© 2020, IJSRMS All Rights Reserved 73
International Journal of Scientific Research in ___________________________ Research Paper .
Multidisciplinary Studies E-ISSN: 2454-9312
Vol.6, Issue.2, pp.73-79, February (2020) P-ISSN: 2454-6143
Assessment of Irrigation Water Quality Index for Upper Cauvery
Karnataka India
Mohammed Badiuddin Parvez1*
, M. Inayathulla2
1,2
Department of Civil Engineering, UVCE, Bangalore University, Bangalore, Karnataka, India
*Corresponding Author: parvezuvce@gmail.com
Available online at: www.isroset.org
Received: 21/Jan/2020, Accepted: 13/Feb/2020, Online: 28/Feb/2020
Abstract- An attempt has been made to develop water quality index (WQI), using Five water quality parameters pH,
Nitrates, Chloride, electrical conductivity and fluoride measured at 137 different locations in the study area rating scale is
developed based on FAO standards. It was found that 133 samples have the water quality index less than 150 and 4
samples have water quality index between 150-300. By spatial variation of WQI it can be found that 97.08 percent of the
water in the area is excellently suitable for irrigation.
Keywords: Chloride, Electrical Conductivity, Fluoride, Irrigation, pH, WQI.
I. INTRODUCTION
The Cauvery river enters Tamil Nadu at Hognekal of
Dharmapuri district from the west and takes a southern
course from Mettur and again takes south-eastern course at
Erode and then flows to Bay of Bengal flowing through
Trichirapalli, Thanjavur and Cuddalore districts. The
study area forms part of Cauvery basin, which lies on left
banks of Cauvery river. Lakshmantirtha river is a major
tributary to river Cauvery and has its originates in
Brahmagiri Devasi Hills of Western Ghats in southern
Kodagu district and flows through a distance of about 130
km. It enters the Mysore district near Chikkahejjur, south
west of Konana Hosahalli in Hunsur taluk and flows
through Hangodu, Hunsur and Kattemalavadi before its
confluence with Cauvery on the right side at Sagarkatte in
Krishnarajanagar taluk.
Water Quality Index allows for a general analysis of water
quality on many levels that affect a stream’s ability to host
life and whether the overall quality of water bodies poses a
potential threat to various uses of water. Relevant studies
on water quality index (WQI) and its modeling were
reviewed. WQI is valuable and unique rating to depict the
overall water quality status in a single term that is helpful
for the selection of appropriate treatment technique to
meet the concerned issues. .Water quality indices are tools
to determine conditions of water quality. Creating the WQI
involves three main steps (1) obtain measurements on
individual water quality indicators (2) transform
measurements into ‘‘subindex’’ values to represent them
on a common scale (3) aggregate the individual subindex
values into an overall WQI value.
II. MATERIALS AND METHODS
2.1 Study Area
The study area geographically lies between 750
29’ 19” E
and 760
37’ 40” E longitude and 110
55’ 54” N and
130
23’ 12.8” N latitude, as shown in Fig 1, and it covers
an area of 10874.65 Sq km. The maximum length and
width of the study area is approximately equal to 143.73
km and 96.75 km respectively. The maximum and
minimum elevation of the basin is 1867 m and 714 m
above MSL, respectively. The study area covers five
district of Karnataka state i.e., Chikmangalur, Hassan,
Kodagu, Mandya and Mysore as shown in Fig 2. There
are 137 sample location named as S1, S2 upto S137 as
shown in Table 3 the water parameters such as pH , EC,
Cl, NO3 and F are considered for estimation of irrigation
water quality index.
Fig 1 Location Map of Study Area
Int. J. Sci. Res. in Multidisciplinary Studies Vol.6, Issue.2, Feb 2020
© 2020, IJSRMS All Rights Reserved 74
Fig 2 Districts in study area
Table 1: Distribution of district area
Sl No District Name Area (sq_km) Percentage area
1 Chikmangalur
761.12 7.00
2 Hassan
4476.15 41.16
3 Kodagu
2559.4 23.54
4 Mandya
1006.56 9.26
5 Mysore
2071.42 19.05
Total Area 10874.65 100%
2.2 Methodology
WQI was determined following three steps. In the first
step, weight was assigned to each parameter (w) according
to its relative importance in the overall quality of water for
irrigation purposes from the FAO standards. Weights of 5,
4, 3, 2 and 1 are assigned to the quality parameters when
0-20, 21-40, 41-60, 61-80 and 81-100 % of samples are
within the permissible limit respectively (Raychaudhuri et
al 2014). The maximum weight of 5 has been assigned to
the parameters with 80 % or more than 80 % of the
samples are beyond the permissible limit. The pH, chloride
is given the minimum weight of 1 as >= 80 % of the
samples are within the permissible limit and of no harm
for irrigation use. % of the samples for the remaining
parameters are EC, F and NO3 are 36.4, 85.8, and 72 %
respectively hence these are assigned weight of 4,1 and 2
respectively. The second step was followed and relative
weight was assigned accordingly .The relatives weights of
the each parameters are given in the Table 2 .The third
step, a quality rating scale (qi) for each parameter is
assigned and then WQI is developed for each water
samples
Table 2: Weightage assigned to individual parameters for
irrigation use
Parameters Units FAO
standards
%
compliance
Weight Relative
weight
pH - 6.5-8.5 100 1 0.111
