Volume 9, Number 2 (January 2022):3367-3377, doi:10.15243/jdmlm.2022.092.3367 ISSN: 2339-076X (p); 2502-2458 (e), www.jdmlm.ub.ac.id
Open Access 3367 Research Article
Groundwater quality mapping for drinking and irrigation purposes using statistical, hydrochemical facies, and water quality indices in Tercha District, Dawuro Zone, Southern Ethiopia
Arefegn Arota1, Abunu Atlabachew2, Abel Abebe1, Muralitharan Jothimani1*
1 Department of Geology, College of Natural Sciences, Arba Minch University, P O Box:21, Ethiopia
2 Faculty of Water Resources and Irrigation Engineering, Arba Minch University, P O Box:21, Ethiopia
*corresponding author: [email protected]
Abstract Article history:
Received 24 October 2021 Accepted 22 December 2021 Published 1 January 2022
When groundwater quality is good, it may be a substantial water supply for various applications. However, no systematic research on hydrogeochemistry and water quality features for drinking and irrigation has been undertaken in the present study area. As a result, the current study looked at hydrogeochemical variables and groundwater quality for drinking and irrigation in Tercha district, Dawuro Zone, Southern Ethiopia. Forty- seven groundwater samples were collected and tested to satisfy the required target for various physicochemical properties. The hydrogeochemical features of the groundwater in the study region were assessed using in-situ testing and laboratory analysis of physicochemical parameters. Groundwater samples from the research region were slightly acidic to slightly basic, with the principal cations and anions decreasing in sequence: Na+ > Ca2+ > Mg2+
> K+ and HCO3-> Cl-> SO42-. The hadrochemical facies of the studied region evolved from mildly mineralized dominant highland Ca-HCO3 water types to moderately mineralized mixed Ca-Na-HCO3 water types to highly mineralized deep rift floor Na-HCO3 water types. Additionally, the World Health Organization and the Ethiopian Standard Agency were utilized to compare the drinking water quality. Except for NO3- (4.25 %), Fe (8.51 %), and F- (2.12%), all groundwater samples from the research region were determined to be within permitted limits and appropriate for drinking.
According to the Water Quality Index, about 80.86% of groundwater samples are excellent, and 19.14% are good drinking water. Sodium absorption ratio (SAR), sodium (Na) percentage, residual sodium carbonate RSC, permeability index (PI), and magnesium hazard were among the irrigation water quality indicators calculated (MH). The great majority of groundwater samples are suitable for agricultural use.
Keywords:
Dawuro Zone drinking water groundwater quality irrigation
Southern Ethiopia
To cite this article: Arota, A., Atlabachew, A., Abebe, A. and Jothimani, M. 2022. Groundwater quality mapping for drinking and irrigation purposes using statistical, hydrochemical facies, and water quality indices in Tercha District, Dawuro Zone, Southern Ethiopia. Journal of Degraded and Mining Lands Management 9(2):3367-3377, doi:10.15243/jdmlm.2022.092.3367.
Introduction
Water is one of the essential natural resources for all living beings on the planet, and it has a significant impact on socio-economic growth. In areas where surface water is scarce, groundwater is the essential water supply for human use and industrial and
agricultural operations (Delgado et al., 2010). Natural variables (geology, geochemical processes, salt solubility, and recharge water quality) and anthropogenic activities (agricultural and industrial effects) influence its physico-chemical properties (Hosseinifard and Aminiyan, 2015). As a result, the
Open Access 3368 intricacy of groundwater management is regulated by
the variability and interactions of various elements (Xing et al., 2018).
The quality of groundwater is determined by all of its actions from the time it condenses in the atmosphere until it is discharged by a well (Arumugam and Elangovan, 2009). As a result, groundwater chemistry may reveal vital details about the aquifers’
geological history and appropriateness for household, industrial, and agricultural use. Groundwater geochemical processes and their interactions with aquifer minerals significantly impact water quality.
