Understanding of the aquifer hydraulic properties and hydrochemical characteristics of water is crucial for management plan and study skims in the target area, and flow motions and chemical species of groundwater are regarded as precious information on the geological history of the aquifers and the suitability of various usages. Cations and anions of groundwater are used to estimate the characteristics and origin of groundwater. In this study, we try to evaluate the quality of groundwater based on the comparison of the physiochemical characteristics and distribution of cations and anions in groundwater from rural areas. Therefore we focused on the evaluation of groundwater as some specific purposes such as agricultural and industrial use, general types of groundwater, lithological origin of chemical component in groundwater. In this point of view, major objectives of this study were grouped as following three categories: 1) quality assessment of groundwater as a special usage (agricultural, industrial); 2) determination of groundwater types; 3) tracing of ion sources of groundwater. The quality of agricultural water was evaluated using SAR, sodium (%), RSC, PI, SSP, MH, PS, and Kelly’s ratio, and was classified as SAR (Excellent (100%)), Sodium ((Excellent (34%), Good (55%), Permissible (9%), Doubtful (1.6%), Unsuitable (0.4%)), RSC (Good (95.7%), Medium (3.5%), Bad (0.8%)), PI((Excellent (40.6%), Good (59%), Unsuitable (0.4%)), SSP ((Excellent (26.3%), Good (59.8%), Fair (13.1%), Poor (0.8%)), MH ((Acceptable (94.4%), Non-Acceptable (5.6%)), Kelly’s Ratio ((Permissible (93%), Non-Permissible (7%)), PS ((Excellent to Good (98%), Good to Injurious (1.2%), and Injurious to Unsatisfactory (0.2%)). Evaluation based on the Wilcox diagram was classified as “excellent to good” or “good to permissible”, and the water quality evaluated using the U.S. salinity Laboratory’s Diagram was classified as C1S1 (Excellent/Excellent) and C2S1 (Good/Excellent). And, in the applications of two factors of Langelier Saturation Index (LSI) and Corrosive ratio (CR), we could get similar results for defining the suitabilities of groundwater for the industrial purpose. And the groundwater samples were also classified groundwater using the Piper diagram and estimated the origin of ions using the Gibbs and Chadah diagram, and the classifications based on the Piper diagram showed that the types of the groundwater are type and type. And, estimation of dominance type (evaporation, rock, precipitation) based on the Gibbs diagram showed that the origin of anion and cation in groundwater are from the rock-dominance, and the estimation of origin of anions using the Chadha diagram showed that the most of the ionic species was originated from the interactions between alkaline earths and alkali metals contained in the soil. And through the source-rock deduction followed by the comparison of Gibbs and Chadah diagram, it was shown that the chemical components in the groundwater were mostly induced from the water-rock deduction and major types of groundwater samples following the Chadah diagram were categorized such as following group types: dolomite type, gypsum type, alkaline and alkaline earth type.
Water is not only the essence of life but also one of the most crucial factors determining the quality of life of the people. The climate change and increasing disruptions in the rainfall patterns, temperature and soil moisture directly impacted the water availability and its quality for drinking, livestock use, agriculture and various other purposes, and in this respect, the latest patterns of climate changes and water deficit reflected the depletion of water sources and deterioration of water quality in many parts of the world [
In this study, many assessing methods of groundwater using specific purposes were carried out for agricultural purposes, industrial usages and deduction of water-rock interactions. The assessment of groundwater for agricultural purpose was done by using SAR (Sodium Adsorption Ratio), Na(%), RSC (Residual Sodium Carbonate), PI (Permeability Index), SSP (Soluble Sodium Percent), MH (Magnesium Hazard), KR (Kelly’s Ratio) and PS (Potential soil Salinity). The Wilcox diagram based on Na (%) and electrical conductivity, as well as the U.S. salinity Laboratory’s Diagram based on SAR and electrical conductivity, is also used to evaluate water quality for agricultural usage [
The overall objective of most groundwater sampling is to collect samples that are representative, that is, samples that accurately reflect in situ groundwater conditions in the formation of interest at the site under investigation. A representative ground-water sample must reflect the physical and chemical properties of the groundwater in that portion of formation open to the well to be samples. Therefore, many investigators have acknowledge the difficulty of obtaining samples that are truly representative of subsurface conditions [
In this study, all samples were collected for two different seasons representing (Pre-monsoon/PRM (June) and Post-monsoon/POM (July-November) to broadly cover the seasonal variations. A total of 486 (Pre-monsoon; 206 samples, Post- monsoon; 280 samples) groundwater samples were collected in one liter acid washed, well rinsed low density polyethylene bottles with inside stopper from bore wells and analyzed for chemical parameters following the guidelines. The samples were collected after pumping the wells for enough time of 15 - 20 min, and by subsequent filtering through 0.45 um membranes. The analyzed parameters include the activity of hydrogen ion concentration (pH), electrical conductivity (EC), total hardness(TH), total dissolved solids (TDS) and cation groups like Calcium (Ca2+), magnesium (Mg2+), sodium (Na+), potassium(K+) and anion groups like bicarbonate (
Many parameters are used to define irrigation water quality, to assess salinity hazards, and to determine appropriate management strategies. A complete water quality analysis will include the determination of such as following factors: 1) the total concentration of soluble salts; 2) the relative proportion of sodium to the other cations; 3) the bicarbonate concentration as related to the concentration of calcium and magnesium; 4) the concentration of specific elements and compounds. Therefore, the amounts and combinations of these substances define the suitability water for irrigation and the potential for plant toxicity. In most
Items | anion | cation |
---|---|---|
Column | Ion Pac AS12A (25 cm(L.), 4 mm × 250 mm | Ion Pac CS12A, 4 mm × 250 mm |
Eluent | 3.5 mM sodium carbonate + 1.0 mM sodium-bicarbonate | Methanesulfonic acid 20 mM |
Velocity of eluent | 1.2 mL/min. | 1.0 mL/min |
Injection volume | 50 uL | 50 uL |
Detector | Electric conductivity detector | Electric conductivity detector |
irrigation situations, the primary water quality concern is salinity levels, since salts can affect both the soil structure and crop yield. But, a number of trace elements are found in water which can limit its use for irrigations. In this point of view, in this study we focused on the property and suitability of groundwater for irrigation of farm fields and rice fields, so most of the sampling sites are located in the rural area of middle and southern province of Korea. As we mentioned, irrigation waters pumped from wells contain considerable chemical constituents derived from natural soil environment and man activities that may influence crop yield and soil fertilities [
SAR (Sodium adsorption ratio)
Sodium adsorption ratio also expressed as sodium content or alkali hazard is very important for determining the quality of water used for irrigation purposes.
