# Evaluation of Groundwater Quality for Suitability of Irrigation Purposes: A Case Study in the Udham Singh Nagar, Uttarakhand

Authors: Kshitindra Kr. Singh; Geeta Tewari; Suresh Kumar
Journal: Journal of Chemistry
 (2020)

---

## Abstract

In the present study, the groundwater quality for suitability in agriculture from Udham Singh Nagar district, Uttarakhand, has been evaluated. A total of 50 groundwater samples have been collected and analysed for pH, EC, TH, HCO3−, CO32−, Cl−, SO42−, NO3–, Ca2+, Mg2+, Na+ and K+. To assess the groundwater quality for irrigation purpose, parameters like sodium adsorption ratio (SAR), soluble sodium percentage (SSP), residual sodium carbonate (RSC), magnesium hazards (MHs), permeability index (PI), and chloroalkaline index (CAI) values have been calculated. In USSL diagram, most of the groundwater samples fall in the C2S1 category and were safe for irrigation purpose. Only seven groundwater samples fall in the C3S1 category, indicating medium to high salinity which is safe for irrigation purpose for all types of soils but with limited care of exchangeable sodium. On the basis of RSC, all groundwater samples were observed to be suitable for irrigation purpose. Piper diagram indicated that 50% of the groundwater samples belonged to the Mg2+-Ca2+-HCO3− type and 48% was classified as the Ca2+-Mg2+-Cl− type. Durov diagram suggested possibilities of ion mixing and simple dissolution of ions from polluted soil.


---

## Body

## 1. Introduction

Groundwater plays an important role all over the world for the survival of both flora and fauna. India is one of the largest users of groundwater, particularly for drinking and agriculture purposes [1] Agriculture is one of the most important sectors of Indian economy. In rural areas, the major sources of groundwater for drinking and irrigation purpose are hand pump and tub well. According to a national sample survey, 56% households get drinking water from hand pump or tube well, 14% from open well, and 25% based on piped water [2]. Groundwater gets contaminated with a variety of pollutants such as domestic, agriculture, and industrial due to utilization of fertilizers, pesticides, and other chemical products [3]. The groundwater quality assessment based on different agriculture indices has been studied in different parts of world [4, 5]. There are a number of reports on the assessment of groundwater quality from Bangladesh [6], Cameroon [7], Ghana [8], Tamil Nadu [9–12], Madhya Pradesh [13, 14], Bhatina, South west Punjab [15] and Sant Ravidas Nagar, Bhadohi, Uttar Pradesh [16]. In Uttarakhand, irrigation water quality assessment has been done in Doon Valley [17], Nainital [18], Almora [19, 20], and Haridwar [21].To the best of our knowledge, no study on the assessment of irrigation water quality has been undertaken from Udham Singh Nagar District of Uttarakhand with especial reference to dug well and hand pump water. Therefore, in the present study, an attempt has been made to determine the groundwater suitability for irrigation purpose from Udham Singh Nagar district of Uttarakhand.


## 2. Materials and Methods

Udham Singh Nagar district located in Tarai belt of Kumaun region and geographical area of the district is 3055 cm2. It is situated between latitude 28°52′N and 29°23′N and longitudes 78°45′N and 80°08′N. The district Udham Singh Nagar covers Champawat and Nainital district in North region of Uttarakhand, south region with Pilibhit, Moradabad, and Bareilly district of UP, and Biznor district of UP on the west and Nepal on the east.


### 2.1. Collection of Samples

Fifty groundwater samples (hand pump and dug well) were collected in premonsoon season in the year 2018 from different sites of Khatima, Bazpur, Gadarpur, Kashipur, Jaspur Kicha, and Sitarganj blocks of Udham Singh Nagar district, Uttarakhand (Table1; Figure 1). The samples were collected in prewashed polyethylene narrow mouth bottles (three times rinsed with same water to be sampled). Locations (longitude, latitude, and altitude) of sampling point were measured by using a global positioning system (GPS).Table 1
Sampling sites along with the coordinates.
S. no.
Sample location
Block
Source of groundwater
Longitude
Latitude
Altitude (m)
1
Nagla KU1
Rudrapur
HP
29.01861397
79.51723429
174
2
Khurpia KU2
HP
28.93800460
79.52050952
158
3
Bara KU3
HP
28.87547059
79.58577626
151
4
Kathangri KU4
HP
28.86720898
79.64385116
148
5
Baghora KU5
HP
28.93216090
79.72764192
163
6
Haldi KU6
HP
29.02966348
79.47521444
184
7
Matkota KU7
HP
29.00883778
79.40033672
167
8
Dungarpur KU8
HP
29.10925542
79.52622965
235
9
Maharajpur KU9
HP
28.94565023
79.47518752
253
10
Rudrapur KU10
HP
28.97872029
79.39966655
153
11
Turka tishor KU11
Khatima
HP
28.93867576
79.72527877
154
12
Jhankat KU12
HP
28.94002867
79.90025061
162
13
Khatima KU13
HP
28.92166172
79.97217708
155
14
Chakarpur KU14
SS
28.969117
80.01612670
167
15
Pachpera KU15
SS
28.91784380
79.9003284
127
16
Deori KU16
HP
28.99376716
79.92128573
170
17
Barhani KU17
Bazpur
HP
29.20438305
79.20892647
184
18
Seekaniya KU18
HP
29.03828582
79.17878673
150
19
Maseet KU19
HP
29.08021447
79.19893901
163
20
Bazpur KU20
HP
29.15936853
79.15165552
174
21
Bannakhera KU21
SS
29.24025916
79.15940395
196
22
Hazeera KU22
HP
29.19309604
79.21226626
189
23
Gumsani (KU23)
HP
29.13447556
79.15176307
177
24
Mohali jungle KU24
HP
29.15465869
79.26299815
180
25
Sultanpur patti KU25
Gadarpur
SS
29.15738948
79.06430293
168
26
Gularbhoj KU26
HP
29.11357514
79.30314093
165
27
Gadarpur KU27
HP
29.05569688
79.23079049
166
28
Dinehpur KU28
SS
29.05331738
79.32256362
176
29
Gularbhoj KU29
HP
29.11357514
79.30314093
165
30
Singhali KU30
HP
29.2178301
79.17684401
201
31
Jhagarpuri KU31
HP
29.06149689
79.2233027
160
32
Fatehganj KU32
Kashipur
HP
29.09195119
79.21388612
177
33
Mandua Khera KU33
HP
29.13092602
78.94894251
162
34
Kanakpur KU34
SS
29.16310206
78.97692242
173
35
Kanchnal Gosai KU35
HP
29.17990566
78.98805976
169
36
Nandrampur KU36
HP
29.1864069
79.0160997
178
37
Dhakia Kalan KU37
HP
29.20987463
79.0391834
165
38
Bhimnagar KU38
SS
29.24697166
79.0273784
188
39
Chandpur KU39
SS
29.27920450
79.01905650
199
40
Chaity more KU40
HP
29.19604884
78.977699178
176
41
Manpur KU41
HP
29.23402707
78.96438855
169
42
Hempur kechari KU42
Jaspur
HP
29.30418079
78.97646790
229
43
Bharatpur KU43
HP
29.24817043
78.91853846
186
44
Karanpur KU44
HP
29.27077540
78.92668359
186
45
Haldua KU45
SS
29.24366721
78.88074054
183
46
Narayanpur KU46
HP
29.26560579
78.85106087
187
47
Patrampur KU47
HP
29.33296726
78.87312241
211
48
Mandua Khera KU48
HP
29.29226677
78.82597353
190
49
Birpuri KU49
SS
29.31519877
78.82405974
186
50
Kasampur KU50
SS
29.26969627
78.80603843
187
HP = hand pump; SS = summer savil.Figure 1
Location map of the sampling sites.


### 2.2. Chemical Parameters of the Samples

Electrical conductivity (EC) and pH were measured using a potable kit. The water samples were filtered with using 0.45 Millipore membrane filter paper for the separation of suspended solids. Sulphate (SO42−) content was determined by the UV spectrophotometric method, while chloride (Cl−) and bicarbonate (HCO3−) content were measured by the titration method [22]. The detection of Ca2+, Mg2+, and total hardness (TH) was done by the titration method, while Na+ and K+ were estimated by the flame photometer method [22].


### 2.3. Evaluation of Irrigation Water Quality

The concentrations of different parameters were interrelated, and irrigation indexes like soluble sodium percentage (SSP), sodium adsorption ratio (SAR), residual sodium carbonate (RSC), magnesium hazard (MH), permeability index (PI), and chloroalkaline index (CAI) were calculated to assess groundwater quality. USSL salinity, Wilcox, permeability index, and Gibbs diagrams were drawn with the help of Grapher free software to assess irrigation quality of collected water samples. Hydrochemical analysis was evaluated by drawing Piper and Durov diagrams using Aquachem (2004) software.


### 2.4. Salinity and Alkalinity Hazard (SAH)

Electrical conductivity and US Salinity Laboratory diagram helped in explaining salinity and alkalinity hazard in the study area.


### 2.5. Sodium Hazard (SH)

Sodium hazard was assessed by evaluating soluble sodium percentage and sodium absorption ratio and drawing Wilcox diagram.


#### 2.5.1. Soluble Sodium Percentage (SSP)

Soluble sodium percentage (SSP) was calculated by employing the equation given by Todd [23]. The ionic concentration was presented in meq L−1:(1)SSP=Na++K+Ca2++Mg2++Na++K+×100.


#### 2.5.2. Sodium Adsorption Ratio (SAR)

SAR was calculated using the equation given by Raghunath [24]. The concentration of the ions was expressed in meq L−1:(2)SAR=Na+Ca2++Mg2+/2.


#### 2.5.3. Carbonate and Bicarbonate Hazard (CBH)

Carbonate and bicarbonate hazard was assessed by evaluating soluble sodium carbonate.


#### 2.5.4. Residual Sodium Carbonate (RSC)

This was evaluated employing the following equation of Eaton [25]:(3)RSC=HCO3−+CO32−−Ca2++Mg2+.


#### 2.5.5. Magnesium Hazard (MH)

This was evaluated by the equation given by Szabolcs and Darab [26], where the concentration of each cation was expressed in meq L−1:(4)MH=Mg2+Ca2++Mg2+×100.


### 2.6. Permeability Index (PI)

Permeability index (PI) was used to classify the irrigation water quality and was calculated by the formula given by Doneen [27]. The concentration of all ions was taken in meq L−1:(5)PI=Na++HCO3−Ca2++Mg2++Na+×100.


### 2.7. Chloroalkaline Index (CAI)

Chloroalkaline index (CAI I and CAI II) was calculated by the formula given by Scholler [28]:(6)CAI  I=Cl−−Na++K+Cl−,CAI  II=Cl−−Na++K+SO42−+HCO3−+NO3−+CO32−.


