Hydrogeochemical Evaluation of Groundwater Quality and Its Applicability for Various Purposes in the Drought-Prone Konso Zone, Rift Valley, Southern Ethiopia

Abstract

The present study area, the Konso Zone, is in Rift Valley, Southern Ethiopia, and highly depends on rivers and groundwater for economic and social development. Water availability in this area faces multiple challenges, including scarcity, quality concerns, and seasonal variations. In the Rift Valley region, including the present study area, groundwater quality is particularly problematic due to high fluoride levels. Moreover, the high concentrations of total dissolved solids in Konso Zone groundwater pose challenges for industrial, agricultural, and drinking purposes. GIS-based spatial analysis techniques, hydrogeochemical analyses, and water quality indices were used in the current study. The evaluation of water quality involved the utilization of both groundwater quality and irrigation water quality indices. In the study area, the cations and anions exhibited a general trend with Na⁺ > Mg²⁺ > Ca²⁺ > K⁺ > Fe²⁺ and HCO₃⁻ > Cl⁻, SO4²⁻ > NO₃⁻ > F⁻. Multiple water types were identified within the research area, including Na-HCO₃, Ca-Na-HCO₃, NaCl, and Ca-Mg/Cl, with Na-HCO₃ being the most prevalent. The formation of the NaHCO₃ water type is primarily attributed to ion exchange processes, with siliciclastic aquifers being linked to cation exchange in sodium bicarbonate groundwater. Total Dissolved Solids and SO₄²⁻ contaminants significantly impact the water quality, resulting in deterioration. Gibbs’s figure indicates that 50% of the water samples were found where rocks were weathered, demonstrating the importance of water-rock interactions in groundwater composition. Water samples containing more fluoride than the WHO’s limit of 1.50 mg/L were deemed unsuitable for consumption. Regarding irrigation suitability, most water samples from the Konso area were acceptable, except for the sodium percentage in 66.6% of the samples, which was unsuitable for irrigation. There are 26.67% of samples that are of questionable quality, 66.67% that are deemed inappropriate, and 26.67% that are deemed unacceptable. These findings underscore the pressing need for comprehensive strategies and interventions to address water quality issues in the Konso Zone, emphasizing the critical importance of monitoring and managing groundwater resources to ensure sustainable and safe water access for various regional uses.

This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

1. Introduction

In arid and semiarid regions such as Ethiopia, groundwater is essential for drinking and economic development; because of their low and variable patterns of precipitation, arid and semiarid regions typically have limited surface water. This scarcity makes it difficult to access adequate surface water for drinking, especially during drought. As a result, people in these areas usually turn to groundwater as an increasingly reliable and long-lasting drinking water supply [1]. Recent research indicates that there are 124 billion cubic meters (BCM) of river water, 70 billion cubic meters (BCM) of lake water, and 30 billion cubic meters (BCM) of groundwater throughout the nation [1]. Approximately 90% of Ethiopia’s potable drinking water is derived from groundwater due to its affordability compared to alternative water supply sources, especially in areas where surface water availability and rainfall have become more irregular [2, 3]. The groundwater quality in Ethiopia’s Rift Valley is at risk despite its critical relevance. Several variables may negatively affect the suitability of groundwater for irrigation and drinking [4]. Volcanic rock formations primarily characterize the Rift Valley in Ethiopia. Water sources in the region are limited to a few perennial streams, and despite numerous lakes, the region relies heavily on rainfall for its water supply. This is primarily due to surface water sources’ inadequate physical and chemical quality. The lack of data concerning water availability has led to a significant focus on assessing groundwater quality in this region [5].

Fluoride poses a significant health concern for communities in the Ethiopian Rift Valley that rely on groundwater sources [6–9]. Approximately 8 million people in this region consume water containing high fluoride levels [7]. Excessive fluoride intake can lead to a condition known as fluorosis, which can manifest as dental fluorosis (affecting teeth) or skeletal fluorosis (affecting bones). Dental fluorosis results in discoloration, pitting, and weakening of tooth enamel, while skeletal fluorosis can cause joint pain, stiffness, and skeletal deformities [10, 11]. It has been shown that prolonged consumption of such high-fluoride water can lead to dental and skeletal fluorosis among residents of the Rift Valley [12, 13]. Numerous studies conducted in various African nations, including Tanzania, Sudan, Nigeria, and Kenya, have consistently indicated that populations consuming excessively fluoridated water are more likely to develop dental fluorosis [14–16].

Water availability in the present study area, the Konso region of Southern Ethiopia, Rift Valley, is greatly affected by scarcity, quality issues, and seasonality. This unpredictability challenges both surface water and groundwater supply.In the Highlands, local communities rely primarily on intermittent springs for drinking water, agriculture, residential use, and industrial use, with limited access to the surface water. The region’s water resources are of significant importance, but a comprehensive evaluation of the deterioration of water quality for drinking and irrigation purposes has not been conducted. Furthermore, previous studies have not focused on essential aspects such as geological, hydrogeological, and hydrochemical research. Examining groundwater quality, identifying hydrogeochemical processes, and using groundwater resources are necessary for good management, as are promoting sustainable growth and protecting public health.

Hydrogeochemical assessment has dramatically enhanced a comprehensive understanding of groundwater quality by systematically consolidating intricate data matrixes [17–21]. In addition, this approach can identify potential sources of contamination affecting groundwater resources, which presents a promising tool for addressing contamination issues as soon as possible [22]. Therefore, hydrogeochemical studies are essential for determining and understanding the mechanisms that could affect groundwater quality [4].

Scholars widely use these indices to assess the suitability of water for human consumption. The spatial distribution and trends of groundwater quality variables can be better understood by combining and analyzing spatial data layers using a Geographic Information System (GIS) [23–25]. Through the visualization and management of large amounts of data, GIS facilitates the understanding of potential sources of contamination and the assessment of risks, thus contributing to informed decision making regarding the management and protection of groundwater [26]. As a result of its modelling capabilities, GIS contributes to proactive measures and sustainable resource utilization by predicting and simulating groundwater quality [27]. Recent research conducted in Ethiopia has used hydrogeochemical, GIS, and water quality indices to assess groundwater quality for various reasons [3, 28–32].

Numerous water quality assessment studies have been undertaken in Ethiopia, encompassing the Main Ethiopian Rift Valley region. Fito et al. [33] studied groundwater quality in Haramaya Woreda, Ethiopia, focusing on physicochemical and heavy metal constituents. Kujiek and Sahile [34] conducted a water quality assessment of Elgo River in Ethiopia using various indices (CCME, WQI, and IWQI) for domestic and agricultural uses. Tadesse et al. [35] assessed the physicochemical parameters and heavy metal levels in Rebu River, Oromia Region, Ethiopia. Menberu et al. [36] evaluated water quality and eutrophication status of Hawassa Lake using different water quality indices. Tibebe et al. [37] investigated spatiotemporal variations in selected water quality parameters and the trophic status of Lake Tana for sustainable management in Ethiopia. Dabassa and Demissie [38] evaluated physicochemical parameters and antimicrobial susceptibility patterns of microorganisms isolated from Awetu River, Jimma Town, Ethiopia. Kanno et al. [39] conducted a sanitary survey and assessed a treatment plant’s drinking water quality performance in Dilla Town, Ethiopia. Gule et al. [40] explored the implications of land use/land cover dynamics on urban water quality in Addis Ababa, Ethiopia. Getachew et al. [41] discussed the challenges for water quality protection in the greater metropolitan area of Addis Ababa and the upper Awash basin, Ethiopia. Kebede et al. [42] explored the impact of land cover change on water quality and stream flow in the Lake Hawassa watershed of Ethiopia.

Water quality is determined primarily by the water category and the amount of dissolved solids and salts [43, 44]. Irrigation has increased significantly due to the growth in irrigation operations and the increasing food demand in an expanding population [28, 45, 46]. Additionally, inadequate irrigation water quality negatively affects soil permeability, reducing crop production due to insufficient water availability [47]. Frequent monitoring of irrigation water quality is necessary to ensure that agricultural regions continue to flourish. To assess the quality of groundwater for irrigation, irrigation indices including “sodium percent (%Na), sodium absorption ratio (SAR), residual sodium carbonate (RSC), permeability index (PI), Keller index (KI), and magnesium hazard ratio (MHR)” are frequently utilized [48–50].

Using hydrochemical characterization and geographical evaluation, this study assesses the groundwater quality utilized for irrigation and drinking in the Konso Zone of the Rift Valley in Southern Ethiopia. The integrated approach allows an accurate evaluation of water sources by considering irrigation requirements and human consumption. During the hydrochemical analysis of the groundwater, elements such as dissolved solids were examined. In addition to carrying out a hydrochemical analysis, the study maps the various water quality characteristics using spatial evaluation methodologies. These findings contribute to a better understanding of the quality of the groundwater resources in the Konso Zone. Water resource managers and policymakers can use detailed insights about hydrochemical characteristics and water suitability to make informed water use and management decisions. This study provides a holistic perspective on groundwater quality by incorporating both human consumption and irrigation requirements.

In general, the novelty of this method lies in its focused examination of hydrochemical characteristics in a drought-prone area, the comprehensive evaluation of water suitability using several parameters, the utilization of advanced analytical techniques, and the potential implications for sustainable water resource management. It is important to note that these aspects contribute to our understanding of water quality in drought-prone regions and provide a valuable foundation for future research and practical application.

2. Materials and Methods

2.1. Description of the Research Area

The present study area, Konso Zone, is located between 37°11′ and 37°33′E longitude and 5°13′ and 5°39′N latitude in the Southern Nations, Nationalities, and Peoples’ Region, Ethiopia; this area has a total area of 1057 square kilometers. Within the larger research area, the study focuses on the settlements of Konso, Gewada, Gato, and Gidole. The study area’s altitude varies between 831 and 2712 meters above sea level, exhibiting a diverse topography. The area is divided into three main physiographic zones: rift, floor, escarpment, and plateau. The Main Ethiopian Rift is a geological feature of elongated rift valleys caused by tectonic plate movement. These rift valleys have lower heights than the surrounding plateaus and are frequently inhabited by rivers, lakes, and alluvial plains. Escarpments are steep slopes or cliffs that define the limits of distinct geological formations [51, 52]. In the Konso Zone, escarpments can operate as barriers to surface water flow, forcing water to accumulate or drain depending on the slope orientation [51, 52]. Plateaus are elevated, flat, or gently sloping terrain that frequently constitute large water catchment zones. Plateaus in the Konso Zone can be key groundwater recharge locations because rainwater infiltrates the soil and percolates downward into underlying aquifers [51, 52]. As a result of these discrete areas, the research area’s overall topography and hydrological characteristics are influenced. Within the research area, the drainage system follows a dendritic pattern, with water flowing primarily from the northwest to the southeast (Figure 1).