EC µS/cm 1000 36.4 4 0.444
Cl mg/l 1065 100 1 0.111
F mg/l 1 85.8 1 0.222
NO3 mg/l 45 72.2 2 0.111
Table 3 Hydro-chemical values of observatory well samples
Sample
latitude
(N)
longitude
(E) pH EC Cl NO3 F
S1 12.960 75.780 7.51 1010 96 5 0.04
S2 13.190 75.770 7.21 1600 207 47 0.53
S3 12.970 75.980 8.27 1270 185 74 1.20
S4 12.990 76.030 8.48 1410 196 51 0.42
S5 12.930 75.770 8.00 990 88 40 0.06
S6 13.030 75.850 7.89 1200 166 84 0.12
S7 12.770 76.050 8.25 1060 95 53 0.60
S8 13.020 76.370 8.38 1920 293 5 0.54
S9 13.050 75.980 8.60 1450 188 5 0.79
S10 12.770 76.030 8.25 840 63 20 0.08
S11 12.610 76.120 8.38 1100 141 11 0.15
S12 13.170 75.880 8.47 1180 194 7 0.45
S13 13.080 75.850 7.87 1520 269 12 0.12
S14 12.770 76.040 8.44 990 74 35 0.70
S15 13.040 75.900 8.00 1090 138 11 0.32
S16 12.600 76.180 8.79 1770 247 69 1.70
S17 12.910 76.380 8.21 1620 283 3 0.45
S18 12.910 76.030 8.07 700 57 6 0.19
S19 12.820 76.200 8.50 1860 311 27 0.28
S20 13.180 75.750 8.40 1140 168 20 1.10
S21 12.810 75.850 8.06 960 81 12 0.09
S22 12.940 76.380 8.46 1440 211 6 0.47
S23 13.120 75.900 8.19 1170 177 1 0.44
S24 12.850 76.170 8.65 1490 218 12 0.64
S25 12.970 76.170 8.89 2500 461 49 0.77
S26 12.840 75.850 8.08 310 22 44 0.07
S27 12.830 75.830 7.89 350 24 8 0.10
S28 12.770 76.150 8.29 1480 184 66 0.34
S29 12.780 76.180 8.37 2700 411 49 0.21
S30 12.790 76.250 8.22 900 107 33 0.17
S31 13.120 76.170 8.21 930 56 6 0.20
S32 12.700 76.030 8.72 1460 196 39 0.70
S33 12.920 75.980 8.25 1690 218 32 0.66
S34 12.750 76.220 8.92 4100 838 4 0.89
S35 13.030 76.340 8.47 1890 356 13 1.00
S36 12.880 76.430 8.51 1600 241 16 0.47
S37 13.020 75.930 8.40 1870 226 47 0.29
S38 12.700 76.050 8.17 1070 131 3 0.11
S39 12.890 76.080 8.42 910 96 2 0.60
S40 12.970 75.820 8.05 1040 98 5 0.04
S41 12.860 75.850 7.63 850 69 6 0.34
S42 12.580 76.170 8.62 1390 227 15 0.25
S43 12.620 76.080 8.31 940 81 3 0.32
S44 12.880 75.770 7.95 1040 84 7 0.02
S45 13.050 76.350 8.40 1420 238 2 0.26
S46 12.660 76.180 7.49 1040 128 6 0.12
S47 13.030 75.880 8.26 950 77 5 0.27
S48 12.890 76.500 8.56 170 20 61 1.30
S49 12.810 76.200 8.81 1840 256 36 0.50
S50 12.610 76.100 8.05 1140 173 3 0.62
S51 13.000 76.470 8.59 2100 419 6 0.36
S52 12.860 76.160 8.58 2200 437 29 0.55
S53 12.610 76.090 8.52 1150 138 6 0.31
S54 13.030 76.170 8.34 1250 157 27 0.18
S55 12.950 75.780 7.80 320 26 16 0.05
S56 12.940 76.060 8.35 1950 336 41 0.16
S57 12.990 76.220 8.32 1510 209 60 0.46
S58 12.870 76.030 8.38 2200 457 27 1.20
S59 12.760 75.970 8.00 860 103 3 0.13
S60 13.190 75.780 7.85 860 65 12 0.20
S61 12.610 76.100 8.24 870 69 6 0.29
S62 12.850 76.350 8.08 1750 261 7 0.50
S63 12.860 75.800 7.98 810 67 8 0.04
S64 12.810 76.060 8.63 1430 220 43 0.15
S65 12.770 76.000 8.37 950 81 31 0.14
S66 13.240 75.650 7.97 870 85 28 0.27
S67 13.140 75.530 7.92 860 39 18 0.15
S68 13.120 75.600 7.68 1010 36 13 0.04
S69 13.140 75.550 8.32 920 39 6 0.12
S70 13.320 75.720 8.20 1310 138 38 0.34
S71 13.090 75.650 7.71 1020 53 31 0.07
S72 13.290 75.800 8.00 1310 256 55 0.57
S73 13.260 75.680 8.07 1310 217 113 0.25
Int. J. Sci. Res. in Multidisciplinary Studies Vol.6, Issue.2, Feb 2020
© 2020, IJSRMS All Rights Reserved 75
S74 13.260 75.830 7.90 1110 142 38 0.92
S75 13.120 75.620 8.01 840 82 2 0.70
S76 13.120 75.620 7.73 950 99 35 0.15
S77 13.290 75.730 8.06 1240 131 53 0.23
S78 13.250 75.700 8.21 1060 50 1 0.07
S79 12.520 76.550 8.25 886 75 26 0.39
S80 12.670 76.480 8.59 591 60 7 0.36
S81 12.680 76.530 8.22 528 36 14 0.72
S82 12.700 76.550 8.17 921 117 7 0.68
S83 12.830 76.400 8.26 832 60 32 0.56
S84 12.570 76.530 8.52 517 53 12 1.09
S85 12.310 76.450 10.02 870 43 9 0.80
S86 12.490 76.140 8.26 1080 36 25 1.30
S87 12.510 76.380 9.12 2500 263 112 6.60
S88 12.500 76.270 8.75 1600 199 52 0.69
S89 12.310 76.270 8.75 1470 64 10 0.71
S90 12.330 76.280 8.04 1250 71 34 0.66
S91 12.330 76.280 9.71 1440 78 40 0.54
S92 12.450 76.040 8.55 1810 213 127 0.32
S93 12.500 76.230 8.30 2100 320 54 0.40
S94 12.340 76.160 8.75 1190 64 46 1.00
S95 12.390 76.030 8.30 1160 64 83 0.34
S96 12.430 76.000 8.71 1440 114 39 0.41
S97 12.330 75.850 8.12 1050 57 49 0.18
S98 12.240 75.870 7.98 1320 64 87 0.14
S99 12.350 75.570 7.90 880 14 4 0.04
S100 12.380 75.530 7.89 760 21 2 0.08
S101 12.250 75.850 8.15 1150 92 40 0.36
S102 12.790 75.920 7.85 920 36 19 0.13
S103 12.120 75.930 8.21 1030 21 0 0.16
S104 12.370 75.830 8.08 900 50 1 0.16
S105 12.380 75.570 7.41 700 21 1 0.05
S106 12.440 75.920 8.27 880 36 45 0.05
S107 12.230 75.680 7.81 780 43 45 0.07
S108 12.180 75.920 8.10 1440 107 55 0.18
S109 12.710 75.880 8.19 1210 50 45 0.16
S110 12.380 75.700 7.85 750 21 14 0.07
S111 12.220 75.930 7.87 930 21 3 0.07
S112 12.380 75.900 7.93 860 57 25 0.23
S113 12.220 75.870 9.73 850 36 17 0.05
S114 12.510 75.850 7.46 860 36 47 0.08
S115 12.540 75.830 8.34 1250 64 12 0.31
S116 12.270 75.850 8.03 1190 57 38 0.15
S117 12.220 75.730 7.72 650 43 47 0.08
S118 12.210 75.750 7.75 870 92 42 0.18
S119 12.250 75.630 7.68 720 14 12 0.03
S120 12.260 75.750 7.77 770 36 4 0.12
S121 12.440 75.800 7.79 860 71 50 0.10
S122 12.370 75.750 7.77 940 36 14 0.05
S123 12.800 75.880 7.72 950 50 52 0.11
S124 12.460 75.950 7.77 790 43 2 0.10
S125 12.500 75.930 8.01 970 36 39 0.23
S126 12.510 75.750 7.83 1140 28 3 0.08
S127 12.300 75.680 7.29 820 21 40 0.04
S128 12.300 75.630 7.83 810 28 0 0.16
S129 12.780 75.930 8.05 920 71 41 0.18
