Table 1 shows various aggregation functions



122

Table 1: Various aggregation functions

Aggregation

function

Formula Remarks

Weighted sum

index ��

� This method of aggregation is free

from ambiguity but suffers from

eclipsing.

Multiplicative

product index or

weighted geometric

function

WQI � �Qi��

In this aggregation function, an

index is zero if any one sub index

is zero. This characteristic

eliminates the eclipsing as well as

ambiguity problem

Weighted Solway

function

�� 1100 ��

Un-weighted

Solway function �� 1100 �1��

Un-weighted

geometric function

WQI= �∑ �� }1/n

Root mean square

function

�� 0.5�!"�#��$��% &#1/�$(∑��)

Un-weighted

harmonic

square mean function

�� * �+∑ #��$�� ,

Maximum Operator

index �� !-. �I1, I2, I3, …… In� This is ideally suited to

applications in which an index

must report if at least one

recommended unit is violated

Minimum Operator

index �� !"� �I1, I2, I3, …… In� This aggregation method is free

from eclipsing as well as

ambiguity

Where, �" = sub-index for "th variable

�" = relative weight for "th variable

2.0 MATERIALS AND METHODS

2.1 Development of Water Quality Index The indices are formulated based either on studies conducted by the indices developers or are

formulated based on the Delphi technique which takes into account the opinion of experts or

mathematical formulation or by using fuzzy logic. In this study WQI is developed as follows



123

2.1.1 Selection of parameters Water quality parameters were selected based on the criteria- Parameters considered by

previous researchers, parameters for which data is available and will be available over wide range of

time, parameters producing adverse effect on human health It includes twenty five water quality

parameters such as Color water temperature, pH, Electrical Conductivity (EC), Turbidity, Suspended

Solids (SS), Total Dissolved Solids (TDS), Total Hardness (TH), Total Alkalinity (TA), Dissolved

Oxygen (DO), Biochemical oxygen demand (BOD), Chemical oxygen demand (COD), Sulfates

(SO4- -

),, Chlorides, Total Phosphates ( TP -

), Calcium (Ca++

),

Magnesium (Mg++

), Fluorides

Ammonium- Nitrogen (NH3-N), Nitrate-Nitrogen (NO3-N), Nitrite-Nitrogen (NO2-N) Total coliform

(TC), Fecal coliform (FC), Sodium (Na+) and Boron(B)

2.1.2 Assigning weight Each selected parameter was assigned a weight (WA) based on the criteria shown in Table 2

and Table 3. The parameter which produces adverse effect on human health, has more concentration

relative to other parameters and requiring advance or special treatment method for its removal, is

assigned less weight so that it should lower the WQI. The parameters which does not have any

adverse effect on human health, has less concentration relative to other parameters and requires

conventional method for its removal is assigned a higher weight so that it should increase the WQI.

Excursion for parameter is determined based on the concentration (test value) of parameter and the

guideline value. It is determined as follows.

Table 2: Importance of water quality parameters

Parameter

Unit

WHO [30],

BIS [31],

and CPCB

[32]

permissible

limits

Effect on human health

beyond permissible

limit/ guideline value

Method for

removal

Remarks

Color TCU 15 No direct health effect

Aesthetically unpleasant

[31]

Conventional

* treatment

Color is due to

natural organic matter

and colloidal matter

from suspended

solids, iron,

manganese, Here true

color is considered.

Temperature O C 18 - 22 No health effect Only

aesthetic effect

-

Higher temperature

suggests that the

water has fewer

amount of insoluble

pollutants [33]

Temperature is

known to influence

pH, alkalinity and

DO [34] Rate of

biological reaction

and production of

bacteria increases [1]



124

pH - 6.5 – 8.5 No sufficient evidences

for adverse effect are

available Only aesthetic

effect

Conventional

treatment

pH > 8.5, water is

bitter in taste. [35]

Ammonia changes to

more toxic state of

un-ionized ammonia

at pH> 7. Color

intensity increases

with increase in pH

[36]

Electrical

Conductivity

µS/cm

750

No health effect It

greatly affects the taste

[26]

Conventional

treatment

Depends on amount

of total dissolved

solids in water. It

represents he salinity

It is function of

temperature and

number of dissolved

ions in water. [10, 33]

Water reach in

bicarbonate, calcium

and magnesium has

low conductivity.

Water with high

conductivity has

more concentration of

sodium and chlorides.

