Development and sensitivity analysis of water quality index for evaluation of

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. Valunjkar2
1
Research Scholar, Department of Civil Engineering, Government College of Engineering,
Aurangabad, Maharashtra, India
2
Professor 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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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 ܹܳ‫ܫ‬ ൌ ෍ ܳ௜
௡
௜ୀଵ
ܹூ
This method of aggregation is free
from ambiguity but suffers from
eclipsing.
Multiplicative
product index or
weighted geometric
function
WQI ൌ ෑ Qi୛୧
୬
୧ୀଵ
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
ܹܳ‫ܫ‬ ൌ
1
100
ሼܹ௜ܳ௜ሽଶ
Un-weighted
Solway function ܹܳ‫ܫ‬ ൌ
1
100
൜
1
݊
෍ܳ௜ሽଶ
௡
௜ୀଵ
Un-weighted
geometric function WQI= ሼ∑ ܳ௜
௡
௜ୀ଴ }1/n
Root mean square
function ܹܳ‫ܫ‬ ൌ ඥ0.5ሼ‫݊݅ܯ‬ሺܳ௜ሻଶሽ
൅ ቈሺ1/݊ሻට∑ܳ௜
ଶ
቉
Un-weighted
harmonic
square mean function
ܹܳ‫ܫ‬ ൌ ඨ
݊
൛∑ ሺܳ௜ሻ௡
௜ୀଵ
ଶ
ൟ
Maximum Operator
index
ܹܳ‫ܫ‬ ൌ ‫ݔܽܯ‬ ሼI1, I2, I3, … … Inሽ This is ideally suited to
applications in which an index
must report if at least one
recommended unit is violated
Minimum Operator
index
ܹܳ‫ܫ‬ ൌ ‫݊݅ܯ‬ ሼI1, I2, I3, … … Inሽ 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 2Aesthetic 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 2Advance / Special treatment
process
1
Minimum / Maximum weight 3 6
Test value exceeds the guideline value excursion ൌ ቂ
்௘௦௧ ௏௔௟௨௘
ீ௨௜ௗ௘௟௜௡௘ ௩௔௟௨௘
െ 1ቃ (1)
Test value below the guideline value excursion ൌ ቂ
ீ௨௜ௗ௘௟௜௡௘ ௏௔௟௨௘
்௘௦௧ ௏௔௟௨௘
െ 1ቃ (2)
Calculation of relative weight
A relative weight ሺܹRሻ 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 ሺ ∑ܹA ሻ].
ܹோ ൌ
ௐಲ
∑ ௐಲ
, and ∑ܹRൌ 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
+412.2x4
-
888.8x3
+685.8x2
-
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
+1.468x2
+
9.519x-2.088
y = 100
y = -0.14x3
+1.468x2
+
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)”
ܹܳ‫ܫ‬ ൌ ∑ ൫ܳ௜
ௐ೔
൯௡
௜ୀଵ (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 O
C–22 O
C 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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