Furthermore, changes in land use for urbanization and farming activities substantially affect the deterioration of water quality. As a result, water quality has become a critical issue for water resource development and human health.
Water-rock interaction, recharge and discharge (percolation and pumping), ion exchange, residence time, atmospheric inputs (precipitation-dissolution processes), chemical inputs from human activities, geological structures, and mineralogy of aquifers are some of the main processes that govern groundwater chemistry (Jeong, 2001). The interaction of all of these variables results in various water types and provides valuable information about the host rocks’ geological history. Groundwater’s hydrogeochemical composition can also reveal its source and the history of its passage via subterranean strata. The following authors from the different parts of the world were evaluated water quality for drinking, domestic, and irrigation purposes using various methods, such as
“Entropy-weighted water quality index (EWQI) modeling” (Wagh et al., 2017; Kumar et al., 2020;
Kumar and Augustine, 2021), geostatistical assessment of groundwater pollution (Kumar, 2017;
Olofinlade et al., 2018; Sylus and Ramesh, 2018; Ukah et al., 2021), evaluation of groundwater quality using GIS (Shinde et al., 2021), groundwater quality assessment for drinking purpose (Khan et al., 2020),
“groundwater quality assessment by using Water Quality Index (WQI) and multivariate statistical techniques” (Deepa and Venkateswaran, 2018),
“groundwater quality assessment for irrigation using geostatistical analysis combined with a linear regression method” (Yazdanpanah, 2016), groundwater quality assessment through spatial interpolation technique (Khorsandi et al., 2017).
In the current study area, the mechanism of rock- water interaction and groundwater quality for irrigation and drinking is undetermined. Even though water quality is an issue in the study region, no comprehensive investigations of the hydrogeochemical characteristics of the groundwater have been conducted so far. As a result, the main goal of this study is to look at the hydrogeochemical aspects and groundwater quality in the study area for drinking and irrigation purposes. As a result, this study is critical for understanding the hydrochemical features
of groundwater and supporting groundwater management in the current study region.
Materials and Methods Study area
The study area is in Ethiopia’s Southern Nations Nationalities and People’s Regional State. It is located between UTM readings of 769725 to 798581 m N and longitude 281443 to 304260 m E, covering a 301.5 km2 area (Figure 1). The study area’s climatic conditions correspondingly include mean minimum and maximum temperatures of 12.3 0C and 34.6 0C.
Furthermore, the mean annual rainfall ranges from 1400 mm to 1716 mm, and the area’s rainfall patterns analysis and temporal variability are defined as a bimodal pattern.
Water sampling and chemical analysis
During February and March 2020, 47 groundwater samples were collected using conventional sampling procedures from shallow wells, deep wells, and springs. Sampling wells were pumped for 3-5 minutes before taking groundwater samples to remove pollutants from stagnant water. After the wells were pumped, samples were collected in 1 L plastic water bottles that have been washed, rinsed with distilled water, and afterwards rinsed 2 to 3 times before being used to sample water. In-situ tests for sensitive parameters such as pH, total dissolved solids (TDS), and electrical conductivity (EC) were performed using standard instruments such as a pH meter, TDS meter, and conductometer. Groundwater samples were collected and promptly sent to Arba Minch University Technology Institute Faculty of Water Supply and Environmental Engineering’s Water Quality Laboratory for examination. Water samples collected during fieldwork were analyzed for major cations and anions using standard methods/ techniques such as titration for Ca2+, Mg2+, HCO3-, and CO3-, Argentometric method for chlorine (Cl), UV-Vis Spectrophotometric method for SO42-, Flame photometric method for K+ and Na+, and DR-2800 Spectrophotometry for NO3-, F-, and Fe (APHA, 1998). The correctness of the studied water quality characteristics data was verified using cation-anion balance. Ion balance error was calculated using the following equation 1.
