Introduction

In recent times, huge population growth, intense urbanization, increasing industries and tremendous agricultural activities all over the world have contributed to tremendous increase in demand for freshwater for household applications, agricultural and industries (Adimalla and Venkatayogi 2018; Alexakis and Tsakiris 2010). Due to insufficient supply of surface water, most of the people in arid and semiarid regions in India are depending primarily on groundwater for their daily needs and irrigation usages. Moreover, groundwater today accounts for a whopping 62.4% of net irrigation needs, 85% of rural drinking water needs and 50% of urban water needs (Raju 1998). He et al. (2015) have estimated that more than 1.5 billion people worldwide rely on groundwater as their chief source of drinking water. Hence, it is concluded that the groundwater is an elixir of life and other hand groundwater resource is facing more problems in recent years including quality aspects especially in arid and semiarid regions. Specifically, agricultural chemicals, such as, fertilizers, pesticides and other metal pollution, make the water unfit for drinking purposes (Kelly 1997). Therefore, knowledge of hydrogeochemistry of water is very essential to evaluate the water for drinking, irrigation and other needs. Eventually, the quality of groundwater is controlled by many factors such as rainfall, topographic relief, mineral dissolution, mineral solubility, ion exchange, oxidation, reduction, natural and anthropogenic activities such as geological structure and mineralogy of the watersheds and aquifers, the residence time, poor sanitary conditions, application of fertilizers and pesticides for higher crop yields without understanding the chemical characteristics of soils and industrial development without following any appropriate remedial measures (Todd 1980; Appelo and Postma 2005; Drever 1997; Wang et al. 2015; Hajizadeh Namaghi et al. 2011; Sappa et al. 2015). Therefore, it is most essential to monitor the quality of water resources in arid and semiarid regions in India particularly groundwater, which is considered as a principal source for drinking and irrigation purposes.

There are number of studies that have been conducted on groundwater quality assessment in many parts of the arid and semiarid regions. Kaur et al. (2016) have studied the groundwater quality for drinking and irrigation purposes in Malwa region, Punjab. Subramani et al. (2005) have studied groundwater quality and its suitability for drinking and agricultural use in Tamil Nadu. Tamma et al. (2015) have studied hydrochemical assessment of groundwater in Jalandhar district. Thakur et al. (2016) have studied that assessment of groundwater for drinking and agriculture in parts of Punjab. Ravikumar et al. (2012) have studied geochemistry of groundwater quality and its evaluation in Karnataka. Narsimha and Sudarshan (2017a) have studied contamination of fluoride in groundwater in Siddipet and reported high fluoride concentration in southern part of Siddipet, Medak district. Amiri et al. (2015) have reported that groundwater chemistry and its suitability for drinking and agricultural purpose in central Iran. Moreover, in India and many parts of the world, abundant studies have been carried out to assess the geochemical characteristics of groundwater quality with respect of drinking and irrigation (Kudoda and Abdalla 2015; Adimalla et al. 2018a; Murkute 2014; Raju et al. 2011; Dimitris Alexakis 2011; Subba Rao et al. 2012; Sudarshan et al. 2014; Li et al. 2017a, b; Jeevanandam et al. 2006; Li et al. 2012; 2014a, b; Cheng Qian et al. 2016; Sappa et al. 2015; Narsimha and Sudarshan 2013; Salem et al. 2015; Sethy et al. 2016; He et al. 2015; Panaskar et al. 2016). Furthermore, a number of researchers have used electrical conductivity (EC), sodium absorption ratio (SAR), per cent sodium (%Na), residual sodium carbonate (RSC) and permeability index (PI) classifications for irrigation water quality in many parts of the country (Adimalla and Venkatayogi 2018; Adimalla et al. 2018a; Qian et al. 2016; Sappa et al. 2015; Narsimha et al. 2013a, b; Aghazadeh and Mogaddam 2011; Ravikumar et al. 2012; Li et al. 2012). Eventually, Nalgonda district represents a true picture of hard terrain, where there is no sufficient surface water; therefore, most of the district people depend on groundwater for their daily needs. Mothkur region is one of the mandal in Nalgonda district, where people rely on groundwater and observed tremendous increase day by day and with number of water quality issues in various places in this region. This is one of the main reasons to select Mothkur region to evaluate the groundwater and surface water quality issues with main objective to assess the groundwater and surface water quality for drinking and irrigation purposes.