## 2.1. Collection of Samples

Fifty groundwater samples (hand pump and dug well) were collected in premonsoon season in the year 2018 from different sites of Khatima, Bazpur, Gadarpur, Kashipur, Jaspur Kicha, and Sitarganj blocks of Udham Singh Nagar district, Uttarakhand (Table1; Figure 1). The samples were collected in prewashed polyethylene narrow mouth bottles (three times rinsed with same water to be sampled). Locations (longitude, latitude, and altitude) of sampling point were measured by using a global positioning system (GPS).Table 1
Sampling sites along with the coordinates.
S. no.
Sample location
Block
Source of groundwater
Longitude
Latitude
Altitude (m)
1
Nagla KU1
Rudrapur
HP
29.01861397
79.51723429
174
2
Khurpia KU2
HP
28.93800460
79.52050952
158
3
Bara KU3
HP
28.87547059
79.58577626
151
4
Kathangri KU4
HP
28.86720898
79.64385116
148
5
Baghora KU5
HP
28.93216090
79.72764192
163
6
Haldi KU6
HP
29.02966348
79.47521444
184
7
Matkota KU7
HP
29.00883778
79.40033672
167
8
Dungarpur KU8
HP
29.10925542
79.52622965
235
9
Maharajpur KU9
HP
28.94565023
79.47518752
253
10
Rudrapur KU10
HP
28.97872029
79.39966655
153
11
Turka tishor KU11
Khatima
HP
28.93867576
79.72527877
154
12
Jhankat KU12
HP
28.94002867
79.90025061
162
13
Khatima KU13
HP
28.92166172
79.97217708
155
14
Chakarpur KU14
SS
28.969117
80.01612670
167
15
Pachpera KU15
SS
28.91784380
79.9003284
127
16
Deori KU16
HP
28.99376716
79.92128573
170
17
Barhani KU17
Bazpur
HP
29.20438305
79.20892647
184
18
Seekaniya KU18
HP
29.03828582
79.17878673
150
19
Maseet KU19
HP
29.08021447
79.19893901
163
20
Bazpur KU20
HP
29.15936853
79.15165552
174
21
Bannakhera KU21
SS
29.24025916
79.15940395
196
22
Hazeera KU22
HP
29.19309604
79.21226626
189
23
Gumsani (KU23)
HP
29.13447556
79.15176307
177
24
Mohali jungle KU24
HP
29.15465869
79.26299815
180
25
Sultanpur patti KU25
Gadarpur
SS
29.15738948
79.06430293
168
26
Gularbhoj KU26
HP
29.11357514
79.30314093
165
27
Gadarpur KU27
HP
29.05569688
79.23079049
166
28
Dinehpur KU28
SS
29.05331738
79.32256362
176
29
Gularbhoj KU29
HP
29.11357514
79.30314093
165
30
Singhali KU30
HP
29.2178301
79.17684401
201
31
Jhagarpuri KU31
HP
29.06149689
79.2233027
160
32
Fatehganj KU32
Kashipur
HP
29.09195119
79.21388612
177
33
Mandua Khera KU33
HP
29.13092602
78.94894251
162
34
Kanakpur KU34
SS
29.16310206
78.97692242
173
35
Kanchnal Gosai KU35
HP
29.17990566
78.98805976
169
36
Nandrampur KU36
HP
29.1864069
79.0160997
178
37
Dhakia Kalan KU37
HP
29.20987463
79.0391834
165
38
Bhimnagar KU38
SS
29.24697166
79.0273784
188
39
Chandpur KU39
SS
29.27920450
79.01905650
199
40
Chaity more KU40
HP
29.19604884
78.977699178
176
41
Manpur KU41
HP
29.23402707
78.96438855
169
42
Hempur kechari KU42
Jaspur
HP
29.30418079
78.97646790
229
43
Bharatpur KU43
HP
29.24817043
78.91853846
186
44
Karanpur KU44
HP
29.27077540
78.92668359
186
45
Haldua KU45
SS
29.24366721
78.88074054
183
46
Narayanpur KU46
HP
29.26560579
78.85106087
187
47
Patrampur KU47
HP
29.33296726
78.87312241
211
48
Mandua Khera KU48
HP
29.29226677
78.82597353
190
49
Birpuri KU49
SS
29.31519877
78.82405974
186
50
Kasampur KU50
SS
29.26969627
78.80603843
187
HP = hand pump; SS = summer savil.Figure 1
Location map of the sampling sites.


## 2.2. Chemical Parameters of the Samples

Electrical conductivity (EC) and pH were measured using a potable kit. The water samples were filtered with using 0.45 Millipore membrane filter paper for the separation of suspended solids. Sulphate (SO42−) content was determined by the UV spectrophotometric method, while chloride (Cl−) and bicarbonate (HCO3−) content were measured by the titration method [22]. The detection of Ca2+, Mg2+, and total hardness (TH) was done by the titration method, while Na+ and K+ were estimated by the flame photometer method [22].


## 2.3. Evaluation of Irrigation Water Quality

The concentrations of different parameters were interrelated, and irrigation indexes like soluble sodium percentage (SSP), sodium adsorption ratio (SAR), residual sodium carbonate (RSC), magnesium hazard (MH), permeability index (PI), and chloroalkaline index (CAI) were calculated to assess groundwater quality. USSL salinity, Wilcox, permeability index, and Gibbs diagrams were drawn with the help of Grapher free software to assess irrigation quality of collected water samples. Hydrochemical analysis was evaluated by drawing Piper and Durov diagrams using Aquachem (2004) software.


## 2.4. Salinity and Alkalinity Hazard (SAH)

Electrical conductivity and US Salinity Laboratory diagram helped in explaining salinity and alkalinity hazard in the study area.


## 2.5. Sodium Hazard (SH)

Sodium hazard was assessed by evaluating soluble sodium percentage and sodium absorption ratio and drawing Wilcox diagram.


### 2.5.1. Soluble Sodium Percentage (SSP)

Soluble sodium percentage (SSP) was calculated by employing the equation given by Todd [23]. The ionic concentration was presented in meq L−1:(1)SSP=Na++K+Ca2++Mg2++Na++K+×100.


### 2.5.2. Sodium Adsorption Ratio (SAR)

SAR was calculated using the equation given by Raghunath [24]. The concentration of the ions was expressed in meq L−1:(2)SAR=Na+Ca2++Mg2+/2.


### 2.5.3. Carbonate and Bicarbonate Hazard (CBH)

Carbonate and bicarbonate hazard was assessed by evaluating soluble sodium carbonate.


### 2.5.4. Residual Sodium Carbonate (RSC)

This was evaluated employing the following equation of Eaton [25]:(3)RSC=HCO3−+CO32−−Ca2++Mg2+.


### 2.5.5. Magnesium Hazard (MH)

This was evaluated by the equation given by Szabolcs and Darab [26], where the concentration of each cation was expressed in meq L−1:(4)MH=Mg2+Ca2++Mg2+×100.


## 2.5.1. Soluble Sodium Percentage (SSP)

Soluble sodium percentage (SSP) was calculated by employing the equation given by Todd [23]. The ionic concentration was presented in meq L−1:(1)SSP=Na++K+Ca2++Mg2++Na++K+×100.


## 2.5.2. Sodium Adsorption Ratio (SAR)

SAR was calculated using the equation given by Raghunath [24]. The concentration of the ions was expressed in meq L−1:(2)SAR=Na+Ca2++Mg2+/2.


## 2.5.3. Carbonate and Bicarbonate Hazard (CBH)

Carbonate and bicarbonate hazard was assessed by evaluating soluble sodium carbonate.


## 2.5.4. Residual Sodium Carbonate (RSC)

This was evaluated employing the following equation of Eaton [25]:(3)RSC=HCO3−+CO32−−Ca2++Mg2+.


## 2.5.5. Magnesium Hazard (MH)

This was evaluated by the equation given by Szabolcs and Darab [26], where the concentration of each cation was expressed in meq L−1:(4)MH=Mg2+Ca2++Mg2+×100.


## 2.6. Permeability Index (PI)

Permeability index (PI) was used to classify the irrigation water quality and was calculated by the formula given by Doneen [27]. The concentration of all ions was taken in meq L−1:(5)PI=Na++HCO3−Ca2++Mg2++Na+×100.


## 2.7. Chloroalkaline Index (CAI)

Chloroalkaline index (CAI I and CAI II) was calculated by the formula given by Scholler [28]:(6)CAI  I=Cl−−Na++K+Cl−,CAI  II=Cl−−Na++K+SO42−+HCO3−+NO3−+CO32−.


## 3. Results and Discussion

### 3.1. pH

The term pH expressed to describe the intensity of acidic and alkaline nature of a solution. The pH value of the groundwater samples in the study area lie in between 7.57 and 8.61. All the groundwater samples belonged to the safe limit for irrigation purpose [29].