S130 12.260 75.820 8.06 940 28 9 0.15
S131 12.170 75.920 8.25 850 36 30 0.11
S132 12.730 75.880 8.19 950 71 50 0.14
S133 12.760 75.900 7.71 850 50 22 0.34
S134 12.450 75.820 8.11 1110 36 11 0.14
S135 12.030 75.970 7.51 670 28 1 0.09
S136 12.340 75.870 8.00 1380 114 55 0.37
S137 12.200 75.800 7.63 780 21 0 0.07
III. RESULTS
For irrigation use the computed WQI values are classified
into four categories based on the restrictions viz., none,
slight, moderate and severe as presented in Table 4
(Raychaudhuri et al. 2014)
Table 4 Classification of groundwater quality for irrigation use based on
WQI
WQI Class Restriction % of water samples
< 150 I None 97.08
150-300 II Slight 2.92
300-450 III Moderate 0
>450 IV Severe 0
Table 5 WATER QUALITY INDEX
Samp
le pH EC Cl NO3 F WQI
WQI
Class
S1 11.115 44.884 1.001 2.467 0.444 59.910 1
S2 10.671 71.104 2.157 23.187 5.883
113.00
2 1
S3 12.240 56.439 1.928 36.507
13.32
0
120.43
3 1
S4 12.550 62.660 2.043 25.160 4.662
107.07
6 1
S5 11.840 43.996 0.917 19.733 0.666 77.152 1
S6 11.677 53.328 1.730 41.440 1.332
109.50
7 1
S7 12.210 47.106 0.990 26.147 6.660 93.113 1
S8 12.402 85.325 3.054 2.467 5.994
109.24
2 1
S9 12.728 64.438 1.959 2.467 8.769 90.361 1
S10 12.210 37.330 0.657 9.867 0.888 60.951 1
S11 12.402 48.884 1.470 5.427 1.665 69.848 1
S12 12.536 52.439 2.022 3.453 4.995 75.445 1
S13 11.648 67.549 2.804 5.920 1.332 89.252 1
S14 12.491 43.996 0.771 17.267 7.770 82.295 1
S15 11.840 48.440 1.438 5.427 3.552 70.697 1
S16 13.009 78.659 2.574 34.040
18.87
0
147.15
2 1
S17 12.151 71.993 2.950 1.480 4.995 93.568 1
S18 11.944 31.108 0.594 2.960 2.109 48.715 1
S19 12.580 82.658 3.241 13.320 3.108
114.90
8 1
S20 12.432 50.662 1.751 9.867
12.21
0 86.921 1
S21 11.929 42.662 0.844 5.920 0.999 62.354 1
S22 12.521 63.994 2.199 2.960 5.217 86.891 1
S23 12.121 51.995 1.845 0.493 4.884 71.338 1
S24 12.802 66.216 2.272 5.920 7.104 94.314 1
S25 13.157
111.10
0 4.805 24.173 8.547
161.78
2 2
S26 11.958 13.776 0.229 21.707 0.777 48.448 1
S27 11.677 15.554 0.250 3.947 1.110 32.538 1
S28 12.269 65.771 1.918 32.560 3.774
116.29
2 1
S29 12.388
119.98
8 4.284 24.173 2.331
163.16
4 2
S30 12.166 39.996 1.115 16.280 1.887 71.444 1
S31 12.151 41.329 0.584 2.960 2.220 59.244 1
S32 12.906 64.882 2.043 19.240 7.770
106.84
1 1
S33 12.210 75.104 2.272 15.787 7.326
112.69
8 1
S34 13.202
182.20
4 8.734 1.973 9.879
215.99
2 2
S35 12.536 83.992 3.710 6.413
11.10
0
117.75
1 1
S36 12.595 71.104 2.512 7.893 5.217 99.321 1
S37 12.432 83.103 2.355 23.187 3.219
124.29
6 1
S38 12.092 47.551 1.365 1.480 1.221 63.709 1
S39 12.462 40.440 1.001 0.987 6.660 61.549 1
S40 11.914 46.218 1.021 2.467 0.444 62.064 1
S41 11.292 37.774 0.719 2.960 3.774 56.520 1
S42 12.758 61.772 2.366 7.400 2.775 87.070 1
S43 12.299 41.774 0.844 1.480 3.552 59.949 1
S44 11.766 46.218 0.875 3.453 0.255 62.568 1
S45 12.432 63.105 2.481 0.987 2.886 81.890 1
S46 11.085 46.218 1.334 2.960 1.332 62.929 1
S47 12.225 42.218 0.803 2.467 2.997 60.709 1
S48 12.669 7.555 0.208 30.093
14.43
0 64.955 1
Int. J. Sci. Res. in Multidisciplinary Studies Vol.6, Issue.2, Feb 2020
© 2020, IJSRMS All Rights Reserved 76
S49 13.039 81.770 2.668 17.760 5.550
120.78
7 1
S50 11.914 50.662 1.803 1.480 6.882 72.741 1
S51 12.713 93.324 4.367 2.960 3.996
117.36
0 1
S52 12.698 97.768 4.555 14.307 6.105
135.43
3 1
S53 12.610 51.106 1.438 2.960 3.441 71.555 1
S54 12.343 55.550 1.636 13.320 1.998 84.848 1
S55 11.544 14.221 0.271 7.893 0.555 34.484 1
S56 12.358 86.658 3.502 20.227 1.776
124.52
1 1
S57 12.314 67.104 2.178 29.600 5.106
116.30
2 1
S58 12.402 97.768 4.763 13.320
13.32
0
141.57
3 1
S59 11.840 38.218 1.074 1.480 1.443 54.055 1
S60 11.618 38.218 0.677 5.920 2.220 58.654 1
S61 12.195 38.663 0.719 2.960 3.219 57.756 1
S62 11.958 77.770 2.720 3.453 5.550
101.45
2 1
S63 11.810 35.996 0.698 3.947 0.444 52.896 1
S64 12.772 63.549 2.293 21.213 1.665
101.49
3 1
S65 12.388 42.218 0.844 15.293 1.554 72.297 1
S66 11.796 38.663 0.886 13.813 2.997 68.155 1
S67 11.722 38.218 0.406 8.880 1.665 60.891 1
S68 11.366 44.884 0.375 6.413 0.444 63.483 1
S69 12.314 40.885 0.406 2.960 1.332 57.897 1
S70 12.136 58.216 1.438 18.747 3.774 94.311 1
S71 11.411 45.329 0.552 15.293 0.777 73.362 1
S72 11.840 58.216 2.668 27.133 6.327
106.18
5 1
S73 11.944 58.216 2.262 55.747 2.775
130.94
3 1
S74 11.692 49.328 1.480 18.747
10.21
2 91.459 1
S75 11.855 37.330 0.855 0.987 7.770 58.796 1
S76 11.440 42.218 1.032 17.267 1.665 73.622 1
S77 11.929 55.106 1.365 26.147 2.553 97.099 1
S78 12.151 47.106 0.521 0.493 0.777 61.049 1
S79 12.210 39.374 0.782 12.827 4.329 69.521 1
S80 12.713 26.264 0.625 3.453 3.996 47.052 1
S81 12.166 23.464 0.375 6.907 7.992 50.904 1
S82 12.092 40.929 1.219 3.453 7.548 65.242 1
S83 12.225 36.974 0.625 15.787 6.216 71.827 1
S84 12.610 22.975 0.552 5.920
12.09
9 54.156 1
S85 14.825 38.663 0.448 4.440 8.880 67.256 1
S86 12.231 47.995 0.375 12.333
14.43
0 87.364 1
S87 13.495
111.10
0 2.741 55.253
73.26
0
255.84
9 2
S88 12.954 71.104 2.074 25.653 7.659
119.44
5 1
S89 12.944 65.327 0.667 4.933 7.881 91.752 1
S90 11.892 55.550 0.740 16.773 7.326 92.281 1
S91 14.365 63.994 0.813 19.733 5.994
104.89
9 1
S92 12.648 80.436 2.220 62.653 3.552
161.51
0 2
S93 12.285 93.324 3.335 26.640 4.440
140.02
5 1
S94 12.956 52.884 0.667 22.693
11.10
0
100.30
0 1
S95 12.285 51.550 0.667 40.947 3.774
109.22
4 1
S96 12.886 63.994 1.188 19.240 4.551
