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Calculating the Groundwater Quality Index and Comparing It to the Carcinogenic and Non-Carcinogenic Risk
Nasser Jabraili Andaryan1 | Ata allah Nadiri2 | Saleh Taheri Zangi3 | Zahra Sedghi4
1. Department of Earth Sciences, Faculty of Natural Sciences, University of Tabriz, Tabriz, Iran. E-mail:
2. Corresponding Author, Department of Earth Sciences, Faculty of Natural Sciences, University of Tabriz, Tabriz, Iran. E-mail: [email protected]
3. Department of Earth Sciences, Faculty of Natural Sciences, University of Tabriz, Tabriz, Iran. E-mail:
4. Department of Earth Sciences, Faculty of Natural Sciences, University of Tabriz, Tabriz, Iran. E-mail:
Article Info ABSTRACT
Article type:
Research Article
Article history:
Received: 7 December 2022 Received in revised form:
16 March 2023 Accepted: 6 June 2023 Published online: 2 July 2023
Keywords:
Carcinogenic and non- carcinogenic health risk Groundwater Quality Index, Geogenic and anthropogenic contamination.
In order to investigate the quality of groundwater in September 2022, 35 samples were collected from various groundwater sources in the Azarshahr plain, and the main elements, nitrates, and trace elements such as chromium, cadmium, nickel, lead, and arsenic, as well as two types of pesticides such as imidacloprid and chlorpyrifos, were analyzed and compared to drinking water standards. The drinking water quality index for the study area was calculated based on the concentration of parameters in the samples, and the health risk of cancerous and non-cancerous diseases for two age groups, children and adults, was calculated using the criteria of the United States Environmental Protection Agency (USEPA).
According to the findings of the studies, the region's water quality index is average, and the non-carcinogenic risk index for children and adults is less than one. It is hazardous, but the risk of carcinogenesis in the entire region is greater than 10-4, and its consumption poses health hazards due to skin contact. The health risk of cancer is many times higher in the region's south, in the cities of Azarshahr and Gogan, as well as the adjacent villages. The correlation between the GQI map and the health risk maps revealed that the correlation of carcinogenic risk is greater than the correlation of non-carcinogenic risk, and based on the correlation between the parameters in the region's groundwater, the elements influencing the health risk of carcinogenesis caused by geogenic factors and human activities do not play a significant role.
Cite this article: Jabraili Andaryan, N., Nadiri, A., Taheri Zangi, S., & Sedghi, Z. (2023). Calculating the Groundwater Quality Index and Comparing It to the Carcinogenic and Non-Carcinogenic Risk. Journal of Water and Irrigation Management, 13 (2), 369-384. DOI: https://doi.org/10.22059/jwim.2023.351923.1034
© The Author(s). Publisher: University of Tehran Press.
DOI: https://doi.org/10.22059/jwim.2023.351923.1034
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Table 1. Statistical description values related to the concentration of analyzed elements in the study area in September 1400.