IBE (%) = (∑ cations − ∑ anions)
(∑ cations + ∑ anions) x 100 − − (1) Ion balance error (IBE) was computed for each set of completed analyses of water samples in the study area to validate water quality analysis. Therefore, based on calculated IBE about 75.5% of the samples were found within preferable limits (<±5%) and 24.5% found within the acceptable limit, i.e., IBE is >±5% but
<±10%.
Open Access 3369 Figure 1. Location map of the study area.
In the current study, the WQI was calculated using the equations 2–5. The given weight ranges from 1 to 5.
Equation 4 was then used to calculate the relative importance of each parameter.
Wi = wi/ wi − − − − − − − − − (2) Where; Wi is the relative weight, wi is the weight of each parameter, and n is the number of parameters. The quality rating scale for each parameter is calculated by dividing its concentration in each water sample by its respective standard (WHO, 2011) and multiplying the results by 100.
Qi = (Ci/Si) *100 − − − − − (3) Where; Qi is the quality rating, Ci is the concentration of each parameter in each groundwater sample in (mg/L), and Si is the (WHO, 2011) standard for each
parameter in mg/L. For computing the final stage of WQI, the sub-index (SIi) is first determined for each parameter. The sum of SI values gives the water quality index for each groundwater sample.
SIi = Wi*Qi − − − − − − − − − − − − − − − (4) WQI = 𝑆𝐼𝑖 − − − − − − − − − − − − − −(5)
Where; SIi is the sub-index of ith parameter, Wi is the relative weight, Qi is the rating based on the concentration of ith parameter, and WQI is the water quality index of each sample.
Studying the irrigation water quality is essential to assessing groundwater suitability for irrigation purposes. In the present study, the following irrigation water quality indices, as shown in (Table 1) were calculated.
Table 1. Methods used to calculate irrigation water quality indices (in meq/L).
Parameters Formula Sources
Sodium Adsorption Ratio (SAR)
SAR = Na
Ca + Mg 2
Richards (1954)
Permeability Index (PI) PI = √ ∗ 100 Doneen (1964)
Residual Sodium Carbonate (RSC) RSC= (CO3- + HCO3- ) – (Ca2+ + Mg2+) Ragunath (1987) Sodium percentage (Na %)
𝑁𝑎 (%) = (Na + K )
(Ca + Mg + K + Na )∗ 100 Wilcox (1955) Magnesium Hazard (MH) MH= Mg2+/(Mg2++Ca2+) *100 Paliwal (1972)
Open Access 3370 Results and Discussion
In-situ measured parameters
The pH of groundwater in the research region ranges from 5.70 to 8.35, with a mean of 7.17 (Table 2), indicating that the groundwater is mildly acidic to slightly basic. The EC and TDS values vary from 10 to 700 (S/cm), with a mean of 278.20 (S/cm) and 6 to 452 mg/L, respectively, with 178.51 (Table 2). Their highest concentrations in the research region might be linked to intense rock-water contact, which emerged as the geothermal gradient increased along the flow direction. The total hardness (TH) content ranges from 5.42 to 204.65 mg/L, with a median of 102.64 mg/L.
In addition, Sawyer and McCartly (1967) classified
“water as soft (75 mg/L), moderately hard (75-150), hard (150-300), and extremely hard (>300) based on the TH value”. According to this categorization, about 29.79%, 55.31%, and 40.90 % of the samples in the research region fell into the soft, moderately hard, and hard water classifications, respectively.
Major ions
It comprises the major cations like Ca2+, Mg2+, Na+, and K+; and anions such as HCO3-, Cl-, and SO42-. In the study area the major cations and anions of the groundwater samples according to decreasing sequence of concentration (in mg/L) are as follows:
“Na+ > Ca2+ > Mg2+ > K+ and HCO3- > Cl- > SO42-“
respectively. The content of sodium (Na+) in the study region ranged from 0.21 to 145.32 mg/L, with a mean of 36.24 (mg/L), and all of the samples were determined to be within the WHO (2011), and ESA (2013) recommended limits and acceptable for drinking (Table 2). The Ca2+ and Mg2+ value concentration ranges from 0.20 to 60 mg/L with a mean of 25.13 mg/L and 1.2 to 24.5 mg/L with a mean of 9.67 mg/L, respectively. All samples were found within permissible limits and suitable for drinking purposes (Table 2).