Items | Equations | Classifications | References |
---|---|---|---|
SAR | Excellent, Good, Permissible, Doubtful | Richards (1954) | |
Na (%) | Excellent, Good, Permissible, Doubtful, Unsuitable | Wilcox (1954) | |
RSC | Good, Medium, Bad | Richards (1954) | |
PI | Excellent, Good, Unsuitable | Doneen (1964) | |
SSP | Excellent, Good, Fair, poor | Joshi (2009) | |
MH | Suitable, Unsuitable | Paliwal (1972) | |
Kelly’s Ratio | Permissible, Non-Permissible | Kelly (1963) | |
PS | Excellent to Good, Good to Injurious, Injurious to Unsatisfactory | Doneen (1954, 1962) |
Higher salinity reduces the osmotic activity of plants and prevents water from reaching the branches and leaves of plants resulting in inferior production [
Na (%)
Sodium is an important ion used for the classification of irrigation water due to its reaction with soil that reduces its permeability. Percentage of Na+ is widely used for assessing the suitability of water for irrigation purposes [
RSC (Residual Sodium Carbonate)
The sum of carbonate and bicarbonate over the sum of calcium and magnesium in water influences the fit of ground-water for irrigation purposes. An excess sodium bicarbonate and carbonate influence the physical properties of soil by dissolution of organic matter in soil that leaves a black stain on its surface on drying [
PI (Permeable Index)
The permeability of soil is influenced by sodium, calcium, magnesium and bicarbonate contents in soil which also influences the quality of irrigation water on long term use. Doneen [
SSP (Soluble sodium percentage)
Soluble Sodium Percentage (SSP) is also used for assessment of irrigation water quality, as an important factor to study the sodium hazard. SSP is defined as the ration of sodium the total cation multiplied by 100. High sodium (Na+) percentage can decrease soil permeability and inhibit plant growth.
MH (Magnesium Hazard)
The Ca2+ and Mg2+ ions maintain a state of equilibrium in most groundwater [
Kelly’s Ratio (KR)
Kelly’s Ratio is used for the classification of water for irrigation purposes. A KI (>1) shows an excess of sodium and KI (<2) signifies its deficit in waters [
PS (Potential Salinity)
Doneen [
Water is considered safe for industrial use if it is neither scale-forming nor scale-removing in nature. The water saturation index is used to assess whether water is precipitating out, dissolving or in equilibrium with calcium carbonate. Indices like LSI, and CR has been calculated to understand groundwater industrial suitability and each equation (all units are in mg/l) are such as followings [
where pHw = measured pH, and
The characteristics of cations and anions in groundwater represent the unique physiochemical characteristics caused by the groundwater’s interaction with rock and soil while flowing in the aquifer. The aquifer represents the characteristics of water bodies with different chemical compositions. Therefore, such characteristics are called the hydrochemical facies of groundwater. The hydrochemical facies is known to be affected by the rocks of the aquifer and the flow of groundwater, and groundwater can be classified using the Piper diagram using the distribution of cations and anions. In this study, we used the Piper diagram which is a major method for classifying groundwater to classify the samples for each sampling period and purposes of groundwater. In addition, the distribution of anions (
Piper diagrams are a combination of anion and cation triangles that lie on a common baseline. Adjacent sides of two triangles are the 60˚ apart. A diamond shape between them is used to replot of the analyses as circles whose areas are proportional to their TDS. The position of an analysis that is plotted on a piper diagram can be used to make tentative conclusion as to the origin of the water represented by the analysis. The study of Piper’s 1944 paper is strongly recommended for anyone using plots extensively.
Gibbs diagram is used to interpret the effect of hydrogeochemical processes such as precipitation, rock-water interaction mechanism and evaporation on ground- water geochemistry. The reaction between groundwater and aquifer minerals has a significant role in groundwater quality which is useful to assume the genesis of water. Gibbs ratio is calculated using the following equation.
Chadah diagram [
In this study, pH, electrical conductivity (EC), dissolved oxygen (DO), and oxidation-reduction potential (ORP) were measured on site. As we mentioned about of the objectives of this paper, Groundwater samples were classified based on their use as agricultural, residential, and drinking water, and was also classified as pre-monsoon and post-monsoon based on the time of sampling. The data of on-site measurements were shown that the ranges of electrical conductivities were 56 - 1885 μs/cm for agricultural water, 24 - 511 μs/cm residential water, 51 - 959 μs/cm drinking water, and 193 - 241 μs/cm for industrial water. These show that the electrical conductivity range of agricultural water is broader than that of groundwater for other purposes, and that the electrical conductivity ranges of industrial water are also slightly broader than that of groundwater for residential or drinking purposes. The dissolved oxygen was 0.6 - 10.0 mg/L for agricultural water, 0.3 - 11.0 mg/L for residential water, 0.5 - 10.9 mg/L for drinking water with an average of 5.5 mg/L, and 3.5 - 4.5 mg/L for industrial water. The monthly average dissolved oxygen was 7.2 mg/L for June, 5.6 mg/L for July, 3.8 mg/L for September, 4.9 mg/L for October, and 6.2 mg/L for November. This shows that the DO is low in September, which is immediately after summer, and the maximum DO in September was 6.1 mg/L, which is lower than that of June and November. The results also showed that the oxidation-reduction potential is −19 - 244 mV with a monthly average of 181.6 mV for June, 166.8 mV for July, 186.2 mV for September, 211.4 mV for October, and 210.7 mV for November. Little differences can be seen between each month, even though the ORP showed an increase after July.