[figure(s) omitted; refer to PDF]

The research area is traversed by three major rivers: Iyenda, Delbena, and Segen, vital to the region’s hydrology and water supply. The region has two distinct precipitation peaks yearly, indicating a bimodal precipitation pattern. Primary rainy seasons occur between April and May, while secondary rainy seasons occur between September and October, characterized by comparatively lower rainfall amounts—the bimodal precipitation distribution in the Konso Zone results in separate wet and dry seasons. The primary rainy season typically lasts from June to September, with a second season occurring from February to May [53, 54]. During these rainy seasons, precipitation replenishes surface water bodies such as lakes, streams, rivers, and groundwater aquifers. More water is available to meet a variety of ecological and human needs, including ecosystem health, agriculture, and the provision of drinking water [53, 54]. Depending on the specific geographical features, temperature varies. In the rift floor region, the average monthly temperature ranges from 21°C to 27.4°C. Alternatively, the high-altitude plateau experiences a cooler climate, with average monthly temperatures ranging from 14.2 to 24.2°C. Several hydrological processes and ecosystem dynamics can be influenced by these temperature ranges, which reflect the climatic characteristics of the study area.

2.2. Geology and Hydrogeology

Lineaments refer to linear features or alignments in the landscape related to geological structures, such as faults or fractures, or to other processes, such as erosion or vegetation patterns. Visual interpretation of satellite imagery can help identify these features by looking for patterns of contrast or discontinuities in the landscape. The Landsat-8 OLI satellite image used in this study may have revealed such lineaments, which could provide crucial information on the underlying geology and hydrology of the study area. Identifying lineaments can also aid in selecting sites for drilling or borehole construction, as they may indicate potential zones of higher permeability or water storage. Moreover, fissures and weathering could significantly impact the ground’s ability to store groundwater. While aquifers with low productivity cover a large percentage of the land, the southwestern portion of the research area was determined to have high-yielding aquifers. Areas with low aquifer productivity are identified by the rugged topography near significant river basins, where the land is dissected by deep valleys and streams that flow towards major rivers along slopes. Because hard rock may not be sufficiently weathered by the infiltration of rainwater that moves as subsurface flow, these areas are typically found on the upper slopes of mountains, along water divides, and in rugged topography. The shallow groundwater flow does not show straight flow because, in the area, the shallow groundwater convergence and divergence depend on local barriers, topography, and lineaments. Figure 2 shows the hydrogeological map of the present study area.

[figure(s) omitted; refer to PDF]

2.3. Data Collection and Analysis

To achieve its objectives, the study employed a systematic approach involving on-site measurements conducted simultaneously with the collecting thirty water samples during a field visit. Factors such as population density, land use patterns, geological formations, and geomorphology were considered when selecting sampling locations for this groundwater composition study. To ensure the integrity of the water samples, thorough measures were taken before their collection. The bottles used to collect water samples were meticulously cleaned three times, first with distilled water and then with the actual sample water, to prevent contamination. To avoid spillage and to maintain accurate volume measurements, these bottles were filled to a height of approximately one to two inches below the brim.

The samples were immediately stored in an ice-filled cooler after collection to preserve their integrity and prevent any changes in their chemical composition during transportation. This ensured a minimum exposure to external factors that could affect their properties. As a result of the rapid delivery of samples to the laboratory, the fidelity of the data collected was maintained. To ensure consistency and reliability in the collected data, a standard and established sampling protocol [55] was adhered to during the dry season in May 2022. This approach collected water samples following prescribed guidelines and methodologies, contributing to the study’s robustness and validity.

Figure 1 illustrates where water sampling points were designated during fieldwork for visual representation and reference. To understand the geographic coverage of the study, this map provided a graphic representation of the spatial distribution of sampling sites. Additionally, Table​ 1 contains the results obtained from both in situ and laboratory assessments of the water samples to provide a comprehensive analysis and documentation. This detailed compilation included the results of on-site measurements and laboratory analyses. Table 1 shows the in situ and laboratory analysis of water samples.

Table 1

The sample locations and the values of various cations and anions.

Location id	X	Y	Z	pH	EC	TDS	Temp	Na+	K+	Mg2+	Ca2+	Fe2+	Cl−	NO3−	HCO3−	SO4−	F−
SP-1	315757	622491	2269	8.00	777	380	19.00	437.5	17.50	8.64	14.40	0.26	6.00	13.00	86.00	1.00	0.12
SP-2	315711	621871	2284	8.69	901	442	19.00	530.0	21.20	14.40	17.60	0.21	6.00	3.60	114.00	0.00	0.11
SP-3	321674	620395	1789	8.40	1558	768	24.00	392.5	15.70	34.56	27.20	0.18	8.00	2.40	226.00	3.00	0.14
RS-1	324009	614101	1275	9.00	1536	767	26.20	562.5	22.50	28.80	24.00	0.15	16.00	1.90	210.00	1.00	0.07
BH-1	324620	610367	1265	7.35	3990	2070	27.00	717.5	28.70	83.52	24.00	0.46	33.99	5.80	500.00	61.00	0.21
RS-2	326564	603725	1207	7.75	2520	1282	27.00	505.0	20.20	54.72	20.80	0.38	21.99	3.60	344.00	48.00	0.47
BH-2	327708	597704	1207	7.85	3020	1540	31.00	625.0	25.00	43.20	17.60	0.41	23.99	2.00	388.00	40.00	0.08
SP-4	322821	590181	1565	7.40	1873	942	24.50	497.5	19.90	44.16	25.60	0.28	8.00	2.30	320.00	3.00	0.22
SP-5	322206	590488	1555	7.46	3050	1566	23.90	360.0	14.40	77.76	16.00	0.43	31.99	14.50	464.00	12.00	0.06
RS-3	318746	595747	1400	7.78	2028	1023	24.00	535.0	21.40	36.48	27.20	0.31	21.99	2.50	360.00	7.00	0.34
RS-4	308487	595280	1505	9.00	1592	796	26.00	525.0	21.00	24.00	27.20	0.72	14.00	1.60	200.00	13.00	0.17
RS-5	308254	595793	1378	9.00	1577	788	30.00	580.0	23.20	28.80	20.80	0.44	16.00	1.20	216.00	14.00	0.10
RS-6	303079	596289	1294	8.70	7350	3940	34.00	650.0	26.00	139.20	8.00	0.52	105.97	1.10	446.00	232.00	0.58
BH-3	301343	596928	1290	8.30	5280	2780	30.40	600.0	24.00	78.72	20.80	0.42	89.97	1.40	384.00	124.00	0.85
RS-5	300916	597371	1286	8.90	3620	1872	32.00	515.0	20.60	73.92	19.20	0.36	35.99	2.40	198.00	98.00	0.39
SP-6	303723	602829	1600	8.30	2143	1083	31.50	422.5	16.90	59.52	16.00	0.24	16.00	4.40	412.00	1.00	0.08
SP-7	303314	603404	1624	7.95	1498	747	28.50	447.5	17.90	30.72	25.60	0.12	10.00	2.90	378.00	4.00	0.09
BH-4	303315	604728	1715	7.81	1382	688	29.70	452.5	18.10	21.12	17.60	0.23	10.00	1.90	182.00	7.00	0.06
RS-7	303590	606000	1656	9.05	1131	559	27.00	487.5	19.50	17.28	17.60	0.17	4.00	1.40	426.00	5.00	0.09
BH-5	303723	602829	1600	8.30	2510	1276	31.50	620.0	24.80	56.64	12.80	0.45	33.99	1.80	414.00	39.00	0.27
SP-8	329883	584769	1064	7.50	5320	2800	21.80	485.0	19.40	97.92	16.00	0.49	95.97	5.40	432.00	111.00	0.35
SP-9	331546	581476	945	8.40	13150	7300	21.50	627.5	25.10	245.76	8.00	2.30	345.89	0.10	138.00	392.00	0.63
BH-6	336564	578785	843	7.90	6330	3360	25.30	657.5	26.30	58.56	1.60	1.10	105.97	1.00	674.00	81.00	1.75
RS-8	336705	578784	860	8.00	4360	2270	24.30	532.5	21.30	29.76	8.00	0.43	69.98	1.10	502.00	9.00	1.66
SP-10	331017	582062	966	8.50	17210	9770	29.50	620.0	24.80	456.00	4.80	1.60	349.89	18.80	644.00	480.00	1.78
BH-7	329122	588888	1272	8.00	7090	3790	28.50	467.5	18.70	28.80	3.20	0.55	131.96	58.80	684.00	65.00	1.40
BH-8	326595	593103	1346	7.50	4570	2390	29.00	567.5	22.70	82.56	3.20	0.31	63.98	23.00	600.00	6.00	0.26
BH-9	327447	600628	1187	7.30	7590	4800	28.60	600.0	24.00	112.32	6.40	0.73	133.96	18.00	768.00	84.00	0.19
SP-11	329482	609539	1186	8.60	3020	1547	30.20	420.0	16.80	50.88	6.40	0.62	8.00	2.70	550.00	5.00	0.21
BH-10	324802	612868	1267	7.80	3450	1779	29.60	672.5	26.90	52.80	1.60	0.70	29.99	5.10	516.00	46.00	0.20

The HANNA HI 9811-5 handheld water analyzer kit measured total dissolved solids (TDS), electrical conductivity, and pH in situ. Before commencing the water analysis, each HANNA HI 9811-5 handheld water analyzer kit underwent a meticulous preparation process. This involved stringent checks and precise calibration against standard solutions at various testing stations. This calibration ensured the devices were accurately calibrated and ready for field deployment. A mercury thermometer submerged in water for an extended period to achieve perfect equilibrium was used to measure the temperature. To guarantee precise temperature measurements, a mercury thermometer was carefully submerged in water for an extended duration to attain optimal equilibrium. This step was crucial as accurate temperature readings are fundamental in water analysis [19, 56, 57]. At Arba Minch University, the analysis of groundwater samples for essential cations such as Ca²⁺, Mg²⁺, Na⁺, K⁺, and Fe²⁺ as well as anions such as HCO₃⁻, SO₄²⁻, F⁻, Cl⁻, and NO₃⁻ was conducted following the American Public Health Association (APHA) standards. The analysis takes between 24 and 48 hours to finish [15]. Volumetric titration, employing ethylene diamine tetraacetic acid (EDTA), was utilized to determine the concentrations of calcium and magnesium present in the groundwater samples. Additionally, the potassium and sodium concentrations were simultaneously measured using an absorption spectrophotometer, enhancing the efficiency and accuracy of the analysis [19, 56, 57]. To assess the chloride content, the American Public Health Association used its silver nitrate measurement method [55]. An acid titration approach was used to determine the amount of bicarbonate and carbonate in the water [19, 56, 57]. In contrast, an ion-selective electrode method was used to determine the amount of fluoride. To analyze sulfate and NO₃⁻, a DR 5000 Spectrophotometer was used. A Piper trilinear plot was used to examine the overall geochemical content of the groundwater in the study area.