Parameters Units Range Min Max Mean Std. Deviation Variance CV (%) WHO Standard ISIRI
pH _ 1.7 6.5 8.2 7.1 0.4 0.1 5.4 6.5-8.5 6.5-8.5
TDS (mg/L) 8106.8 265.2 8372 2194.4 2229.2 4969122.5 101.6 500.0 1500.0
EC (µs/Cm) 12472 408 12880 3391.8 3424.6 11727858.5 101.0 500.0 1500.0
Ca+2 (mg/L) 1562.93 36.07 1599 377.7 393.0 154418.7 104.0 75.0 300.0
Mg+2 (mg/L) 402.99 10.21 413.2 98.4 112.2 12579.0 114.0 30.0 30.0
Na+ (mg/L) 855.21 29.89 885.1 201.4 212.2 45049.2 105.4 200.0 200.0
K+ (mg/L) 25.024 2.346 27.37 10.1 7.0 48.9 69.6 10.0 12.0
HCO3- (mg/L) 6208.24 45.76 6254 575.4 1000.1 1000213.5 173.8 150.0 150.0
SO4-2 (mg/L) 1756.5 20.5 1777 320.2 351.0 123170.8 109.6 200.0 400.0
Cl- (mg/L) 4139.41 26.59 4166 689.8 1033.8 1068662.9 149.9 250.0 400.0
NO3- (mg/L) 34.9 8.6 43.5 26.9 7.0 49.1 26.1 10.0 50.0
Cd (µg/L) 0 0 0 0.0 0.0 0.0 - 5.0 3.0
Cr (µg/L) 72.45 0 72.45 21.1 19.5 380.0 92.6 50.0 50.0
Ni (µg/L) 176.18 38.92 215.1 90.4 51.5 2648.5 56.9 20.0 70.0
Pb (µg/L) 191.72 67.18 258.9 145.9 52.0 2703.9 35.6 10.0 10.0
As (µg/L) 360 4 364 81.4 75.5 5696.8 92.8 10.0 10.0
Imidacloprid (µg/L) 0 0 0 0.0 0.0 0.0 - - -
Chlorpyrifos (µg/L) 5.2 0 5.2 0.1 0.9 0.8 591.6 30.0 30.0
Color Code Pesticide Trace Element Minor Element Major Element Properties Bold Value Exceeding Standards
Table 2. Correlation related to the concentration of analyzed parameters in the study area
EC pH K+ Na+ Mg+2 Ca+2 SO4-2 Cl- HCO3- Cr Ni Pb As NO3-
EC 1
pH -0.65 1
K+ 0.78* -0.50 1
Na+ 0.96** -0.56 0.89** 1 Mg+2 0.99** -0.63 0.77* 0.95** 1 Ca+2 0.99** -0.65 0.71* 0.93** 0.99** 1 SO4-2 0.94** -0.52 0.86** 0.97** 0.94** 0.92** 1 Cl 0.99** -0.62 0.71* 0.94** 0.99** 0.99** 0.93** 1
HCO3- 0.35 -0.44 0.78* 0.46 0.33 0.27 0.43 0.23 1
Cr 0.72* -0.65 0.52 0.64 0.69* 0.73* 0.58 0.70* 0.33 1
Ni 0.98** -0.7* 0.71* 0.9** 0.98** 0.99** 0.90** 0.97** 0.32 0.76* 1 Pb 0.84** -0.36 0.81** 0.83** 0.85** 0.8** 0.84** 0.79** 0.53 0.52 0.84** 1
As 0.58 -0.43 0.91** 0.67* 0.57 0.50 0.63 0.48 0.92** 0.44 0.54 0.76* 1
NO3- -0.31 0.43 -0.12 -0.15 -0.34 -0.31 -0.11 -0.30 -0.11 -0.16 -0.39 -0.43 -0.20 1
** Correlation is significant at the 0.01 level (2-tailed).
* Indicates the degree of reliability of the calculation of the correlation coefficient between the data.
* Minimum confidence 0.95% and ** Best assurance 0.99%.
Items with a high correlation are marked with two asterisks that have an R above 0.05.
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( <6 = > ? @A B G )
(GQI
>87 B
= F # ]
"
X + a7 + 8 # - "D H D ) "/
3 ( D
>
V B )
et al., 2007 Babiker
(.
"ZD # 3 (
= 100 − + + ⋯ +
# ) "/
3 (
" 0 P' - + " # r
+ X
" # (D X B + 8 # - : + ' w
D D D # 0
- P?
P' X +
" # " 0 (D X " D B
=7
"?
> ? @A B X] D 0 (+
< A = > ?
- 0 (+
. D + A < B E <6 D = > ?
2 - 4 - 2 .
11 6
C+ ,- +
"?
#
"Z \ D #
< G? M ( /6 c ZA [
B Pe \ PD e
7# D .
%
= 97
=B FD G
=7
"?
g + c / Z
- X 98D '
"D D
# G X + X
B g h l;
<6 /6
< G? M ( "D
=7 .
€>\
=/ \ R8' 7 ?