In this study, we make an attempt to compare the distribution of four cations, Na+, Ca2+, K+, Mg2+ and focusing on the evaluation of groundwater quality
Items Usage | pH | EC (μS/cm) | DO (mg/L) | ORP (mV) | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Ave. | Min. | Max. | Ave. | Min. | Max. | Ave. | Min. | Max. | Ave. | Min. | Max. | ||
Jun. (n = 206) | Agricultural | 7.1 | 6.5 | 8.6 | 201 | 69 | 697 | 7.1 | 3.4 | 10 | 170 | 0 | 235 |
Living | 6.3 | 6.3 | 8.8 | 68 | 68 | 433 | 2.2 | 2.2 | 10 | 90 | 90 | 271 | |
Drinking | 6.9 | 6.1 | 7.9 | 182 | 51 | 959 | 7.2 | 2.3 | 10.9 | 183.5 | 88 | 301 | |
Ave. | 7.0 | 6.1 | 8.8 | 181 | 51 | 959 | 7.2 | 2.2 | 10.9 | 181.6 | 0 | 301 | |
Jul. (n = 33) | Agricultural | 7.0 | 6.5 | 7.9 | 199 | 78 | 446 | 5.3 | 4.7 | 6 | 152.1 | 57 | 233 |
Living | 7.3 | 6.5 | 8.3 | 178 | 75 | 354 | 5.9 | 4.7 | 11 | 176.5 | 30 | 258 | |
Drinking | 7.3 | 6.4 | 8.2 | 164 | 76 | 447 | 5.4 | 4.6 | 6.3 | 165.2 | 45 | 224 | |
Ave. | 7.2 | 6.4 | 8.3 | 180 | 75 | 447 | 5.6 | 4.6 | 11 | 166.8 | 30 | 258 | |
Sep. (n = 194) | Agricultural | 7.0 | 6.2 | 8.4 | 199 | 56 | 1033 | 3.8 | 0.6 | 5.4 | 180.9 | 58 | 232 |
Living | 6.9 | 6.1 | 7.6 | 157 | 24 | 455 | 3.8 | 0.3 | 6.1 | 188.6 | 69 | 270 | |
Drinking | 6.9 | 6.3 | 7.7 | 153 | 58 | 334 | 3.6 | 0.5 | 5.8 | 184 | 54 | 233 | |
Industrial | 7.1 | 6.9 | 7.2 | 193 | 151 | 241 | 3.9 | 3.5 | 4.5 | 224.7 | 210 | 235 | |
Ave. | 6.9 | 6.1 | 8.4 | 164 | 24 | 1033 | 3.8 | 0.3 | 6.1 | 186.2 | 54 | 270 | |
Oct. (n = 33) | Agricultural | 6.8 | 6.6 | 7 | 338 | 203 | 474 | 4.7 | 4.3 | 5.1 | 223.8 | 204 | 244 |
Living | 7.2 | 6.8 | 7.8 | 203 | 112 | 511 | 4.9 | 3.1 | 5.3 | 206 | 163 | 245 | |
Drinking | 7.2 | 6.8 | 7.6 | 147 | 79 | 252 | 4.9 | 4.6 | 5.3 | 213.1 | 146 | 243 | |
Ave. | 7.2 | 6.6 | 7.8 | 194 | 79 | 511 | 4.9 | 3.1 | 5.3 | 211.4 | 146 | 245 | |
Nov. (n = 17) | Agricultural | 7.7 | 7.1 | 8.4 | 1053 | 220 | 1885 | 5.3 | 3.2 | 7.3 | 26.5 | −19 | 72 |
Living | 7.7 | 6.2 | 8.5 | 242 | 82 | 383 | 6.5 | 4.9 | 7.9 | 192.1 | 91 | 289 | |
Drinking | 7.8 | 7.6 | 8 | 219 | 125 | 357 | 6.1 | 3.6 | 7.5 | 300 | 163 | 460 | |
Ave. | 7.7 | 6.2 | 8.5 | 329 | 82 | 1885 | 6.2 | 3.2 | 7.9 | 210.7 | −19 | 460 | |
Usage (n = 483) | Agricultural | 7.1 | 6.2 | 8.6 | 226 | 56 | 1885 | 5.4 | 0.6 | 10 | 171.8 | −19 | 244 |
Living | 7.0 | 6.1 | 8.8 | 172 | 24 | 511 | 5.6 | 0.3 | 11 | 187.3 | 30 | 289 | |
Drinking | 7.0 | 6.1 | 8.2 | 168 | 51 | 959 | 5.5 | 0.5 | 10.9 | 189.1 | 45 | 460 | |
Industrial | 7.1 | 6.9 | 7.2 | 193 | 151 | 241 | 3.9 | 3.5 | 4.5 | 224.7 | 210 | 235 | |
Ave. | 7.0 | 6.1 | 8.8 | 180 | 24 | 1885 | 5.5 | 0.3 | 11 | 185.5 | −19 | 460 | |
Seasonal (483) | Pre-monsoon | 7.0 | 6.1 | 8.8 | 181 | 51 | 959 | 7.2 | 2.2 | 10.9 | 181.6 | 0.0 | 301 |
Post-monsoon | 7.0 | 6.1 | 8.5 | 179 | 24 | 1885 | 43 | 0.3 | 11.0 | 1884 | −19 | 460 |
described in sampling period and groundwater usages. The results showed to be 17.51 - 68.77 mg/L and 17.63 - 178.8 mg/L for Na+, 2.4 - 40.99 mg/L and 3.79 - 124.4 mg/L for K+, 8.08 - 60.34 mg/L and 6.48 - 62.03 mg/L for Mg2+, and 36.82 - 229.94 mg/L and 33.65 - 189.4 mg/L for Ca2+ in cation groups. The distribution characteristics for groundwater water usages showed that cation concentrations were high in agricultural water while other results were slightly high in October and November comparing the data of June, July, and September. All of the data of cation groups are shown in
Items Usage | Na+ | Ca2+ | K+ | Mg2+ | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Ave. | Min. | Max. | Ave. | Min. | Max. | Ave. | Min. | Max. | Ave. | Min. | Max. | ||