101.85
9 1
S97 12.021 46.662 0.594 24.173 1.998 85.448 1
S98 11.809 58.661 0.667 42.920 1.554
115.61
1 1
S99 11.688 39.107 0.146 1.973 0.488 53.402 1
S100 11.671 33.774 0.219 0.987 0.844 47.495 1
S101 12.065 51.106 0.959 19.733 3.996 87.859 1
S102 11.615 40.885 0.375 9.373 1.443 63.691 1
S103 12.146 45.773 0.219 0.000 1.776 59.914 1
S104 11.961 39.996 0.521 0.493 1.776 54.748 1
S105 10.971 31.108 0.219 0.493 0.533 43.324 1
S106 12.237 39.107 0.375 22.200 0.588 74.507 1
S107 11.560 34.663 0.448 22.200 0.755 69.626 1
S108 11.988 63.994 1.115 27.133 1.998
106.22
8 1
S109 12.115 53.772 0.521 22.200 1.776 90.385 1
S110 11.615 33.330 0.219 6.907 0.788 52.859 1
S111 11.654 41.329 0.219 1.480 0.733 55.414 1
S112 11.736 38.218 0.594 12.333 2.553 65.435 1
S113 14.393 37.774 0.375 8.387 0.555 61.484 1
S114 11.033 38.218 0.375 23.187 0.910 73.724 1
S115 12.340 55.550 0.667 5.920 3.441 77.918 1
S116 11.886 52.884 0.594 18.747 1.665 85.775 1
S117 11.430 28.886 0.448 23.187 0.844 64.794 1
S118 11.463 38.663 0.959 20.720 1.998 73.802 1
S119 11.359 31.997 0.146 5.920 0.377 49.799 1
S120 11.501 34.219 0.375 1.973 1.332 49.400 1
S121 11.528 38.218 0.740 24.667 1.110 76.263 1
S122 11.500 41.774 0.375 6.907 0.533 61.088 1
S123 11.424 42.218 0.521 25.653 1.221 81.038 1
S124 11.497 35.108 0.448 0.987 1.088 49.127 1
S125 11.855 43.107 0.375 19.240 2.553 77.130 1
S126 11.585 50.662 0.292 1.480 0.932 64.951 1
S127 10.791 36.441 0.219 19.733 0.455 67.639 1
S128 11.590 35.996 0.292 0.000 1.776 49.654 1
S129 11.911 40.885 0.740 20.227 1.998 75.761 1
S130 11.933 41.774 0.292 4.440 1.665 60.104 1
S131 12.209 37.774 0.375 14.800 1.221 66.379 1
S132 12.118 42.218 0.740 24.667 1.554 81.297 1
S133 11.414 37.774 0.521 10.853 3.774 64.336 1
S134 12.009 49.328 0.375 5.427 1.554 68.693 1
S135 11.107 29.775 0.292 0.493 0.955 42.622 1
S136 11.843 61.327 1.188 27.133 4.107
105.59
9 1
S137 11.297 34.663 0.219 0.000 0.744 46.923 1
Fig 3 pH variation
0.00
2.00
4.00
6.00
8.00
10.00
12.00
S1
S11
S21
S31
S41
S51
S61
S71
S81
S91
S101
S111
S121
S131
pH
Observed values Standard value
Int. J. Sci. Res. in Multidisciplinary Studies Vol.6, Issue.2, Feb 2020
© 2020, IJSRMS All Rights Reserved 77
Fig 4 Electrical conductivity variation
0
1000
2000
3000
4000
5000
S1
S11
S21
S31
S41
S51
S61
S71
S81
S91
S101
S111
S121
S131
EC
Observed values Standard value
Int. J. Sci. Res. in Multidisciplinary Studies Vol.6, Issue.2, Feb 2020
© 2020, IJSRMS All Rights Reserved 78
Fig 5 Analysis of water parameters in Laboratory
Fig 6 Chlorides variation
Int. J. Sci. Res. in Multidisciplinary Studies Vol.6, Issue.2, Feb 2020
© 2020, IJSRMS All Rights Reserved 79
Fig 7 Nitrates variation
Fig 8 Flouride variation
Fig 9: Spatial variation of water quality index
IV. CONCLUSIONS
In the present study the water quality parameters considered
shows that almost 95 percent are with in the FAO standards
for irrigation. 133 samples of 137 shows class I index
Excellent suitable for irrigation 4 samples shows class II
index . By spatial variation of WQI it can be found that
almost all the portion of the water is suitable for irrigation
with 97 percent of the area is excellently suitable.
REFERENCE
[1] Mohammed Badiuddin Parvez, M Inayathulla “Generation Of
Intensity Duration Frequency Curves For Different Return Period
Using Short Duration Rainfall For Manvi Taluk Raichur District
Karnataka”, International Research Journal of Engineering and
Management Studies (IRJEMS), Volume: 03 Issue: 04 ,Page 1-20,
April -2019.
[2] Mohammed Badiuddin Parvez, M Inayathulla “Prioritization Of
Subwatersheds of Cauvery Region Based on Morphometric
Analysis Using GIS”, International Journal for Research in
Engineering Application & Management (IJREAM), Volume: 05
Issue: 01, Page 85-94, April -2019.
[3] Mohammed Badiuddin Parvez, M Inayathulla “Modelling of Short
Duration Isopluvial Map For Raichur District Karnataka”,
International Journal for Science and Advance Research in
Technology (IJSART), Volume: 05 Issue: 4, Page 973-976, April -
2019.
[4] Mohammed Badiuddin Parvez, M Inayathulla, "Rainfall Analysis
for Modelling of IDF Curves for Bangalore Rural, Karnataka",
International Journal of Scientific Research in Multidisciplinary
Studies , Vol.5, Issue.8, page.114-132, 2019.
[5] Mohammed Badiuddin Parvez, and M Inayathulla. "Generation of
Short Duration Isohyetal Maps For Raichur District Karnataka"
International Journal Of Advance Research And Innovative Ideas In
Education Volume 5 Issue 2 Page 3234-3242 ,2019.
[6] Mohammed Badiuddin Parvez, and M Inayathulla. " Derivation Of
Intensity Duration Frequency Curves Using Short Duration Rainfall
For Yermarus Raingauge Station Raichur District Karnataka"
International Journal of Innovative Research in Technology Volume
6 Issue 2, Page 1-7 ,July 2019.
Authors Profile
Mohammed Badiuddin Parvez Is a life
member of Indian Water Resources Society,
ASCE Born in Gangavathi, Obtained his BE
in Civil Engineering in the year 2009-2013
from UVCE, Banagalore and M.E with
specialization in Water Resources
Engineering during 2013-2015 from UVCE, Bangalore
University and Pursuing Ph.D from Bangalore University.
And has 3 years of teaching experience. Till date, has
presented and published several technical papers in many
National and International seminars, Journals and
conferences.