### 3.2. Water Quality Based on the Absolute Ions

In the present study area, the concentration of cations lies from 20.0 to 140.0 mg L−1 for Ca2+, 14.1 to 85.0 mg L−1 for Mg2+, 0.4 to 62.0 mg L−1 for Na+, and 0.0 to 55.2 mg L−1 for K+ (Table 2). In irrigation water, the permissible limit for Ca2+, Mg2+, Na+, and K+ is 80, 35, 200, and 30 mg L−1, respectively [30, 31]. On the basis of these permissible limits, 96% groundwater samples for Ca2+, 42% for Mg2+, 100% for Na+, and 100% for K+ were fit for irrigation purpose.Table 2
Chemical parameters of the collected water samples from Udham Singh Nagar district.
Sampling location
pH
EC (μS cm−1)
TH (mg·L−1)
Cl− (mg·L−1)
HCO
3
− (mg·L−1)
SO
4
2
− (mg·L−1)
NO
3
− (mg·L−1)
CO
3
2
− (mg·L−1)
Ca2+ (mg·L−1)
Mg2+ (mg·L−1)
Na+ (mg·L−1)
K+ (mg·L−1)
TDS (mg·L−1)
KU1
7.79
1131
444
127.0
338.3
82.7
19.39
0
58.8
72.2
62.0
27.0
735
KU2
7.99
1274
539
252.4
356.7
16.7
22.59
0
140.0
46.0
42.0
1.6
828
KU3
8.49
416
207
18.4
196.0
23.8
0.01
9
32.0
31.0
18.0
1.2
270
KU4
7.71
515
237
28.4
230.0
18.9
0.32
0
42.0
32.0
18.3
1.0
335
KU5
8.32
692
277
72.0
295.2
22.7
0.01
3
50.0
50.0
20.0
5.6
450
KU6
7.92
533
255
13.0
237.0
25.2
9.82
0
42.0
36.5
10.0
12.0
346
KU7
7.97
372
444
22.7
153.0
19.0
5.00
0
40.0
18.8
9.0
1.7
242
KU8
8.41
401
383
14.2
159.9
29.0
8.74
6
42.0
24.0
7.2
1.6
261
KU9
7.79
390
169
43.0
129.2
21.6
0.85
0
44.0
18.0
8.3
0.9
254
KU10
7.57
666
263
31.2
256.0
58.4
19.48
0
58.0
32.0
41.0
6.4
433
KU11
8.32
744
286
144.6
176.0
47.2
10.12
3
46.0
34.0
47.0
2.1
484
KU12
8.05
1022
335
113.4
316.0
66.9
54.66
0
38.0
85.0
12.5
0.0
664
KU13
8.22
810
400
51.1
322.0
40.9
0.48
0
82.0
40.0
34.0
1.1
527
KU14
8.16
401
275
34.0
162.5
16.4
0.07
0
50.0
14.1
12.0
1.3
261
KU15
8.45
545
339
28.4
245.0
0.2
0.06
9
28.0
47.0
8.4
0.7
354
KU16
8.36
645
280
26.0
279.0
28.2
1.34
3
52.0
38.0
23.4
9.5
419
KU17
8.57
705
350
35.5
166.1
124.7
0.73
12
60.0
45.0
24.8
1.4
458
KU18
7.97
850
504
76.6
325.0
43.8
0.64
0
30.0
79.0
19.8
1.3
440
KU19
7.79
766
275
70.9
228.0
86.4
5.54
0
52.0
35.2
31.5
12.3
498
KU20
8.4
955
239
14.2
291.0
150.0
19.47
3
70.0
40.0
39.5
55.2
621
KU21
7.86
750
275
22.7
360.0
19.3
45.97
0
54.0
35.2
30.0
12.4
488
KU22
8.39
755
200
14.18
372.0
37.7
5.50
3
48.0
55.9
13.6
0.8
491
KU23
8.25
710
360
19.85
237.0
78.1
0.07
0
50.0
35.2
37.6
12.4
462
KU24
8.35
645
290
17.01
322.0
39.2
0.02
3
46.0
38.0
12.6
1.1
419
KU25
8.06
481
224
19.85
173.0
57.7
5.23
0
56.0
24.2
12.4
0.7
313
KU26
7.94
530
285
14.18
241.0
30.0
3.79
0
60.0
30.4
0.4
0.0
345
KU27
8.33
460
259
11.34
233.7
8.7
5.73
3
40.0
24.3
16.3
1.3
299
KU28
7.76
741
240
8.5
229.0
150.4
0.00
0
48.0
58.3
11.9
1.3
482
KU29
8.38
635
190
28.36
288.0
30.2
0.12
6
60.0
34.0
12.0
1.3
413
KU30
8.3
614
165
25.52
274.0
52.6
1.13
0
36.0
32.6
29.7
1.1
399
KU31
8.15
602
200
25.52
233.0
49.6
0.08
0
40.0
45.0
19.4
1.5
391
KU32
8.32
487
200
70.9
187.0
1.4
0.15
3
32.0
28.3
16.1
1.2
317
KU33
8.6
611
261
17.01
233.0
19.4
29.00
15
40.0
38.7
31.4
1.3
397
KU34
8.11
579
260
34.04
187.0
52.3
0.22
0
56.0
24.3
30.0
1.5
376
KU35
7.95
390
220
19.85
172.0
11.2
0.56
0
44.0
19.4
9.8
1.6
254
KU36
7.87
353
436
25.52
150.0
8.8
5.04
0
38.0
17.0
7.5
0.9
229
KU37
8.08
392
155
25.52
157.0
11.7
6.36
0
36.0
26.7
7.5
0.8
255
KU38
8.23
413
200
19.85
190.7
6.0
0.15
0
40.0
24.3
11.9
1.3
268
KU39
8.59
690
215
130.45
180.0
5.9
0.07
12
46.0
35.6
18.6
11.3
449
KU40
8.23
540
240
14.18
258.3
17.6
4.58
0
52.0
31.6
11.0
0.6
351
KU41
8.13
576
230
19.85
249.0
6.8
37.12
0
56.0
19.4
34.4
1.3
374
KU42
7.75
920
198
130.45
258.0
55.8
0.18
0
94.0
48.8
15.3
1.0
598
KU43
8.61
467
221
28.36
196.8
1.3
2.48
12
20.0
25.5
38.5
1.0
304
KU44
8.04
555
160
24.81
264.5
1.6
0.37
0
46.0
20.7
48.5
1.0
361
KU45
8.42
520
159
11.34
246.0
27.9
9.19
6
38.0
29.2
20.8
1.5
338
KU46
8.45
600
349
28.36
233.0
33.0
13.00
6
52.0
26.7
41.8
0.8
390
KU47
8.46
540
360
34.03
215.2
6.6
7.13
6
36.0
34.0
22.1
1.0
351
KU48
8.2
520
165
22.68
283.0
5.4
0.12
0
48.0
19.0
24.1
0.4
338
KU49
8.16
560
198
24.1
313.0
0.4
4.14
0
42.0
28.2
19.3
1.5
364
KU50
8.55
395
221
28.3
161
0.2
0.12
0
30.0
20.6
24.3
1.2
257The permissible limit for anions HCO3− and Cl− is 250 mg L−1 [30, 31]. The values of HCO3− and Cl− in the groundwater samples varied from 29.2 to 372.0 mg L−1 and 8.2 to 252.4 mg L−1, respectively (Table 2). The results on major anions revealed that 64% water samples as per the limit of HCO3− and 98% as per the limit of Cl− were observed to be fit for irrigation purpose.


### 3.3. Total Hardness (TH)

In water quality, TH is an important parameter whether it has been used for domestic, irrigation, and industrial purpose. The presence of alkaline Earth metals causes hardness of water which prevents the lather with soap and increases the boiling point. Amount of calcium and magnesium ions in some of the collected samples was high. When calcium reacts with water, either CaCO3 is formed in the form of limestone and chalk, or CaSO4 is formed. The major source of Mg in groundwater is dolomite, CaMg(CO3)2. According to Sawyer and McCarthy (1967) [32], water can be categorized as soft (>75 mg L−1), moderately hard (75 to 150 mg L−1), hard (150 to 300 mg L−1), and very hard (above 300 mg L−1). In the present study, TH varied from 155 to 539 mg L−1, indicating hard to very hard nature of water. Thirty-nine samples had hard category, while 20% samples (11 samples) had hardness higher than 300 mg L−1, which is a desirable limit for drinking purpose (Table 2).


### 3.4. Salinity and Alkalinity Hazard (SAH)

The groundwater becomes saline if high salt content is present. The evaluation of salinity hazard is an important parameter of agriculture water as high salt content of irrigation water causes the soil to become saline, and it also adversely affects the salt intake efficiency of the plants. Electrical conductivity (EC) and total dissolved solid (TDS) values are measure of salinity hazard of irrigation water. In the present study, the values of EC and TDS ranged from 353 to 1274µS–1 cm−1 and 229 to 828 mg L−1, respectively (Table 2). According to the limiting value [33] of TDS for water suitability for irrigation purpose, 28% groundwater samples belonged to the moderate category. Furthermore, the classification and distribution of groundwater samples with respect to salinity (EC) is given in Table 3. The water samples were classified into four groups on the basis of salinity [34]. Irrigation water quality based on salinity indicated that no water sample belonged to the excellent category (C1). Eighty-six percent of the samples belonged to the C2 class, and remaining 14% was found in the C3 class. On the basis of salinity, none of the samples were observed to be unfit for irrigation purpose.Table 3
Classification and distribution of water quality based on salinity.
Level
Salinity (µS cm−1)
Hazards and limitation
Number of samples
C1
<250
Low hazards and no detrimental effects on the plants and no accumulation in soil is expected
No
C2
250–750
Stress can be shown by sensitive plants, and salt accumulation in soil can be prevented due to moderate leaching
43 samples
C3
750–2250
Most plants affected by salinity (salt-tolerant plants are needed), careful irrigation, good drainage, and leaching required
7 samples (KU1, KU2, KU12, KU19, KU20, KU21, and KU42)
C4
>2250
Unsuitable for irrigation except some highly salt-resistant plants, excellent drainage, frequent leaching, and intensive management required
-


### 3.5. United States Salinity Laboratory (USSL) Diagram

USSL diagram has been used to study the quality of groundwater suitability for irrigation purpose [35]. The SAR and EC values of water samples of Udham Singh Nagar District were plotted in the graphical representation (Figure 2) and found that 43 samples fall in C2S1 (medium salinity with low sodium category) and remaining 7 samples fall in C3S1 (high salinity and low sodium category). C3S1-type water cannot be used on soil with restricted drainage. Bhandari and Joshi (2013) reported that 98% of spring water samples from Almora district of Uttarakhand fall in C1S1, which indicated suitability of these samples for irrigation purpose [36].Figure 2
USSL salinity diagram indicating classification of water for irrigation.


### 3.6. Wilcox Diagram

Wilcox diagram is plotted for classification of water for irrigation suitability [37]. In this diagram, the EC was plotted against the percentage of Na. According to Wilcox classification, 86% of the water samples belonged to the excellent good category and remaining 14% groundwater samples fall in good category (Figure 3). Bahukhandi et al. [21] assessed ground and surface water quality of Hardwar district, Uttarakhand, and observed that, according to the US salinity diagram, most of the ground and surface water samples fall in C1S1 and C2S1 categories, while according to Wilcox diagram, large number of water samples was within excellent to good category [38].Figure 3
Wilcox diagram showing classification of water for irrigation on the basis of percent sodium and EC.