The ion chemistry data were accurate using the charge balance error (CBE) in equation (1) [58]. To determine the accuracy of the calculation for significant ions, electroneutrality (EN) was used because both negative and positive charges must balance within the water:$$\begin{array}{}\text{(1)}& \text{CBE}=\frac{{\displaystyle \sum }\text{Cations}-{\displaystyle \sum }\text{Anions}}{{\displaystyle \sum }\text{Cations}+{\displaystyle \sum }\text{Anions}}\times 100\%.\end{array}$$

The measurements of cations and anions are expressed in milliequivalents per liter (meq/L). In particular, sums are computed for Cl⁻, HCO₃₋, and SO₄²⁻, as well as Na⁺, K⁺, Mg²⁺, and Ca²⁺. Other chemical parameters analyzed had relatively low concentrations, which had minimal impact on the charge balance error (CBE) accuracy. The calculated charge-balance error must not exceed 10% [17, 18, 22]. Based on the major ion concentrations, the CBE values were less than 0.5%, within the allowable limit. It is important to note that the threshold for CBE in this study is 10%.

Using the inverse distance weighted (IDW) spatial interpolation method, thematic layers of the ionic content, such as Ca²⁺, Mg²⁺, Na⁺, K⁺, Fe²⁺, HCO₃⁻, NO₃⁻, Cl⁻, and SO₄²⁻, and irrigation water quality indices, such as Sodium Percentage (%Na), Residual Sodium Carbonate (RSC), Sodium Adsorption Ratio (SAR), Kelly’s index (KI), magnesium hazard (MH), and Permeability Index (PI), were carried out to determine how they varied spatially varied within the research region.

The abovementioned chemical properties were assessed using equations (2)–(9) to determine whether using the water resources for irrigation and chloroalkaline indices, CAI-1 and CAI-2, in the research region is feasible.$$\begin{array}{}\text{(2)}& \text{Na\hspace{0.17em}}\%=\frac{{\text{Na}}^{+}+{\mathrm{K}}^{+}\times 100}{{\text{Ca}}^{2+}{{\text{Mg}}^{2+}+\text{Na}}^{+}+{\mathrm{K}}^{+}},\text{(3)}& \text{SAR}=\frac{{\text{Na}}^{+}}{\sqrt{{\text{Ca}}^{2+}+{\text{Mg}}^{2+}/2}},\text{(4)}& \text{RSC}={\text{Co}}_3^{2-}+{\text{HCO}}_3^{-}-{\text{Ca}}^{2+}+{\text{Mg}}^{2+},\text{(5)}& \text{PI}=\frac{{\text{Na}}^{+}+\sqrt{{\text{HCO}}_3^{-}}}{{\text{Ca}}^{2+}+{\text{Mg}}^{2+}+{\text{Na}}^{+}}\ast 100,\text{(6)}& \text{CAI}-1=\text{Cl}-\frac{{\text{Na}}^{+}+{\mathrm{K}}^{+}}{{\text{Cl}}^{-}},\text{(7)}& \text{CAI}-2=Cl-\frac{{\text{Na}}^{+}+{\mathrm{K}}^{+}}{{\text{SO}4}^{2-}+{\text{HCO}3}^{-}+{\text{CO}3}^{2-}+{\text{NO}3}^{-}},\text{(8)}& \mathrm{K}.\mathrm{I}.=\frac{{\text{Na}}^{+}}{{\text{Ca}}^{2+}+{\text{Mg}}^{2+}},\text{(9)}& \text{Magnesium\hspace{0.17em}Hazard\hspace{0.17em}}\mathrm{M}.\mathrm{H}.=\frac{{\text{Mg}}^{2+}}{{\text{Ca}}^{2+}+{\text{Mg}}^{2+}}\ast 100.\end{array}$$

3. Results and Discussion

3.1. Parameters Measured in the Field

It is estimated that the groundwater in the study area averages a temperature of 27.15°C and a temperature range of 19.30°C to 34°C. These temperatures are comparable to the ambient atmospheric temperature, showing a link between the two. Spring waters in the highland area were used to test the lowest groundwater temperature. In contrast, the highest temperature (discharge area) was compared to river water from the lowest raised area. Low temperatures indicate a shallow flow path and rapid infiltration [59].

The negative logarithm of the hydrogen ion, or pH, can be used to determine the acidity or alkalinity of groundwater. Water’s pH can significantly impact the solubility and mobility of certain minerals and compounds. The research area’s water samples had pH values ranging from 7.30 to 9.05, as shown in Table 2. The river water sample had the highest pH (9.05), while the borehole sample had the lowest (7.30). Only eight samples (26.6%) did not meet the 6.50–8.50 standard limit for drinking water recommended in [60]. Water samples from the area under investigation had an alkaline pH. The general quality, taste, and odor of groundwater can all be impacted by the presence of acidic or alkaline elements, which abnormally high pH readings can indicate. Acidic water can corrode metal components, letting lead, copper, zinc, and other heavy metals infiltrate into the water supply for drinking. However, high pH (alkaline) water may result in scaling and mineral deposits that reduce water flow and compromise the efficiency of water treatment facilities. Figure 3 shows the temperature and pH spatial maps.

Table 2

% of samples collected that exceed WHO’s acceptable limits [60] for drinking.

Parameters	Range	Mean	WHO (2011)	% samples above the standard limits	Excessive production of an undesirable consequence
pH	7.3–9.05	8.15	6.5–8.5	26.60	The mucous membrane, taste perception, and the water delivery system
EC	777–17210	4047.53	1000	93.30	Effect of high-concentration laxatives on humans
TDS	380–9770	2170.5	500	93.30	The human body’s gastrointestinal tract may get irritated as palatability declines
Na+	360-717.5	537.08	200	100	Exacerbates persistent congestive heart failure
K+	14.4–28.7	21.48	12	100	Effect of a strong laxative on human
Ca2+	1.6–27.2	15.30	75	0	A severe form of rickets is brought on by insufficiency, while kidney or bladder stones and urinary tract irritation are brought on by excess
Mg2+	8.64–456	72.38	50	50	Its salts have diuretic and cathartic effects. High concentrations could have laxative effects, primarily on first-time users
Fe2+	0.12–2.3	0.52	0.3	70	Constipation is the most typical gastrointestinal symptom; however, nausea, diarrhoea, and vomiting can all happen
Cl−	4–349.89	61.65	250	3.30	Some persons who suffer from heart or kidney disorders may be harmed. Affected include taste, dyspepsia, and palatability
NO3−	0.1–58.8	6.86	50	3.30	Methemoglobinemia in newborns who are bottle-fed
HCO3−	86–768	392.53	500	26.6	Reduces the plant’s ability to absorb nutrients, which causes chlorosis by allowing bicarbonate to enter the plant
SO42−	0–480	66.4	250	6.60	Laxative effects
F−	0.06–1.78	0.43	1.5	10	Above 1.5 mg/l poses a dental risk and too high concentrations can result in severe skeletal fluorosis

[figure(s) omitted; refer to PDF]

Estimating groundwater’s TDS level by adding up all dissolved ion concentrations is possible. In general, shallow groundwater in discharge areas has lower dissolved solids than in recharge zones, with higher dissolved solids than deeper groundwater [58]. TDS levels in groundwater samples range from 380 mg/L to 9770 mg/L, with the lowest levels in spring water collected at the highest elevation (recharge area) in the southern region.

In contrast, the highest TDS value was obtained in the northern part of the investigated area at the lower elevation (discharge area). These high TDS readings in the discharge area suggest that groundwater suffers extensive mineral elements leaching from the rocks through which it moves from recharge to the discharge area. That water had remained in the subsurface for an extended period. In the study area, the majority of the water samples collected were determined to be brackish, meaning that the water had a specific interaction with the surrounding rocks. These data suggest a medium residence time and a modest groundwater flow or circulation rate.

Electrical conductivity (EC) is a measure of dissolved ions in groundwater that can also be used to determine salinity potential. Numerous factors influence the EC of groundwater, including temperature, ion concentration, and the type of ions present [50]. The groundwater’s electrical conductivity ranges from 777 S/cm to 17210 S/cm, which surpasses [60] the permitted limit of 1000 S/cm for drinking water. Groundwater flowing through the path increased total dissolved solids (TDS) and electrical conductivity, likely due to prolonged water-rock contact. The amount of ions in water strongly relates to its electrical conductivity. TDS. content is positively correlated with groundwater electrical conductivity, which increases with increasing TDS content. Table 3 shows the TDS values in mg/L used by Freeze and Cherry [58] to classify groundwater. The spatial maps of EC and TDS are shown in Figure 4.

Table 3

Classification of groundwater based on TDS (mg/l) [58].