[7]

Turbidity NTU 5 Aesthetic ally unpleasant

[31]

Conventional

treatment

Indicates more

amount of suspended

matter and indicates

possibility of harmful

matter [10]

Suspended

Solids

mg/l 25 No direct adverse effect

on human health Only

aesthetic effect

Conventional

treatment

It contributes to

turbidity of water. It

increases water

temperature by

absorbing heat from

sunlight leading to

depletion of DO [37]

Total

Dissolved

Solids

mg/l

500

Only aesthetic effect Conventional

treatment

Affects electrical

conductivity

Total

hardness

mg/l 300 Only aesthetic effect Lime

softening

Reduces toxicity of

cadmium, lead, nickel

and zinc [38]

Total

Alkalinity

mg/l 200 Only aesthetic effect Conventional

treatment

If alkalinity is too

high water becomes

turbid.



125

Biochemical

oxygen

demand

mg/l <3 No direct health effect

Conventional

method

High BOD causes

oxygen depletion [9]

Chemical

oxygen

demand

mg/l <20 No direct health effect Conventional

method

--

Sulfates mg/l 250 No direct health effect

It imparts taste to water

[36]

Ion exchange --

Chlorides mg/l 250 Impart salty taste to

water [36]

Desalination --

Calcium mg/l 75 It imparts taste to water Lime

softening,

Activated

carbon

Increases hardness

Magnesium mg/l 30 It imparts taste to water Lime

softening,

Activated

carbon

Increases hardness

Fluorides mg/l 1.5 Causes dental fluorosis,

skeletal diseases, enamel

mottling and bone

deformations [7, 38]

Excess fluoride causes

sequence o changes in

teeth, bone and tissues

leading to simple

mechanical back pain to

severe crippling and

neurological

impairment, stiffness in

the neck and joints [38]

Fluoride concentration

over 1.5 mg/l poses high

risk of fluorosis to

people. The risk

increases with increase

in fluoride content. [39]

Concentration below

0.6mg/l causes dental

carries [36]

De-

fluoridation

by ion

exchange

activated

alumina

--

Dissolved

Oxygen

mg/l 6 -10 No health effect Only

aesthetic effect

Aeration Depends on

temperature of water

[10] Less

concentration

converts nitrates to

nitrite and sulfates to

sulfides



126

Total

phosphates

mg/l 0.4 Only aesthetic effect Precipitation

with Fe (III),

Aluminum

(III)

Excess phosphorus

causes algal growth

decreasing the DO

level & rises water

temperature [10]

Ammonium-

nitrogen

mg/l

0.5

Only aesthetic effect Ion exchange It depends on

temperature, pH and

total dissolved solids

[3]

Nitrate-

nitrogen

mg/l 10 High concentration

causes

methaemoglobinemia or

blue baby disease in

infants

Ion exchange --

Nitrite-

Nitrogen

mg/l 1 Presence of nitrite in

water is dangerous

Nitrite reacts with nitro-

sotable compounds in

the body to form N-

nitro -so compounds

which are carcinogenic

[36]

Conventional

treatment

(Chlorination

)

--

Parameter Unit WHO

guideline

value / IS /

CPCB

permissible

limits

Effect on human health

beyond permissible

limit/ guideline value

Method for

removal

Remarks

Total

coliform

MPN/

100ml

0

Causes gastroentitis,

urinary tract infection,

diarrhea , typhoid fever,

bacillary dysentery[36]

Conventional

treatment

It is influenced by

temperature

Faecal

coliform

MPN/

100ml

0

Causes gastroentitis,

urinary tract infection,

diarrhea [36]

Conventional

treatment

It is influenced by

temperature

Sodium mg/l 200 Impart taste to water Ion exchange

--

Boron mg/l 0.5 It develops metal

toxicity It is toxic to

reproductive tract

Ion exchange

and Reverse

Osmosis

--



127

Table 3: Criteria for assigning weights to water quality parameters

Sr.

No.

Criteria Description Weight

(WA)

Minimum

weight

Maximum

weight

1 Effect on human

health

Aesthetic effect only 2

1

2 Aesthetic effect and adverse

effect on health

1

Only adverse effect on health 1

2 Parameter

concentration

related to

concentration of

other parameters

Excursion of parameter

concentration less than average

excursion

2

1

2

Excursion of parameter

concentration more than

average excursion

1

3 Treatment method

(Method for

removal)

Conventional treatment process 2

1

2 Advance / Special treatment

process

1

Minimum / Maximum weight 3 6

Test value exceeds the guideline value excursion � A BCDE FGHICJI�KCH��C LGHIC M 1N (1)

Test value below the guideline value excursion � AJI�KCH��C FGHICBCDE FGHIC M 1N (2)