D6 Y X
% 8' 6 +
"D "Z7 jk c o 7 ( ]6
+
=7 )
Scheuhammer, 1987
.(
c]98A h
T
7 c]98A
e '>(
e i 76
"D
?
?
"
+ s
"D R+
% # A
# + + a07 (Y
< F8/
PM >
J87 ? -
#
#
\
• c j 6 +
"D D
=7 )
Miranzadeh et al., 2011
.(
#
C+ ,- D
# 8N E
%
"D 7# D
< G? M ( / 6 c 8
# KD (
<6 (
/ Z "0Z(
D # ZA
= 97 D M (
] ' # D
? ? B "8A -
"? c# M D =7 :' #
8 97 B
"Y D Y < G? M (
#
<6 (
V g h
<6 87 - U G D
6 :' # 8 97 P?
"D i
D
"/ >87 X +
) 4 ) ( 5 ) ( 6 ( B
=7 )
USEPA, 2018
(.
"ZD # 4 (
HQ oral=
' '
X X C X X
"ZD # 5 (
HQ dermal=
! "
"ZD # 6 (
HI= HQ oral + HQ dermal
"/ # ) X + 4 ) ( 5 ) ( 6
"D ( i
HQ oral
h( d8( :' # = ' 12
E # K D ' a7
HQ dermal 13
=7 - ' a7 " D h( d8( :' # = ' 6 " 7 b X D "? =7 P? ZA @A B HI
H D HQ
"D G .=7 B KGY D M (
CDI oral
CDI dermal 14
\ D
Kg.day/mg
"D i
(+
U G <6 g h ' "? =7 h( + " # D # 6 D 87 -
. B
15RFD
D < G? M ( KY
\
Kg.day/mg
8 # - =7 "? =7 h( X# 0 w? \ (+
87 - U G K D ' " #
"D E # h( D 7 ; c j iY "? B D # ' X
. ) % Y # 4 0 ( U 7 DRFD
USEPA
0 .=7 B # 6 I 8J M ( X D KY
K D X D + a7 h(
_ `6 a b =^ >\
='
c]
b8 )
USEPA, 2018
( B
" 7 b
RFD dermal
) "/
7 ) =7 " 7 b PD e (
USEPA, 2018
:(
"ZD # 7 (
ABSGI
×
RFD dermal= RFD oral
) "/ V 7
(
ABSGI
# 0 "? =7 W# 87 <lY i u16
i u
"D G+
KY K D X D +
h(
a7 _ `6
=^ >\
a b ] =' b8 c B
H D 0
"D 6
#
% Y ) 3
"m # ( B
=7 .
CDI oral
CDI dermal
"D i
"/ >87 D X +
) 8 ) ( 9 ( D e P
=7 " 7 b )
USEPA, 2018
(:
"ZD # 8 (
#$ % &' = )×+ ×, ×,
-.×/0
"ZD # 9 (
#$ 12 3&' = )×4/×56×,0×, ×, × 78
7999:;<
-.×/0
c] #
=E ; C
8 # - X
B ) ( 8 / D
17Kp
: i u
=7 - X l-L >
i'\ D
8 7 8 D
= 7
=7 X D "?
h(
? 001 / 0 < 7 001 / 0
? 003 / 0 : (7#6 001
/ 0 P 044 / 0
% Y # .=7 )
3 ( " 7 b X D ] X + 8 # - )CDI
? ? ] ' # D
( ' =7 - K D
"m # .=7 B
Table 3. Parameters for calculating the average daily dose of each element through water consumption and skin contact
Parameters Unit Oral Dermal
Adult Child Adult Child
IR (Ingestion rate) L/day 2.2 1 - -
EF (Exposure frequency) days/year 365 365 350 350
ED (Exposure duration) Year 70 10 30 6
ET (Exposure time) h/event - - 0.58 1
BW (Body weight) Kg 70 25 70 25
AT (Average time) Days 25550 3650 10950 2190
SA (Skin-surface area) cm2 - - 18000 6600
CF (Conversion factor) L/cm3 - - 1.1 _
18AT
: G X + #
"?