Geology of the study region

The studied area is situated in the northern part of Nalgonda district, Telangana State, South India (Fig. 1) and lies between 17.4147N and 17.4542N latitude and 79.1130E and 79.1561E longitude in Survey of India Toposheet No. 56 O3. The entire Mothkur region is under Archaean crystalline rocks, comparing granites, gneisses, schists and intrusive. The crystalline rocks inherently devoid of primary porosity; however, subsequently, with dynamic process of weathering, the rocks undergo fracturing and fissuring and joints over a period of time, leading to the development of secondary porosity, which forms the source for groundwater. July is the wettest month of the year contributing about 23% of annual rainfall. The mean seasonal rainfall is 562 mm in south-west monsoon (June–September), 139 mm in north-east monsoon (October–December), 7 mm rainfall in winter (January–February) and 43 mm in summer (March–May). About 74.8% of the annual rain fall is received from south-west monsoon period during June–September and 18.5% rainfall contributes from north-east monsoon.

Fig. 1
figure 1

Groundwater and surface water sampling locations along with drainage map of the Mothkur region, Telangana State, South India

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Materials and methods

Twenty-five groundwater and five surface water samples were collected in and around Mothkur region (Fig. 1), Nalgonda district, Telangana, in one-litre polyethylene bottles and stored at 10 °C. All containers used for sampling were washed with 10% nitric acid solution followed by double distilled water. Immediately after sampling, pH and electrical conductivity (EC) were measured in the field with using pH/EC/TDS meter (Hanna HI9811-5). Total dissolved solids (TDS) were calculated from EC multiplied by 0.64 (Brown et al. 1970; Hem 1985). Total hardness (TH) bicarbonate (HCO3−), chloride (Cl−), sulphate (SO42−), fluoride (F−), calcium (Ca2+), magnesium (Mg2+), sodium (Na+) and potassium (K+) were analysed with using standard methods (APHA 1995), and detailed procedure is presented in Table 1. Analysed water samples precision expressed as per cent relative standard deviation was below 10%, which is within the acceptable limit (Domenico and Schwartz 1990). Moreover, sodium absorption ratio (SAR), percentage sodium (%Na), residual sodium carbonate (RSC) and permeability index (PI) classifications were used for irrigation water quality and calculation methods are presented in Table 1.

Table 1 Instrumental, titrimetric and calculation methods used for chemical analysis of water samples in Mothkur region, Telangana State
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Preparation of spatial distribution maps

The base map of the study area was prepared using Survey of India topographic sheet 56 O3 and digitized using ArcGIS10.1 software (Fig. 1). The precise locations of sampling points were marked by using GPS (Garman eTrex 30), and the exact longitudes and latitudes of sampling points were imported in GIS platform for further analysis. Spatial analyst tools extension used to interpolate the inverse distance weighed (IDW) algorithm was an effective tool to prepare the spatial distribution maps of the chemical parameters of water of the study area. The IDW technique has been used widely in global scale to generate the spatial distribution maps for various purposes, especially, identify the high, medium and low chemical elements concentration zones.