M Inayathulla Is a life member of
Environmental and Water Resources
Engineering (EWRI), ASCE, WWI,
ASTEE, ASFPM. Born in Karnataka,
Obtained his BE in Civil Engineering in the
year 1987-1991 from UBDT, Davanagere
and M.E with specialization on Water Resources Engineering
during 1992-1994 from UVCE, Bangalore University and got
Doctorate from Bangalore University. Presently working as
Professor at UVCE, Bangalore University, India. And has
more than 25 years of teaching experience. Till date, has
presented and published several technical papers in many
National and International seminars and conferences
0
50
100
150
S1
S11
S21
S31
S41
S51
S61
S71
S81
S91
S101
S111
S121
S131
Nitrate
Observed values Standard value
0.00
1.00
2.00
3.00
4.00
5.00
6.00
7.00
S1
S11
S21
S31
S41
S51
S61
S71
S81
S91
S101
S111
S121
S131
Fluoride
Observed values Standard value

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11 isroset-ijsrms-02993

  • 1. © 2020, IJSRMS All Rights Reserved 73 International Journal of Scientific Research in ___________________________ Research Paper . Multidisciplinary Studies E-ISSN: 2454-9312 Vol.6, Issue.2, pp.73-79, February (2020) P-ISSN: 2454-6143 Assessment of Irrigation Water Quality Index for Upper Cauvery Karnataka India Mohammed Badiuddin Parvez1* , M. Inayathulla2 1,2 Department of Civil Engineering, UVCE, Bangalore University, Bangalore, Karnataka, India *Corresponding Author: [email protected] Available online at: www.isroset.org Received: 21/Jan/2020, Accepted: 13/Feb/2020, Online: 28/Feb/2020 Abstract- An attempt has been made to develop water quality index (WQI), using Five water quality parameters pH, Nitrates, Chloride, electrical conductivity and fluoride measured at 137 different locations in the study area rating scale is developed based on FAO standards. It was found that 133 samples have the water quality index less than 150 and 4 samples have water quality index between 150-300. By spatial variation of WQI it can be found that 97.08 percent of the water in the area is excellently suitable for irrigation. Keywords: Chloride, Electrical Conductivity, Fluoride, Irrigation, pH, WQI. I. INTRODUCTION The Cauvery river enters Tamil Nadu at Hognekal of Dharmapuri district from the west and takes a southern course from Mettur and again takes south-eastern course at Erode and then flows to Bay of Bengal flowing through Trichirapalli, Thanjavur and Cuddalore districts. The study area forms part of Cauvery basin, which lies on left banks of Cauvery river. Lakshmantirtha river is a major tributary to river Cauvery and has its originates in Brahmagiri Devasi Hills of Western Ghats in southern Kodagu district and flows through a distance of about 130 km. It enters the Mysore district near Chikkahejjur, south west of Konana Hosahalli in Hunsur taluk and flows through Hangodu, Hunsur and Kattemalavadi before its confluence with Cauvery on the right side at Sagarkatte in Krishnarajanagar taluk. Water Quality Index allows for a general analysis of water quality on many levels that affect a stream’s ability to host life and whether the overall quality of water bodies poses a potential threat to various uses of water. Relevant studies on water quality index (WQI) and its modeling were reviewed. WQI is valuable and unique rating to depict the overall water quality status in a single term that is helpful for the selection of appropriate treatment technique to meet the concerned issues. .Water quality indices are tools to determine conditions of water quality. Creating the WQI involves three main steps (1) obtain measurements on individual water quality indicators (2) transform measurements into ‘‘subindex’’ values to represent them on a common scale (3) aggregate the individual subindex values into an overall WQI value. II. MATERIALS AND METHODS 2.1 Study Area The study area geographically lies between 750 29’ 19” E and 760 37’ 40” E longitude and 110 55’ 54” N and 130 23’ 12.8” N latitude, as shown in Fig 1, and it covers an area of 10874.65 Sq km. The maximum length and width of the study area is approximately equal to 143.73 km and 96.75 km respectively. The maximum and minimum elevation of the basin is 1867 m and 714 m above MSL, respectively. The study area covers five district of Karnataka state i.e., Chikmangalur, Hassan, Kodagu, Mandya and Mysore as shown in Fig 2. There are 137 sample location named as S1, S2 upto S137 as shown in Table 3 the water parameters such as pH , EC, Cl, NO3 and F are considered for estimation of irrigation water quality index. Fig 1 Location Map of Study Area
  • 2. Int. J. Sci. Res. in Multidisciplinary Studies Vol.6, Issue.2, Feb 2020 © 2020, IJSRMS All Rights Reserved 74 Fig 2 Districts in study area Table 1: Distribution of district area Sl No District Name Area (sq_km) Percentage area 1 Chikmangalur 761.12 7.00 2 Hassan 4476.15 41.16 3 Kodagu 2559.4 23.54 4 Mandya 1006.56 9.26 5 Mysore 2071.42 19.05 Total Area 10874.65 100% 2.2 Methodology WQI was determined following three steps. In the first step, weight was assigned to each parameter (w) according to its relative importance in the overall quality of water for irrigation purposes from the FAO standards. Weights of 5, 4, 3, 2 and 1 are assigned to the quality parameters when 0-20, 21-40, 41-60, 61-80 and 81-100 % of samples are within the permissible limit respectively (Raychaudhuri et al 2014). The maximum weight of 5 has been assigned to the parameters with 80 % or more than 80 % of the samples are beyond the permissible limit. The pH, chloride is given the minimum weight of 1 as >= 80 % of the samples are within the permissible limit and of no harm for irrigation use. % of the samples for the remaining parameters are EC, F and NO3 are 36.4, 85.8, and 72 % respectively hence