### 3.7. Sodium Hazard (SH)

#### 3.7.1. Sodium Adsorption Ratio (SAR)

According to Gholami and Srikantaswamy [39], the alkali or sodium hazard can be expressed in terms of sodium adsorption ratio. Sodium hazard is the main parameter for assessment of groundwater suitability for irrigation purpose. Sodium-enriched groundwater is unsuitable for irrigation of agricultural lands. Biswas et al. [40] reported that excess sodium in water produces undesirable effect of changing soil permeability and water infiltration due to breakdown in the physical structure of the soil. In a previous study, the SAR values ranging from 0 to 10 were measured as excellent, 10–18 were measured as good, and values greater than 18 were measured as unsuitable for irrigation purpose [41]. In the present study, the SAR values ranged between 0.01 and 1.49 and, thus, were classified as the S1 level, which belonged to an excellent category for irrigation purpose (Table 4). Shahidullah et al. reported groundwater quality of Mymensingh district in Bangladesh and suggested that there was a linear relationship between sodium adsorption ratio (SAR) and soluble sodium percentage (SSP) and also observed that groundwater could be safely used for long-term irrigation purpose [42]. Dudeja et al. have also reported that the groundwater of Doon valley in outer Himalaya, Uttarakhand, had suitability for drinking and irrigation purpose [17]. Seth et al. studied that Kosi river water in Almora district, Uttarakhand, could not be used for drinking purpose, while it was found to be suitable for irrigation purpose on the basis of SAR, %Na, and RSC [20].Table 4
Calculated parameters of irrigation water quality.
Collection Sites
SAR
RSC
SSP
MH
PI
CAI I
CAI II
Gibbs 1
Gibbs 2
KU1
1.27
−3.33
27.6
67
43.66
2.6369
3.0698
0.60
0.27
KU2
0.78
−4.92
14.8
35
33.70
6.8758
6.8213
0.24
0.41
KU3
0.54
−0.63
16.4
61
52.24
−1.0530
0.2828
0.38
0.09
KU4
0.52
−0.96
14.8
56
49.56
−0.2270
0.5931
0.31
0.11
KU5
0.48
−1.67
13.3
62
41.05
1.5321
1.8314
0.34
0.20
KU6
0.27
−1.21
12.7
59
43.51
−1.6560
0.1922
0.34
0.05
KU7
0.29
−1.03
10.9
44
44.08
0.0401
0.4821
0.21
0.13
KU8
0.22
−1.25
8.0
49
44.98
0.4823
0.2825
0.17
0.08
KU9
0.27
−1.56
9.5
40
52.42
0.8963
1.0496
0.17
0.25
KU10
1.07
−1.33
26.1
48
52.45
1.3332
0.4910
0.45
0.11
KU11
1.28
−2.11
29.2
55
29.89
3.5656
3.4773
0.52
0.45
KU12
0.26
−3.71
5.8
79
42.62
3.0301
3.1164
0.25
0.26
KU13
0.77
−2.10
17.0
45
51.57
0.3935
1.1760
0.30
0.14
KU14
0.38
−0.99
13.2
32
42.09
0.3821
0.7633
0.21
0.17
KU15
0.22
−0.95
6.8
73
46.84
0.3209
0.7046
0.25
0.10
KU16
0.60
−1.05
18.1
55
35.12
−0.9856
0.4751
0.39
0.09
KU17
0.59
−3.57
14.3
81
35.78
−0.1145
0.7233
0.30
0.18
KU18
0.43
−2.67
10.1
53
48.13
1.7459
2.0054
0.41
0.19
KU19
0.82
−1.76
23.5
49
45.9
1.1576
1.6411
0.46
0.24
KU20
0.93
−1.91
25.6
52
54.14
−7.7824
−0.0790
0.57
0.05
KU21
0.78
0.31
22.5
66
40.36
−1.8956
0.3933
0.44
0.06
KU22
0.31
−0.79
8.0
54
51.31
−1.1301
0.3065
0.23
0.04
KU23
0.99
−1.51
25.6
58
47.67
−2.9227
0.1445
0.50
0.08
KU24
0.33
−0.04
9.6
42
41.79
−0.7210
0.3716
0.23
0.05
KU25
0.35
−1.95
10.4
45
36.39
−0.4352
0.4003
0.01
0.10
KU26
0.01
−1.54
0.3
50
56.68
−0.3561
0.3960
0.31
0.06
KU27
0.50
−0.06
15.7
67
31.85
−2.0005
0.1333
0.22
0.05
KU28
0.27
−3.44
7.1
48
42.68
−2.0577
0.1363
0.18
0.04
KU29
0.31
−0.87
8.7
60
59.12
0.1060
0.6898
0.46
0.09
KU30
0.86
0.01
22.8
65
42.80
−1.1137
0.4585
0.34
0.09
KU31
0.50
−1.87
13.4
69
53.00
−0.5056
0.5164
0.35
0.10
KU32
0.50
−0.76
21.3
61
50.73
1.6345
1.7628
0.45
0.27
KU33
0.84
−0.86
21.9
42
50.11
−2.4359
0.1563
0.36
0.07
KU34
0.84
−1.73
11.0
42
49.88
−0.4387
0.5884
0.21
0.15
KU35
0.31
−0.98
9.6
55
52.32
−0.2744
0.4011
0.18
0.10
KU36
0.25
−0.84
8.0
50
44.67
0.2347
0.5857
0.19
0.15
KU37
0.23
−1.42
12.1
56
50..45
−0.2343
0.5943
0.25
0.14
KU38
0.36
−0.87
17.4
50
41.88
−0.4283
0.3872
0.39
0.09
KU39
0.50
−1.87
8.7
36
44.72
3.3814
3.3154
0.18
0.42
KU40
0.30
−0.96
25.8
46
59.71
−0.8345
0.2894
0.39
0.05
KU41
1.01
−0.31
7.4
68
29.05
−2.1717
0.2230
0.15
0.07
KU42
0.32
−4.48
35.4
43
72.75
3.4920
3.5362
0.66
0.34
KU43
1.34
0.53
34.8
56
68.67
−1.3253
0.2749
0.52
0.13
KU44
1.49
0.34
18.0
46
56.02
−2.3510
0.2096
0.37
0.09
KU45
0.61
−0.06
27.7
61
57.06
−2.6284
0.1065
0.45
0.04
KU46
1.17
−0.77
17.7
39
51.10
−1.4983
0.3723
0.39
0.11
KU47
0.63
−0.87
21.1
53
63.96
−0.0681
0.6910
0.33
0.14
KU48
0.74
0.68
16.6
53
59.08
−1.0147
0.4144
0.34
0.07
KU49
0.56
0.72
25.4
57
63.05
−0.6411
0.5103
0.46
0.07
KU50
0.83
−0.16
0.3
43
29.05
−0.5642
0.3867
0.46
0.15


#### 3.7.2. Soluble Sodium Percentage (SSP)

According to Nagarju et al., the percentage of soluble sodium is an important parameter in classifying irrigation water in terms of soil permeability [43]. Sodium ion present in irrigation water tends to be exchanged by Mg2+ and Ca2+ ions present in clay particles. This exchange process reduces the permeability of soil and causes poor internal drainage and hardening of soil, which further adversely affects the soil quality and seedling emergence [44]. Additionally, high levels of sodium encourage combination of sodium with chloride and carbonates generating salinity and alkalinity in soils. Excessive soil salinity and alkalinity are harmful for plant growth and crop productivity. The classification of irrigation water based on soluble sodium percentage (SSP) is given by Todd [45]. He classified the irrigation water quality into 5 categories (excellent, good, permissible, doubtful, and unsuitable). In the present study, the soluble sodium percentage varied from 0.3 to 35.4%, which suggested that all the groundwater samples had excellent to good quality for irrigation purpose (Table 4).


#### 3.7.3. Residual Sodium Carbonate (RSC)

The quantity of carbonate and bicarbonate surplus to that of alkaline Earth metal ions (Ca2+ and Mg2+) also influences the suitability of groundwater for irrigation purpose [37]. This surplus amount of carbonate and bicarbonate is called residual sodium carbonate (RSC). Higher RSC values indicate that much of the calcium and some magnesium ions get precipitated from the solution, and thus, the percentage of sodium increases in water and soil particles, which in turn increases the potential for sodium hazard. The RSC values of the collected water samples varied in between −4.92 and 0.72 meq L−1. Based on the RSC values, all samples were found to be safe for agriculture purpose (Table 5).Table 5
Classification of groundwater on the basis of RSC.
RSC (meq·L−1)
Quality
Hazards
Samples
<1.25
Good
Low with some removal calcium and magnesium from irrigation water
50 samples
1.25–2.50
Doubtful
Medium with appreciable removal of calcium and magnesium from irrigation water
>2.50
Unsuitable
High with most calcium and magnesium removed leaving sodium to accumulate


### 3.8. Magnesium Hazard (MH)

In the natural water system, magnesium and calcium maintain a state of equilibrium. High value of any one of the cations can increase soil pH and reduces infiltration capacity of soil, which adversely influences the crop yield. As the content of magnesium was found to be high in the collected samples, magnesium hazard was evaluated in this study. If the value of magnesium hazard is more than 50%, the soil becomes alkaline and its opposite impact on crop yield can be observed [46].According to Khodapanah et al., the water samples with MH values higher than the 50 are unsuitable for irrigation [36]. In the present study, MH values varied from 32 to 81, which indicated that 56% samples had MH values more than 50. In the study area, the elevated amount of magnesium might be due to dissolution of dolomite. In a study from Almora district [47], MH values of spring water varied from 0.39 to 38.37. Hence, these samples are observed to be unsuitable for irrigation (Table 4).


### 3.9. Permeability Index (PI)

On the basis of PI values, groundwater quality can be assessed for its suitability for irrigation purpose [48]. According to Singh et al., the concentration of Ca2+, Na+, Mg2+, and HCO3− influences permeability of soil profile [49]. Therefore, these cations and anions are used to calculate PI values of water to evaluate its quality. Xu et al. correlated high PI values with high amount of sodium and bicarbonate ions in groundwater [50]. The high levels of HCO3− and Na+ ions may be due the dissolution of carbonate from calcite and dolomite and the cation exchange process.Nagaraju et al. classified water quality on the basis of PI into Classes I, II, and III. Classes I and II indicate good water quality for irrigation purpose (>75% and 25-75% permeability respectively), while Class III (up to 25% permeability) water is unsuitable for irrigation [43]. A high permeability index is associated with subsurface structural features, which facilitate widespread contamination of groundwater. As per the PI values, the groundwater samples of the study area fall in Classes II (29.05-72.75%) and were described as having excellent to good permeability [51] (Table 4 and Figure 4).Figure 4
Permeability index diagram classification of groundwater quality.


### 3.10. Spatial Distribution Maps

Geographical information system (GIS) is the special tool which is used to create spatial distribution maps, indicating suitable and unsuitable zones based on water quality parameters [52]. In the present study, spatial distribution maps were drawn for EC, TH, SAR, SSP, MH, and PI.The spatial distribution map of EC is shown in Figure5. This indicated that more than half of the study area was alkaline in nature. The spatial distribution map of TH suggested that central part of the study area had the high TH value (Figure 6). SAR distribution map indicated that majority of the locations was within the excellent zone (SAR 0.5–1.0) (Figure 7). Figure 8 is the spatial distribution map of SSP. This map suggested that the SSP values of all the samples were excellent to good. The spatial distribution maps indicated that groundwater collected from the central part of the study area was rich in hardness and salinity along with some small patches in the western region. The spatial distribution map of MH is shown in Figure 9, which indicated that the eastern part of the study area is having very low MH values as compared to the western part of the study area. The spatial distribution map indicated that the western region of the study area had the highest PI value. Most of the study area showed permeability index in between 40 and 50% (Figure 10).Figure 5
Spatial distribution map of EC.Figure 6
Spatial distribution map of TH.Figure 7
Spatial distribution map of SAR.Figure 8
Spatial distribution map of SSP.Figure 9
Spatial distribution map of MH.Figure 10
Spatial distribution map of PI.