Potassium (K+) is another less abundant cation in natural waters due to rocks containing potassium ions being relatively resistant to weathering (Hem, 1985).
Its concentration in the study area varies from 0 to 10 mg/L with a mean of 3.5 (mg/L), and all groundwater samples of the study area were found within the permissible limit of 12 (mg/L) set by (WHO, 2011) and suitable for drinking purposes” (Table 2). The concentration of bicarbonate (HCO3-) values in groundwater range from 36.6 to 488 mg/L with a mean of 196.46 mg/L and all groundwater samples of the study area were found with the permissible limit set by (WHO, 2011) and (ESA, 2013) standards and suitable for drinking purpose” (Table 2).
The concentration of chloride (Cl-) and sulfate (SO42-) ranges from 0.25 to 160 mg/L with a mean of 7.72 (mg/L) and 0 to 15.6 with a mean of 7.72 (mg/L), respectively. All groundwater samples were found within desirable limits as per WHO (2011) and ESA
(2013) standards and suitable for drinking purposes (Table 2). The maximum value of Cl- may be derived from the leaching of chlorine-bearing minerals from acidic igneous rocks due to rock-water interactions and rainfall. Additionally, the study area is relatively high in most densely populated areas; this may also indicate a possible source of Cl- may be derived from percolation of domestic sewage and agricultural land water (Bhatia, 2003). The potential sources of SO42- in the area may be derived from certain igneous rock minerals of the feldspathoid group, sulfide mineral- bearing rocks, and anthropogenic effects like agricultural fertilizers. In the study area, the concentration of nitrate (NO3- )value ranges from 0.00 to 170 mg/L with a mean of 11.28 mg/L. Except for two groundwater samples, all are found within the allowable limit of guidelines of (50 mg/L) in the area (Table 2). The Fluoride (F-) values investigated range from 0 to 2.09 mg/L, with a mean of 0.45 mg/L. The WHO (2011) established a maximum acceptable F- level in drinking water of 1.5 mg/L. “Furthermore, fluoride levels exceeding 1.5 mg/L in drinking water induce skeletal and dental fluorosis, which is distinguished by opaque white patches, staining, mottling, and pitting of teeth” (Adimalla and Venkatayogi, 2017). The iron (Fe) concentration in the study region ranges from 0.00 to 0.60 mg/L, with a mean of 0.10 mg/L. According to WHO (2011) recommendations, about 8.51% of samples surpassed the permitted level of 0.3 mg/L, rendering them unfit for human consumption. According to the ESA (2013) guideline, about 6.38% of groundwater samples were above the permitted level of (0.4 mg/L) and were unfit for human consumption (Table 2).
Correlation analysis
The mutual association between two variables is referred to as correlation. A direct connection arises whenever an increment in one parameter’s value is connected with an increase or decrease in another parameter’s value. When one variable rises while the other falls, there is a negative connection. In other circumstances, no link is seen, indicating that the movement of one variable cannot be anticipated from the movement of the other (Shroff et al., 2015).
According to the Pearson correlation matrix in (Table 3), a substantial positive connection between TH and Ca2+ (r = 0.93) and Mg (r = 0.78) indicates that they were derived from the same sources. Similarly, the high positive connection between HCO3- and TH (r = 0.72), TDS (r = 0.80), EC (r = 0.80), Na+ (r = 0.77), and Ca2+ (r = 0.77) might imply rock-water interaction variables.
Hadrochemical facies
Hydrochemical facies refer to the distinction between chemically distinct groundwater bodies in an aquifer.
Geology, solution material movement, and aquifer flow patterns all have a role.
Open Access 3371 Table 2. Statistical analysis of the physicochemical parameters.