X D D # :' #
7 ;
7
"D i "/ >87 D
) 10 ) ( 11
=7 " 7 b PD e ( )
USEPA, 2018
(:
"ZD # 10 (
AT nc =ED×365
"ZD # 11 (
AT c =70×365
X D
" 7 b :' # 7
' < G? M ( 87 - K D
:' # 7 P?
"D i
) c]
12 ) ( 13 ) ( 14
>87 ( .=7 B
.
# 0
19ELCR
(+
% G8\
B#
7
#
%
= GY
#
"FY D 7 =7 )
USEPA, 2018
.(
"ZD # 12 (
ELCR oral = CDI oral × CSF oral
"ZD # 13 (
ELCR dermal = CDI dermal × CSF dermal
"ZD # 14 (
ELCR total = ELCR oral + ELCR dermal
X D " 7 b V CSF
"FY 87 - ) "/
15 "ZD # # .=7 B >87 (
# 8? N CSF
i B 7
=7
"?
# 0 6 ' 87 - K D X D
< 7 P ? ? < G? M (
% Y # : (7#6 4)
) =7 B # 6 ( USEPA, 2018
.(
8 # - w? \ (+
=7 h( X# 0
"?
"D E # h( D 87 - U G K D ' " # c j iY B D # ' X
7 ; .
"ZD # 15 (
#=>12 3&' =)4
/-4 ?+
Table 4. Oral and Dermal reference dose of trace elements and Nitrate in the body (USEPA, 2018)
Element RfD oral (Kg-day/mg) RfD dermal (Kg-day/mg) CSF oral (Kg-day/mg) CSF dermal (Kg-day/mg)
NO3- 1.6 0.025 - -
Cr 3 0.075 4.1 4.1
Ni 20 0.8 0.84 0.84
Pb 1.4 0.42 0.042 0.042
As 0.3 0.12 1.5 3.6
Cd 0.5 0.025 0.63 0.63
3 . 7/
3 - 1 . ) " 89 : GQI
P B "D "Y D )
3 0 C+ ,- # ( > ? @A B
U 7 D [ c 7 b V < B <6 # 87 "8N
4 / 58 6 / 68 <6 = > ? "? =7 G D s8
C+ ,- # b
U 7 D <6 # 87
D a7 8 \ # B6
= > ? JD6 <6
< B E (" ls "0Z( ) e B =G'e #
PD e
% e
=G'e .=7 JD6 (" J "0Z( ) D ; X + U 7 D
<6 87 FB # (
6 g X + 87 #
=G'e 7 D "' 0 # - = > ? JD6 X +
=B Y A JD6 =G'e "? =7 ?L "D ] # X
D c# [ #
" # "S #
=7 Ke .
3 - 2 . 6 " 89 :
/ 6 d 8 "D "Y D +
0 D] D
=E ;
< G? M ( c 8 X
B
#
=B JD6 FB#L6
= '
# 87 "D d # X +
) X D# ? b8 c] =' a b =^ >\ 7
# 87 FY =B FD 7
( B6 <6 8 (M c 0 0b 7 :' # % G8\
7 ; FD (? 7 X D
<6 (
b B6
" / Z # . # Y
3 - 3 . 4 3 $ 4 ,
"
; :' # 7
# M # ZA = ' "?
HI total
C D :
# 7 ; c j D % G8\ B D
# Y "Y z # = GY "? / \ #
HI total
R?
X ' :
B D G F # = GY X ZA
) (?
Kamarani et al., 2019
.(
Figure 3. GQI groundwater quality index map of Azarshahr Plain based on the drinking water standard of Iran.
D # =FY / Z "0Z( # 7 ; :' #
ZA = ' P?
)
HI total
( X D (7
‚ ?
% ' # D
" 7 b B
"D " 0
=7 P B # 6 )
4 ( B
:' # K " 0 "D "Y D "?