Jun. (n = 206) | Agricultural | 18.93 | 4.27 | 63.61 | 42.79 | 5.54 | 193.81 | 2.21 | 0.39 | 13.42 | 9.56 | 2.46 | 60.34 |
Living | 0.59 | 0.59 | 62.11 | 2.66 | 2.66 | 164.22 | 0.36 | 0.36 | 40.99 | 0.55 | 0.55 | 46.15 | |
Drinking | 17.82 | 4.97 | 68.77 | 38.7 | 6.67 | 229.94 | 1.90 | 0.00 | 35.65 | 7.98 | 0.81 | 37.84 | |
Ave. | 17.51 | 0.59 | 68.77 | 36.82 | 2.66 | 229.94 | 2.40 | 0.00 | 40.99 | 8.08 | 0.55 | 60.34 | |
Jul. (n = 33) | Agricultural | 21.56 | 11.28 | 51.7 | 45.62 | 13.53 | 102.81 | 8.19 | 2.55 | 19.49 | 4.25 | 0.76 | 20.07 |
Living | 15.58 | 4.97 | 34.78 | 26.72 | 12.51 | 57.02 | 4.61 | 0.72 | 9.59 | 2.94 | 0.37 | 18.4 | |
Drinking | 16.36 | 6.13 | 54.91 | 28.77 | 7.78 | 64.81 | 4.00 | 1.02 | 6.68 | 3.81 | 0.61 | 12.57 | |
Ave. | 17.43 | 4.97 | 54.91 | 32.43 | 7.78 | 102.81 | 5.42 | 0.72 | 19.49 | 3.54 | 0.37 | 20.07 | |
Sep. (n = 194) | Agricultural | 21 | 1.95 | 178.15 | 36.29 | 4.36 | 189.4 | 3.03 | 0.21 | 10.87 | 9.89 | 1.01 | 62.03 |
Living | 14.82 | 0.92 | 77.83 | 1.9 | 3.39 | 117.41 | 2.89 | 0.23 | 23.68 | 5.96 | 0.31 | 21.19 | |
Drinking | 16.12 | 3.27 | 55.77 | 30.57 | 7.72 | 87.08 | 1.56 | 0.4 | 8.99 | 6.16 | 1.05 | 23.37 | |
Industrial | 21.79 | 9.85 | 32.19 | 32.77 | 19.59 | 43.57 | 3.06 | 2.72 | 3.3 | 7.75 | 3.57 | 14.97 | |
Ave. | 16.51 | 0.92 | 178.15 | 32.23 | 3.39 | 189.4 | 2.45 | 0.21 | 23.68 | 6.74 | 0.31 | 62.03 | |
Oct. (n = 33) | Agricultural | 69 | 5.6 | 178.7 | 60.83 | 20.9 | 147 | 34.5 | 1.9 | 124.4 | 24.18 | 11.2 | 35.4 |
Living | 18.94 | 5.7 | 41.7 | 41.64 | 12.5 | 125.4 | 5.74 | 0.4 | 23.4 | 6.83 | 1.3 | 14.5 | |
Drinking | 16.31 | 7.5 | 55.8 | 27.03 | 9.06 | 51.1 | 1.28 | 0.3 | 5.6 | 4.41 | 1 | 12.6 | |
Ave. | 23.81 | 5.6 | 178.7 | 37.32 | 9.06 | 147 | 7.2 | 0.3 | 124.4 | 7.83 | 1 | 35.4 | |
Nov. (n = 17) | Agricultural | 28.97 | 5.89 | 52.04 | 73.53 | 32.87 | 114.18 | 37.42 | 1.93 | 72.9 | 20.53 | 12.68 | 28.37 |
Living | 22.04 | 5.85 | 51.37 | 46 | 13.31 | 138.89 | 7.75 | 0.47 | 34.38 | 5.68 | 0.29 | 15.65 | |
Drinking | 10.86 | 4.83 | 16.58 | 34.29 | 25.25 | 40.1 | 2.23 | 0.45 | 5.85 | 3.72 | 0.29 | 8.82 | |
Ave. | 18.91 | 4.83 | 52.04 | 45.1 | 13.31 | 138.89 | 9.29 | 0.45 | 72.9 | 6.74 | 0.29 | 28.37 | |
Usage (n = 483) | Agricultural | 22.65 | 1.95 | 178.7 | 41.98 | 4.36 | 193.81 | 5.53 | 0.21 | 124.4 | 10.09 | 0.76 | 62.03 |
Living | 16.21 | 0.59 | 77.83 | 33.09 | 2.66 | 164.22 | 3.42 | 0.23 | 40.99 | 6.48 | 0.29 | 46.15 | |
Drinking | 16.75 | 3.27 | 68.77 | 34.02 | 6.67 | 229.94 | 1.84 | 0.00 | 35.65 | 6.65 | 0.29 | 37.84 | |
Industrial | 21.79 | 9.85 | 32.19 | 32.77 | 19.59 | 43.57 | 3.06 | 2.72 | 3.3 | 7.75 | 3.7 | 14.92 | |
Ave. | 17.58 | 0.59 | 178.7 | 35 | 2.66 | 229.94 | 3.19 | 0.00 | 124.4 | 7.17 | 0.29 | 62.03 | |
Seasonal (483) | Pre-monsoon | 17.51 | 0.59 | 68.77 | 36.82 | 2.66 | 229.94 | 2.4 | 0.00 | 40.99 | 8.08 | 0.55 | 60.34 |
Post-monsoon | 17.63 | 0.92 | 178.8 | 33.65 | 3.39 | 189.4 | 3.79 | 0.21 | 124.4 | 6.48 | 0.29 | 62.03 |
Items Usage | Cl− | |||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Ave. | Min. | Max. | Ave. | Min. | Max. | Ave. | Min. | Max. | Ave. | Min. | Max. | Ave. | Min. | Max. | ||
Jun. (n = 206) | Agricultural | 26 | 8 | 78 | 20.31 | 0.00 | 50 | 62.12 | 8.82 | 431.27 | 126.16 | 17.91 | 875.81 | 0.00 | 0.00 | 0.00 |
Living | 3 | 3 | 179 | 0.0 | 0.00 | 65 | 42.38 | 1.20 | 338.74 | 2.44 | 2.44 | 687.92 | 0.00 | 0.00 | 0.00 | |
Drinking | 30 | 6 | 512 | 19.28 | 7.00 | 58 | 41.61 | 4.20 | 154.91 | 84.49 | 8.54 | 314.59 | 0.00 | 0.00 | 0.00 | |
Ave. | 28 | 3 | 512 | 19.03 | 0.00 | 65 | 45.42 | 1.20 | 431.27 | 92.24 | 2.44 | 875.81 | 0.00 | 0.00 | 0.00 | |