Parameter Unit Minimum Maximum Mean Std WHO Guideline
(2011) No. of samples exceeding
(WHO) standard ESA (2013)
Guideline No. of samples exceeding (ESA) standard
pH - 5.70 8.35 7.17 0.57 6.5-8.5 None 7-8.5 None
TDS mg/L 6.0 452 178.51 125.80 500 None 1000 None
EC μS/cm 10 700 278.20 193.22 1000 None - None
TH mg/L 5.42 204.65 102.64 47.73 300 None 500 None
Na+ mg/L 0.21 145.32 36.24 36.47 200 None 358 None
K+ mg/L 0.0 10 3.50 2.45 12 None 12 None
Ca2+ mg/L 0.20 60 25.13 13.69 75 None 75 None
Mg2+ mg/L 1.20 24.50 9.67 4.96 50 None 50 None
Fe mg/L 0.0 0.60 0.10 0.15 0.3 4 0.4 3
Cl- mg/L 0.25 160 7.72 22.99 250 None 200 None
SO42- mg/L 0.00 15.60 2.34 3.46 250 None 483 None
HCO3- mg/L 36.6 488 196.46 122.11 500 None 600 None
NO3- mg/L 0.0 170.8 11.28 27.21 50 2 50 2
F- mg/L 0.0 2.09 0.45 0.42 1.5 1 3 None
TDS = Total Dissoloved Solids; EC = Electrical Conductivity; TH = Total Hardness;*WHO = World Health Organization; *ESA = Ethiopian Standard Agency.
Table 3. Major physiochemical parameters’ correlation coefficient matrix.
TH pH TDS EC Na+ K+ Ca2+ Mg2+ Fe2+ Cl- SO42- HCO3- NO3-
TH 1
pH 0.35* 1
TDS 0.59** 0.37** 1
EC 0.59** 0.37* 0.99** 1
Na+ 0.33* 0.34* 0.55** 0.55** 1
K+ 0.18 0.27 0.47** 0.47** 0.33* 1
Ca2+ 0.93** 0.28 0.62** 0.62** 0.38** 0.29* 1
Mg2+ 0.78** 0.34* 0.33* 0.33* 0.12* -0.05 0.49** 1
Fe2+ -0.14 -0.18 -0.08 -0.08 -0.11 0.01 -0.14 -0.10 1
Cl- 0.16 -0.08 -0.01 -0.01 0.38** -0.12 0.23 -0.01 0.09 1
SO42- -0.14 0.47** 0.16 0.16 0.42** 0.12 -0.15 -0.09 -0.05 0.11 1
HCO3- 0.72** 0.41** 0.80** 0.80** 0.77** 0.47** 0.77** 0.39** -0.16 0.07 0.21 1
NO3- -0.04 -0.11 -0.16 -0.16 0.19 -0.15 -0.13 0.12 -0.07 -0.07 -0.11 -0.08 1
F- 0.43** 0.17 0.54** 0.54** 0.36* 0.26 0.47** 0.22 -0.13 -0.02 -0.03 0.45** 0.42**
TDS = Total Dissolved Solids; TH= Total Hardness; EC= Electrical Conductivity;**. Correlation is significant at the 0.01 level (2-tailed) and *. Correlation is significant at the 0.05 level (2-tailed).
Open Access 3372 Piper’s (1944) trilinear diagram helps determine water
types based on the ionic concentrations of groundwater samples collected from diverse sources across the study area. It is also a good tool for identifying chemical relationships in groundwater samples. The Piper diagram presented the chemical data values of groundwater samples obtained in the study area (Figure 2). According to the Piper diagram, the water types in the research region are classified into four categories: Ca-HCO3, mixed Ca-Na-HCO3, Na-HCO3, and Na-Cl. Except for Na-Cl type, all water types of the area were associated with the dominant anion of bicarbonate; this is maybe due to the hydrogeological
regime and prevalence of the lithologically homogeneous aquifers with a relatively high amount of rainfall that the study area receives. Ca-HCO3 is a recharge area water dominated by Ca and Mg due to the essential volcanic igneous rock dominance. Na- HCO3 water type is another group of water associated with the deep rift floor parts of the study area; this might indicate the ion exchange, deep circulation, and longer residence time. In general, in the study area, groundwater mineralization increases from young highland dominant water types of Ca-HCO3 toward deep rift floor water types of Na-HCO3 along the groundwater flow path.