Result and discussion

In order to give the general picture of the surface water and groundwater, analytical results are presented in Tables 2 and 3. The pH values of surface water and groundwater of the study area varied from 7.2 to 7.8 and 7.0 to 8.4, respectively, indicating marginally alkaline nature (Tables 2, 3). The obtained electrical conductivity (EC) values of surface water and groundwater samples varied were ranged from 908 to 2860 μS/cm and 676 to 4016 μS/cm at 25 °C, respectively (Tables 2, 3). Concentration of total dissolved solids (TDS) in surface water and groundwater ranged from 595 to 1887 mg/L and 446 to 2650 mg/L, respectively (Tables 2, 3). However, Freeze and Cherry (1979) categorized water on the basis of TDS concentration into four groups which are represented as fresh (TDS < 1000 mg/L), brackish (> 1000 mg/L), saline (> 10,000 mg/L) and brine (100,000 mg/L). Based on this classification, surface water and groundwater fall in fresh category in about 4 and 17 samples only and remaining are in brackish category (Fetter 1990; Table 4). The TH in surface water and groundwater ranges from 285 to 870 mg/L and 280 to 1185 mg/L, respectively (Tables 2, 3). The TH classification according to Sawyer and McCarty (1967) is clearly illustrated in Table 5, and based on this most of the surface and groundwater samples fall in very hard category, which is not useful for drinking purposes (Table 5).

Table 2 Hydrogeochemical characteristics of groundwater (BH) and surface water (SW) of the Mothkur region, Telangana State, South India
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Table 3 Minimum, maximum and mean of groundwater and surface water samples from the study area and its analytical data and comparison with the WHO and BIS standards for drinking purposes
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Table 4 Distribution of water samples based on the classification of TDS
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Table 5 Distribution of water samples based on the classification of TH
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Cation and anion chemistry