Jul. (n = 33) | Agricultural | 32 | 3 | 70 | 25.04 | 2.66 | 70.21 | 54.19 | 28.82 | 114.05 | 110.05 | 58.52 | 231.61 | 0.00 | 0.00 | 0.00 |
Living | 20 | 4 | 49 | 16.98 | 0.56 | 52.8 | 41.25 | 15.01 | 84.67 | 83.76 | 30.48 | 171.96 | 0.00 | 0.00 | 0.00 | |
Drinking | 21 | 4 | 98 | 15.2 | 4.14 | 41.16 | 32.14 | 7.21 | 49.36 | 65.26 | 14.64 | 100.25 | 0.00 | 0.00 | 0.00 | |
Ave. | 24 | 3 | 98 | 18.69 | 0.56 | 70.21 | 42.29 | 7.21 | 114.05 | 85.89 | 14.64 | 231.61 | 0.00 | 0.00 | 0.00 | |
Sep. (n = 194) | Agricultural | 28 | 2 | 181 | 20.21 | 4.00 | 70 | 60.28 | 13.80 | 424.08 | 122.42 | 28.03 | 861.22 | 0.27 | 0.19 | 0.35 |
Living | 27 | 1 | 247 | 17.02 | 2.00 | 73 | 38.61 | 1.80 | 171.73 | 78.40 | 3.66 | 348.74 | 0.00 | 0.00 | 0.00 | |
Drinking | 20 | 2 | 100 | 14.54 | 2.00 | 98 | 41.09 | 12.01 | 117.80 | 83.45 | 24.40 | 239.22 | 0.00 | 0.00 | 0.00 | |
Industrial | 42 | 23 | 60 | 35.33 | 15.00 | 64 | 36.39 | 22.23 | 58.26 | 73.91 | 45.14 | 118.31 | 0.00 | 0.00 | 0.00 | |
Ave. | 25 | 1 | 247 | 17.02 | 2.00 | 98 | 43.37 | 1.80 | 424.08 | 88.07 | 3.66 | 861.22 | 0.27 | 0.19 | 0.35 | |
Oct. (n = 33) | Agricultural | 96 | 16 | 177 | 12.25 | 6.00 | 27 | 324.65 | 49.85 | 867.59 | 659.31 | 101.24 | 1761.91 | 0.00 | 0.00 | 0.00 |
Living | 44 | 3 | 248 | 21.85 | 2.00 | 79 | 44.33 | 12.01 | 127.31 | 90.02 | 24.40 | 258.55 | 0.17 | 0.17 | 0.17 | |
Drinking | 15 | 6 | 39 | 74.5 | 2.00 | 25 | 49.03 | 21.62 | 91.30 | 163.36 | 24.40 | 1761.91 | 0.15 | 0.12 | 0.17 | |
Ave. | 37 | 3 | 248 | 14.13 | 2.00 | 79 | 80.44 | 12.01 | 867.59 | 163.36 | 24.40 | 1761.91 | 0.15 | 0.12 | 0.17 | |
Nov. (n = 17) | Agricultural | 60 | 18 | 101 | 7.5 | 7.00 | 8 | 304.87 | 135.86 | 473.88 | 619.14 | 275.91 | 962.36 | 0.00 | 0.00 | 0.00 |
Living | 58 | 3 | 271 | 23.89 | 4.00 | 33 | 32.63 | 4.81 | 84.07 | 66.26 | 9.76 | 170.72 | 0.21 | 0.21 | 0.21 | |
Drinking | 16 | 9 | 29 | 15.5 | 4.00 | 26 | 46.79 | 24.62 | 73.75 | 95.01 | 49.99 | 149.78 | 0.00 | 0.00 | 0.00 | |
Ave. | 44 | 3 | 271 | 19 | 4.00 | 33 | 69.65 | 4.81 | 473.88 | 141.45 | 9.76 | 962.36 | 0.21 | 0.21 | 0.21 | |
Usage (n = 483) | Agricultural | 31 | 2 | 181 | 20.09 | 0.00 | 70.21 | 78.59 | 8.82 | 867.59 | 159.60 | 17.91 | 1761.91 | 0.02 | 0.00 | 0.35 |
Living | 29 | 1 | 271 | 18.16 | 0.00 | 79 | 40.48 | 1.20 | 338.74 | 82.20 | 2.44 | 687.92 | 0.00 | 0.00 | 0.21 | |
Drinking | 24 | 2 | 512 | 16.27 | 2.00 | 98 | 41.73 | 4.21 | 154.91 | 84.74 | 8.54 | 314.59 | 0.00 | 0.00 | 0.12 | |
Industrial | 42 | 23 | 60 | 35.33 | 15.00 | 64 | 36.39 | 22.23 | 58.26 | 73.91 | 45.14 | 118.31 | 0.00 | 0.00 | 0.00 | |
Ave. | 28 | 1 | 512 | 17.9 | 0.00 | 98 | 47.63 | 1.20 | 867.59 | 96.72 | 2.44 | 1761.91 | 0.01 | 0.00 | 0.35 | |
Seasonal (483) | Pre-monsoon | 28 | 3 | 512 | 19.03 | 0.00 | 65 | 45.42 | 1.20 | 431.27 | 92.24 | 2.44 | 875.81 | 0.00 | 0.00 | 0.00 |
Post-monsoon | 27 | 1 | 271 | 17.01 | 0.56 | 98 | 49.27 | 1.80 | 867.59 | 100.06 | 3.66 | 1761.91 | 0.21 | 0.12 | 0.35 |
The suitability of groundwater for irrigation is contingent on the effects of the mineral constituents in the water on both the plants and soil. Salts may harm plant’s growth physically by limiting the uptake of water through modification in the osmotic processes or chemically by metabolic reactions such as those caused by toxic constituents. Effects of salts on soils cause changes in soil structure, permeability, and aeration, which indirectly affect plant growth. An important factor allied to the relation of crop growth to water quality is drainage. If a soil is open and well drained, crops may be grown on it with the application of generous amounts of saline water; on the other hand, a poorly drained area combined with application of good quality water may fail to produce as satisfactory a crop. The important hydrochemical parameters of groundwater used to determine its suitability for irrigation are EC, Salinity, Percent sodium (Na (%)), Sodium Adsorption Ratio (SAR), RSC, Permeability Index (PI) and Magnesium Ratio. As a results of applying the equations and classifications for evaluating of groundwater (