Figure 2. Piper diagram showing hadrochemical facies of the study area.
Figure 3. Gibb’s plot indicating general mechanisms of groundwater evolution.
Groundwater chemistry and governing factors The interaction between groundwater and aquifer minerals plays a key role in water, critical for understanding groundwater genesis (Bozdag and Gocmez, 2013). Ion exchange (Na+ and K+ in
groundwater with Ca2+ and Mg2+), evaporation, silicate weathering, and carbonate minerals are among the numerous processes that regulate groundwater chemistry (Kim et al., 2005). As a result, the Gibbs plot greatly influences the link between groundwater chemistry and aquifer lithology (Gibbs, 1970). The
Open Access 3373 analyzed groundwater samples in the research region
were shown in Gibb’s diagram (Figure 3) using the ratios of (Na + K)/(Na + K + Ca) and Cl/(Cl + HCO3) as a function of TDS. According to the graphic, the bulk of the samples fell into the field of rock-water interaction. The Gibbs diagram indicates that the vital hydrogeochemical variables that govern groundwater chemistry in the research region are rock-water interaction, including silicate weathering and ion exchange. Standards were employed to assess groundwater quality for drinking purposes. Except for NO3- (4.25%), Fe (8.51%), and F- (2.12%), all samples were determined to be below the allowed level of the recommendations, according to the World Health Organization and Ethiopian Standard Agency criteria.
It signifies that rock-water interaction is the primary
driver of groundwater chemistry and evolution in the study area.
Drinking-Water Quality Index (WQI)
The water quality index (WQI) is a straightforward yet efficient tool for measuring the overall quality of groundwater and its suitability for drinking. It is widely used worldwide (Vasanthavigar et al., 2010). It is also used to examine the influence of natural and human activities on groundwater chemistry through a set of essential parameters (Kumar et al., 2015). To calculate the WQI, each physicochemical characteristic was assigned a weight depending on its relevance in overall water quality for potable water.
Table 4 shows the WQI weights assignment and relative weight calculation.
Table 4. Analyzed Physico-chemical parameters with their respective assigned weight and relative weight.
Parameter WHO (2011) standard (mg/L) (Si)
Assigned
weight 𝒘𝒊
Relative weight
TH 300 2 49 0.040816327
Turbidity 5 1 49 0.020408163
pH 6.5-8.5 2 49 0.040816327
EC 1000 4 49 0.081632653
TDS 500 5 49 0.102040816
Na+ 200 4 49 0.081632653
K+ 12 2 49 0.040816327
Ca2+ 75 2 49 0.040816327
Mg2+ 50 2 49 0.040816327
Fe 0.3 4 49 0.081632653
Cl- 250 5 49 0.102040816
SO42- 250 5 49 0.102040816
HCO3- 500 1 49 0.020408163
NO3- 50 5 49 0.102040816
F- 1.5 5 49 0.102040816
Total ∑ wi = 49 ∑ Wi = 1
The calculated WQI value in the study region spans from 10.47 to 70.97, with a mean of 30.38. The calculated WQI values were classified as follows:
excellent, good, poor, extremely poor, and unfit for drinking (Table 5). As a result, groundwater samples were excellent and suitable for potable water, based on computed WQI values of about 80.86% and 19.14% of the research region, respectively.