7 ; 8 97 T G[
= ' ZA ' K D
=7 - )
HI total
( X D (7
‚ ? D # 32 / 0
38 / 1 (7 X D ] ' # D
D # 23 / 0 99 / 0 s8 ? ? X D ] D :' # Y % G8\ D =7
"D = ' ] ' # D
=7 . R+
(S ; ZA % G8\
7
< B <6 KD ( D a
# b X D
" / Z #
] ' # D "8B Y
G D :' # ? ? X D
# Y X#
"D " 0 "D "Y D
=7 (? 7 X D 6
=G'e C+ ,- # b 6 g X + 87 # FB#L6 87 FB " \ # JD6 < (Y
" 0D "D = '
=G'e + X# G D :' # Y % G8\
7 ; X + Y ? ? X D
=B + A R+
(S D VD Z
+ G(+#
X
USEPA
7 ZA "(
6) 10- 4- 10-
( =7
"?
0 R?LECR
6
10-
D ZA
7 D
R S PD e B -
=7 7 ZA 0 X D
C DLECR
4
10-
=7 % e PD e ;
)
Dashtizadeh et al., 2019
(.
D K " 0 "D "Y D / Z "0Z( # U 7 =G'e D6 KD (
< ;
E g X + 87 # 87 FB " \ # JD6 7
g h X D ] ' # D
t ? ?
=7
P B) 5 T G[ .(
= ' ZA ' K D
=7 - )
ELCR total
( X D X + 8 # - X
C+ ,- # B #
) P B 5
B (
0 "?
6 X D (7
‚ ? D #
3
10 -
× 7 /
2 1 10 -
× 12 / 3 ] ' # D (7 X D
D #
3
10 -
× 3 /
1 1 10 -
× 47 / 2 7 :' # E =7 s8 FD = GY
F z # D6 KD ( (
D X# G 7 X + C D c ZA c B i "D JD6 < ; =G'e # "? # # e
.=7
(b) (a)
Figure 4. Distribution map of Non-carcinogenic health index for (a) Adults (b) Children.
(b) (a)
Figure 5. Carcinogenic health index distribution map for (a) Adults (b) Children
3 - 4 .
6
$ "
"
U 7 D ) <6 = > ? @A B " 0 8' G+
" 0 D (GQI
7 :' # X + ;
7 X D
] ' # D % Y # "? ? ?
5)
@A B =7 B (
7 8' G+
C D "D = ' X
; 7 D
=7 GQI
U 7 D D 8' G+
% Y # "? < G? N M X + )
2 (
=7 B D
"
; D M ( " 0D c 8 8' G+ M M ( EC
"8B ] D
"?
D D
k ( /6
~(7 %9b j # "? =7 + <6 # "0Z( # Y +6 ("; 7) X# 6#L6 X +
B (
<6 G #
( X +
=
"8B =7 T u _ D c 8 X D (
DEC
+ c 8 8' G
"8B ' 6 k ( "? =7
ƒ] G8\
b D6 KD ( "D c 8 B 6
" / Z # B
= / N X # ? X +
<9u N A X +
=7 FB#L6 JD6 b # U 7 D . D] D % G8\
:' #
X# G D 7 X + P d8(
D ƒ] G8\
' P X# G D D D
7 ; X +
" 0 X] D 8' G+ .=7
" 0 DGQI
7 :' # @A B X + )
7 / 0
=
R2
JD6 # "? =7 = "D (
"D FB#L6 "8B # 87 C D =E ; "? B / 6 (< G? M ) M ( " 0D c 8 ;
=7 ƒ] G8\
k (
M ( =7
6 N #
+ D 87 G+
Y =FY
=7
< G? M ( . C D
jk
# #
7 :' # < B <6 = > ?
"8B X# G D X D
7 ; X + P F(
jk c 8 M # l
K .=7 D D c 8
=7 c >8 =B M ( " 0D K
=G'e #
= / N "? =B + ' X +
? >87 (
<9u N G B X +
W 8' A X +
# X ] D 0 c 8
.=7 B = j
Table 5. Correlation of health risk index with GQI Correlation coefficient (r2) GQI
ELCR (Adult) 0.72
ELCR (Child) 0.71
HI (Adult) 0.19
HI (Child) 0.18
4 .