EC and Na concentrations are important in classifying irrigation water. High salt
Classification of assessment | SAR | Na (%) | RSC | PI | ||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
10 - 20 | Excellent (E) | Up to 20 | Excellent (E) | <1.25 | Good/Safe (G) | >75% | Excellent (E) | |||||||||||
10 - 18 | Good (G) | 20 - 40 | Good (G) | 1.25 - 2.5 | Medium/Marginal(M) | 2 - 75% | Good (G) | |||||||||||
18 - 26 | Fair (F) | 40 - 60 | Permissible (P) | >2.5 | Bad/Unsuitable (B) | >25% | Unsuitable (U) | |||||||||||
>26 | Poor (P) | 60 - 80 | Doubtful (D) | - | - | - | - | |||||||||||
- | - | >80 | Unsuitable (U) | - | - | - | - | |||||||||||
Grade Usage | (E) | (G) | (F) | (P) | (E) | (G) | (P) | (D) | (U) | (G) | (M) | (B) | (E) | (G) | (U) | |||
Agriculture | 17.2 | 0.0 | 0.0 | 0.0 | 5.8 | 9.9 | 0.8 | 0.6 | 0.0 | 16.8 | 0.0 | 0.4 | 6.4 | 10.8 | 0.0 | |||
Living | 44.7 | 0.0 | 0.0 | 0.0 | 15.3 | 24.8 | 4.3 | 0.2 | 0.0 | 40.9 | 3.3 | 0.5 | 16.8 | 27.9 | 0.0 | |||
Drinking | 37.5 | 0.0 | 0.0 | 0.0 | 13.2 | 19.9 | 3.1 | 0.8 | 0.4 | 37.3 | 0.2 | 0.0 | 17.2 | 19.9 | 0.8 | |||
Industrial | 0.6 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6 | - | - | - | - | - | - | 0.2 | 0.4 | - | |||
Total (%) | 100 | 0.0 | 0.0 | 0.0 | 34.3 | 55.2 | 8.2 | 1.6 | 0.4 | 95.0 | 3.5 | 0.8 | 40.6 | 59.0 | 0.8 | |||
483 (100%) | 483 (100%) | 483 (100%) | 483 (100%) | |||||||||||||||
Classification | SSP | MH | Kelly’s Ratio | PS | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
<20 | Excellent (E) | >50 | Non-Acceptable (NA) | >1.0 | Permissible (P) | <5 | Excellent to Good (E) | |||||
20 - 40 | Good (G) | <0 | Acceptable (A) | <1.0 | Non-permissible (NP) | 5 - 10 | Good to Injurious (G) | |||||
40 - 80 | Fair (F) | - | - | - | - | >10 | Injurious to Unsatisfactory (I) | |||||
>80 | Poor (P) | - | - | - | - | - | - | |||||
Grade Usage | (E) | (G) | (F) | (P) | (NA) | (A) | (P) | (NP) | (E) | (G) | (I) | |
Agriculture | 5.8 | 10.3 | 2.1 | 0.0 | 3.3 | 13.9 | 14.1 | 3.1 | 16.8 | 0.4 | 0.0 | |
Living | 12.8 | 24.8 | 7.0 | 0.0 | 0.4 | 44.3 | 43.3 | 1.4 | 44.5 | 0.2 | 0.0 | |
Drinking | 8.7 | 24.0 | 3.9 | 0.8 | 1.9 | 35.6 | 35.2 | 2.3 | 36.6 | 0.6 | 1.0 | |
Industrial | - | 0.6 | - | - | - | 0.6 | 0.6 | - | 0.6 | - | - | |
Total (%) | 27.3 | 59.7 | 13.0 | 0.8 | 5.6 | 94.4 | 93.2 | 6.8 | 98.5 | 1.2 | 0.3 | |
483 (100%) | 483 (100%) | 483 (100%) | 483 (100%) | |||||||||
content (high EC) in irrigation water leads to formation of saline soil. Salinization, on the irrigated lands, is the major cause of loss of production, and it has adverse environmental impacts on irrigation. Saline conditions severely limit the choice of crops and adversely affect crop germination and yields. It is important that all evaluations regarding irrigation water quality are linked to the evaluation of the soils to be irrigated [