### 3.11. Hydrochemistry

#### 3.11.1. Piper and Durov Diagrams

Hydrochemical interpretation of the analysed samples has been attempted by plotting the data in the Piper and Durov [53] diagrams (Figure 11). In the Piper diagram, analysed chemical data are plotted in two triangular fields, which are ultimately projected into an upper diamond-shaped field. Similar groundwater samples can be identified using this diagram as they are plotted as a cluster. The data plots in the Piper diagram suggested that 50% samples were the Mg2+-Ca2+-HCO3− type along with 48% Ca2+–Mg2+-Cl−type and only two water samples belonged to the Ca-Na-HCO3 water type. The data plots in Piper diagram and Durov diagram revealed that cations were dominated by Mg2+ followed by Ca2+ and Na+, while anions were dominated by HCO3−, followed by Cl− and SO42− (Figure 11). The results of the study were similar to the reports on hydrogeochemical analysis of groundwater samples from India [54] and South Africa [55], where they observed that the alkaline earth metals were the dominant metal ions in groundwater samples. High levels of calcium may present naturally, but the dominance of sodium and magnesium ions is due to their dissolution from polluted rocks and soils [56].Figure 11
Classification of water samples according to (a) Piper and (b) Durov diagrams.
(a)
(b)


#### 3.11.2. Chloroalkaline Index

Scholler observed the change in the chemical composition of groundwater, and its flow can be represented by chloroalkaline indices CAI I and CAI II [28]. Positive value of chloroalkaline index revealed direct ion exchange between Na+ and K+ from water and Ca2+ and Mg2+ with the rocks. When the value of CAI is negative, ion exchange between Mg2+ and Ca2+ from water and Na+ and K+ with rocks happens. The resultant value of CAI I was lying in between −7.7824 and 6.8758 and CAI II −0.0790 and 6.8213 (Table 4). These values indicated that 70% studied area belonged to negative category and 30% felt in the positive zone. Thus, the findings clearly indicated that exchangeable cations can also be used to indicate the chemical composition of groundwater of the study area.


#### 3.11.3. Gibbs Diagram

Gibbs (1970) proposed a diagram for interpretation of the mechanism of major ion chemistry of groundwater samples [57]. The Gibbs diagram explains the three different fields, namely, precipitation dominance, evaporation dominance, and rock dominance. Gibbs ratio was calculated with the help of the following formula:(7)Gibbs ratio1anion=Cl−+NO3−Cl−+NO3−+HCO3−,Gibbs ratio2cation=Na++K+Na++K++Ca2+.The concentration of all ions was taken in meq L−1.Gibbs diagram was plotted in between Gibbs ratio (cation or anion) and total dissolved solid. In the present study area, the value of Gibbs ratio 1 ranged from 0.01 to 0.66 with an average value of 0.33. The value of Gibbs ratio 2 was in between 0.04 and 0.45 with an average value of 0.143 (Table4). From Figure 12, it can be interpreted that most of the samples belonged to the rock dominance area, representing the influence of the rocks on groundwater aquifer.Figure 12
Gibbs diagram for anion and cation against TDS.


## 3.1. pH

The term pH expressed to describe the intensity of acidic and alkaline nature of a solution. The pH value of the groundwater samples in the study area lie in between 7.57 and 8.61. All the groundwater samples belonged to the safe limit for irrigation purpose [29].


## 3.2. Water Quality Based on the Absolute Ions

In the present study area, the concentration of cations lies from 20.0 to 140.0 mg L−1 for Ca2+, 14.1 to 85.0 mg L−1 for Mg2+, 0.4 to 62.0 mg L−1 for Na+, and 0.0 to 55.2 mg L−1 for K+ (Table 2). In irrigation water, the permissible limit for Ca2+, Mg2+, Na+, and K+ is 80, 35, 200, and 30 mg L−1, respectively [30, 31]. On the basis of these permissible limits, 96% groundwater samples for Ca2+, 42% for Mg2+, 100% for Na+, and 100% for K+ were fit for irrigation purpose.Table 2
Chemical parameters of the collected water samples from Udham Singh Nagar district.
Sampling location
pH
EC (μS cm−1)
TH (mg·L−1)
Cl− (mg·L−1)
HCO
3
− (mg·L−1)
SO
4
2
− (mg·L−1)
NO
3
− (mg·L−1)
CO
3
2
− (mg·L−1)
Ca2+ (mg·L−1)
Mg2+ (mg·L−1)
Na+ (mg·L−1)
K+ (mg·L−1)
TDS (mg·L−1)
KU1
7.79
1131
444
127.0
338.3
82.7
19.39
0
58.8
72.2
62.0
27.0
735
KU2
7.99
1274
539
252.4
356.7
16.7
22.59
0
140.0
46.0
42.0
1.6
828
KU3
8.49
416
207
18.4
196.0
23.8
0.01
9
32.0
31.0
18.0
1.2
270
KU4
7.71
515
237
28.4
230.0
18.9
0.32
0
42.0
32.0
18.3
1.0
335
KU5
8.32
692
277
72.0
295.2
22.7
0.01
3
50.0
50.0
20.0
5.6
450
KU6
7.92
533
255
13.0
237.0
25.2
9.82
0
42.0
36.5
10.0
12.0
346
KU7
7.97
372
444
22.7
153.0
19.0
5.00
0
40.0
18.8
9.0
1.7
242
KU8
8.41
401
383
14.2
159.9
29.0
8.74
6
42.0
24.0
7.2
1.6
261
KU9
7.79
390
169
43.0
129.2
21.6
0.85
0
44.0
18.0
8.3
0.9
254
KU10
7.57
666
263
31.2
256.0
58.4
19.48
0
58.0
32.0
41.0
6.4
433
KU11
8.32
744
286
144.6
176.0
47.2
10.12
3
46.0
34.0
47.0
2.1
484
KU12
8.05
1022
335
113.4
316.0
66.9
54.66
0
38.0
85.0
12.5
0.0
664
KU13
8.22
810
400
51.1
322.0
40.9
0.48
0
82.0
40.0
34.0
1.1
527
KU14
8.16
401
275
34.0
162.5
16.4
0.07
0
50.0
14.1
12.0
1.3
261
KU15
8.45
545
339
28.4
245.0
0.2
0.06
9
28.0
47.0
8.4
0.7
354
KU16
8.36
645
280
26.0
279.0
28.2
1.34
3
52.0
38.0
23.4
9.5
419
KU17
8.57
705
350
35.5
166.1
124.7
0.73
12
60.0
45.0
24.8
1.4
458
KU18
7.97
850
504
76.6
325.0
43.8
0.64
0
30.0
79.0
19.8
1.3
440
KU19
7.79
766
275
70.9
228.0
86.4
5.54
0
52.0
35.2
31.5
12.3
498
KU20
8.4
955
239
14.2
291.0
150.0
19.47
3
70.0
40.0
39.5
55.2
621
KU21
7.86
750
275
22.7
360.0
19.3
45.97
0
54.0
35.2
30.0
12.4
488
KU22
8.39
755
200
14.18
372.0
37.7
5.50
3
48.0
55.9
13.6
0.8
491
KU23
8.25
710
360
19.85
237.0
78.1
0.07
0
50.0
35.2
37.6
12.4
462
KU24
8.35
645
290
17.01
322.0
39.2
0.02
3
46.0
38.0
12.6
1.1
419
KU25
8.06
481
224
19.85
173.0
57.7
5.23
0
56.0
24.2
12.4
0.7
313
KU26
7.94
530
285
14.18
241.0
30.0
3.79
0
60.0
30.4
0.4
0.0
345
KU27
8.33
460
259
11.34
233.7
8.7
5.73
3
40.0
24.3
16.3
1.3
299
KU28
7.76
741
240
8.5
229.0
150.4
0.00
0
48.0
58.3
11.9
1.3
482
KU29
8.38
635
190
28.36
288.0
30.2
0.12
6
60.0
34.0
12.0
1.3
413
KU30
8.3
614
165
25.52
274.0
52.6
1.13
0
36.0
32.6
29.7
1.1
399
KU31
8.15
602
200
25.52
233.0
49.6
0.08
0
40.0
45.0
19.4
1.5
391
KU32
8.32
487
200
70.9
187.0
1.4
0.15
3
32.0
28.3
16.1
1.2
317
KU33
8.6
611
261
17.01
233.0
19.4
29.00
15
40.0
38.7
31.4
1.3
397
KU34
8.11
579
260
34.04
187.0
52.3
0.22
0
56.0
24.3
30.0
1.5
376
KU35
7.95
390
220
19.85
172.0
11.2
0.56
0
44.0
19.4
9.8
1.6
254
KU36
7.87
353
436
25.52
150.0
8.8
5.04
0
38.0
17.0
7.5
0.9
229
KU37
8.08
392
155
25.52
157.0
11.7
6.36
0
36.0
26.7
7.5
0.8
255
KU38
8.23
413
200
19.85
190.7
6.0
0.15
0
40.0
24.3
11.9
1.3
268
KU39
8.59
690
215
130.45
180.0
5.9
0.07
12
46.0
35.6
18.6
11.3
449
KU40
8.23
540
240
14.18
258.3
17.6
4.58
0
52.0
31.6
11.0
0.6
351
KU41
8.13
576
230
19.85
249.0
6.8
37.12
0
56.0
19.4
34.4
1.3
374
KU42
7.75
920
198
130.45
258.0
55.8
0.18
0
94.0
48.8
15.3
1.0
598
KU43
8.61
467
221
28.36
196.8
1.3
2.48
12
20.0
25.5
38.5
1.0
304
KU44
8.04
555
160
24.81
264.5
1.6
0.37
0
46.0
20.7
48.5
1.0
361
KU45
8.42
520
159
11.34
246.0
27.9
9.19
6
38.0
29.2
20.8
1.5
338
KU46
8.45
600
349
28.36
233.0
33.0
13.00
6
52.0
26.7
41.8
0.8
390
KU47
8.46
540
360
34.03
215.2
6.6
7.13
6
36.0
34.0
22.1
1.0
351
KU48
8.2
520
165
22.68
283.0
5.4
0.12
0
48.0
19.0
24.1
0.4
338
KU49
8.16
560
198
24.1
313.0
0.4
4.14
0
42.0
28.2
19.3
1.5
364
KU50
8.55
395
221
28.3
161
0.2
0.12
0
30.0
20.6
24.3
1.2
257The permissible limit for anions HCO3− and Cl− is 250 mg L−1 [30, 31]. The values of HCO3− and Cl− in the groundwater samples varied from 29.2 to 372.0 mg L−1 and 8.2 to 252.4 mg L−1, respectively (Table 2). The results on major anions revealed that 64% water samples as per the limit of HCO3− and 98% as per the limit of Cl− were observed to be fit for irrigation purpose.