; 4 <
" / Z #
< G? M ( X D / 6 d 8 >87 D c 8
M
"D G+
>87 D G B X + 8 # - A D
@A B
@A B GQI
:' # X + 7) 8 97
- 7 ;
< B <6 = > ? D # "D ( b
"8A - FB#L6 JD6 U 7 D .=7 B
7# D d 8 D "0Z( <6 = > ? @A B K " 0 "' 0 +
" 0 7 :' # @A B X + 7 ;
=G'e # B @J
? / Z "0Z( + < B <6 "
- = > ? X# G D :' # % G8\ "8B X
] D 7 X +
=7
"D
# D6 # ? :' # FB#L6 J
X# G D
; X +
< (Y \ # JD6 X b =G'e # F( D R? # 'D 7 g # "0Z( e B
" 876 \ X] D FB#L6 87 FB
USEPA
D
# Y ? ? X D 8 97 :' #
% G8\
:' #
7
"D = / 6
< G? M ( ] D
=7 R+
(S U 7 D 8' G+
" 7 b B D # P A M (
X# G D 7 X + k (
= / N "8B . # (S C0 ' X +
= / N + X # ? (
<9u N <6 # c 8 =E ; C N D JD6 X b =G'e # 8 (M A X + ƒ] G8\
8N#] D iY
X# G D "D [( :' #
? ? X D 7 ; X +
B + A
@A B . :' # @A B D < B <6 = > ?
7 "? "8B ] D 8' G+
< G? M ( + jk
C D 8 # - "D = ' X = > ? D +
( <6
C+ ,- # b
=7 "8B M ( K D FB#L6 JD6 ( <6 M ( K ? #
7 < G?
k (
# ' .
5 .
>"* ? @ A
F( - u \ " / Z d 8 U 7 D =? B 8b / &' B
[ D#L6 87 <9u N <6 L J e B
M ( G8' C - Gu "? ( N
< G?
KD ( / Z "0Z( # C D
c# M < G? M ( / 6 X
< J8 D ( N h <6 "8N B
B D "8B # M ( =E ; Pe \ "?
R+
(S 7# D
C - ( D X + FD (? 7 X D < G? M ( B /6 " >h " GY ] D . [ D6 KD ( (
FD (? 7 8 97 87 <6 KD ( bD a B "D "Y
# , JD6 =7 " # "S # " B \ X +
8' X D# ? c / Z [ ( 6 # X
. l-
6 . A + , 1. Water Quality Index
2. National Sanitation Foundation Water Quality 3. Groundwater Quality Index
4. non-carcinogenic 5. Carcinogenic
6. The Institute of Standards & Industrial Research of Iran 7. World Health Organization
8. U.S. Environmental Protection Agency 9. Imidacloprid
10. Chlorpyrifos 11. Health Risk Index 12. Oral Hazard Quotient 13. Dermal Hazard Quotient 14. Chronic Daily Intake (CDI) 15. Reference Dose (RFD)
16. Fraction of contaminant adsorbed in gastrointestina tract (ABSGI) 17. Permeability coefficient (Kp)
18. Average Time (AT)
19. Excess Lifetime Cancer Risk (ELCR)
7 . DE F !
… + . # Y (' a7 N ( z# "
8 . D
Adimalla, N. (2019). Groundwater Quality for Drinking and Irrigation Purposes and Potential Health Risks Assessment: A Case Study from Semi‑Arid Region of South India. Water Quality Exposure and Health, 2019(11), 109-12.
Alipour A., Rahimi J., & Azarnivand, A. (2017). Groundwater Quality Analysis for Drinking and Agricultural Purposesa Prerequisite for Land Use Planning in the Arid and Semi-arid Regions of Iran. Journal of Range and Watershed Management, 70(2), 423-434. (In Persian).