The major ions like calcium, magnesium, sodium, potassium, bicarbonate, sulphate, nitrate and chloride are present in most of the water having > 1 mg/L (Younger 2007). The major cations according to their decreasing concentration expressed in mg/L are as follows: Na+ > Ca2+ > Mg2+ > K+. Sodium is the most profuse alkali metal. The analytical data reveals that the concentration of Na+ in surface water and groundwater samples range between 131 and 400 mg/L and 129 and 545 mg/L with an average of 193.6 and 214.8 mg/L, respectively (Tables 2, 3). The maximum allowable limit for Na+ is 200 mg/L (WHO 1997; BIS 2003). Twelve (BH-1 to BH-5, BH-8, BH-16 to BH-18, BH-21 and BH-25) groundwater samples and one (SW-2) surface water sample have Na+ concentration above the permissible limit (Tables 2, 3). However, the intake of high levels of Na+ in groundwater may cause hypertension, arteriosclerosis, circulatory diseases, renal, oedema and kidney problems (Li et al. 2017a, b; Srinivas et al. 2013). The analytical results show that the Ca2+ in surface water and groundwater samples varied from 56 to 92 mg/L and 24 to 242 mg/L was on average 72.6 mg/L and 77.2 mg/L, respectively (Tables 2, 3). The maximum admissible limit for Ca2+ is 200 mg/L, and all collected samples are well within the maximum tolerable limits except one location as prescribed by WHO (1997) and BIS (2003) (Table 3). Surface water and groundwater samples concentration of K+ varies from 1 to 4 mg/L and 2 to 6 mg/L, respectively (Tables 2, 3). Moreover, K+ is an essential nutrient but if ingested in excess may behave as a laxative (Alam et al. 2012). 100% of surface water and groundwater samples are within the recommended limit of 12 mg/L prescribed by WHO (1997) (Table 3). Furthermore, the Mg2+ concentration in surface water and groundwater ranges from 25 to 56 mg/L and 15 to 176 mg/L, with a mean value of 38.8 and 42.6 mg/L, respectively (Tables 2, 3). A major portion of the study area (95%) contains Mg2+ within its maximum approved limit 150 mg/L, and in about four (SW-1, SW-2, SW-3, SW-4) surface water samples and eight (BH-1, BH-14, BH-16, BH-18, BH-17, BH-21, BH-22, BH-25) groundwater samples the concentration exceeds the maximum desirable limit < 30 mg/L (Table 2). The HCO3− is the dominant anion in the study area and surface water and groundwater samples concentration ranges from 360 to 470 mg/L and 299 to 628 mg/L with an average value of 422 mg/L and 408 mg/L, respectively (Tables 2, 3). Deepali et al. (2012) have confirmed that the SO42− is one of the naturally occurring and recurrently present in surface and groundwater of leaching from gypsum and other common minerals and at ingestion of higher concentration of SO42− may lead to gastrointestinal irritation. So, the present analytical data show that SO42− concentration in surface water and groundwater samples varied from 27 to 140 mg/L and 18 to 240 mg/L, with an average value of 89.6 mg/L and 70.3 mg/L, respectively (Tables 2, 3), of which only one sample (BH-16) exceeded the maximum desirable limit 200 mg/L (BIS 2003; WHO 1997; Table 3). Cl− majorly derives from the different sources such as domestic wastage, industrial wastes, municipal effluents and weathering of rocks, and it is considered as an index of pollution (Karanth 1987; Hem 1985; Loizidou and Kapetanios 1993). The Cl− content in the surface water and groundwater samples varied from 40 to 545 mg/L and 10 to 785 mg/L, with an average 245 mg/L and 218 mg/L, respectively; 20% of samples from surface water whereas 40% of groundwater samples exceeded the desirable limits (BIS 2003; WHO 1997; Tables 2, 3). However, in the remaining surface water and groundwater samples, the Cl− concentration is below the maximum permissible limits. Fluoride contamination in groundwater is one of the foremost issues in water quality studies (Ayoob and Gupta 2006; Narsimha and Sudarshan 2017a, b; Narsimha 2012). Fluorite (CaF2) is the only principal mineral of fluorine, mostly present as accessory minerals in granitic and occasionally in alkaline rocks (e.g. syenite and nepheline syenites). Apatite, amphiboles and micas, which are ubiquitous in igneous and metamorphic rocks, contain fair amounts of fluorine in their structure (Handa 1975; Adimalla and Venkatayogi 2017; Wenzel and Blum 1992; Narsimha and Sudarshan 2017a, b). Koritnig (1951) has obviously illustrated that fluoride is percolated in the initial stages of weathering of granite massifs. The maximum acceptance limit of fluoride in drinking water specified by the World Health Organization WHO (1997) is 1.5 mg/L. Fluoride (F−) is an essential element for human body when consumed in low amount (< 1.5 mg/L) and excess intake of F− (> 1.5 mg/L) will have adverse effects on human health (Adimalla and Venkatayogi 2017; Adimalla et al. 2018b, c; Narsimha and Sudarshan 2017a, b). Furthermore, continually consumption of water with fluoride concentrations above 1.5 mg/L results in dental fluorosis characterized initially by opaque white patches, staining, mottling and pitting of teeth (Adimalla et al. 2018c; Narsimha and Rajitha 2018; Narsimha 2018; Narsimha et al. 2018; Kundu et al. 2001). Moreover, F− concentration in surface water and groundwater of the study area varied from 0.63 to 0.81 mg/L and 0.84 to 1.85 mg/L, with mean value of 0.69 and 1.22 mg/L, respectively (Tables 2, 3). Surface water is within the maximum permissible limits, besides 32% of groundwater samples having higher concentrations above the maximum permissible limits (Table 3). Low content (< 1 mg/L) of fluoride implies near absence of fluoride-bearing minerals, and higher concentrations (> 1.5 mg/L) of fluoride are prominent in the southern part of the study area.