## 3.3. Total Hardness (TH)

In water quality, TH is an important parameter whether it has been used for domestic, irrigation, and industrial purpose. The presence of alkaline Earth metals causes hardness of water which prevents the lather with soap and increases the boiling point. Amount of calcium and magnesium ions in some of the collected samples was high. When calcium reacts with water, either CaCO3 is formed in the form of limestone and chalk, or CaSO4 is formed. The major source of Mg in groundwater is dolomite, CaMg(CO3)2. According to Sawyer and McCarthy (1967) [32], water can be categorized as soft (>75 mg L−1), moderately hard (75 to 150 mg L−1), hard (150 to 300 mg L−1), and very hard (above 300 mg L−1). In the present study, TH varied from 155 to 539 mg L−1, indicating hard to very hard nature of water. Thirty-nine samples had hard category, while 20% samples (11 samples) had hardness higher than 300 mg L−1, which is a desirable limit for drinking purpose (Table 2).


## 3.4. Salinity and Alkalinity Hazard (SAH)

The groundwater becomes saline if high salt content is present. The evaluation of salinity hazard is an important parameter of agriculture water as high salt content of irrigation water causes the soil to become saline, and it also adversely affects the salt intake efficiency of the plants. Electrical conductivity (EC) and total dissolved solid (TDS) values are measure of salinity hazard of irrigation water. In the present study, the values of EC and TDS ranged from 353 to 1274µS–1 cm−1 and 229 to 828 mg L−1, respectively (Table 2). According to the limiting value [33] of TDS for water suitability for irrigation purpose, 28% groundwater samples belonged to the moderate category. Furthermore, the classification and distribution of groundwater samples with respect to salinity (EC) is given in Table 3. The water samples were classified into four groups on the basis of salinity [34]. Irrigation water quality based on salinity indicated that no water sample belonged to the excellent category (C1). Eighty-six percent of the samples belonged to the C2 class, and remaining 14% was found in the C3 class. On the basis of salinity, none of the samples were observed to be unfit for irrigation purpose.Table 3
Classification and distribution of water quality based on salinity.
Level
Salinity (µS cm−1)
Hazards and limitation
Number of samples
C1
<250
Low hazards and no detrimental effects on the plants and no accumulation in soil is expected
No
C2
250–750
Stress can be shown by sensitive plants, and salt accumulation in soil can be prevented due to moderate leaching
43 samples
C3
750–2250
Most plants affected by salinity (salt-tolerant plants are needed), careful irrigation, good drainage, and leaching required
7 samples (KU1, KU2, KU12, KU19, KU20, KU21, and KU42)
C4
>2250
Unsuitable for irrigation except some highly salt-resistant plants, excellent drainage, frequent leaching, and intensive management required
-


## 3.5. United States Salinity Laboratory (USSL) Diagram

USSL diagram has been used to study the quality of groundwater suitability for irrigation purpose [35]. The SAR and EC values of water samples of Udham Singh Nagar District were plotted in the graphical representation (Figure 2) and found that 43 samples fall in C2S1 (medium salinity with low sodium category) and remaining 7 samples fall in C3S1 (high salinity and low sodium category). C3S1-type water cannot be used on soil with restricted drainage. Bhandari and Joshi (2013) reported that 98% of spring water samples from Almora district of Uttarakhand fall in C1S1, which indicated suitability of these samples for irrigation purpose [36].Figure 2
USSL salinity diagram indicating classification of water for irrigation.


## 3.6. Wilcox Diagram

Wilcox diagram is plotted for classification of water for irrigation suitability [37]. In this diagram, the EC was plotted against the percentage of Na. According to Wilcox classification, 86% of the water samples belonged to the excellent good category and remaining 14% groundwater samples fall in good category (Figure 3). Bahukhandi et al. [21] assessed ground and surface water quality of Hardwar district, Uttarakhand, and observed that, according to the US salinity diagram, most of the ground and surface water samples fall in C1S1 and C2S1 categories, while according to Wilcox diagram, large number of water samples was within excellent to good category [38].Figure 3
Wilcox diagram showing classification of water for irrigation on the basis of percent sodium and EC.


## 3.7. Sodium Hazard (SH)

### 3.7.1. Sodium Adsorption Ratio (SAR)

According to Gholami and Srikantaswamy [39], the alkali or sodium hazard can be expressed in terms of sodium adsorption ratio. Sodium hazard is the main parameter for assessment of groundwater suitability for irrigation purpose. Sodium-enriched groundwater is unsuitable for irrigation of agricultural lands. Biswas et al. [40] reported that excess sodium in water produces undesirable effect of changing soil permeability and water infiltration due to breakdown in the physical structure of the soil. In a previous study, the SAR values ranging from 0 to 10 were measured as excellent, 10–18 were measured as good, and values greater than 18 were measured as unsuitable for irrigation purpose [41]. In the present study, the SAR values ranged between 0.01 and 1.49 and, thus, were classified as the S1 level, which belonged to an excellent category for irrigation purpose (Table 4). Shahidullah et al. reported groundwater quality of Mymensingh district in Bangladesh and suggested that there was a linear relationship between sodium adsorption ratio (SAR) and soluble sodium percentage (SSP) and also observed that groundwater could be safely used for long-term irrigation purpose [42]. Dudeja et al. have also reported that the groundwater of Doon valley in outer Himalaya, Uttarakhand, had suitability for drinking and irrigation purpose [17]. Seth et al. studied that Kosi river water in Almora district, Uttarakhand, could not be used for drinking purpose, while it was found to be suitable for irrigation purpose on the basis of SAR, %Na, and RSC [20].Table 4
Calculated parameters of irrigation water quality.
Collection Sites
SAR
RSC
SSP
MH
PI
CAI I
CAI II
Gibbs 1
Gibbs 2
KU1
1.27
−3.33
27.6
67
43.66
2.6369
3.0698
0.60
0.27
KU2
0.78
−4.92
14.8
35
33.70
6.8758
6.8213
0.24
0.41
KU3
0.54
−0.63
16.4
61
52.24
−1.0530
0.2828
0.38
0.09
KU4
0.52
−0.96
14.8
56
49.56
−0.2270
0.5931
0.31
0.11
KU5
0.48
−1.67
13.3
62
41.05
1.5321
1.8314
0.34
0.20
KU6
0.27
−1.21
12.7
59
43.51
−1.6560
0.1922
0.34
0.05
KU7
0.29
−1.03
10.9
44
44.08
0.0401
0.4821
0.21
0.13
KU8
0.22
−1.25
8.0
49
44.98
0.4823
0.2825
0.17
0.08
KU9
0.27
−1.56
9.5
40
52.42
0.8963
1.0496
0.17
0.25
KU10
1.07
−1.33
26.1
48
52.45
1.3332
0.4910
0.45
0.11
KU11
1.28
−2.11
29.2
55
29.89
3.5656
3.4773
0.52
0.45
KU12
0.26
−3.71
5.8
79
42.62
3.0301
3.1164
0.25
0.26
KU13
0.77
−2.10
17.0
45
51.57
0.3935
1.1760
0.30
0.14
KU14
0.38
−0.99
13.2
32
42.09
0.3821
0.7633
0.21
0.17
KU15
0.22
−0.95
6.8
73
46.84
0.3209
0.7046
0.25
0.10
KU16
0.60
−1.05
18.1
55
35.12
−0.9856
0.4751
0.39
0.09
KU17
0.59
−3.57
14.3
81
35.78
−0.1145
0.7233
0.30
0.18
KU18
0.43
−2.67
10.1
53
48.13
1.7459
2.0054
0.41
0.19
KU19
0.82
−1.76
23.5
49
45.9
1.1576
1.6411
0.46
0.24
KU20
0.93
−1.91
25.6
52
54.14
−7.7824
−0.0790
0.57
0.05
KU21
0.78
0.31
22.5
66
40.36
−1.8956
0.3933
0.44
0.06
KU22
0.31
−0.79
8.0
54
51.31
−1.1301
0.3065
0.23
0.04
KU23
0.99
−1.51
25.6
58
47.67
−2.9227
0.1445
0.50
0.08
KU24
0.33
−0.04
9.6
42
41.79
−0.7210
0.3716
0.23
0.05
KU25
0.35
−1.95
10.4
45
36.39
−0.4352
0.4003
0.01
0.10
KU26
0.01
−1.54
0.3
50
56.68
−0.3561
0.3960
0.31
0.06
KU27
0.50
−0.06
15.7
67
31.85
−2.0005
0.1333
0.22
0.05
KU28
0.27
−3.44
7.1
48
42.68
−2.0577
0.1363
0.18
0.04
KU29
0.31
−0.87
8.7
60
59.12
0.1060
0.6898
0.46
0.09
KU30
0.86
0.01
22.8
65
42.80
−1.1137
0.4585
0.34
0.09
KU31
0.50
−1.87
13.4
69
53.00
−0.5056
0.5164
0.35
0.10
KU32
0.50
−0.76
21.3
61
50.73
1.6345
1.7628
0.45
0.27
KU33
0.84
−0.86
21.9
42
50.11
−2.4359
0.1563
0.36
0.07
KU34
0.84
−1.73
11.0
42
49.88
−0.4387
0.5884
0.21
0.15
KU35
0.31
−0.98
9.6
55
52.32
−0.2744
0.4011
0.18
0.10
KU36
0.25
−0.84
8.0
50
44.67
0.2347
0.5857
0.19
0.15
KU37
0.23
−1.42
12.1
56
50..45
−0.2343
0.5943
0.25
0.14
KU38
0.36
−0.87
17.4
50
41.88
−0.4283
0.3872
0.39
0.09
KU39
0.50
−1.87
8.7
36
44.72
3.3814
3.3154
0.18
0.42
KU40
0.30
−0.96
25.8
46
59.71
−0.8345
0.2894
0.39
0.05
KU41
1.01
−0.31
7.4
68
29.05
−2.1717
0.2230
0.15
0.07
KU42
0.32
−4.48
35.4
43
72.75
3.4920
3.5362
0.66
0.34
KU43
1.34
0.53
34.8
56
68.67
−1.3253
0.2749
0.52
0.13
KU44
1.49
0.34
18.0
46
56.02
−2.3510
0.2096
0.37
0.09
KU45
0.61
−0.06
27.7
61
57.06
−2.6284
0.1065
0.45
0.04
KU46
1.17
−0.77
17.7
39
51.10
−1.4983
0.3723
0.39
0.11
KU47
0.63
−0.87
21.1
53
63.96
−0.0681
0.6910
0.33
0.14
KU48
0.74
0.68
16.6
53
59.08
−1.0147
0.4144
0.34
0.07
KU49
0.56
0.72
25.4
57
63.05
−0.6411
0.5103
0.46
0.07
KU50
0.83
−0.16
0.3
43
29.05
−0.5642
0.3867
0.46
0.15


### 3.7.2. Soluble Sodium Percentage (SSP)

According to Nagarju et al., the percentage of soluble sodium is an important parameter in classifying irrigation water in terms of soil permeability [43]. Sodium ion present in irrigation water tends to be exchanged by Mg2+ and Ca2+ ions present in clay particles. This exchange process reduces the permeability of soil and causes poor internal drainage and hardening of soil, which further adversely affects the soil quality and seedling emergence [44]. Additionally, high levels of sodium encourage combination of sodium with chloride and carbonates generating salinity and alkalinity in soils. Excessive soil salinity and alkalinity are harmful for plant growth and crop productivity. The classification of irrigation water based on soluble sodium percentage (SSP) is given by Todd [45]. He classified the irrigation water quality into 5 categories (excellent, good, permissible, doubtful, and unsuitable). In the present study, the soluble sodium percentage varied from 0.3 to 35.4%, which suggested that all the groundwater samples had excellent to good quality for irrigation purpose (Table 4).