ASTM (2002) Annual book of ASTM standards. Section 11, Water and environmental technology, American Society for Testing and Materials.
Babiker I., Mohamed M., & Hiyama, T. (2007). Assessing groundwater quality using GIS.
Water Resources Management, 21, 699-715.
Bagheri, M. (2000). Effects of effluent irrigation systems in some physical, chemical properties and soil pollution for several crop under cultivation (Dissertation for MSe degree of Water Resources) Faculty of Agriculture, Isfahan Industrial University, September; P. 156. (In Persian).
Dashti Barmaki, M., Rezaei, M., & Saberi Nasr, A. (2014). Evaluation of Groundwater Quality Index (GQI) in Lenjanat aquifer using GIS. Journal of Engineering Geology, Summer, 8(2), 21- 38. (In Persian).
Dashtizadeh, M., Kamani, H., Ashrafi, S.D., Panahi, A.H., Mahvi, A.H., Balarak, D., et al.
(2019). Human health risk assessment of trace elements in drinking tap water in Zahedan city, Iran. Journal of Environmental Health Scienceand Engineering, 17(2), 1163-9.
El Baba, M., Kayastha, P., Huysmans, M., & De Smedt, F. (2020). Evaluation of the Groundwater QualityUsing the Water Quality Index and Geostatistical Analysis in the Dier al-Balah Governorate, Gaza Strip, Palestine. Water, 12(1), 262.
EPA, U. (2018). edition of the drinking water standards and health advisories Tables. EPA 822- F-18-001.
Ghaderpoori, M. (2018). Heavy metals analysis and quality assessment in drinking water–
Khorramabad city, Iran. Data in brief, 16, 685.
Giordani, G., Zaldívar, J.M., & Viaroli, P. (2009). Simple tools for assessing water quality and trophic status in transitional water ecosystems. Ecol Indic, 9(9), 82-91.
Kamarani, B., Jafari, A., Zarei, A., Fakhri, Y., Ghaderpoori, M., & Alinejad, A. (2019). Non- carcinogenic health risk assessment of nitrate in bottled drinking waters sold in Iranian markets:
A Monte Carlo simulation. Accreditation andQuality Assurance, 24(6), 417-26.
Kamari, Z., Alipour, V., Dindarloo, K., Fazlzadeh, M., Ghanbarnejad, A., (2022). Ghaffari, H.
R. Assessing the Risk of Carcinogenesis Caused by Exposure to Heavy Metals Through the Consumption of Drinking Water (A Case Study of Bandar Abbas Drinking Water). J Prevent Med., 9 (1), 74-83. (In Persian).
Khosravi, H., Heydari, E., Zehtabian, G., & Bazrafshan, J. (2016). Analysis of spatial and temporal trends of groundwater index (GRI) (Case study: Yazd-Ardakan plain), 22(4), 711- 720. (In Persian).
Kumar, M., Ramanathan, A., Tripathi, R., Farswan, S., Kumar, D., & Bhattacharya, P. (2017). A study of trace element contamination using multivariate statistical techniques and health risk assessment in groundwater of Chhaprola Industrial Area, Gautam Buddha Nagar, Uttar Pradesh, India. Chemosphere, 135-145.
Lobato, T.C., Hauser-Davis, R.A., Oliveira, T.F., Silveira, A.M., Silva, H.A.N, & Tavares, M.R.M.
(2015). Construction of a novel water quality index and quality indicator for reservoir water quality evaluation: a case study in the amazon region. Journal of Hydrology, 522(6), 74-83.
Miranzadeh, M.B., Mahmoodzadeh, A.A., Hasanzadeh, M., & Bigdeli, M.. (2011)., Concentrations of Heavy Metals in Kashan Water Distribution Network in 2010. Journal of Health Ardabail, 2(3), 58-68. (In Persian).
Mohammadi, E., Ahmad pari, H., Zolfagharan, A., & Dehghan, A. (2021). Investigation of quantity and quality of groundwater resources in Momenabad watershed of Semnan. Journal of New Approaches in Basic Sciences. Technical and Engineering Research, 3(11), 47-66.