Spatial distribution of physico-chemical parameters

The hydrogeochemical study with geographical information system (GIS) divulges the zones where the quality of water is suitable for drinking and agricultural purposes. In any area around the world, groundwater quality and spatial distribution maps are significant as protective indicators of potential risk environmental health problems. GIS has been widely used to create spatial distribution maps, which are indicators of suitable and unsuitable zones (Sheikh et al. 2017; Sudhakar and Narsimha 2013; Narsimha et al. 2013a, b; Panaskar et al. 2016; Sudarshan et al. 2014; Amiri et al. 2015; Sappa et al. 2015). In this study, spatial distribution maps are prepared for pH, electrical conductivity (EC), total dissolved solids (TDS), total hardness (TH), bicarbonate (HCO3−), chloride (Cl−), sulphate (SO42−), fluoride (F−), calcium (Ca2+), magnesium (Mg2+), sodium (Na+) and potassium (K+) of the groundwater to delineate the safe and unsafe zones. pH spatial distribution map of the study area is depicted in Fig. 2, and it demonstrates that more than half the area is under alkaline nature. The spatial distribution map of the electrical conductivity in the study area is shown in Fig. 3. Distribution map of TDS is shown in Fig. 4, in which southern part of the study region is having high concentrations up to 2650 mg/L. Figure 5 shows the spatial distribution map of TH. Spatial distribution map indicates that in majority of the locations the TH is above the desirable limit of 100 mg/L and southern part of the study region having higher concentration, which is above the maximum permissible limit of 500 mg/L. Higher concentration of Na+ was in patches of eastern, western and southern part of the study area, which is clearly illustrated in Fig. 6. Spatial distribution map of Ca2+ (Fig. 7) shows that central part of the region is very low in concentration comparing to eastern, western and southern parts. Additionally, the spatial distribution of K+, Mg2+ and HCO3− concentration is shown in Figs. 8, 9 and 10 respectively. Spatial distribution of SO42− is shown in Fig. 11, and it clearly indicates that the high concentration is in southern and small patches from western part and low concentration is in northern part, and eventually it shows dissimilar concentrations throughout the study region, due to changes in infiltration of rainfall. The concentration of Cl− was relatively high in eastern and western parts of the study area (Fig. 12). Figure 13 shows the spatial distribution map of fluoride which shows that maximum area is under the permissible limits and southern and eastern parts of the study area is having higher concentration (> 1.5 mg/L) in the study area. Moreover, it is observed that fluoride, bicarbonate, chloride, sulphate, calcium, magnesium, sodium and potassium concentrations are less in surface water when compared to groundwater (Fig. 14).

Fig. 2
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Spatial Distribution map of pH in Mothkur region, Telangana State, South India

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Fig. 3
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Spatial distribution map of EC (µS/cm) in Mothkur region, Telangana State, South India

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Fig. 4
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Spatial distribution map of TDS in Mothkur region, Telangana State, South India

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Fig. 5
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Spatial distribution map of TH in Mothkur region, Telangana State, South India

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Fig. 6
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Spatial distribution map of Na+ in Mothkur region, Telangana State, South India

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Fig. 7
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Spatial distribution map of Ca2+ in Mothkur region, Telangana State, South India

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Fig. 8
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Spatial distribution map of K+ in Mothkur region, Telangana State, South India

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Fig. 9
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Spatial distribution map of Mg2+ in Mothkur region, Telangana State, South India

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Fig. 10
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Spatial distribution map of HCO3− in Mothkur region, Telangana State, South India

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Fig. 11
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Spatial distribution map of SO42− in Mothkur region, Telangana State, South India

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Fig. 12
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Spatial distribution map of Cl− in Mothkur region, Telangana State, South India

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Fig. 13
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Spatial distribution map of F− in Mothkur region, Telangana State, South India

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Fig. 14
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Physico-chemical parameters concentrations and variation between groundwater and surface water samples in Mothkur region, Telangana State, South India

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Hydrogeochemical evaluation

The analyses data reveals that the Na+ concentration is high in the study region. There are two reasons for higher Na+ concentration, i.e. halite dissolution and silicate weathering. For this, Na+/Cl− ratio plays vital and if Na+/Cl− < 1 the halite dissolution is responsible for high sodium, whereas if Na+/Cl− > 1, Na+ is released from silicate weathering (Meybeck 1987). In the present study, the molar ratio Na+/Cl− of water samples ranges from 0.63 to 19.89 meq/L, and for 80% of the samples Na+/Cl− ratio is more than 1, which indicates that the Na+ derives from silicate weathering (Stallard and Edmond 1983; Narsimha and Sudarshan 2017a; Fig. 15a; Supplementary material Table 1). Moreover, Na+ versus TDS scatter plot shown in Fig. 15b reveals that Na+ concentration shows an increasing trend with increasing TDS and in addition to the weathering of silicate minerals it might be related to the anthropogenic sources such as sewage, domestic waste (Williams et al. 1999; Choi et al. 2005). In addition, Na+/(Na++Cl−) molar ratio was calculated, and 93% of water locations have above 0.5 meq/L (Supplementary material Table 1), which indicates that Na+ derives not from the halite and other source like silicate weathering (Fig. 15d) and ion exchange process (Hounslow 1995). Furthermore, Jankowski and Acworth (1997) have used Na+/Cl− ratio vs EC, which would be an effective indicator to estimate the evaporation dominant process. Hence, Fig. 15c clearly reveals that the trend line is inclined, and Na+/Cl− ratio decreases with increasing EC which indicates that evaporation is not the major controlling process in groundwater chemistry in this terrain.