TDS in mg/L	Water types	Number of water samples > WHO standard	% samples > WHO standard
<1,000	Fresh	10	33.3
1,000–10,000	Brackish	20	66.6
10,000–100,000	Saline	Null	Null
>100,000	Brine	Null	Null

[figure(s) omitted; refer to PDF]

3.2. Hydrogeochemistry

3.2.1. Cations

Magnesium concentrations in the study region ranged from 8.64 to 456 mg/L, with a mean value of 72.38 mg/l (Figure 5). The calcium concentration ranged from 1.60 to 27.20 mg/L, with a mean value of 15.30 mg/L. The substantial water-rock interaction due to increasing depth and prolonged residence time in the subsurface resulted in the lowest calcium concentration in a shallow borehole. In contrast, the highest concentration was observed in river samples. According to Herschy’s [60] drinking water standards, roughly 50% of magnesium and 75% of calcium water samples are unfit for consumption due to extreme Ca²⁺ and Mg²⁺ concentrations. Magnesium present in the research area’s groundwater may have originated from the decomposition of ferromagnesian minerals such as pyroxene, olivine, dark-colored mica, and amphiboles, which are also found in metamorphic rocks such as chlorite, montmorillonite, and serpentine formations.

[figure(s) omitted; refer to PDF]

In the research area, sodium concentrations range from 360 to 719 mg/L, an average of 536 mg/l (Figure 5), with greater concentrations observed in water samples collected from the rift floor. Therefore, the concentration of Na⁺ increases from highland groundwater to rift floor groundwater, indicating a clear trend. The safe levels established by Herschy’s [60] drinking water regulations are not met by any water samples in the catchment. When water interacts vigorously with numerous acidic volcanic rocks in the direction of the groundwater flow, sodium is released into the groundwater. Potassium concentrations at the research site are usually high; all samples exceed safe levels for human consumption [60]. The content of K⁺ in the watershed samples varied from 14.4 to 28.7 mg/l, similar to that of Na⁺ (Figure 6). It has been suggested that the positive trend of the rift might be attributed to the weathering of K⁺₋ rich minerals (e.g., K-feldspars/orthoclases) in the originating rocks across the groundwater flow path [61].

[figure(s) omitted; refer to PDF]

In the research region, 70% of the water samples examined exceeded the maximum permissible limit of Fe²⁺ established by Herschy [60], with levels ranging from 0.12 to 2.30 mg/L (Figure 7). Despite being the primary sources of iron release in groundwater, such as pyroxene, amphibole, and olivine, natural weathering and dissolution processes of iron-rich minerals such as these significantly impact the concentration of iron in the water samples [61].

[figure(s) omitted; refer to PDF]

3.2.2. Anions

The most prevalent anion discovered in water samples from the Iyenda River basin is bicarbonate, followed by sulfates, chloride, and nitrates. Out of the water samples collected from the watershed, 26.6% exceeded the acceptable limit set by Herschy [60] for bicarbonate content. In contrast, the remaining samples show an average bicarbonate concentration of 393 mg/L, ranging from 86 to 768 mg/l (Figure 8). Consistent with the spatial maps’ increased Na⁺ and K⁺ content, the bicarbonate concentration increases from the rift floor to the highland escarpment. Fluoride is helpful in small concentrations (0.50 to 1.50 mg/L) in potable water because it aids in the hardening of tooth enamel, but high levels can induce dental and skeletal fluorosis. Although some local anomalies of high and low values were observed throughout the flow direction, the high-land aquifer generally had relatively low fluoride concentrations, indicating an increasing tendency towards the discharge area along the groundwater flow path. The fluoride concentration source in water samples is likely from minerals that contain fluoride, such as fluorite, as well as silicate minerals like muscovite, amphiboles, and biotite [62].

[figure(s) omitted; refer to PDF]

Even though the mean fluoride concentration in the study was 0.43 mg/l, with a range of 0.060 to 1.80 mg/L (Figure 9), 10% of the water samples studied surpassed the [60] maximum level for safe drinking water, suggesting that they were unfit for human consumption. Mining, industrial activities, agricultural techniques that use sulfate-containing fertilizers, sewage disposal, and farming practices can all influence sulfate and chloride concentrations in water samples. If these activities have not touched the research area, natural processes contributing to sulfate concentrations could be related to the oxidation of sulfide minerals or the dissolution of gypsum or anhydrite in the region’s geological formations. Sulfate concentrations in groundwater may increase due to high evaporation rates in the alluvial plain as sulfate minerals precipitate in soil. In contrast, chlorides are more likely to be present as pollutants due to their high solubility and rare occurrence as an essential mineral component [63]. The chloride concentration enters groundwater from different sources, such as rainwater and agricultural activity [64].

[figure(s) omitted; refer to PDF]

In areas with extensive chloride-containing fertilizers or disposal of chloride-rich effluents, chloride concentrations in groundwater can be significantly higher than natural levels. Therefore, it is essential to monitor and control human activities that may lead to increased chloride levels in groundwater to ensure the safety of drinking water sources. Aside from the progressive increase caused by groundwater evolution, the anomalous Cl⁻ and SO₄² content in the watershed’s rift floor section could be attributed to volcanic activity and lacustrine deposits. Figure 9 shows the spatial maps of sulfate and chloride.

The concentration of NO₃⁻ in the study area ranged from 0.100 to 58.8 mg/L, with a mean of 6.86 mg/L. Except for one water sample in the overpopulated settlements, almost all water samples in the watershed had NO₃⁻ values below the permitted level [60]. Agricultural activities and other human-related activities like animal husbandry and sewage, as well as excessive use of nitrogen-rich fertilizers such as urea and ammonium nitrate and inappropriate animal disposal of wastes, can contribute to the accumulation of nitrates in groundwater. Monitoring and regulating nitrate contamination in groundwater is critical because nitrates can cause health problems such as methemoglobinemia in babies and are difficult to remove once they enter the system.

3.3. Hydrochemical Facies and Evolution

The Ca-Na-HCO₃ groundwater is likely created in the catchment by weathering carbonate minerals in the aquifer. In contrast, NaCl groundwater is formed by the subsurface dissolving of halite deposits, and Ca-Mg/Cl groundwater is related to mixing groundwater with seawater or evaporite dissolution. The Piper diagram helps identify potential sources of pollution by providing information on the primary geochemical processes affecting groundwater quality. Ca-Na-HCO₃ water types were detected in escarpment or intermediate area water samples, indicating less geochemical evolution and no substantial water-rock contact, whereas Na-HCO3 water types imply highly developed and mineralized groundwater corresponds to the discharge area [3]. Despite other anions, such as SO₄²⁻ or Cl⁻ in some regions, HCO₃⁻ is the dominant anion identified in all water samples within the research area. In general, the cation and anion distribution in the studied region follows this pattern: Na⁺> Mg²⁺ > Ca²⁺ > K⁺ > Fe²⁺ and HCO₃⁻ > Cl⁻, SO₄²⁻ > NO₃⁻ > F⁻. Figure 10 shows the Piper diagram of the present study area.

[figure(s) omitted; refer to PDF]

Ion exchange, evaporation, and weathering of minerals are the three main processes that govern groundwater chemistry [59]. According to the Gibbs plot, which is utilized to identify the hydrochemical processes that contribute to groundwater chemistry, including precipitation and evaporation [65], poor groundwater quality and poor chemistry are primarily a result of evaporation and rock-water interaction. According to the Gibbs plot analysis (Figure 11), half of the water samples come from areas where rock weathering occurs, indicating that evaporation and water-rock interaction are the primary natural processes affecting groundwater chemistry.

[figure(s) omitted; refer to PDF]

3.4. Ion Exchange Processes

The numerous chemical changes groundwater undergoes as it travels beneath the surface must be understood [66]. According to [67], the ion exchange between groundwater and its host surroundings can be measured using the chloralkaline indices, CAI-1 and CAI-2, and their values can be positive and negative. Positive results indicate that the Mg²⁺ and Ca²⁺ ions from the rocks interact with the Na⁺ and K⁺ ions in the water. Cation-anion direct base exchange is demonstrated in this example. On the other hand, suppose the index is negative. This indicates the chloroalkaline disequilibrium between the water’s Mg²⁺ and Ca²⁺ ions and the rocks’ Na⁺ and K⁺ ions.

The chloralkaline indices were determined for the research area’s water samples. It was discovered that the CAI-1 values range between −197.14 and 7.07 (Figure 12), and the CAI-2 values fall between −12.08 and 8.54 (Figure 13). Most of the samples’ computed CAI-1 and CAI-2 values, which on average have values of −45.01 and −2.28, respectively, practically all exhibit negative results. Na⁺ and K⁺ in the aquifer material with Ca²⁺ and Mg²⁺ in the groundwater exchanged ions, resulting in the negative chloralkaline index. This explains why groundwater Na+ and K+ concentrations rise along groundwater flow directions as depth increases while Ca²⁺ and Mg²⁺ concentrations fall. The outcome of these indices showed that forward ion exchange in groundwater is the dominant activity, whereas only a small number of water samples exhibit reverse ion exchange.

[figure(s) omitted; refer to PDF]

3.5. Suitability for Irrigation Purposes

Water quality substantially impacts crop productivity, soil fertility, and environmental safety during irrigation, as excess dissolved ions in irrigation water can reduce crop production, soil permeability, and work performance of irrigation systems, diminishing their performance [68]. By developing irrigation quality indices, including SAR, %Na, RSC, and PI, the objective was to assess the suitability of groundwater for irrigated agriculture in the Konso region and its importance and regional variability. Table 4 displays the irrigation water quality indicators in water samples from the research area.

Table 4

Irrigation water quality indices in water samples from the study area.