### 3.7.3. Residual Sodium Carbonate (RSC)

The quantity of carbonate and bicarbonate surplus to that of alkaline Earth metal ions (Ca2+ and Mg2+) also influences the suitability of groundwater for irrigation purpose [37]. This surplus amount of carbonate and bicarbonate is called residual sodium carbonate (RSC). Higher RSC values indicate that much of the calcium and some magnesium ions get precipitated from the solution, and thus, the percentage of sodium increases in water and soil particles, which in turn increases the potential for sodium hazard. The RSC values of the collected water samples varied in between −4.92 and 0.72 meq L−1. Based on the RSC values, all samples were found to be safe for agriculture purpose (Table 5).Table 5
Classification of groundwater on the basis of RSC.
RSC (meq·L−1)
Quality
Hazards
Samples
<1.25
Good
Low with some removal calcium and magnesium from irrigation water
50 samples
1.25–2.50
Doubtful
Medium with appreciable removal of calcium and magnesium from irrigation water
>2.50
Unsuitable
High with most calcium and magnesium removed leaving sodium to accumulate


## 3.7.1. Sodium Adsorption Ratio (SAR)

According to Gholami and Srikantaswamy [39], the alkali or sodium hazard can be expressed in terms of sodium adsorption ratio. Sodium hazard is the main parameter for assessment of groundwater suitability for irrigation purpose. Sodium-enriched groundwater is unsuitable for irrigation of agricultural lands. Biswas et al. [40] reported that excess sodium in water produces undesirable effect of changing soil permeability and water infiltration due to breakdown in the physical structure of the soil. In a previous study, the SAR values ranging from 0 to 10 were measured as excellent, 10–18 were measured as good, and values greater than 18 were measured as unsuitable for irrigation purpose [41]. In the present study, the SAR values ranged between 0.01 and 1.49 and, thus, were classified as the S1 level, which belonged to an excellent category for irrigation purpose (Table 4). Shahidullah et al. reported groundwater quality of Mymensingh district in Bangladesh and suggested that there was a linear relationship between sodium adsorption ratio (SAR) and soluble sodium percentage (SSP) and also observed that groundwater could be safely used for long-term irrigation purpose [42]. Dudeja et al. have also reported that the groundwater of Doon valley in outer Himalaya, Uttarakhand, had suitability for drinking and irrigation purpose [17]. Seth et al. studied that Kosi river water in Almora district, Uttarakhand, could not be used for drinking purpose, while it was found to be suitable for irrigation purpose on the basis of SAR, %Na, and RSC [20].Table 4
Calculated parameters of irrigation water quality.
Collection Sites
SAR
RSC
SSP
MH
PI
CAI I
CAI II
Gibbs 1
Gibbs 2
KU1
1.27
−3.33
27.6
67
43.66
2.6369
3.0698
0.60
0.27
KU2
0.78
−4.92
14.8
35
33.70
6.8758
6.8213
0.24
0.41
KU3
0.54
−0.63
16.4
61
52.24
−1.0530
0.2828
0.38
0.09
KU4
0.52
−0.96
14.8
56
49.56
−0.2270
0.5931
0.31
0.11
KU5
0.48
−1.67
13.3
62
41.05
1.5321
1.8314
0.34
0.20
KU6
0.27
−1.21
12.7
59
43.51
−1.6560
0.1922
0.34
0.05
KU7
0.29
−1.03
10.9
44
44.08
0.0401
0.4821
0.21
0.13
KU8
0.22
−1.25
8.0
49
44.98
0.4823
0.2825
0.17
0.08
KU9
0.27
−1.56
9.5
40
52.42
0.8963
1.0496
0.17
0.25
KU10
1.07
−1.33
26.1
48
52.45
1.3332
0.4910
0.45
0.11
KU11
1.28
−2.11
29.2
55
29.89
3.5656
3.4773
0.52
0.45
KU12
0.26
−3.71
5.8
79
42.62
3.0301
3.1164
0.25
0.26
KU13
0.77
−2.10
17.0
45
51.57
0.3935
1.1760
0.30
0.14
KU14
0.38
−0.99
13.2
32
42.09
0.3821
0.7633
0.21
0.17
KU15
0.22
−0.95
6.8
73
46.84
0.3209
0.7046
0.25
0.10
KU16
0.60
−1.05
18.1
55
35.12
−0.9856
0.4751
0.39
0.09
KU17
0.59
−3.57
14.3
81
35.78
−0.1145
0.7233
0.30
0.18
KU18
0.43
−2.67
10.1
53
48.13
1.7459
2.0054
0.41
0.19
KU19
0.82
−1.76
23.5
49
45.9
1.1576
1.6411
0.46
0.24
KU20
0.93
−1.91
25.6
52
54.14
−7.7824
−0.0790
0.57
0.05
KU21
0.78
0.31
22.5
66
40.36
−1.8956
0.3933
0.44
0.06
KU22
0.31
−0.79
8.0
54
51.31
−1.1301
0.3065
0.23
0.04
KU23
0.99
−1.51
25.6
58
47.67
−2.9227
0.1445
0.50
0.08
KU24
0.33
−0.04
9.6
42
41.79
−0.7210
0.3716
0.23
0.05
KU25
0.35
−1.95
10.4
45
36.39
−0.4352
0.4003
0.01
0.10
KU26
0.01
−1.54
0.3
50
56.68
−0.3561
0.3960
0.31
0.06
KU27
0.50
−0.06
15.7
67
31.85
−2.0005
0.1333
0.22
0.05
KU28
0.27
−3.44
7.1
48
42.68
−2.0577
0.1363
0.18
0.04
KU29
0.31
−0.87
8.7
60
59.12
0.1060
0.6898
0.46
0.09
KU30
0.86
0.01
22.8
65
42.80
−1.1137
0.4585
0.34
0.09
KU31
0.50
−1.87
13.4
69
53.00
−0.5056
0.5164
0.35
0.10
KU32
0.50
−0.76
21.3
61
50.73
1.6345
1.7628
0.45
0.27
KU33
0.84
−0.86
21.9
42
50.11
−2.4359
0.1563
0.36
0.07
KU34
0.84
−1.73
11.0
42
49.88
−0.4387
0.5884
0.21
0.15
KU35
0.31
−0.98
9.6
55
52.32
−0.2744
0.4011
0.18
0.10
KU36
0.25
−0.84
8.0
50
44.67
0.2347
0.5857
0.19
0.15
KU37
0.23
−1.42
12.1
56
50..45
−0.2343
0.5943
0.25
0.14
KU38
0.36
−0.87
17.4
50
41.88
−0.4283
0.3872
0.39
0.09
KU39
0.50
−1.87
8.7
36
44.72
3.3814
3.3154
0.18
0.42
KU40
0.30
−0.96
25.8
46
59.71
−0.8345
0.2894
0.39
0.05
KU41
1.01
−0.31
7.4
68
29.05
−2.1717
0.2230
0.15
0.07
KU42
0.32
−4.48
35.4
43
72.75
3.4920
3.5362
0.66
0.34
KU43
1.34
0.53
34.8
56
68.67
−1.3253
0.2749
0.52
0.13
KU44
1.49
0.34
18.0
46
56.02
−2.3510
0.2096
0.37
0.09
KU45
0.61
−0.06
27.7
61
57.06
−2.6284
0.1065
0.45
0.04
KU46
1.17
−0.77
17.7
39
51.10
−1.4983
0.3723
0.39
0.11
KU47
0.63
−0.87
21.1
53
63.96
−0.0681
0.6910
0.33
0.14
KU48
0.74
0.68
16.6
53
59.08
−1.0147
0.4144
0.34
0.07
KU49
0.56
0.72
25.4
57
63.05
−0.6411
0.5103
0.46
0.07
KU50
0.83
−0.16
0.3
43
29.05
−0.5642
0.3867
0.46
0.15


## 3.7.2. Soluble Sodium Percentage (SSP)

According to Nagarju et al., the percentage of soluble sodium is an important parameter in classifying irrigation water in terms of soil permeability [43]. Sodium ion present in irrigation water tends to be exchanged by Mg2+ and Ca2+ ions present in clay particles. This exchange process reduces the permeability of soil and causes poor internal drainage and hardening of soil, which further adversely affects the soil quality and seedling emergence [44]. Additionally, high levels of sodium encourage combination of sodium with chloride and carbonates generating salinity and alkalinity in soils. Excessive soil salinity and alkalinity are harmful for plant growth and crop productivity. The classification of irrigation water based on soluble sodium percentage (SSP) is given by Todd [45]. He classified the irrigation water quality into 5 categories (excellent, good, permissible, doubtful, and unsuitable). In the present study, the soluble sodium percentage varied from 0.3 to 35.4%, which suggested that all the groundwater samples had excellent to good quality for irrigation purpose (Table 4).