Fig. 15
figure 15

Relation between a Na+ and Cl−, b Na+ and TDS, c Na+/Cl− and EC, d Na+ and (Na+ + Cl−)

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Classification of water samples

IIED (2002) and Soltan (1998) have proposed classification of water based on the milliequivalent per litre (meq/L) content of chloride, sulphate and bicarbonates. The water is normal Cl− type if Cl− is < 15 meq/L, normal SO42− type if SO42− is < 6 meq/L and normal HCO3− type if HCO3− varies between 2 and 7 meq/L. Detailed distribution of water samples based on the (APHA 1992; IIED 2002; Soltan 1998) classification has showed that the majority of the samples belongs to normal sulphate, normal chloride and finally normal bicarbonate (Table 6).

Table 6 Groundwater and surface water classification according to Cl−, SO42− and HCO3−
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Base-exchange indices (BEI) and meteoric genesis indices (MGI)

The base-exchange indices (BEI) and meteoric genesis indices (MGI) (Matthess 1982; Soltan 1998, 1999) were determined by using Eqs. 1 and 2, respectively. These are very worthwhile for the further classification of groundwater.

$${\text{BEI}} = \left[ {{\text{Na}}^{ + } - {\text{Cl}}^{ - } } \right] / {\text{SO}}_{4}^{2 - }$$
(1)
$${\text{MGI}} = \left[ {\left( {{\text{Na}}^{ + } + {\text{K}}^{ + } } \right) - {\text{Cl}}^{ - } } \right] / {\text{ SO}}_{4}^{2 - }$$
(2)

where all ionic (Na+, K+, Cl−, SO42−) concentrations are expressed in meq/L. The water can be arranged in different groups as Na+–HCO3− type if BEI > 1 and Na+–SO42− type with BEI < 1, whereas the water source is of deep meteoric water percolation type if MGI < 1 and MGI > 1 indicates that the water is of shallow meteoric percolation type and also its detailed illustration has been presented in Table 7.

Table 7 Groundwater and surface water classification according to base-exchange index (BGI) and meteoric genesis index (MGI) criteria
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Hydrogeochemical facies and water types

The Piper (1944) trilinear diagram is very useful to reveal the water types based on the ionic composition of surface water and groundwater from the different aquifers (Narsimha and Sudarshan 2017a, b; Adimalla and Venkatayogi 2017; Subba Rao et al. 2012; Li et al. 2012), and it is a very effective tool to identify the chemical relationship in water samples. This diagram contains two triangular charts for depicting the proportions of cations (Na+, Ca2+, K+, Mg2+) and anions (CO32−, HCO3−, SO42−, Cl−), expressed in meq/L. The triangle for cations has 100% Ca2+ in the left corner, 100% Na++K+ towards the right and 100% Mg2+ upwards and for anions it has 100% carbonates and bicarbonates to the left, 100% Cl− to the right and 100% SO42− on top. The obtained chemical data values from the different water samples collected from the study region are plotted on the Piper (1944) diagram Fig. 16. On the basis of Piper diagram, collected water of the study area are divided into six types, that are Ca2+–HCO3−, Na+–Cl−, mixed Ca2+–Na+–HCO3−, mixed Ca2+–Mg2+–Cl−, Na+–Cl− and Na+–HCO3−. The prevalent water types are mixed Ca2+–Na+–HCO − 3 > Na+–Cl− > Na+–HCO3− identified in the Mothkur region. About 44% and 60% collected groundwater and surface water samples are significantly dominated by mixed Ca2+–Na+–HCO3−, 30% is from Na+–Cl− and eventually, 29% of water samples was from Na+–HCO3− (Fig. 16). In the study area, chemical analysis reveals that the HCO3− and Na+ concentrations are high with other ions, and it is because of the entire study area occupied by crystalline hard rocks, where silicate minerals are generally present. Therefore, high HCO3− and Na+ concentration and high pH values are controlled by the rock–water interaction (Adimalla and Venkatayogi 2017; Narsimha and Sudarshan 2017a, b).