Water quality indices in meq/L	Range	Class	Number of samples	Percent
SAR	<10	Excellent	30	100
	10–18	Good	0	0
	18–26	Doubtful	0	0
	>26	Unsuitable	0	0
%Na	<20	Excellent	0	0
	20–40	Good	0	0
	40–60	Permissible	2	6.67
	60–80	Doubtful	8	26.67
	>80	Unsuitable	20	66.67
RSC	<1.25	Safe	18	60
	1.25–2.5	Marginally suitable	4	13.33
	>2.5	Not suitable	8	26.67
PI	>75	Excellent	28	93.33
	25–75	Good	2	6.67
	<25	Unsuitable	0	0

3.6. U.S. Salinity Diagram and Sodium Absorption Ratio (SAR)

A significant determinant of irrigation groundwater quality is the SAR [50]. This method is critical in assessing the potential risk of sodium or alkali-related issues in soil due to irrigation practices. When sodium replaces calcium and magnesium (alkaline earth metals) in the soil, it adheres to clay surfaces, damaging the soil’s structure. When sodium attaches itself to clay particles, it disrupts the natural arrangement, causing the soil structure to collapse. As a result of this disruption, the soil is often compacted, and its permeability is reduced, obstructing water and air movement within the soil. Consequently, this inhibits root growth, nutrient absorption, and overall plant development [69]. The soil becomes compacted and impermeable, posing significant obstacles to the healthy growth of plants.

Excess sodium ions in irrigation water can exacerbate these issues, further altering the soil structure. The presence of high levels of Na⁺ can increase the density and impermeability of soil, making it unsuitable for agricultural use. Determining the SAR in irrigation water is crucial to determine the relative sodium concentration to calcium and magnesium ions. In addition to serving as an indicator of the potential hazards posed by excessive sodium levels, this ratio determines whether water is suitable for irrigation. In order to calculate the SAR, ion concentrations are expressed in milliequivalents per liter (meq/L). The SAR provides insight into the risk of soil structural degradation caused by high sodium levels by comparing the concentrations of Na⁺, Ca²⁺, and Mg²⁺ ions in irrigation water.

Figure 14 illustrates the U.S. Salinity chart for assessing salinity and alkalinity hazards in irrigation water. This chart shows a visual representation of the potential risks associated with different salinity and alkalinity levels in irrigation water. Figure 14 is divided into four salinity classes (C1, C2, C3, and C4) and four sodium hazard classes (S1, S2, S3, and S4). The most suitable irrigation water for most crops falls in the C1S1 class, which has low salinity and low sodium hazard. Water in the C2S1 and C3S1 classes can be used for irrigation but with some limitations. Water in the C4S1 and higher classes is generally not suitable for irrigation. In the present study, the number of samples falls into the following categories C1: Low salinity (C1-S1, C1-S2) 0 samples, C2: Medium salinity (C2-S1, C2-S2) 2 samples, C3: High salinity (C3-S1, C3-S2, C3-S3) 12 samples, C4: Very high salinity (C4-S1, C4-S2, C4-S3) 2 samples. In addition, Figure 15 illustrates the spatial distribution of SAR values, which provides a geographical perspective on areas susceptible to soil structural issues due to sodium-rich irrigation water.

[figure(s) omitted; refer to PDF]

3.7. Wilcox Diagram and Sodium Percentage (%Na)

Increasing salt in water can reduce soil permeability, reducing water and air circulation in the soil layer throughout rainy seasons [69]. Sodium content, due to its impact on soil permeability, is an essential factor used to categorize irrigation water and assess groundwater’s suitability for irrigation. An important factor in determining irrigation water quality is the amount of sodium present, expressed as a percentage of the overall sodium concentration [70]. Equation (2) was used to calculate the sodium percentage, and the ion concentrations are reported in milligrams per liter.

The findings revealed that the amount of Na⁺ in the groundwater system was 80.5%, indicating that the sodium percentage in the research location ranged from acceptable to unacceptable [70]. In the study region, the more significant percentage of Na⁺ is from the weathering of felsic, volcanic, and metamorphic rocks and ion exchange processes, making most water samples unsuitable for irrigation (Figures 16 and 17).

[figure(s) omitted; refer to PDF]

The Wilcox diagram is a graphical representation of the suitability of irrigation water for various crops. It is based on two key factors: EC of the water, which is a measure of the salinity, and the SAR, which is a measure of the relative concentration of sodium ions compared to calcium and magnesium ions. The diagram is divided into four zones: excellent to good, good to permissible, doubtful to unsuitable, and unsuitable. The suitability of water for irrigation depends on the crop’s tolerance to salinity and sodium. More tolerant crops can be irrigated with water in the “excellent to good” or “good to permissible” zones.

In contrast, less tolerant crops can only be irrigated with water in the “excellent to good” zone. In the present study, the Wilcox diagram shows that the water sample falls in the “doubtful to unsuitable” zone. This means the water is moderately saline and has a high sodium adsorption ratio. This water may not be suitable for irrigation of all crops, and it is essential to consider the tolerance of the crop that wants to grow before using this water.

3.8. Residual Sodium Carbonate (RSC)

Water’s suitability for irrigation depends on how much carbonate and bicarbonate it contains, as well as calcium and magnesium. Negative RSC values indicate safe irrigation since they indicate that soil structure will not be compromised and that water and airflow will be constrained [71]. The analysis of RSC levels in water in the region discovered a range of −27 to 8.69 meq/L, with 60% of the samples appropriate for irrigation, 13.33% slightly suitable, and 26.67% unsuitable.

According to this investigation, most groundwater samples (73.33%) were rated as “Good to Doubtful” and were discovered in the Highland and transitional escarpment regions, making them exceptionally suited for irrigation. However, 26.67% of the collected samples were deemed inappropriate and found in the southeast and northeastern sections of the catchment. Figure 18 shows the spatial distribution of RSC.

[figure(s) omitted; refer to PDF]

3.9. Permeability Index (PI)

The amount of magnesium, salt, bicarbonate, and calcium in the soil is associated with the permeability of the soil and the quality of irrigation water [72]. According to the findings, 93.33% of groundwater samples collected throughout the research region are classed as Class I using the PI criterion, while the remaining 6.67% are classified as Class II. All samples in the research area fall into class I or II, and PI values show that the water is suitable for this use (Figure ​ 19), which is good to excellent for irrigation purposes. Figure 20 shows the spatial distribution of PI.

[figure(s) omitted; refer to PDF]

3.10. Kelly’s Index

The Kelly index was used to assess the suitability of water samples from the Konso region for irrigation. According to the results, Kelly’s index ranged from 0.714 to 13.3. Except for one water sample, all samples had Kelly’s index values greater than one, indicating they were unsuitable for irrigation [73]. A great majority, 96.6%, of the water samples obtained from the study area demonstrated poor water quality for irrigation, as indicated by the Kelly ratio index. In other words, the vast majority of the water in the region does not meet the necessary standards to support healthy crop growth and sustainable irrigation practices. However, the study also identified a small percentage, approximately 3.33%, of water samples deemed suitable for irrigation due to a favourable Kelly’s index value. Within the study area, these selected water samples were the only exceptions that met the requirements for supporting agricultural activities. Figure 21 shows the spatial distribution map of Kelly’s ratio.

[figure(s) omitted; refer to PDF]

3.11. Magnesium Hazard

As indicated in [74], the magnesium adsorption ratio (MH) above 50 has detrimental effects on the soil. The magnesium (Mg²⁺) concentration in water is critical in determining the predominant alkaline earth element. Groundwater with high magnesium levels can cause alkalinity in the soil. In addition, clay and magnesium particles absorb excessive amounts of water, reducing soil infiltration capacity and negatively impacting crop growth [74]. Most liquids maintain a balance between calcium and magnesium when they are in equilibrium.

In contrast, an increase in magnesium concentration disrupts this equilibrium and negatively impacts crop production. MH values ranged from 49.72 to 99.37 in the study area, averaging 81.27. According to these results, 96.67% of the water samples were unsuitable for irrigation. As a comparison, MH values appropriate for irrigation were found in 3.33% of the water samples. According to the research area, the mean value of MH is 81.27, ranging from 49.72 to 99.37. Based on these numbers, 96.67% of the water samples were inappropriate for irrigation, while only 3.33% were suitable for irrigation (Table 5). Figure 22 shows the spatial distribution map of the magnesium hazard.

Table 5

Magnesium hazard for irrigation water.

MH category	No. of samples	% samples
Less than 25 (suitable)	0	0
25–50 (permissible)	1	3.33
50–75 (doubtful)	10	33.33
75–100 (unsuitable)	19	63.33

[figure(s) omitted; refer to PDF]

3.12. Discussion

An assessment of the water quality in the Konso region of Southern Ethiopia for agricultural and drinking purposes was conducted using hydrogeochemical and Geographic Information System (GIS) techniques. Thirty primary subsurface water samples were examined for their physicochemical characteristics. It was identified that the predominant cations and anions in the area were Na⁺, Mg²⁺, Ca²⁺, K⁺, Fe²⁺, and HCO₃₋, Cl⁻, SO₄²⁻, NO₃⁻, and F⁻. The key findings of the present study are as follows. The groundwater was divided into four types, with Na-HCO3 being the most prevalent and associated with ion exchange. In contrast, the Na-HCO3 type is associated with cation exchange in siliciclastic aquifers, and the other classes are Ca-Na-HCO₃, NaCl, and Ca-Mg/Cl. The Gibbs diagram data show that 50% of the water samples were discovered in areas where rocks weather, indicating that the interaction of water and rock is the essential natural mechanism affecting the chemical composition of groundwater. TDS and SO₄²⁻ are pollutants that impact groundwater quality. According to the WHO drinking water quality standards, the allowed F− (1.50 mg/l) was surpassed by approximately 10% of the water samples, making them unsafe for consumption. Moreover, numerous other readings, including pH (26.6%), TDS (93.3%), Na⁺ (100%), K⁺ (100%), Mg²⁺ (50%), Fe²⁺ (50%), Cl⁻ (3.3%), NO₃⁻ (3.3%), EC (93.3%), SO₄²⁻ (6.60%), and HCO₃₋ (26.6%), were also over the acceptable limit. Contrarily, most of the water samples from the Konso area were suitable for irrigation applications, except for Na% (66.6%), which is not good for irrigation. On the other hand, SAR (100%), RSC (60%), and PI (93.3%) are acceptable. In addition to the well-known aquifer heterogeneity, the slow evolution of groundwater caused by rock-water interactions (such as silicate hydrolysis and cation exchange along the flow path) affects groundwater quality in the study area’s rift floor region, where the majority of the water samples are unfit for drinking and agricultural use.