Calculation of relative weight

A relative weight #�R$ for each parameter is calculated by using “equation (3)” [i.e. dividing

assigned weight of parameter (WA) by sum of assigned weights of all parameters # ∑�A $]. �Q � RS∑RS , and ∑�R� 1 (3)

2.1.3 Construction of Sub-Index Equations for Individual Selected Parameter To assign the sub-index values, the water quality parameters guideline values (permissible

limits) of World Health Organization [30], Bureau of Indian Standards (BIS) [31] and Central

Pollution Control Board (CPCB) [32] are used The water quality sub-index equations are formulated

according to the water quality classification used in this study The For a parameter which requires

only conventional method of treatment, the parameter concentration equal to guideline value is

considered at WQI value of 80 whereas for a parameter which requires advance or special method of

treatment, parameter concentration equal to guideline value is considered at a WQI value of 60 This

is done so that WQI should represent correct water quality The sub-index equations for various

parameters are shown in Table 4



128

Table 4: Sub-index equations Water

quality

parameter

Sub-index equation Water

quality

parameter

Sub-index equation

Color x ≤ 5,

15 < x ≤ 300,

x ≤ 15

x > 300,

y=100

y = -0.254x+81

y = -1.872x+106.1

y = 0

Chlorides x ≤ 78,

75 < x ≤ 5000

x > 5000,

y = 100

y = -23.3ln(x)+198.9

y = 100

Temperature x ≤ 3,

x ≤ 18,

18 > x ≤22,

22 < x ≤37,

x > 37,

y = 0

y = 6.441x-12.37

y = 100

y = -6.228x+233.7

y = 0

Calcium x ≤ 10,

10 < x ≤ 425,

x > 425

y = 100

y = 0.0001x2-

0.274x+98.73

y = 0

pH x ≤ 2,

2 < x < 7

7 ≤ x ≤13,

x >13,

y = 0

y = 2.695x2-5.95x+2

y = 2.914x2-78.66x+528

y = 0

Magnesium x ≤ 5,

5 < x ≤ 180,

x > 180,

y = 100

y = 0.001x2-0.716x+100

y = 0

Electrical

conductivity

x ≤ 275,

275<x ≤ 5000

3700<x≤7500

x>7500,

y = 100

y = 2E-06x2-0.081x+108.4

y = 3E+06x-1.41

y = 0

Fluorides x ≤ 0.15,

{0.15< x≤ 0.7,

and

1 < x ≤ 2.2}

0,7 < x ≤ 1,

x > 2.2,

y = 0

y = 65.8x5+412.2x

4-

888.8x3+685.8x

2-

47.27x+3.415

y = 100

y = 0

Turbidity x ≤ 2,

2 < x ≤ 200,

x> 200,

y = 100

y = -21.4ln(x)+115

y = 0

Total

phosphates

x ≤ 0.1,

0.1 < x ≤7.5,

x > 7.5,

y = 100

y = -22.4ln(x)+47.88

y = 0

Suspended

solids

x ≤ 5,

5 < x ≤ 190,

x > 190,

y = 100

y = 0.001x2-0.542x+102

y = 0

NH3 - N

x ≤ 0.03,

0.3 < x ≤ 40,

x> 40,

y = 100

y = -13.8ln(x)+51.78

y = 0

Total

dissolved

solids

x ≤ 180,

180<x < 28000

x > 28000

y = 0

y = -18.5ln(x)+196.4

y = 0

NO3 – N

x ≤ 2,

2 < x ≤ 14.5,

15 < x ≤ 50,

x > 40,

y = 100

y = -4.356x+102

y = -30.6ln(x)+120.3

y = 0

Total

hardness

x ≤ 50,

50< x ≤ 2500,

x > 2500,

y = 100

y = 1E-05x2-0.066x+109.8

y = 0

NO2 - N

x ≤ 0.04,

0.4 < x ≤ 28,

x > 28,

y = 100

y = -15.3ln(x)+52.11

Total

alkalinity

x ≤ 20,

20 < x ≤ 780,

750<x≤3000,

x>3000,

y = 100

y = -0.105x+102

y = -0.008x+26

y = 0

Total

Coliform

x ≤ 0,

0< x ≤ 50,

50< x ≤ 400,

400 < x ≤ 70000

x>70000,

y = 100

y = -0.403x+100

y = -0.028x+81.2

y = -0.001x+70.77

y = 0

Dissolved

oxygen

x ≤< 1,

1 ≤ x <8,

8 ≤ x ≤ 10,

10 < x ≤ 13,

x >13,

y = 0

y = -0.14x3+1.468x

2+

9.519x-2.088

y = 100

y = -0.14x3+1.468x

2+

9.519x-2.088

y = 0

Fecal

Coliform

x ≤ 0,

0< x ≤ 20,

20 < x ≤ 200,

200 < x ≤ 34000,

x> 350000,

y = 100

y = -x+100

y=-0.055+81.11

y = -0.002x+69.76

y= 0

BOD x ≤ 1,

1 < x ≤ 90,

x > 90,

y = 100

y = -23.3ln(x)+105.7

y = 0

Sodium

x ≤ 65,

65 < x ≤ 2000,

x > 2000,

y = 100

y = -27.8ln(x)+212.1

y = 0

COD x ≤ 9,

9 < x ≤ 450,

x > 450,

y = 100

y = -25.3ln(x)+155.5

y = 0

Boron

x ≤ 0.075,

0.075 < x ≤ 10,

x>10,

y = 100

y = -19.9ln(x)+47.22

y = 0

Sulfates x ≤ 40,

40 < x ≤ 2000,

x > 2000,

y = 100

y = -23.4ln(x)+188.8

y = 0