(In Persian with English abstract).
Muhammad, S., & Ahmad, K. (2020). Heavy metal contamination in water and fish of the Hunza River and its tributaries in Gilgit–Baltistan: evaluation of potential risks and provenance. Environmental Technology & Innovation, 20, 101159.
Nadiri, A.A. (2022). Sadeghi Aghdam F, Razzagh S, Barzegar R, Jabraili-Andaryan N, Senapathi V, Using a soft computing OSPRC risk framework to analyze multiple contaminants from multiple sources; a case study from Khoy Plain, NW Iran, Chemosphere, 308(3), 136527, ISSN 0045-6535.
Nadiri, A. A., Taheri Zangi, S., & Jabraili Andaryan, N. (2021). Spatial Mapping of Northeast Bijar Plain Aquifer Quality Index and Comparison of Water Quality Using Different Methods. Iranian journal of Ecohydrology, 8(1), 235-247. (In Persian).
Rajaei, Q., Pourkhabbaz, A. R., & Hesari Motlagh, S. (2012). Assessment of heavy metals health risk of groundwater in Ali Abad Katoul Plian. Journal of North Khorasan University of Medical Sciences, 4(2), 155-162.
Rezaei, H., Zarei, A., Kamarehie, B., Jafari, A., Fakhri, Y., Bidarpoor, F., ... & Shalyari, N.
(2019). Levels, distributions and health risk assessment of lead, cadmium and arsenic found in drinking groundwater of Dehgolan’s villages, Iran. Toxicology and Environmental Health Sciences, 11(1), 54-62.
Rezaei, H., Zarei, A., Kamarehie, B., Jafari, A., Fakhri, Y., Bidarpoor, F., ... & Shalyari, N.
(2019). Levels, distributions and health risk assessment of lead, cadmium and arsenic found in drinking groundwater of Dehgolan’s villages, Iran. Toxicology and Environmental Health Sciences, 11(1), 54-62.
Sabzevari, Y., Nasrolahi, A., & Yonesi, H. (2020). Investigation of temporal-spatial variations of groundwater resources quality in Borujerd-Dorood Plain. Irrigation and Water Engineering, 11(1), 150-167. (In Persian).
Samavati, A. (1999). Nitrogen compounds in water. Journal of Water and Environment, 9(2), 8- 13. (In Persian).
Scheuhammer, A. (1987). The chronic toxicity of aluminum, cadmium, mercury, and lead in birds: a review. Environmental Pollution, 46, 263-95.
Şener, E., Şener, Ş., & Varol, S. (2022). Appraisal of grounwater quality with WQI and human health risk assesment in Karamik wetland and surroundings (Afyonkarahisar/Turkey).
Shahriari, J., & Rezaei, M. (2019) Carcinogenic and non-carcinogenic risk assessment of heavy metals in the drinking water distribution network of the city Zabol. Neishabur Journal of Medical Sciences, 8(9), 53-75.
Sun, X., Zhang, H., Zhong, M., Wang, Z., Liang, X., Huang, T., & Huang, H. (2019). Analyses on the Temporal and Spatial Characteristics of Water Quality in a Seagoing River Using Multivariate Statistical Techniques: A Case Study in the Duliujian River, China.
International Journal of Environment and Research Public Health, 16, 1020.
Zhang, Q., Wang, L., Wang, H., Zhu, X., & Wang, L. (2020). Spatio-Temporal Variation of Groundwater Quality and Source Apportionment Using Multivariate Statistical Techniques for the Hutuo River Alluvial-Pluvial Fan, China. International Journal of Environ and Reserch Public Health, 17, 1055.
Zhao, L., Gong, D., Zhao, W., Lin, L., Yang, W., Guo, W., Tang, X., & Li, Q. (2020). Spatial- temporal distribution characteristics and health risk assessment of heavy metals in surface water of the Three Gorges Reservoir, China. Science of The Total Environment, 704, 134883.