The U.S. Salinity chart provides a visual representation of irrigation water salinity and sodium hazards. Water is classified into different salinity and sodium hazard classes for irrigation purposes. According to the study, the majority of samples are classified as high salinity (C3 and C4), indicating that irrigation is not suitable. The spatial distribution of SAR values provides insight into areas potentially prone to soil structural issues as a result of sodium-rich irrigation water. The findings indicate that a significant portion of groundwater samples exhibit high sodium percentages, rendering them unsuitable for irrigation, primarily attributed to weathering processes and ion exchange mechanisms from specific rock types. Based on EC and SAR values, the Wilcox diagram categorizes water samples for irrigation. Most samples fall into the “doubtful to unsuitable” zone, suggesting moderately saline water with a high sodium adsorption ratio. Thus, crop tolerance to salinity and sodium should be considered when considering these water sources for irrigation.

RSC values show that a significant percentage of groundwater samples are rated “Good to Doubtful,” particularly in Highland and transitional escarpment regions. Samples deemed inappropriate are concentrated in specific geographical areas, emphasizing spatial variability in water quality. According to the PI criteria, the majority of groundwater samples meet Class I or II standards, indicating good to excellent irrigation suitability. Based on Kelly index results, most samples are unsuitable for irrigation due to high values, meaning a shortage of water sources that meet essential crop growth standards. Additionally, MH values reveal that most groundwater samples in the region are unsuitable for irrigation due to high magnesium concentrations that cause soil alkalinity issues.

Within the domain of water quality assessment, contrasting present studies with recent ones is an essential means to comprehend the progression and advancements within this field. Several studies concerning water quality have been executed across the Main Ethiopian Rift Valley, and the subsequent summary encapsulates their key findings. In [42], the authors analyzed the effect of land use/land cover change (LULCC) on water quality and quantity in the Lake Hawassa watershed of Ethiopia. Water quality parameters such as turbidity, suspended solids, total dissolved solids, and electrical conductivity were significantly higher due to LULC changes [34]. Water Quality Assessment was conducted in Elgo River, Rift Valley, in Ethiopia, using the Canadian Council of Ministers of the Environment Water Quality Index (CCME), WQI, and Irrigation Water Quality Index (IWQI) for domestic and agricultural usage. The results showed that the CCME WQI categorization indicates that the Elgo River water is classified as poor, with results ranging from 0 to 44, indicating unsuitability for various uses, including domestic and agricultural purposes. The water quality and eutrophication status of Hawassa Lake (Ethiopian Rift Valley Lake) were evaluated based on different water quality indices, and the study results showed that the water quality of the lake was unfit. It is clear from the mentioned studies that most of the water quality in the Main Ethiopian Rift Valley is problematic due to geological interaction, LULC changes, and anthropogenic activities.

When brackish TDS, sodium concentrations, and fluoride levels in groundwater exceed the recommended thresholds in Ethiopia’s Rift Valley, assessing the associated health risks is necessary. Total Dissolved Solids (TDS) and sodium concentrations, ranging from 360 to 719 mg/L, are above WHO drinking water standards. Long-term exposure to high levels of TDS can adversely affect human health, potentially resulting in digestive issues as well as an increased risk of cardiovascular disease. It should also be noted that elevated sodium levels can result in hypertension or cardiovascular problems in susceptible individuals. Understanding the extent of these risks to the local population’s health requires conducting a comprehensive health risk assessment. In addition, the fluoride concentration, averaging 0.43 mg/L with a range of 0.060 to 1.80 mg/L, is also of concern.

A small amount of fluoride is necessary for dental health. However, excessive consumption can cause dental and skeletal fluorosis, posing significant health risks. To safeguard the local population’s health, it is necessary to assess the potential health effects of fluoride levels above the WHO recommended range. An evaluation of human health risk involves evaluating exposure pathways, assessing the population’s vulnerability, and determining potential adverse health effects. Groundwater contamination can be ingested, inhaled, or contacted through dermal contact. A vulnerability assessment must consider factors such as age, health status, and duration of exposure.

4. Conclusion

An assessment of the water quality in the Konso region of Southern Ethiopia for agricultural and drinking purposes was conducted using hydrogeochemical and GIS techniques. Groundwater in this area has a wide range of fluoride concentrations ranging from 0.06 mg/L to 1.78 mg/L. The highest levels of fluoride were observed in the rift area, suggesting a possible connection with the geological composition of the volcanic rocks sourced in the region. Various rocks are included in this group, such as ignimbrite, rhyolite, tuff, and lacustrine sediments. Furthermore, geothermal activity along groundwater flow routes and the heterogeneous distribution of fluoride-bearing minerals may have contributed to the elevated fluoride concentrations. To ensure drinking water safety, it is crucial to understand fluoride levels and their regional distribution to implement appropriate strategies.

In the area’s groundwater, Na⁺, Mg²⁺, Ca²⁺, K⁺, Fe²⁺, and HCO₃₋ dominated as dominant cations and anions. This investigation revealed several key findings. There were diverse classifications of groundwater present, primarily the Na-HCO3 type associated with ion exchange, reflecting the various types of aquifer, including Na-HCO₃, Ca-Na-HCO₃, NaCl, and Ca-Mg/Cl. Rock weathering processes significantly influenced the chemical composition of groundwater in approximately 50% of samples, while pollutants like TDS and SO₄²⁻ adversely affected its quality. According to the WHO standards, approximately 10% of samples exceeded the permitted F- levels, rendering them unfit for human consumption. The pH, TDS, Na⁺, K⁺, Mg²⁺, Fe²⁺, Cl⁻, NO₃⁻, EC, SO₄²⁻, and HCO₃₋ readings also exceeded acceptable limits. In contrast, most samples were considered suitable for irrigation, except those containing a high Na% content, indicating that such a use was inappropriate. However, SAR, RSC, and PI values were generally within acceptable limits.

The study emphasized the considerable unsuitability of most groundwater samples for drinking and agriculture due to fluoride concentration variations (0.06 mg/L to 1.78 mg/L), particularly in the rift area, possibly related to regional geology and geothermal activity. To ensure the safety of drinking water, it is crucial to understand the distribution of fluoride levels. Moreover, the comprehensive evaluation using a variety of indicators and diagrams revealed the heterogeneous nature of groundwater quality, highlighting prevalent issues with elevated salinity, sodium content, and magnesium hazards, which necessitate targeted interventions for sustainable irrigation practices and agricultural development. The detailed assessment of groundwater quality in the Konso region sheds light on a variety of factors that affect water suitability for consumption and irrigation. Strategic interventions and continuous monitoring are necessary to safeguard water resources and ensure safe drinking water sources and sustainable agricultural practices.

Based on the findings of this study, future research can be conducted in some areas related to water quality and management in the Konso region. Studies of long-term monitoring can provide valuable insights into the region’s temporal variability of water quality parameters. We investigate the geological and hydrological factors that control groundwater quality in detail, assess the potential health effects of elevated fluoride levels in drinking water, and develop and evaluate effective water treatment technologies to remove fluoride and other contaminants from groundwater.

This study acknowledges certain limitations, particularly in terms of representative sampling. Despite the limited spatial coverage, this was mainly due to the inaccessibility and security threats associated with specific areas within the Konso Zone. Nonetheless, the selected sites were chosen to be representative of the diverse hydrogeological conditions, land uses, and potential pollution sources in the region. Water quality assessments across a study area can be logistically challenging and resource-intensive. This study maximized the efficient use of resources, including time, workforce, and laboratory analysis, by focusing on a manageable number of sites. As a result of this approach, a more detailed analysis of the selected sites is possible, resulting in valuable insights within the constraints available.

Acknowledgments

The funding for this study was provided by Arba Minch University, Ethiopia (Grant No. GOV/AMU/TH4/GEOL/02/2011), and the authors express their gratitude for this support. The first author also extends thanks to the International Sustainability Academy (ISA), a project of SDW Hamburg, for providing intensive training and funding to the project for an eight-month fellowship period in Hamburg, Germany.

References

[1] B. Berhanu, Y. Seleshi, A. M. Melesse, Surface Water and Groundwater Resources of Ethiopia: Potentials and Challenges of Water Resources Development. Nile River Basin, 2014.

[2] N. Adimalla, R. Dhakate, A. Kasarla, A. K. Taloor, "Appraisal of groundwater quality for drinking and irrigation purposes in Central Telangana. India," Groundwater for Sustainable Development, vol. 10,DOI: 10.1016/j.gsd.2020.100334, 2020.

[3] G. T. Bawoke, Z. L. Anteneh, "Spatial assessment and appraisal of groundwater suitability for drinking consumption in Andasa watershed using water quality index (WQI) and GIS techniques: blue Nile Basin. Northwestern Ethiopia," Cogent Engineering, vol. 7 no. 1,DOI: 10.1080/23311916.2020.1748950, 2020.

[4] T. T. Aragaw, G. Gnanachandrasamy, "Evaluation of groundwater quality for drinking and irrigation purposes using GIS-based water quality index in urban area of Abaya-Chemo sub-basin of Great Rift Valley, Ethiopia," Applied Water Science, vol. 11 no. 9,DOI: 10.1007/s13201-021-01482-6, 2021.

[5] S. M. R. Bonetto, C. Caselle, D. A. De Luca, M. Lasagna, "Groundwater resources in the main Ethiopian Rift Valley: an overview for a sustainable development," Sustainability, vol. 13 no. 3,DOI: 10.3390/su13031347, 2021.

[6] H. Kloos, R. T. Haimanot, "Distribution of fluoride and fluorosis in Ethiopia and prospects for control," Tropical Medicine and International Health, vol. 4 no. 5, pp. 355-364, DOI: 10.1046/j.1365-3156.1999.00405.x, 1999.

[7] T. Rango, J. Kravchenko, B. Atlaw, P. G. McCornick, M. Jeuland, B. Merola, A. Vengosh, "Groundwater quality and its health impact: an assessment of dental fluorosis in rural inhabitants of the Main Ethiopian Rift," Environment International, vol. 43, pp. 37-47, DOI: 10.1016/j.envint.2012.03.002, 2012.

[8] T. Rango, A. Vengosh, M. Jeuland, R. Tekle-Haimanot, E. Weinthal, J. Kravchenko, C. Paul, P. McCornick, "Fluoride exposure from groundwater as reflected by urinary fluoride and children’s dental fluorosis in the Main Ethiopian Rift Valley," Science of the Total Environment, vol. 496, pp. 188-197, DOI: 10.1016/j.scitotenv.2014.07.048, 2014.