these are assigned weight of 4,1 and 2 respectively. The second step was followed and relative weight was assigned accordingly .The relatives weights of the each parameters are given in the Table 2 .The third step, a quality rating scale (qi) for each parameter is assigned and then WQI is developed for each water samples Table 2: Weightage assigned to individual parameters for irrigation use Parameters Units FAO standards % compliance Weight Relative weight pH - 6.5-8.5 100 1 0.111 EC µS/cm 1000 36.4 4 0.444 Cl mg/l 1065 100 1 0.111 F mg/l 1 85.8 1 0.222 NO3 mg/l 45 72.2 2 0.111 Table 3 Hydro-chemical values of observatory well samples Sample latitude (N) longitude (E) pH EC Cl NO3 F S1 12.960 75.780 7.51 1010 96 5 0.04 S2 13.190 75.770 7.21 1600 207 47 0.53 S3 12.970 75.980 8.27 1270 185 74 1.20 S4 12.990 76.030 8.48 1410 196 51 0.42 S5 12.930 75.770 8.00 990 88 40 0.06 S6 13.030 75.850 7.89 1200 166 84 0.12 S7 12.770 76.050 8.25 1060 95 53 0.60 S8 13.020 76.370 8.38 1920 293 5 0.54 S9 13.050 75.980 8.60 1450 188 5 0.79 S10 12.770 76.030 8.25 840 63 20 0.08 S11 12.610 76.120 8.38 1100 141 11 0.15 S12 13.170 75.880 8.47 1180 194 7 0.45 S13 13.080 75.850 7.87 1520 269 12 0.12 S14 12.770 76.040 8.44 990 74 35 0.70 S15 13.040 75.900 8.00 1090 138 11 0.32 S16 12.600 76.180 8.79 1770 247 69 1.70 S17 12.910 76.380 8.21 1620 283 3 0.45 S18 12.910 76.030 8.07 700 57 6 0.19 S19 12.820 76.200 8.50 1860 311 27 0.28 S20 13.180 75.750 8.40 1140 168 20 1.10 S21 12.810 75.850 8.06 960 81 12 0.09 S22 12.940 76.380 8.46 1440 211 6 0.47 S23 13.120 75.900 8.19 1170 177 1 0.44 S24 12.850 76.170 8.65 1490 218 12 0.64 S25 12.970 76.170 8.89 2500 461 49 0.77 S26 12.840 75.850 8.08 310 22 44 0.07 S27 12.830 75.830 7.89 350 24 8 0.10 S28 12.770 76.150 8.29 1480 184 66 0.34 S29 12.780 76.180 8.37 2700 411 49 0.21 S30 12.790 76.250 8.22 900 107 33 0.17 S31 13.120 76.170 8.21 930 56 6 0.20 S32 12.700 76.030 8.72 1460 196 39 0.70 S33 12.920 75.980 8.25 1690 218 32 0.66 S34 12.750 76.220 8.92 4100 838 4 0.89 S35 13.030 76.340 8.47 1890 356 13 1.00 S36 12.880 76.430 8.51 1600 241 16 0.47 S37 13.020 75.930 8.40 1870 226 47 0.29 S38 12.700 76.050 8.17 1070 131 3 0.11 S39 12.890 76.080 8.42 910 96 2 0.60 S40 12.970 75.820 8.05 1040 98 5 0.04 S41 12.860 75.850 7.63 850 69 6 0.34 S42 12.580 76.170 8.62 1390 227 15 0.25 S43 12.620 76.080 8.31 940 81 3 0.32 S44 12.880 75.770 7.95 1040 84 7 0.02 S45 13.050 76.350 8.40 1420 238 2 0.26 S46 12.660 76.180 7.49 1040 128 6 0.12 S47 13.030 75.880 8.26 950 77 5 0.27 S48 12.890 76.500 8.56 170 20 61 1.30 S49 12.810 76.200 8.81 1840 256 36 0.50 S50 12.610 76.100 8.05 1140 173 3 0.62 S51 13.000 76.470 8.59 2100 419 6 0.36 S52 12.860 76.160 8.58 2200 437 29 0.55 S53 12.610 76.090 8.52 1150 138 6 0.31 S54 13.030 76.170 8.34 1250 157 27 0.18 S55 12.950 75.780 7.80 320 26 16 0.05 S56 12.940 76.060 8.35 1950 336 41 0.16 S57 12.990 76.220 8.32 1510 209 60 0.46 S58 12.870 76.030 8.38 2200 457 27 1.20 S59 12.760 75.970 8.00 860 103 3 0.13 S60 13.190 75.780 7.85 860 65 12 0.20 S61 12.610 76.100 8.24 870 69 6 0.29 S62 12.850 76.350 8.08 1750 261 7 0.50 S63 12.860 75.800 7.98 810 67 8 0.04 S64 12.810 76.060 8.63 1430 220 43 0.15 S65 12.770 76.000 8.37 950 81 31 0.14 S66 13.240 75.650 7.97 870 85 28 0.27 S67 13.140 75.530 7.92 860 39 18 0.15 S68 13.120 75.600 7.68 1010 36 13 0.04 S69 13.140 75.550 8.32 920 39 6 0.12 S70 13.320 75.720 8.20 1310 138 38 0.34 S71 13.090 75.650 7.71 1020 53 31 0.07 S72 13.290 75.800 8.00 1310 256 55 0.57 S73 13.260 75.680 8.07 1310 217 113 0.25
  • 3. Int. J. Sci. Res. in Multidisciplinary Studies Vol.6, Issue.2, Feb 2020 © 2020, IJSRMS All Rights Reserved 75 S74 13.260 75.830 7.90 1110 142 38 0.92 S75 13.120 75.620 8.01 840 82 2 0.70 S76 13.120 75.620 7.73 950 99 35 0.15 S77 13.290 75.730 8.06 1240 131 53 0.23 S78 13.250 75.700 8.21 1060 50 1 0.07 S79 12.520 76.550 8.25 886 75 26 0.39 S80 12.670 76.480 8.59 591 60 7 0.36 S81 12.680 76.530 8.22 528 36 14 0.72 S82 12.700 76.550 8.17 921 117 7 0.68 S83 12.830 76.400 8.26 832 60 32 0.56 S84 12.570 76.530 8.52 517 53 12 1.09 S85 12.310 76.450 10.02 870 43 9 0.80 S86 12.490 76.140 8.26 1080 36 25 1.30 S87 12.510 76.380 9.12 2500 263 112 6.60 S88 12.500 76.270 8.75 1600 199 52 0.69 S89 12.310 76.270 8.75 1470 64 10 0.71 S90 12.330 76.280 8.04 1250 71 34 0.66 S91 12.330 76.280 9.71 1440 78 40 0.54 S92 12.450 76.040 8.55 1810 213 127 0.32 S93 12.500 76.230 8.30 2100 320 54 0.40 S94 12.340 76.160 8.75 1190 64 46 1.00 S95 12.390 76.030 8.30 1160 64 83 0.34 S96 12.430 76.000 8.71 1440 114 39 0.41 S97 12.330 75.850 8.12 1050 57 49 0.18 S98 12.240 75.870 7.98 1320 64 87 0.14 S99 12.350 75.570 7.90 880 14 4 0.04 S100 12.380 75.530 7.89 760 21 2 0.08 S101 12.250 75.850 8.15 1150 92 40 0.36 S102 12.790 75.920 7.85 920 36 19 0.13 S103 12.120 75.930 8.21 1030 21 0 0.16 S104 12.370 75.830 8.08 900 50 1 0.16 S105 12.380 75.570 7.41 700 21 1 0.05 S106 12.440 75.920 8.27 880 36 45 0.05 S107 12.230 75.680 7.81 780 43 45 0.07 S108 12.180 75.920 8.10 1440 107 55 0.18 S109 12.710 75.880 8.19 1210 50 45 0.16 S110 12.380 75.700 7.85 750 21 14 0.07 S111 12.220 75.930 7.87 930 21 3 0.07 S112 12.380 75.900 7.93 860 57 25 0.23 S113 12.220 75.870 9.73 850 36 17 0.05 S114 12.510 75.850 7.46 860 36 47 0.08 S115 12.540 75.830 8.34 1250 64 12 0.31 S116 12.270 75.850 8.03 1190 57 38 0.15 S117 12.220 75.730 7.72 650 43 47 0.08 S118 12.210 75.750 7.75 870 92 42 0.18 S119 12.250 75.630 7.68 720 14 12 0.03 S120 12.260 75.750 7.77 770 36 4 0.12 S121 12.440 75.800 7.79 860 71 50 0.10 S122 12.370 75.750 7.77 940 36 14 0.05 S123 12.800 75.880 7.72 950 50 52 0.11 S124 12.460 75.950 7.77 790 43 2 0.10 S125 12.500 75.930 8.01 970 36 39 0.23 S126 12.510 75.750 7.83 1140 28 3 0.08 S127 12.300 75.680 7.29 820 21 40 0.04 S128 12.300 75.630 7.83 810 28 0 0.16 