Where, x = Concentration of parameter and y = Water quality

Sub-index

2.1.4 Overall WQI The multiplicative product method of aggregation is used to overcome problems of eclipsing

and ambiguity Overall water quality index is determined by formula given in “equation (4)”

�� ∑ T��RUV�� (4)



129

2.1.5 Water Quality Categorization The water quality is classified into five categories Table 5 shows the water quality index

(WQI) ranges and the classification of water

Table 5: Ranges of Water Quality Index and water quality category (CCME, 2001)

Water quality

category

Water Quality

Index Values

Water quality description

Excellent 95 - 100 Water quality is protected with a virtual absence of threat or

impairment. All measurements are within objectives virtually of all

the time

Good 80 - 94 Water quality is protected with minor degree of threat or

impairment; conditions rarely depart from desirable levels

Fair 65 - 79 Water quality is protected but occasionally threatened or impaired;

conditions sometimes depart from desirable levels

Marginal 45 - 64 Water quality is frequently threatened or impaired; conditions often

depart from desirable levels

Poor 0 - 44 Water quality is almost always threatened or impaired; conditions

usually depart from desirable levels

Source: Canadian water quality guidelines for protection of aquatic life : CCME water quality

index”, User’s manual. CCME 2001

3.0 STUDY AREA

The study area includes Purna (Tapi) river basin of Maharashtra, INDIA Purna river originates at It

flows southwards through Amravati district, then westwards through Akola and Buldana districts to

discharge itself into Tapi river near Changdeo in Jalgaon district Total length of Purna river is 334 m

The river is perennial and has many tributaries The climate of this area is dry and hot except for

monsoon (June-September) The basin area is about 7800 Km2

out of which central 3000 Km2

is

known as saline track Yearly rainfall is 700-800 mm Six stations were identified for development of

WQI Fig 1 shows Purna (Tapi) river basin and location of identified stations

Fig 1: Purna (Tapi) river basin



130

4.0 RESULTS AND DISCUSSION

Table 6 shows typical water quality characteristics of Purna (Tapi) river basin WQI so

developed is applied to selected stations of Purna (Tapi) river basin Temperature, total coliform,

Fecal coliform, Suspended solids and turbidity exceeded the guideline value deteriorating the water

quality and lowering WQI Fig shows parameters that are exceeded (as percentage of total

exceedance) over the guideline value More than 50% exceedance is due to temperature, total

coliform and Fecal coliform together where as parameters like Sulfates, Chlorides, Calcium,

Magnesium, Total phosphates, Nitrate Nitrogen and sodium are not exceeded the guideline value at

all The water quality of these stations is categorized as good.

Table 6: Water quality characteristics of Purna (Tapi) river basin

Parameter Mean± SD Parameter Mean± SD Parameter Mean± SD

Color 6 ±0.167 DO 6.29±0.669 TP 0.066±0.079

Temperature 28.7 ± 8.440 BOD 2.73±0.924 NH3-N 0.202±0.041

1.041pH 8.34±0.213 COD 10.05±0.637 NO3-N 0.688±0.597

EC 438±162 Sulfates 12.44±6.152 NO2-N 0.07±0.200

Turbidity 32±70 Chlorides 51.78±41.903 Total Coli 91±99

SS 33±48 Calcium 26.50±8.091 Faecal Coli 37±48

TDS 289±120 Magnesium 22.25±9.886 Sodium 87.24±27.552

TH 158± Fluorides 0.534±0,267 Boron 0.151±0.152

TA 164±51

Fig 2 shows variation in WQI in winter and summer for these stations Due to increased

concentration of turbidity, suspended solids, total coliform and fecal coliform in winter lower the

WQI whereas the water is very clean with concentration of turbidity and suspended solids improved

the WQI in summer Fig 3 shows variation in WQI for these stations during 2005- 2008.