Fig. 16
figure 16

The piper diagram, graphically displaying the 30 water samples from the Mothkur region, Telangana State, South India

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Multivariate graphical methods for irrigation utility

It is necessary to know the suitability of surface water and groundwater for irrigation/agricultural purposes depending on the effect of mineral constituents of the water on both plants and soils (Wilcox 1955; Richards 1954). For this, the effective multivariate graphical methods are used to determine its suitability for agricultural needs, that are EC, sodium adsorption ratio (SAR), per cent of sodium (%Na), residual sodium carbonate (RSC) and permeability index (PI) playing a vital role in suitability of water for irrigation, and these graphical methods are extensively used all over the world (Li et al. 2014a, 2017b; Sappa et al. 2015; Ghazaryan and Chen 2016; Panaskar et al. 2016; Amiri et al. 2015; Li et al. 2012). The classifications of irrigation water, based on SAR, %Na, RSC and EC are reviewed in Tables 8 and 9. It is well known that EC and SAR are good measures for salinity hazard and sodium hazard to crops, respectively (Tables 9, 10). The US Salinity Laboratory’s diagram (1954) is used broadly to assess the irrigation waters, where SAR is plotted against EC (Fig. 17) and shows that 44% and 60% of the groundwater and surface water samples fall in the category of C3S1, indicating water of high salinity and low sodium type, which is very useful for irrigation in almost all types of soils (US Salinity Laboratory Staff 1954; Table 10). However, 32% of the groundwater samples fall in the field of C3S2, indicating high salinity and medium sodium type, which can be used to irrigate salt-tolerant and semi-tolerant crops under favourable drainage conditions (US Salinity Laboratory Staff 1954; Table 10). About 24% of the groundwater and surface water samples fall in the field of C4S2, indicating very high salinity and medium sodium type, and this type of water is not useful for irrigation. Eventually, 40% of the water samples fall in C2S1, indicating medium salinity and low sodium type which can be used for irrigation on all types of soil without danger of exchangeable sodium (Table 10). Moreover, sodium adsorption ratio (SAR) is widely used for determining the suitability of surface water and groundwater for irrigation (Todd 1980; Karanth 1987) and is expressed as below:

$${\text{SAR}} = \frac{{{\text{Na}}^{ + } }}{{\sqrt {({\text{Ca}}^{2 + } + {\text{Mg}}^{2 + } )/2} }}$$

where Na+, Ca2+ and Mg2+ are expressed in meq/L and Richards (1954) classified SAR values into four groups (Table 9). In the present study, the SAR values varied from 3.38 to 8.19 and 3.36 to 4.83 for groundwater and surface water, respectively, indicating that the water of the study area has excellent quality for irrigation (Table 9). In addition, sodium concentration is another significant factor in classifying irrigation water, because sodium reacts with soil to affect the soil permeability and texture. Furthermore, sodium content is usually expressed in terms of per cent sodium (%Na), which is calculated using the below formula given by Wilcox (1955):

$$\% {\text{Na}} = \frac{{{\text{Na}}^{ + } + {\text{K}}^{ + } }}{{({\text{Ca}}^{2 + } + {\text{Mg}}^{2 + } + {\text{Na}}^{ + } + {\text{K}}^{ + } )}} \times 100$$