S129 12.780 75.930 8.05 920 71 41 0.18 S130 12.260 75.820 8.06 940 28 9 0.15 S131 12.170 75.920 8.25 850 36 30 0.11 S132 12.730 75.880 8.19 950 71 50 0.14 S133 12.760 75.900 7.71 850 50 22 0.34 S134 12.450 75.820 8.11 1110 36 11 0.14 S135 12.030 75.970 7.51 670 28 1 0.09 S136 12.340 75.870 8.00 1380 114 55 0.37 S137 12.200 75.800 7.63 780 21 0 0.07 III. RESULTS For irrigation use the computed WQI values are classified into four categories based on the restrictions viz., none, slight, moderate and severe as presented in Table 4 (Raychaudhuri et al. 2014) Table 4 Classification of groundwater quality for irrigation use based on WQI WQI Class Restriction % of water samples < 150 I None 97.08 150-300 II Slight 2.92 300-450 III Moderate 0 >450 IV Severe 0 Table 5 WATER QUALITY INDEX Samp le pH EC Cl NO3 F WQI WQI Class S1 11.115 44.884 1.001 2.467 0.444 59.910 1 S2 10.671 71.104 2.157 23.187 5.883 113.00 2 1 S3 12.240 56.439 1.928 36.507 13.32 0 120.43 3 1 S4 12.550 62.660 2.043 25.160 4.662 107.07 6 1 S5 11.840 43.996 0.917 19.733 0.666 77.152 1 S6 11.677 53.328 1.730 41.440 1.332 109.50 7 1 S7 12.210 47.106 0.990 26.147 6.660 93.113 1 S8 12.402 85.325 3.054 2.467 5.994 109.24 2 1 S9 12.728 64.438 1.959 2.467 8.769 90.361 1 S10 12.210 37.330 0.657 9.867 0.888 60.951 1 S11 12.402 48.884 1.470 5.427 1.665 69.848 1 S12 12.536 52.439 2.022 3.453 4.995 75.445 1 S13 11.648 67.549 2.804 5.920 1.332 89.252 1 S14 12.491 43.996 0.771 17.267 7.770 82.295 1 S15 11.840 48.440 1.438 5.427 3.552 70.697 1 S16 13.009 78.659 2.574 34.040 18.87 0 147.15 2 1 S17 12.151 71.993 2.950 1.480 4.995 93.568 1 S18 11.944 31.108 0.594 2.960 2.109 48.715 1 S19 12.580 82.658 3.241 13.320 3.108 114.90 8 1 S20 12.432 50.662 1.751 9.867 12.21 0 86.921 1 S21 11.929 42.662 0.844 5.920 0.999 62.354 1 S22 12.521 63.994 2.199 2.960 5.217 86.891 1 S23 12.121 51.995 1.845 0.493 4.884 71.338 1 S24 12.802 66.216 2.272 5.920 7.104 94.314 1 S25 13.157 111.10 0 4.805 24.173 8.547 161.78 2 2 S26 11.958 13.776 0.229 21.707 0.777 48.448 1 S27 11.677 15.554 0.250 3.947 1.110 32.538 1 S28 12.269 65.771 1.918 32.560 3.774 116.29 2 1 S29 12.388 119.98 8 4.284 24.173 2.331 163.16 4 2 S30 12.166 39.996 1.115 16.280 1.887 71.444 1 S31 12.151 41.329 0.584 2.960 2.220 59.244 1 S32 12.906 64.882 2.043 19.240 7.770 106.84 1 1 S33 12.210 75.104 2.272 15.787 7.326 112.69 8 1 S34 13.202 182.20 4 8.734 1.973 9.879 215.99 2 2 S35 12.536 83.992 3.710 6.413 11.10 0 117.75 1 1 S36 12.595 71.104 2.512 7.893 5.217 99.321 1 S37 12.432 83.103 2.355 23.187 3.219 124.29 6 1 S38 12.092 47.551 1.365 1.480 1.221 63.709 1 S39 12.462 40.440 1.001 0.987 6.660 61.549 1 S40 11.914 46.218 1.021 2.467 0.444 62.064 1 S41 11.292 37.774 0.719 2.960 3.774 56.520 1 S42 12.758 61.772 2.366 7.400 2.775 87.070 1 S43 12.299 41.774 0.844 1.480 3.552 59.949 1 S44 11.766 46.218 0.875 3.453 0.255 62.568 1 S45 12.432 63.105 2.481 0.987 2.886 81.890 1 S46 11.085 46.218 1.334 2.960 1.332 62.929 1 S47 12.225 42.218 0.803 2.467 2.997 60.709 1 S48 12.669 7.555 0.208 30.093 14.43 0 64.955 1
  • 4. Int. J. Sci. Res. in Multidisciplinary Studies Vol.6, Issue.2, Feb 2020 © 2020, IJSRMS All Rights Reserved 76 S49 13.039 81.770 2.668 17.760 5.550 120.78 7 1 S50 11.914 50.662 1.803 1.480 6.882 72.741 1 S51 12.713 93.324 4.367 2.960 3.996 117.36 0 1 S52 12.698 97.768 4.555 14.307 6.105 135.43 3 1 S53 12.610 51.106 1.438 2.960 3.441 71.555 1 S54 12.343 55.550 1.636 13.320 1.998 84.848 1 S55 11.544 14.221 0.271 7.893 0.555 34.484 1 S56 12.358 86.658 3.502 20.227 1.776 124.52 1 1 S57 12.314 67.104 2.178 29.600 5.106 116.30 2 1 S58 12.402 97.768 4.763 13.320 13.32 0 141.57 3 1 S59 11.840 38.218 1.074 1.480 1.443 54.055 1 S60 11.618 38.218 0.677 5.920 2.220 58.654 1 S61 12.195 38.663 0.719 2.960 3.219 57.756 1 S62 11.958 77.770 2.720 3.453 5.550 101.45 2 1 S63 11.810 35.996 0.698 3.947 0.444 52.896 1 S64 12.772 63.549 2.293 21.213 1.665 101.49 3 1 S65 12.388 42.218 0.844 15.293 1.554 72.297 1 S66 11.796 38.663 0.886 13.813 2.997 68.155 1 S67 11.722 38.218 0.406 8.880 1.665 60.891 1 S68 11.366 44.884 0.375 6.413 0.444 63.483 1 S69 12.314 40.885 0.406 2.960 1.332 57.897 1 S70 12.136 58.216 1.438 18.747 3.774 94.311 1 S71 11.411 45.329 0.552 15.293 0.777 73.362 1 S72 11.840 58.216 2.668 27.133 6.327 106.18 5 1 S73 11.944 58.216 2.262 55.747 2.775 130.94 3 1 S74 11.692 49.328 1.480 18.747 10.21 2 91.459 1 S75 11.855 37.330 0.855 0.987 7.770 58.796 1 S76 11.440 42.218 1.032 17.267 1.665 73.622 1 S77 11.929 55.106 1.365 26.147 2.553 97.099 1 S78 12.151 47.106 0.521 0.493 0.777 61.049 1 S79 12.210 39.374 0.782 12.827 4.329 69.521 1 S80 12.713 26.264 0.625 3.453 3.996 47.052 1 S81 12.166 23.464 0.375 6.907 7.992 50.904 1 S82 12.092 40.929 1.219 3.453 7.548 65.242 1 S83 12.225 36.974 0.625 15.787 6.216 71.827 1 S84 12.610 22.975 0.552 5.920 12.09 9 54.156 1 S85 14.825 38.663 0.448 4.440 8.880 67.256 1 S86 12.231 47.995 0.375 12.333 14.43 0 87.364 1 S87 13.495 111.10 0 2.741 55.253 73.26 0 255.84 9 2 S88 12.954 71.104 2.074 25.653 7.659 119.44 5 1 S89 12.944 65.327 0.667 4.933 7.881 91.752 1 S90 11.892 55.550 0.740 16.773 7.326 92.281 1 S91 14.365 63.994 0.813 19.733 5.994 104.89 9 1 S92 12.648 80.436 2.220 62.653 3.552 161.51 0 2 S93 12.285 93.324 3.335 26.640 4.440 140.02 5 1 S94 12.956 52.884 0.667 22.693 11.10 0 100.30 0 1 S95 12.285 51.550 0.667 40.947 3.774 109.22 4 1 S96 12.886 63.994 1.188 19.240 4.551 101.85 9 1 S97 12.021 46.662 0.594 24.173 1.998 85.448 1 S98 11.809 58.661 0.667 42.920 1.554 115.61 1 1 S99 11.688 39.107 0.146 1.973 0.488 53.402 1 S100 11.671 33.774 0.219 0.987 0.844 47.495 1 S101 12.065 51.106 0.959 19.733 3.996 87.859 1 S102 11.615 40.885 0.375 9.373 1.443 63.691 1 S103 12.146 45.773 0.219 0.000 1.776 59.914 1 S104 11.961 39.996 0.521 0.493 1.776 54.748 1 S105 10.971 31.108 