Irrigation Water Quality
The total salinity and sodium concentrations in groundwater, connected to other ion concentrations, are essential to assessing groundwater suitability for agricultural usage. Irrigation agricultural programs are created and managed by supplying irrigation water to the field and managing salt and alkali levels (Haritash et al., 2008). As a result, salinity and sodium ion risks are the primary concerns in irrigation water quality evaluation. Salinity and irrigation water quality indicators such as sodium absorption ratio (SAR),
Na%, RSC, PI, and MH are essential characteristics used to assess groundwater suitability for irrigation (Raju, 2009). The groundwater samples from the research region were divided into several groups based on the derived indices, as shown in Table 6 .
Table 5. Groundwater quality classification for drinking purpose based on WQI.
Range of
WQI Water Quality Percentage of samples
<50 Excellent
Water 80.86
50-100 Good Water 19.14
100-200 Poor Water Nil
200-300 Very poor
water Nil
>300 Unsuitable
Water Nil
Open Access 3374 Salinity Hazard (SH)
EC is a significant parameter used to measure total salinity and classify agricultural water quality. Excess salinity concentration increases the osmotic pressure of the soil solution that can lead to drought conditions.
According to the Wilcox (1955) criteria based on the study area’s EC value (Table 6), about 55.32% and 44.68% of the groundwater samples of the study area belong to excellent and suitable for irrigation purposes, respectively.
Sodium Adsorption Ratio (SAR)
SAR assesses the soil’s capability of absorbing salts from irrigation water. As a result, it’s a valuable indicator to evaluate the danger of salt or alkali toxicity in plants (Xiaomin et al., 2018). The estimated SAR values of groundwater samples in the research region varied from 0.02-16.1 (meq/l), with a mean of 2.42 (meq/lL) (Table 6). According to Deshpande and Aher (2012), agricultural water quality classifications are dependent on SAR value (Table 6); all groundwater samples from the research region fall into the good category and are appropriate for irrigation water usage.
According to the United States Salinity Laboratory (USSL) diagram in (Figure 4), approximately 29.80%, 68.08%, and 2.12% of groundwater samples from the study area fall into the C1S1 (low salinity with low alkalinity hazard), C2S1 (medium salinity with low alkalinity hazard), and C1S2 (low salinity with medium alkalinity hazard) classes, respectively.
Sodium percentage (Na%)
Another important indicator of the sodium risk in agricultural water is the percentage Na. When sodium concentrations in irrigation reach too high, it is likely to disintegrate calcium and magnesium ions in the soil.
With a mean of 39.20 (meq/L), the estimated value of Na% ranges from 5.26 to 96.14 meq/L. According to Wilcox (1955), the classifications of irrigation water quality based on Na% in (Table 6) show that approximately 19.15%, 34.04%, 31.91%, 12.77%, and 2.13% of the groundwater samples from the study area fall into the excellent, good, permissible, doubtful, and unsuitable for irrigation purposes categories, respectively. Based on EC against Na% values in the research region, roughly 89.36% and 10.64% of groundwater samples fell within the excellent to acceptable and permitted to dubious categories for irrigation purposes, respectively, per the Wilcox diagram (Figure 5).
Residual Sodium Carbonate (RSC)
A high RSC in water enhances sodium absorption in soil (Kumar, 2017). The computed RSC value of the research area’s groundwater samples ranged from - 0.14 to 5.73 meq/L, with a mean of 1.19 meq/L) As per (Deshpande and Aher, 2012), the water is classified as safe at 1.25 meq/l, marginally appropriate from 1.25- 2.5, and unsuitable for agricultural uses at >2.5 (Table 6).
Table 6. Classifications of irrigation water quality based on irrigation water quality indices.