## 3.7.3. Residual Sodium Carbonate (RSC)

The quantity of carbonate and bicarbonate surplus to that of alkaline Earth metal ions (Ca2+ and Mg2+) also influences the suitability of groundwater for irrigation purpose [37]. This surplus amount of carbonate and bicarbonate is called residual sodium carbonate (RSC). Higher RSC values indicate that much of the calcium and some magnesium ions get precipitated from the solution, and thus, the percentage of sodium increases in water and soil particles, which in turn increases the potential for sodium hazard. The RSC values of the collected water samples varied in between −4.92 and 0.72 meq L−1. Based on the RSC values, all samples were found to be safe for agriculture purpose (Table 5).Table 5
Classification of groundwater on the basis of RSC.
RSC (meq·L−1)
Quality
Hazards
Samples
<1.25
Good
Low with some removal calcium and magnesium from irrigation water
50 samples
1.25–2.50
Doubtful
Medium with appreciable removal of calcium and magnesium from irrigation water
>2.50
Unsuitable
High with most calcium and magnesium removed leaving sodium to accumulate


## 3.8. Magnesium Hazard (MH)

In the natural water system, magnesium and calcium maintain a state of equilibrium. High value of any one of the cations can increase soil pH and reduces infiltration capacity of soil, which adversely influences the crop yield. As the content of magnesium was found to be high in the collected samples, magnesium hazard was evaluated in this study. If the value of magnesium hazard is more than 50%, the soil becomes alkaline and its opposite impact on crop yield can be observed [46].According to Khodapanah et al., the water samples with MH values higher than the 50 are unsuitable for irrigation [36]. In the present study, MH values varied from 32 to 81, which indicated that 56% samples had MH values more than 50. In the study area, the elevated amount of magnesium might be due to dissolution of dolomite. In a study from Almora district [47], MH values of spring water varied from 0.39 to 38.37. Hence, these samples are observed to be unsuitable for irrigation (Table 4).


## 3.9. Permeability Index (PI)

On the basis of PI values, groundwater quality can be assessed for its suitability for irrigation purpose [48]. According to Singh et al., the concentration of Ca2+, Na+, Mg2+, and HCO3− influences permeability of soil profile [49]. Therefore, these cations and anions are used to calculate PI values of water to evaluate its quality. Xu et al. correlated high PI values with high amount of sodium and bicarbonate ions in groundwater [50]. The high levels of HCO3− and Na+ ions may be due the dissolution of carbonate from calcite and dolomite and the cation exchange process.Nagaraju et al. classified water quality on the basis of PI into Classes I, II, and III. Classes I and II indicate good water quality for irrigation purpose (>75% and 25-75% permeability respectively), while Class III (up to 25% permeability) water is unsuitable for irrigation [43]. A high permeability index is associated with subsurface structural features, which facilitate widespread contamination of groundwater. As per the PI values, the groundwater samples of the study area fall in Classes II (29.05-72.75%) and were described as having excellent to good permeability [51] (Table 4 and Figure 4).Figure 4
Permeability index diagram classification of groundwater quality.


## 3.10. Spatial Distribution Maps

Geographical information system (GIS) is the special tool which is used to create spatial distribution maps, indicating suitable and unsuitable zones based on water quality parameters [52]. In the present study, spatial distribution maps were drawn for EC, TH, SAR, SSP, MH, and PI.The spatial distribution map of EC is shown in Figure5. This indicated that more than half of the study area was alkaline in nature. The spatial distribution map of TH suggested that central part of the study area had the high TH value (Figure 6). SAR distribution map indicated that majority of the locations was within the excellent zone (SAR 0.5–1.0) (Figure 7). Figure 8 is the spatial distribution map of SSP. This map suggested that the SSP values of all the samples were excellent to good. The spatial distribution maps indicated that groundwater collected from the central part of the study area was rich in hardness and salinity along with some small patches in the western region. The spatial distribution map of MH is shown in Figure 9, which indicated that the eastern part of the study area is having very low MH values as compared to the western part of the study area. The spatial distribution map indicated that the western region of the study area had the highest PI value. Most of the study area showed permeability index in between 40 and 50% (Figure 10).Figure 5
Spatial distribution map of EC.Figure 6
Spatial distribution map of TH.Figure 7
Spatial distribution map of SAR.Figure 8
Spatial distribution map of SSP.Figure 9
Spatial distribution map of MH.Figure 10
Spatial distribution map of PI.


## 3.11. Hydrochemistry

### 3.11.1. Piper and Durov Diagrams

Hydrochemical interpretation of the analysed samples has been attempted by plotting the data in the Piper and Durov [53] diagrams (Figure 11). In the Piper diagram, analysed chemical data are plotted in two triangular fields, which are ultimately projected into an upper diamond-shaped field. Similar groundwater samples can be identified using this diagram as they are plotted as a cluster. The data plots in the Piper diagram suggested that 50% samples were the Mg2+-Ca2+-HCO3− type along with 48% Ca2+–Mg2+-Cl−type and only two water samples belonged to the Ca-Na-HCO3 water type. The data plots in Piper diagram and Durov diagram revealed that cations were dominated by Mg2+ followed by Ca2+ and Na+, while anions were dominated by HCO3−, followed by Cl− and SO42− (Figure 11). The results of the study were similar to the reports on hydrogeochemical analysis of groundwater samples from India [54] and South Africa [55], where they observed that the alkaline earth metals were the dominant metal ions in groundwater samples. High levels of calcium may present naturally, but the dominance of sodium and magnesium ions is due to their dissolution from polluted rocks and soils [56].Figure 11
Classification of water samples according to (a) Piper and (b) Durov diagrams.
(a)
(b)


### 3.11.2. Chloroalkaline Index

Scholler observed the change in the chemical composition of groundwater, and its flow can be represented by chloroalkaline indices CAI I and CAI II [28]. Positive value of chloroalkaline index revealed direct ion exchange between Na+ and K+ from water and Ca2+ and Mg2+ with the rocks. When the value of CAI is negative, ion exchange between Mg2+ and Ca2+ from water and Na+ and K+ with rocks happens. The resultant value of CAI I was lying in between −7.7824 and 6.8758 and CAI II −0.0790 and 6.8213 (Table 4). These values indicated that 70% studied area belonged to negative category and 30% felt in the positive zone. Thus, the findings clearly indicated that exchangeable cations can also be used to indicate the chemical composition of groundwater of the study area.


### 3.11.3. Gibbs Diagram

Gibbs (1970) proposed a diagram for interpretation of the mechanism of major ion chemistry of groundwater samples [57]. The Gibbs diagram explains the three different fields, namely, precipitation dominance, evaporation dominance, and rock dominance. Gibbs ratio was calculated with the help of the following formula:(7)Gibbs ratio1anion=Cl−+NO3−Cl−+NO3−+HCO3−,Gibbs ratio2cation=Na++K+Na++K++Ca2+.The concentration of all ions was taken in meq L−1.Gibbs diagram was plotted in between Gibbs ratio (cation or anion) and total dissolved solid. In the present study area, the value of Gibbs ratio 1 ranged from 0.01 to 0.66 with an average value of 0.33. The value of Gibbs ratio 2 was in between 0.04 and 0.45 with an average value of 0.143 (Table4). From Figure 12, it can be interpreted that most of the samples belonged to the rock dominance area, representing the influence of the rocks on groundwater aquifer.Figure 12
Gibbs diagram for anion and cation against TDS.


## 3.11.1. Piper and Durov Diagrams

Hydrochemical interpretation of the analysed samples has been attempted by plotting the data in the Piper and Durov [53] diagrams (Figure 11). In the Piper diagram, analysed chemical data are plotted in two triangular fields, which are ultimately projected into an upper diamond-shaped field. Similar groundwater samples can be identified using this diagram as they are plotted as a cluster. The data plots in the Piper diagram suggested that 50% samples were the Mg2+-Ca2+-HCO3− type along with 48% Ca2+–Mg2+-Cl−type and only two water samples belonged to the Ca-Na-HCO3 water type. The data plots in Piper diagram and Durov diagram revealed that cations were dominated by Mg2+ followed by Ca2+ and Na+, while anions were dominated by HCO3−, followed by Cl− and SO42− (Figure 11). The results of the study were similar to the reports on hydrogeochemical analysis of groundwater samples from India [54] and South Africa [55], where they observed that the alkaline earth metals were the dominant metal ions in groundwater samples. High levels of calcium may present naturally, but the dominance of sodium and magnesium ions is due to their dissolution from polluted rocks and soils [56].Figure 11
Classification of water samples according to (a) Piper and (b) Durov diagrams.
(a)
(b)


## 3.11.2. Chloroalkaline Index

Scholler observed the change in the chemical composition of groundwater, and its flow can be represented by chloroalkaline indices CAI I and CAI II [28]. Positive value of chloroalkaline index revealed direct ion exchange between Na+ and K+ from water and Ca2+ and Mg2+ with the rocks. When the value of CAI is negative, ion exchange between Mg2+ and Ca2+ from water and Na+ and K+ with rocks happens. The resultant value of CAI I was lying in between −7.7824 and 6.8758 and CAI II −0.0790 and 6.8213 (Table 4). These values indicated that 70% studied area belonged to negative category and 30% felt in the positive zone. Thus, the findings clearly indicated that exchangeable cations can also be used to indicate the chemical composition of groundwater of the study area.


## 3.11.3. Gibbs Diagram

Gibbs (1970) proposed a diagram for interpretation of the mechanism of major ion chemistry of groundwater samples [57]. The Gibbs diagram explains the three different fields, namely, precipitation dominance, evaporation dominance, and rock dominance. Gibbs ratio was calculated with the help of the following formula:(7)Gibbs ratio1anion=Cl−+NO3−Cl−+NO3−+HCO3−,Gibbs ratio2cation=Na++K+Na++K++Ca2+.The concentration of all ions was taken in meq L−1.Gibbs diagram was plotted in between Gibbs ratio (cation or anion) and total dissolved solid. In the present study area, the value of Gibbs ratio 1 ranged from 0.01 to 0.66 with an average value of 0.33. The value of Gibbs ratio 2 was in between 0.04 and 0.45 with an average value of 0.143 (Table4). From Figure 12, it can be interpreted that most of the samples belonged to the rock dominance area, representing the influence of the rocks on groundwater aquifer.Figure 12
Gibbs diagram for anion and cation against TDS.


## 4. Conclusions

The groundwater of Udham Singh Nagar district was alkaline and hard to very hard in nature. The values plotted on the USSL diagram suggested that the groundwater samples belonged to C2S1 and C3S1 categories, indicating medium to high salinity and low sodium hazard. The Wilcox diagram suggested that most of the groundwater samples fall in excellent to good category, and some water samples belonged to good category. On the basis of SAR, RSC, SSP, and PI, all the groundwater samples were observed to be suitable for irrigation purpose. Based on the MH values, 54% groundwater samples were found to be unsuitable for irrigation purpose. The most dominated cation was Ca2+ followed by Mg2+, Na+, and K+, while the order of domination of anions was HCO3− > Cl− > SO42− > NO3– > CO32−. Predominance of cations such as magnesium and calcium in the groundwater indicated pollution to anthropogenic activities. All the groundwater samples showed simple mixing of ions as no ion is predominant.



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*Source: 6924026-2020-03-21.xml*