0.219 0.493 0.533 43.324 1 S106 12.237 39.107 0.375 22.200 0.588 74.507 1 S107 11.560 34.663 0.448 22.200 0.755 69.626 1 S108 11.988 63.994 1.115 27.133 1.998 106.22 8 1 S109 12.115 53.772 0.521 22.200 1.776 90.385 1 S110 11.615 33.330 0.219 6.907 0.788 52.859 1 S111 11.654 41.329 0.219 1.480 0.733 55.414 1 S112 11.736 38.218 0.594 12.333 2.553 65.435 1 S113 14.393 37.774 0.375 8.387 0.555 61.484 1 S114 11.033 38.218 0.375 23.187 0.910 73.724 1 S115 12.340 55.550 0.667 5.920 3.441 77.918 1 S116 11.886 52.884 0.594 18.747 1.665 85.775 1 S117 11.430 28.886 0.448 23.187 0.844 64.794 1 S118 11.463 38.663 0.959 20.720 1.998 73.802 1 S119 11.359 31.997 0.146 5.920 0.377 49.799 1 S120 11.501 34.219 0.375 1.973 1.332 49.400 1 S121 11.528 38.218 0.740 24.667 1.110 76.263 1 S122 11.500 41.774 0.375 6.907 0.533 61.088 1 S123 11.424 42.218 0.521 25.653 1.221 81.038 1 S124 11.497 35.108 0.448 0.987 1.088 49.127 1 S125 11.855 43.107 0.375 19.240 2.553 77.130 1 S126 11.585 50.662 0.292 1.480 0.932 64.951 1 S127 10.791 36.441 0.219 19.733 0.455 67.639 1 S128 11.590 35.996 0.292 0.000 1.776 49.654 1 S129 11.911 40.885 0.740 20.227 1.998 75.761 1 S130 11.933 41.774 0.292 4.440 1.665 60.104 1 S131 12.209 37.774 0.375 14.800 1.221 66.379 1 S132 12.118 42.218 0.740 24.667 1.554 81.297 1 S133 11.414 37.774 0.521 10.853 3.774 64.336 1 S134 12.009 49.328 0.375 5.427 1.554 68.693 1 S135 11.107 29.775 0.292 0.493 0.955 42.622 1 S136 11.843 61.327 1.188 27.133 4.107 105.59 9 1 S137 11.297 34.663 0.219 0.000 0.744 46.923 1 Fig 3 pH variation 0.00 2.00 4.00 6.00 8.00 10.00 12.00 S1 S11 S21 S31 S41 S51 S61 S71 S81 S91 S101 S111 S121 S131 pH Observed values Standard value
  • 5. Int. J. Sci. Res. in Multidisciplinary Studies Vol.6, Issue.2, Feb 2020 © 2020, IJSRMS All Rights Reserved 77 Fig 4 Electrical conductivity variation 0 1000 2000 3000 4000 5000 S1 S11 S21 S31 S41 S51 S61 S71 S81 S91 S101 S111 S121 S131 EC Observed values Standard value
  • 6. Int. J. Sci. Res. in Multidisciplinary Studies Vol.6, Issue.2, Feb 2020 © 2020, IJSRMS All Rights Reserved 78 Fig 5 Analysis of water parameters in Laboratory Fig 6 Chlorides variation
  • 7. Int. J. Sci. Res. in Multidisciplinary Studies Vol.6, Issue.2, Feb 2020 © 2020, IJSRMS All Rights Reserved 79 Fig 7 Nitrates variation Fig 8 Flouride variation Fig 9: Spatial variation of water quality index IV. CONCLUSIONS In the present study the water quality parameters considered shows that almost 95 percent are with in the FAO standards for irrigation. 133 samples of 137 shows class I index Excellent suitable for irrigation 4 samples shows class II index . By spatial variation of WQI it can be found that almost all the portion of the water is suitable for irrigation with 97 percent of the area is excellently suitable. REFERENCE [1] Mohammed Badiuddin Parvez, M Inayathulla “Generation Of Intensity Duration Frequency Curves For Different Return Period Using Short Duration Rainfall For Manvi Taluk Raichur District Karnataka”, International Research Journal of Engineering and Management Studies (IRJEMS), Volume: 03 Issue: 04 ,Page 1-20, April -2019. [2] Mohammed Badiuddin Parvez, M Inayathulla “Prioritization Of Subwatersheds of Cauvery Region Based on Morphometric Analysis Using GIS”, International Journal for Research in Engineering Application & Management (IJREAM), Volume: 05 Issue: 01, Page 85-94, April -2019. [3] Mohammed Badiuddin Parvez, M Inayathulla “Modelling of Short Duration Isopluvial Map For Raichur District Karnataka”, International Journal for Science and Advance Research in Technology (IJSART), Volume: 05 Issue: 4, Page 973-976, April - 2019. [4] Mohammed Badiuddin Parvez, M Inayathulla, "Rainfall Analysis for Modelling of IDF Curves for Bangalore Rural, Karnataka", International Journal of Scientific Research in Multidisciplinary Studies , Vol.5, Issue.8, page.114-132, 2019. [5] Mohammed Badiuddin Parvez, and M Inayathulla. "Generation of Short Duration Isohyetal Maps For Raichur District Karnataka" International Journal Of Advance Research And Innovative Ideas In Education Volume 5 Issue 2 Page 3234-3242 ,2019. [6] Mohammed Badiuddin Parvez, and M Inayathulla. " Derivation Of Intensity Duration Frequency Curves Using Short Duration Rainfall For Yermarus Raingauge Station Raichur District Karnataka" International Journal of Innovative Research in Technology Volume 6 Issue 2, Page 1-7 ,July 2019. Authors Profile Mohammed Badiuddin Parvez Is a life member of Indian Water Resources Society, ASCE Born in Gangavathi, Obtained his BE in Civil Engineering in the year 2009-2013 from UVCE, Banagalore and M.E with specialization in Water Resources Engineering during 2013-2015 from UVCE, Bangalore University and Pursuing Ph.D from Bangalore University. And has 3 years of teaching experience. Till date, has presented and published several technical papers in many National and International seminars, Journals and conferences. M Inayathulla Is a life member of Environmental and Water Resources Engineering (EWRI), ASCE, WWI, ASTEE, ASFPM. Born in Karnataka, Obtained his BE in Civil Engineering in the year 1987-1991 from UBDT, Davanagere and M.E with specialization on Water Resources Engineering during 1992-1994 from UVCE, Bangalore University and got Doctorate from Bangalore University. Presently working as Professor at UVCE, Bangalore University, India. And has more than 25 years of teaching experience. Till date, has presented and published several technical papers in many National and International seminars and conferences 0 50 100 150 S1 S11 S21 S31 S41 S51 S61 S71 S81 S91 S101 S111 S121 S131 Nitrate Observed values Standard value 0.00 1.00 2.00 3.00 4.00 5.00 6.00 7.00 S1 S11 S21 S31 S41 S51 S61 S71 S81 S91 S101 S111 S121 S131 Fluoride Observed values Standard value