[9] T. Rango, A. Vengosh, M. Jeuland, G. M. Whitford, R. Tekle-Haimanot, "Biomarkers of chronic fluoride exposure in groundwater in a highly exposed population," Science of the Total Environment, vol. 596-597,DOI: 10.1016/j.scitotenv.2017.04.021, 2017.

[10] T. Rango, J. Kravchenko, B. Atlaw, P. Mccornick, M. Jeuland, B. Merola, A. Vengosh, "Groundwater quality and its health impact: an assessment of dental fluorosis in rural inhabitants of the Main Ethiopian Rift," Environment International, vol. 43, pp. 37-47, DOI: 10.1016/j.envint.2012.03.002, 2012.

[11] M. Haji, D. Wang, L. Li, D. Qin, Y. Guo, "Geochemical evolution of fluoride and implication for F− enrichment in groundwater: example from the bilate River basin of southern main Ethiopian rift," Water, vol. 10 no. 12,DOI: 10.3390/W10121799, 2018.

[12] S. Dey, B. Giri, "Fluoride fact on human health and health problems: a review," Reviews in Clinical Medicine, vol. 02 no. 01,DOI: 10.21767/2471-299x.1000011, 2016.

[13] F. Wondwossen, A. N. Åstrøm, K. Bjorvatn, A. Bårdsen, "The relationship between dental caries and dental fluorosis in areas with moderate-and high-fluoride drinking water in Ethiopia," Community Dentistry and Oral Epidemiology, vol. 32 no. 5, pp. 337-344, DOI: 10.1111/j.1600-0528.2004.00172.x, 2004.

[14] J. Malago, E. Makoba, A. N. Muzuka, "Fluoride levels in surface and groundwater in Africa: a review," American Journal of Water Science and Engineering, vol. 3 no. 1,DOI: 10.11648/j.ajwse.20170301.11, 2017.

[15] M. Dessalegne, F. Zewge, "Daily dietary fluoride intake in rural villages of the Ethiopian Rift Valley," Toxicological and Environmental Chemistry, vol. 95 no. 6, pp. 1056-1068, DOI: 10.1080/02772248.2013.827685, 2013.

[16] A. A. Mohammadi, M. Morovati, H. Najafi Saleh, S. Ghale Askari, M. Ghaderpoori, M. Shams, S. Kalteh, S. Sadeghi, "Groundwater quality evaluation for drinking and industrial purposes. A case study in northeastern Iran," International Journal of Environmental Analytical Chemistry, vol. 102 no. 17, pp. 6094-6104, DOI: 10.1080/03067319.2020.1807533, 2020.

[17] N. H. Hussin, I. Yusoff, W. Z. Wan Muhd Tahir, I. Mohamed, A. I. N. Ibrahim, A. Rambli, "Multivariate statistical analysis for identifying water quality and hydrogeochemical evolution of shallow groundwater in Quaternary deposits in the Lower Kelantan River Basin, Malaysian Peninsula," Environmental Earth Sciences, vol. 75 no. 14,DOI: 10.1007/s12665-016-5705-3, 2016.

[18] Y. Zhou, P. Li, L. Xue, Z. Dong, D. Li, "Solute geochemistry and groundwater quality for drinking and irrigation purposes: a case study in Xinle City, North China," Geochemistry, vol. 80 no. 4,DOI: 10.1016/j.chemer.2020.125609, 2020.

[19] N. S. Kawo, S. Karuppannan, "Groundwater quality assessment using water quality index and GIS technique in Modjo River Basin, Central Ethiopia," Journal of African Earth Sciences, vol. 147, pp. 300-311, DOI: 10.1016/j.jafrearsci.2018.06.034, 2018.

[20] B. Panneerselvam, S. Karuppannan, K. Muniraj, "Evaluation of drinking and irrigation suitability of groundwater with special emphasizing the health risk posed by nitrate contamination using nitrate pollution index (NPI) and human health risk assessment (HHRA)," Human and Ecological Risk Assessment: An International Journal, vol. 27 no. 5, pp. 1324-1348, DOI: 10.1080/10807039.2020.1833300, 2020.

[21] P. Balamurugan, P. S. Kumar, K. Shankar, "Dataset on the suitability of groundwater for drinking and irrigation purposes in the Sarabanga River region, Tamil Nadu, India," Data in Brief, vol. 29,DOI: 10.1016/j.dib.2020.105255, 2020.

[22] A. Ghobadi, M. Cheraghi, S. Sobhanardakani, B. Lorestani, H. Merrikhpour, "Hydrogeochemical characteristics, temporal, and spatial variations for evaluation of groundwater quality of Hamedan–Bahar Plain as a major agricultural region, West of Iran," Environmental Earth Sciences, vol. 79 no. 18,DOI: 10.1007/s12665-020-09177-y, 2020.

[23] Z. F. Makki, A. A. Zuhaira, S. M. Al-Jubouri, R. K. S. Al-Hamd, L. S. Cunningham, "GIS-based assessment of groundwater quality for drinking and irrigation purposes in central Iraq," Environmental Monitoring and Assessment, vol. 193 no. 2, pp. 107-127, DOI: 10.1007/s10661-021-08858-w, 2021.

[24] M. Silva, A. M. L. Gonçalves, W. A. Lopes, M. T. V. Lima, C. T. F. Costa, M. Paris, P. R. A. Firmino, F. J. De Paula Filho, "Assessment of groundwater quality in a Brazilian semi-arid basin using an integration of GIS, water quality index and multivariate statistical techniques," Journal of Hydrology, vol. 598,DOI: 10.1016/j.jhydrol.2021.126346, 2021.

[25] N. Rajmohan, M. H. Z. Masoud, B. A. M. Niyazi, "Assessment of groundwater quality and associated health risk in the arid environment, Western Saudi Arabia," Environmental Science and Pollution Research, vol. 28 no. 8, pp. 9628-9646, DOI: 10.1007/s11356-020-11383-x, 2021.

[26] B. M. Reddy, V. Sunitha, M. Prasad, Y. S. Reddy, M. R. Reddy, "Evaluation of groundwater suitability for domestic and agricultural utility in semi-arid region of Anantapur, Andhra Pradesh State, South India," Groundwater for Sustainable Development, vol. 9,DOI: 10.1016/j.gsd.2019.100262, 2019.

[27] V. Sunitha, B. M. Reddy, "Geochemical characterization, deciphering groundwater quality using pollution index of groundwater (PIG), water quality index (WQI), and geographical information system (GIS) in hard rock aquifer, South India," Applied Water Science, vol. 12 no. 3,DOI: 10.1007/s13201-021-01527-w, 2022.

[28] G. Beyene, D. Aberra, F. Fufa, "Evaluation of the suitability of groundwater for drinking and irrigation purposes in Jimma Zone of Oromia, Ethiopia," Groundwater for Sustainable Development, vol. 9,DOI: 10.1016/j.gsd.2019.100216, 2019.

[29] A. Gidey, "Geospatial distribution modeling and determining suitability of groundwater quality for irrigation purpose using geospatial methods and water quality index (WQI) in Northern Ethiopia," Applied Water Science, vol. 8 no. 3,DOI: 10.1007/s13201-018-0722-x, 2018.

[30] A. Arota, A. Atlabachew, A. Abebe, M. Jothimani, "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, vol. 9 no. 2, pp. 3367-3377, DOI: 10.15243/jdmlm.2022.092.3367, 2022.

[31] B. Tigistu, A. Abunu, A. Abel, G. Jagadeshan, J. Murlitharan, "Hydrogeochemical characterization and assessment of groundwater chemistry in Satama River catchment, Ethiopia," Indian Journal of Environmental Protection, vol. 41 no. 10, pp. 1160-1165, 2023.

[32] A. Demelash, A. Atlabachew, M. Jothimani, A. Abebe, "Hydrogeochemical characterization and appraisal of groundwater quality in yisr river catchment, blue nile River basin, Ethiopia, by using the GIS, WQI, and statistical techniques," Journal of Chemistry, vol. 28, 2023.

[33] J. Fito, G. Bultosa, H. Kloos, "Correction to: physicochemical and heavy metal constituents of the groundwater quality in Haramaya Woreda, Oromia regional state, Ethiopia," International Journal of Energy and Water Resources, vol. 3 no. 2,DOI: 10.1007/s42108-019-00014-y, 2019.

[34] D. Kujiek, Z. Sahile, "Water quality assessment of Elgo River in Ethiopia using CCME, WQI and Iwqi for domestic and agricultural usages," Heliyon,DOI: 10.2139/ssrn.4484438, 2023.

[35] M. Tadesse, D. Tsegaye, G. Girma, "Assessment of the level of some physico-chemical parameters and heavy metals of Rebu River in Oromia Region, Ethiopia," MOJ Biology and Medicine, vol. 3 no. 3, pp. 99-118, DOI: 10.15406/mojbm.2018.03.00085, 2018.

[36] Z. Menberu, B. Mogesse, D. Reddythota, "Evaluation of water quality and eutrophication status of Hawassa Lake based on different water quality indices," Applied Water Science, vol. 11 no. 3,DOI: 10.1007/s13201-021-01385-6, 2021.

[37] D. Tibebe, Y. Kassa, A. Melaku, S. Lakew, "Investigation of spatio-temporal variations of selected water quality parameters and trophic status of Lake Tana for Sustainable Management, Ethiopia," Microchemical Journal, vol. 148, pp. 374-384, DOI: 10.1016/j.microc.2019.04.085, 2019.

[38] A. Dabassa, S. Demissie, "Evaluation of physico-chemical and antimicrobial susceptibility patterns of microorganisms isolated from Awetu River, Jimma Town," Research Journal of Environmental Sciences, vol. 8 no. 2, pp. 101-108, DOI: 10.3923/rjes.2014.101.108, 2014.

[39] G. Kanno, Z. Ashuro, B. Negassa, A. Alembo, Z. Abate, B. Getahun, "Sanitary Survey and drinking water quality performance of treatment plant: the case of Dilla Town, Ethiopia," Science and Medicine, vol. 1, 2020.