Table 7 show correlation coefficient between WQI and concentration of parameters All parameters

shown negative correlation with negative correlation with WQI except for color, pH, temperature,

dissolved oxygen, sulfates and fluorides Positive correlation between WQI and dissolve oxygen

indicates that as dissolved oxygen increases WQI also increases pH values are mostly less than 8.5

As pH concentration approaches to guideline value of 6.5-8.5, WQI increases Guideline value range

for temperature is 18 OC–22

OC as water temperature approaches to this range WQI increases For

color and sulfates the concentrations are well within guideline value, so the decrease in WQI is not

due to these parameters but it is due to the combined effect of all other parameters. While deciding

the water quality sub-index equation, lower guideline value of 0.6 mg/l is decided to avoid dental

carries Fluoride concentration are well within guideline value and as these concentrations approaches

to 0.6 mg/l, it lowers the WQI



131

Fig 2: Variation in WQI in winter and summer Fig 3: Variation in WQI during 2005-2008

Table 7: Correlation coefficient between WQI and Concentration of parameters

Parameter r Parameter r Parameter r

Color 0.435 DO 0.880 TP -0.901

Temperature 0.486 BOD -0.898 NH3-N -0.597

pH 0.411 COD -0.838 NO3-N -0.255

EC -0.610 Sulfates 0.172 NO2-N -0.250

Turbidity -0.689 Chlorides -0.795 Total Coli -0.955

SS -0.960 Calcium -0.303 Fecal Coli -0.831

TDS -0.7 Magnesium -0.449 Sodium -0.804

TH -0.777 Fluorides 0.346 Boron -0.064

TA -0.496

r =Correlation coefficient

4.1 Sensitivity Analysis

WQI was also determined by removing each parameter at a time Fig 6 shows WQI after

removal of the said parameter. It is observed that WQI is not varied much due to removal of an

individual parameter. Table 8 shows correlation coefficient between WOI and WQI after a particular

parameter is removed. All parameters have shown positive correlation with WQI after its removal.

No parameters have shown negative correlation with WQI after its removal. It shows that WQI is not

influenced only by one or few parameters but it is the combined effect of all the parameters. It is

varied much due to turbidity, temperature and fluorides. Turbidity is exceeded much the guideline

value during winter particularly in monsoon which contributed to lower the overall WQI

After removal of turbidity, WQI is increased. Climate of Purna (Tapi) river basin being dry and hot

throughout the year, water temperature exceeded the guideline value to lower WQI. After removal of

temperature WQI is increased Fluoride concentration is well within guideline value. The water

quality sub-index equation is such that it lowers WQI if concentration of fluoride is less than 0.6

mg/l to avoid dental carries, after its removal WQI is increased. Though percentage exceedance of

concentration is more, but as it is within certain limit which have not contributed much to lower WQI

after removal of these parameter.

78

80

82

84

86

88

90

S1 S2 S3 S4 S5 S6

WQI Winter

WQI Summer

WQI

70

75

80

85

90

S1 S2 S3 S4 S5 S6

2005

2006

2007

2008

WQI



132

Table 8: Correlation coefficient between WQI and WQI after removal of particular parameters

Parameter r Parameter r Parameter r

Color 0.840 DO 0.872 TP 0.830

Temperature 0.913 BOD 0.901 NH3-N 0.895

pH 0.843 COD 0.827 NO3-N 0.843

EC 0.748 Sulfates 0.809 NO2-N 0.880

Turbidity 0.896 Chlorides 0.840 Total Coli 0.830

SS 0.872 Calcium 0.830 Fecal Coli 0.830

TDS 0.757 Magnesium 0.895 Sodium 0.840

TH 0.783 Fluorides 0.651 Boron 0.871

TA 0.895

r =Correlation coefficient

5.0 CONCLUSION

In this study, WQI based mathematical formulation by assigning weights to various physio-

chemical water quality parameters are proposed based on its adverse effect on human health, its

concentration relative to the concentration of other parameters and method of treatment required for

it. The new WQI is believed to assist the decision makers in reporting the state of water quality for

drinking purpose. The applicability & usefulness of proposed methodology is revealed by a case

study. The sensitivity analysis shows that this WQI is not influenced by any one or few parameters

but it is a combined effect of all the parameters this WQI could be used to evaluate the water quality

of any water body to judge its suitability for drinking purpose. This WQI forces the researchers to

assign same weight to the same parameter, moreover this WQI is free from ambiguity and eclipsing.

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