On the basis of EC values, Richards classified total concentration of soluble salts in irrigation water into four groups. High-salinity problems are encountered where irrigation activity is in poor drainage agricultural soils and also where water logging allows the water table to rise close to the root zone of plants, causing accumulation of sodium salts in the soil solution through capillary rise following surface evaporation. The sodium or alkali hazard in the use of water for irrigation is determined by the absolute and relative concentration of cations. The relative activity of sodium ion in the exchange reaction with soil is expressed in terms of SAR. If high sodium content and low calcium content are present in waters used for irrigation purpose, the base-exchange complex may become saturated with sodium. This can destroy the soil structure due to the de-flocculation (dispersion of clay particles) process. The U.S. salinity Laboratory’s Diagram uses electrical conductivity, and SAR classifies groundwater as CxSx which is a combination of electrical conductivity (C1 - C4) and SAR (S1 - S4) (
Residual sodium carbonate (RSC) also influences the suitability of water for irrigation uses. RSC can be estimated by subtracting the quantity of alkaline earths
Wilcox diagram | Classes/Ranges and quality | |||
---|---|---|---|---|
Classes | Range | Quality | ||
Conductivity | C1 | 100 - 200 | Excellent | |
C2 | 250 - 750 | Good | ||
C3 | 750 - 2250 | Doubtful | ||
C4 - C5 | >2250 | Unsuitable | ||
SAR | S1 | <10 | Excellent | |
S2 | 10 - 18 | Good | ||
S3 | 19 - 26 | Doubtful/Fairly | ||
S4 - S5 | >26 | Unsuitable |
(
Soil permeability is affected by long-term use of irrigation water with high salt content. Permeability is influenced by sodium, calcium, magnesium, chloride, and bicarbonate contents of the soil. Doneen has classified irrigation waters based on the PI, which indicates the suitability of groundwater for irrigation use. The groundwater may be classified into classes 1 (Excellent), 2 (Good), and 3 (Unsuitable) based on the permeability indices. Classes 1 and 2 are suitable for irrigation, with 75% or more maximum permeability, and class 3 is unsuitable, with 25% maximum permeability. Based on the above classification, 40.6% of the samples fall in class 1 (Excellent), 59% of samples fall in class 2 (Good) and 0.8% samples fall in unsuitable for irrigation usage.
Szabolcs and Darab [
Sodium measured against Ca2+ and Mg2+ was considered by Kelly and Paliwal [
This is an important factor for studying sodium hazards. Sodium has the potential of reacting with soil thereby reducing its permeability and supports little or no plant growth. Based on SSP values, 27.3% of samples belongs to “Excellent” class, 59.7% of samples belongs to “Good”, 13.0% samples belongs to “Fair”, 0.8% samples belongs to “Poor”.
Doneen explained that the suitability of water for irrigation is not dependent on soluble salts. Because, the low solubility salts precipitate in the soil and accumulate with each successive irrigation, the concentration of highly soluble salts increase of the soil salinity. The potential salinity of groundwater samples were classified such as following 3 classes; “Excellent to Good (<5)”, “Good to Injurious (5 - 10)”, “Injurious to Unsatisfactory (>10)”. Based on the above classification, 98.5% of the samples fall in “Excellent to Good”, 1.2% of samples fall in “Good to Injurious” and 0.3% samples fall in “Injurious to Unsatisfactory”.
The Langelier saturation index (LSI) is used to determine the need for calcium carbonate precipitation scale control in water sources containing a TDS concentration of less than 10,000 mg/l (ASTM 1998) [
It defines the susceptibility of groundwater to corrosion and is expressed as ratio of alkaline earths to saline salts in groundwater. The effect of corrosion is loss in the hydraulic capacity of pipes (
The Piper diagram is a representative method for classifying groundwater by producing a diagram of the distribution of cations and anions in groundwater.