[40] T. T. Gule, B. Lemma, B. Tesfaw Hailu, "Implications of land use/land cover dynamics on urban water quality: case of Addis Ababa city, Ethiopia," Heliyon, vol. 10 no. 1, 2023.

[41] M. Getachew, W. L. Mulat, S. T. Mereta, G. S. Gebrie, M. Kelly-Quinn, "Challenges for water quality protection in the greater metropolitan area of Addis Ababa and the upper Awash basin, Ethiopia – time to take stock," Environmental Reviews, vol. 29 no. 1, pp. 87-99, DOI: 10.1139/er-2020-0042, 2021.

[42] W. Kebede, M. Tefera, T. Habitamu, T. Alemayehu, "Impact of land cover change on water quality and stream flow in Lake Hawassa watershed of Ethiopia," Agricultural Sciences, vol. 05 no. 08, pp. 647-659, DOI: 10.4236/as.2014.58068, 2014.

[43] S. Duraisamy, V. Govindhaswamy, K. Duraisamy, S. Krishinaraj, A. Balasubramanian, S. Thirumalaisamy, "Hydrogeochemical characterization and evaluation of groundwater quality in Kangayam taluk, Tirupur district, Tamil Nadu, India, using GIS techniques," Environmental Geochemistry and Health, vol. 41 no. 2, pp. 851-873, DOI: 10.1007/s10653-018-0183-z, 2019.

[44] S. Hema, T. Subramani, "Scientific methods of assessing groundwater for irrigation purpose-a case study in a part of Cauvery River basin, South India," Indian Journal of Ecology, vol. 44 no. 2, pp. 185-191, 2017.

[45] M. A. Molla, Y. D. Fitsume, "Irrigation water quality of River Kulfo and its implication in irrigated agriculture, South West Ethiopia," International Journal of Water Resources and Environmental Engineering, vol. 9 no. 6, pp. 127-132, DOI: 10.5897/ijwree2016.0703, 2017.

[46] P. Aravinthasamy, D. Karunanidhi, N. T. Subba Rao, T. Subramani, K. Srinivasamoorthy, "Irrigation risk assessment of groundwater in a non-perennial river basin of South India: implication from irrigation water quality index (IWQI) and geographical information system (GIS) approaches," Arabian Journal of Geosciences, vol. 13 no. 21,DOI: 10.1007/s12517-020-06103-1, 2020.

[47] N. Subba Rao, Hydrogeology: Problems with Solutions, 2017.

[48] N. Subba Rao, "Groundwater quality from a part of Prakasam district, Andhra Pradesh, India," Applied Water Science, vol. 8 no. 1,DOI: 10.1007/s13201-018-0665-2, 2018.

[49] P. Aravinthasamy, D. Karunanidhi, T. Subramani, P. D. Roy, "Demarcation of groundwater quality domains using GIS for best agricultural practices in the drought-prone Shanmuganadhi River basin of South India," Environmental Science and Pollution Research, vol. 28 no. 15, pp. 18423-18435, DOI: 10.1007/s11356-020-08518-5, 2021.

[50] S. M. D. U. Islam, K. Majumder, M. J. Uddin, I. Khalil, M. Ferdous Alam, "Hydrochemical characteristics and quality assessment of groundwater in patuakhali district, southern coastal region of Bangladesh," Exposure and Health, vol. 9 no. 1, pp. 43-60, DOI: 10.1007/s12403-016-0221-y, 2016.

[51] S. Nagaoka, S. Katoh, G. Woldegabriel, H. Sato, H. Nakaya, Y. Beyene, G. Suwa, "Lithostratigraphy and sedimentary environments of the hominid-bearing pliocene-pleistocene Konso formation in the southern main Ethiopian rift, Ethiopia," Palaeogeography, Palaeoclimatology, Palaeoecology, vol. 216 no. 3-4, pp. 333-357, DOI: 10.1016/J.PALAEO.2004.11.008, 2005.

[52] G. Corti, "Continental rift evolution: from rift initiation to incipient break-up in the Main Ethiopian Rift, East Africa," Earth-Science Reviews, vol. 96 no. 1-2,DOI: 10.1016/J.EARSCIREV.2009.06.005, 2009.

[53] D. Meshesha, A. Tsunekawa, M. Tsubo, N. Haregeweyn, E. Adgo, "Drop size distribution and kinetic energy load of rainfall events in the highlands of the Central Rift Valley, Ethiopia," Hydrological Sciences Journal, vol. 59 no. 12, pp. 2203-2215, DOI: 10.1080/02626667.2013.865030, 2014.

[54] B. Tesfamariam, B. Gessesse, F. Melgani, "Characterizing the spatiotemporal distribution of meteorological drought as a response to climate variability: the case of rift valley lakes basin of Ethiopia," Weather and Climate Extremes, vol. 26,DOI: 10.1016/j.wace.2019.100237, 2019.

[55] Apha, "Standard methods for the examination of water and wastewater," 2012. https://www.standardmethods.org/

[56] V. Amiri, M. Nakhaei, R. Lak, M. Kholghi, "Assessment of seasonal groundwater quality and potential saltwater intrusion: a study case in Urmia coastal aquifer (NW Iran) using the groundwater quality index (GQI) and hydrochemical facies evolution diagram (HFE-D)," Stochastic Environmental Research and Risk Assessment, vol. 30 no. 5, pp. 1473-1484, DOI: 10.1007/s00477-015-1108-3, 2016.

[57] S. M. Nzama, T. O. B. Kanyerere, H. W. T. Mapoma, "Using groundwater quality index and concentration duration curves for classification and protection of groundwater resources: relevance of groundwater quality of reserve determination, South Africa," Sustain. Water Resource management, vol. 7 no. 3,DOI: 10.1007/s40899-021-00503-1, 2021.

[58] R. A. Freeze, J. A. Cherry, Groundwater, 1979.

[59] A. A. Ako, J. Shimada, T. Hosono, K. Ichiyanagi, G. E. Nkeng, W. Y. Fantong, G. E. T. Eyong, N. N. Roger, "Evaluation of groundwater quality and its suitability for drinking, domestic, and agricultural uses in the banana plain (mbanga, njombe, penja) of the Cameroon volcanic line," Environmental Geochemistry and Health, vol. 33 no. 6, pp. 559-575, DOI: 10.1007/s10653-010-9371-1, 2011.

[60] R. W. Herschy, "Water quality for drinking: WHO guidelines," Encyclopedia of Lakes and Reservoirs. Encyclopedia of Earth Sciences Series, 2012.

[61] Y. Mesele, A. Mechal, "Hydrochemical characterization and quality assessment of groundwater in meki River basin, Ethiopian rift," Sustainable Water Resources Management, vol. 6 no. 6, pp. 117-121, DOI: 10.1007/s40899-020-00471-y, 2020.

[62] R. Qin, Y. Wu, Z. Xu, D. Xie, C. Zhang, "Assessing the impact of natural and anthropogenic activities on groundwater quality in coastal alluvial aquifers of the lower Liaohe River Plain, NE China," Applied Geochemistry, vol. 31, pp. 142-158, DOI: 10.1016/j.apgeochem.2013.01.001, 2013.

[63] J. D. Hem, Study and Interpretation of the Chemical Characteristics of Natural Water, 2005.

[64] M. Tadesse, D. Tsegaye, G. Girma, "Assessment of the level of some physico-chemical parameters and heavy metals of Rebu river in Oromia region, Ethiopia," MOJ Biology and Medicine, vol. 3 no. 3, pp. 99-118, DOI: 10.15406/mojbm.2018.03.00085, 2018.

[65] R. J. Gibbs, "Mechanisms controlling world water chemistry," Science, vol. 170 no. 3962, pp. 1088-1090, DOI: 10.1126/science.170.3962.1088, 1970.

[66] M. E. Al-Ahmadi, "Hydrochemical characterization of groundwater in wadi sayyah, western Saudi arabia," Applied Water Science, vol. 3 no. 4, pp. 721-732, DOI: 10.1007/s13201-013-0118-x, 2013.

[67] H. Schoeller, "Geochemistry of groundwater," Groundwater studies an international guide for research and practice, vol. 15, 1977.

[68] E. A. Kaka, T. T. Akiti, V. K. Nartey, E. K. P. Bam, "Hydrochemistry and evaluation of groundwater suitability for irrigation and drinking purposes in the southeastern Volta River basin: manya Krobo area, Ghana," Elixir Agriculture, vol. 39, pp. 4793-4807, 2011.

[69] D. K. Todd, Groundwater Hydrology, 2005.

[70] L. A. Richards, Diagnosis and Improvement of saline and Alkaline Soil, 1954.

[71] G. Murtaza, M. Z. Rehman, M. Qadir, M. T. Shehzad, N. Zeeshan, H. R. Ahmad, Z. R. Farooqi, R. Naidu, "High residual sodium carbonate water in the Indian subcontinent: concerns, challenges, and remediation," International journal of Environmental Science and Technology, vol. 18 no. 10, pp. 3257-3272, DOI: 10.1007/s13762-020-03066-4, 2021.

[72] L. D. Doneen, Notes on Water Quality in Agriculture, 1964.

[73] M. Kelly, Mining and Freshwater Environment, 1988.

[74] S. Khalid, S. Khalid, "An assessment of groundwater quality for irrigation and drinking purposes around brick kilns in three districts of Balochistan province, Pakistan, through water quality index and multivariate statistical approaches," Journal of Geochemical Exploration, vol. 197, pp. 14-26, DOI: 10.1016/j.gexplo.2018.11.007, 2019.

[75] H. Adams, G. Burlingame, K. Ikehata, L. Furatian, I. Suffet, "The effect of pH on taste and odor production and control of drinking water," Journal of Water Supply: Research and Technology-Aqua, vol. 71 no. 11, pp. 1278-1290, DOI: 10.2166/aqua.2022.133, 2022.

[76] L. Mosley, R. Fitzpatrick, D. Palmer, E. Leyden, P. Shand, "Changes in acidity and metal geochemistry in soils, groundwater, drain and river water in the Lower Murray River after a severe drought," Science of the Total Environment, vol. 485-486, pp. 281-291, DOI: 10.1016/j.scitotenv.2014.03.063, 2014.