Parameters Range Class No. of samples
within range Percentage
of samples Source
EC <250 Excellent 26 55.32 Wilcox (1955)
250-750 Good 21 44.68
750-2250 Permissible Nil Nil
2250-5000 Doubtful Nil Nil
>5000 Unsuitable Nil Nil
SAR <10 Excellent All 100 Deshpande and Aher
(2012)
10-18 Good Nil Nil
18-26 Doubtful Nil Nil
>26 Unsuitable Nil Nil
PI >75 Excellent 42 89.36 Doneen (1964)
25-75 Good 5 10.64
<25 Unsuitable Nil Nil
%Na <20 Excellent 9 19.15 Wilcox (1955)
20-40 Good 16 34.04
40-60 Permissible 15 31.91
60-80 Doubtful 6 12.77
>80 Unsuitable 1 2.13
RSC < 1.25 Safe 33 70.2 Deshpande and Aher
(2012)
1.25-2.5 Marginally suitable 7 14.9
>2.5 Not suitable 7 14.9
MH <50 Suitable 38 80.85 Paliwal (1972)
>50 Unsuitable 9 19.15
Open Access 3375 Figure 4. USSL diagram indicates salinity and alkalinity hazards of irrigation water.
Figure 5. Wilcox diagram showing (%Na vs EC) to assess agricultural water.
So, based on the calculated RSC value of the study area’s groundwater samples, about 70.2%, 14.9%, and 14.9% of the study area’s groundwater samples were classified as safe, marginally appropriate, and unsuitable for irrigation, respectively. In general, most of the groundwater samples in the research region are safe to drink and suitable for irrigation.
Permeability Index (PI)
The permeability index (PI) is another essential irrigation water quality metric that is often used to analyze the effects of long-term agriculture on hydraulic soil qualities that the soil’s Na+ impacts, Ca2+, Mg2+, and HCO3 levels” (Nematollahi et al., 2015). According to Doneen (1964), irrigation water quality is classified into three classes depending on the PI value: Class-I (>75) is of high quality, Class-II (25- 75) is suitable for agriculture, and Class-III (25) is inappropriate for irrigation (Table 6). The estimated PI
value varied from 58.66 to 147.67 meq/L in the study area, with a mean of 93.3 meq/L. According to the computed PI value, approximately 89.36 % and 10.64 percent of groundwater samples in the study area were classified as Class-I and Class-II, respectively.
Consequently, based on the PI value, all groundwater samples in the study area are suitable for agricultural use.
Magnesium Hazard (MH)
Another important metric used to measure groundwater suitability for agricultural uses is MH.
The calculated MH value ranged from 7.69 to 90.91 meq/l in the study area, with a mean of 41.70 meq/l.
So, based on the computed MH value, about 80.85%
and 15.15% of the groundwater samples in the research region corresponded to acceptable and unfit water agricultural purposes, respectively (Table 6).
Open Access 3376 Conclusion
Groundwater is an important water supply for various applications when its quality is determined using chemistry-governing variables. The primary goal of this research was to evaluate the hydrogeochemical properties and quality of groundwater for drinking and agricultural use in Tercha district, Dawuro Zone, Southern Ethiopia. The physicochemical examination of groundwater samples taken from various sources in the research region reveals that the rising sequence of main cations and anions is as follows: Na+ > Ca2+ >
Mg2+ > K+ and HCO3- > Cl- > SO42-. The prevalence of Na+ and HCO3- indicates that silicate weathering is a significant factor governing groundwater chemistry in the research region. In terms of hydrogeochemical facies, the water types studied are classified into four categories: Ca-HCO3, mixed Ca-Na-HCO3, Na-Cl, and Na-HCO3. Rock weathering (silicates, carbonates, and sulfates), which is also strongly influenced by evaporation and cation exchange processes, and to a lesser extent, by anthropogenic inputs, is the major contributor to the hydrochemical features of groundwater, according to the Gibbs diagram analysis.
Water Quality Index analysis shows that most groundwater samples are excellent and suitable for drinking water. The calculated irrigation water quality indices show that most groundwater samples in the present study area are ideal for agricultural use.
Acknowledgements
The authors would like to express genuine thanks and appreciation to Arba Minch University for their financial support and fundings for the first author. The authors also would like to express sincere thanks to the Water Quality Laboratory, Faculty of Water Supply and Environmental Engineering, Arba Minch University, Ethiopia, for their assistance and analysis of the water samples.
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