Items Usage | Langelier Saturation Index | Corrosivity Index | |||
---|---|---|---|---|---|
Safe | Unsafe | Safe zone | Unsafe zone | ||
Jun. (n = 206) | Agricultural | 32 | 3 | 31 | 4 |
Living | 87 | 1 | 68 | 20 | |
Drinking | 81 | 2 | 70 | 13 | |
Sum. | 200 | 6 | 169 | 37 | |
(%) | 97.1 | 2.9 | 82.0 | 18.0 | |
Jul. (n = 33) | Agricultural | 10 | 0 | 10 | 0 |
Living | 13 | 1 | 12 | 2 | |
Drinking | 9 | 0 | 7 | 2 | |
Sum. | 32 | 1 | 29 | 4 | |
(%) | 97.0 | 3.0 | 87.9 | 12.1 | |
Sep. (n = 194) | Agricultural | 32 | 2 | 32 | 2 |
Living | 91 | 0 | 80 | 11 | |
Drinking | 66 | 0 | 62 | 4 | |
Industrial | 3 | 0 | 2 | 1 | |
Sum. | 189 | 2 | 176 | 18 | |
(%) | 97.4 | 2.6 | 90.7 | 9.7 | |
Oct. (n = 33) | Agricultural | 3 | 0 | 3 | 0 |
Living | 14 | 0 | 10 | 4 | |
Drinking | 15 | 1 | 15 | 1 | |
Sum. | 32 | 1 | 28 | 5 | |
(%) | 97.0 | 3.0 | 84.9 | 15.1 | |
Nov. (n = 17) | Agricultural | 1 | 0 | 1 | 0 |
Living | 8 | 1 | 7 | 2 | |
Drinking | 5 | 2 | 6 | 1 | |
Sum. | 14 | 3 | 14 | 3 | |
(%) | 82.4 | 17.6 | 82.4 | 17.6 | |
Usage (n = 483) | Agricultural | 78 | 5 | 77 | 6 |
Living | 213 | 3 | 177 | 39 | |
Drinking | 176 | 5 | 160 | 21 | |
Industrial | 3 | 0 | 2 | 1 | |
Sum. | 470 | 13 | 416 | 67 | |
(%) | 97.3 | 2.7 | 86.1 | 13.9 |
The samples obtained for this study were classified for their usage (drinking, living, agricultural, industrial) and period of sampling (pre-monsoon (June), post-monsoon (July-November) to produce the Piper diagram. The
As we know, major ions constitute a significant part of the total dissolved solids in groundwater and the concentrations of these ions in groundwater depend on the hydrogeochemical processes that take place in the aquifer system. These processes occur when the groundwater moves toward equilibrium in major ion concentration. Therefore, the studies of concentrations of various major ions present in groundwater have been used for the identification of geochemical processes. In this study, we focused on the comparative study to give weight on the two or three kinds of major ion groups such as followings; calcium and magnesium, sodium and potassium, Chloride and sulfate. Because the combination of two or three ions are very important for looking into weathering type of solutes (calcite, gypsum, dolomite), dominance type of ions in solution, influence type for mutual interaction between one ion and the other ion.
Calcium is the dominant ion found in the groundwater of all samples. Generally, the abundance of Ca2+, Na+, and Mg2+ is associated with minerals such as montmorillonite, illite, and chlorite [
(
falling above the equiline result from carbonate weathering, whereas those falling along the equiline are caused by both carbonate weathering and silicate weathering (Equation (3)). Such a (
Carbonate weathering by carbonic acid water saturated with CO2 is an intensive process. This water can easily dissolve the carbonate minerals available in its flow path. This process has increased the soluble ion content like chloride, sodium, potassium, magnesium, and bicarbonate ion in the groundwater. The Chloro Alkaline Indices (CAI) may be positive or negative depending upon the exchange of sodium and potassium from rock with magnesium and calcium in water and vice versa (
Source-Rock deduction is to gain insight into the possible origin of water analysis. It is useful both as an analytical check and as an investigative procedure if the origin of groundwater is not known. It is derived from a simplistic mass balance approach to water quality data [
(<0.5); 3) Dolomite dissolution, calcite precipitation. In
While the Piper diagram is a method for classifying groundwater based on the distribution of both cations and anions, and the Gibbs diagram is a method for estimating the origin of ions in groundwater by focusing on the correlation between the concentration of cations (Na+, Ca2+) and anions (Cl−,
combination of two diagrams would be convenient to illustrate the general types of groundwater in laboratory scales.
This study compared the geochemical characteristics of groundwater from samples obtained in rural areas of Korea. The SAR (Sodium Adsorption Ratio), Sodium (%), RSC (Residual Sodium Carbonate), PI (Permeability Index), SSP (Residual sodium Percentage), MH (Magnesium Hazard), PS (Potential Salinity) and Kelly’s Ratio were evaluated using the concentration distribution of ions. According to the results, 100% was classified as excellent after applying SAR; approximately 98% was classified as excellent/good/permissible after applying Na (%); 95.0% was classified as good/safe after applying RSC; 99.6% was classified as excellent/good after applying PI; 99.2% was classified as excellent/good after applying SSP; 94.4% was classified as acceptable after applying MH; 98.5% was classified as excellent to good after applying PS; and 93.2% was classified as permissible after applying Kelly’s ratio. Most groundwater samples were classified as “excellent to good” or “good to permissible” using the Wilcox diagram. The evaluation using the U.S. salinity Laboratory’s Diagram also showed that most groundwater samples are C1S1 (Excellent/Excellent) or C2S1 (Good/Ex- cellent). And, in the applications of two factors of Langelier Saturation Index (LSI) and Corrosive ratio (CR) we could get similar results for defining the suitabilities of goroundwater for the industrial purpose. In the Piper diagrams, the
Hwang, J.Y., Park, S., Kim, H.-K., Kim, M.-S., Jo, H.-J., Kim, J.-I., Lee, G.-M., Shin, I.-K. and Kim, T.-S. (2017) Hydrochemistry for the Assessment of Groundwater Quality in Korea. Journal of Agricultural Chemistry and Environ- ment, 6, 1-29. https://doi.org/10.4236/jacen.2017.61001