where Na+, K+, Ca2+ and Mg2+ are expressed in meq/L. The %Na in the study region ranges from 43.87% to 74.41% and 50.01% to 65.55% in the groundwater and surface water, respectively. About 56% of collected groundwater and 100% surface water are under permissible limits for irrigation, and remaining groundwater samples fall under doubtful category for irrigation (Wilcox 1955; Table 8), since they cause deflocculation and impairment of the tilth and the permeability of soil (Karanth 1989). However, Wilcox (1955) designed a graphical model for irrigation utility, where water has been classified into five classes which are excellent to good (EG), good to permissible (GP), permissible to doubtful (PD), doubtful to unsuitable (DUS) and unsuitable (Fig. 18). Wilcox diagram (Fig. 18) shows that out of twenty-five groundwater samples, 16% and 20% of the samples belong to excellent to good and good to permissible category, followed by 40% and 20% of the samples belonging to permissible to doubtful and doubtful to unsuitable, and all surface water samples belong to good to permissible category, which are suitable for irrigation (Fig. 18).

Table 8 Classification of water quality for irrigation on the basis of %Na and RSC in the study region, Telangana State, South India
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Table 9 Zone classification of water quality for irrigation on the basis of EC and SAR
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Table 10 Criteria for water quality for irrigation following the (US Salinity Laboratory Staff 1954), in Mothkur region, Telangana State, South India
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Fig. 17
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US salinity diagram for classification of irrigation waters (after Richards 1954), samples from the Mothkur region, Telangana State, South India

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Fig. 18
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Wilcox diagram for classification of water based on EC and %Na (EG—excellent to good, GP—good to permissible, DUS—doubtful to unsuitable, PD—permissible to doubtful, US—unsuitable)

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Residual sodium carbonate (RSC) of the water reveals that the bicarbonate value is very high compared to other anions (Tables 1, 2). Hence, carbonate ions (HCO − 3 + CO32−) influence the water quality through the precipitation of alkaline earths (Ca2+ + Mg2+), where the water in the soil is more concentrated. By this reason estimation of RSC is vital for suitability of irrigation and calculated with following equation (Eaton 1950):

$${\text{RSC}} = \left( {{\text{CO}}_{3}^{ - } + {\text{HCO}}_{3}^{ - } } \right) - \left( {{\text{Ca}}^{2 + } + {\text{Mg}}^{2 + } } \right)$$

where all ionic concentrations are expressed in meq/L. Calculated RSC values ranged from − 13.37 to 3.76 and − 3.30 to 2. 30 meq/L in groundwater and surface water, respectively. About 56% and 80% of collected groundwater and surface water samples are under the safe limits, followed by 20% of water samples that are doubtful for irrigation and its illustration has been given in Table 8.

Permeability index (PI) is another important parameter to estimate the suitability of water for irrigation. Sodium, calcium, magnesium and bicarbonate contents were always influenced soil permeability, and it is defined by the following equation (Doneen 1964; Ragunath 1987):

$${\text{PI}} = \frac{{{\text{Na}}^{ + } + \sqrt {{\text{HCO}}_{3} }^{{}} }}{{({\text{Ca}}^{2 + } + {\text{Mg}}^{2 + } + {\text{Na}}^{ + } )}} \times 100$$

where all the ions are expressed in meq/L. The computed analytical data explains that the 60% and 100% of the collected groundwater and surface water samples fall in class I and 37% in class II, indicating that the groundwater is in good quality for irrigation purposes; only one water sample belongs to class III which is unsuitable for irrigation purposes (Fig. 19; Domenico and Schwartz 1990).

Fig. 19
figure 19

Doneen (1964) classification of irrigation water quality based on the permeability index

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Conclusions

The groundwater and surface water samples of the Mothkur region have been studied to assess the suitability for drinking and irrigation purposes. The analytical data were compared with WHO and BIS standards to know the suitability. The dominant constituents of water are as follows: Na+ > Ca2+ > Mg2+ > K+ for cation and Cl− > HCO − 3 > SO 2− 4 > F− for anions. The results indicate that Na+, Mg2+, Cl− and F− concentrations are above maximum permissible limits recommended by World health organization (WHO) and Bureau of Indian standards (BIS) in the study region. The US salinity diagram reveals that 44% and 60% of the groundwater and surface water samples fall in the category of C3S1 and 32% of groundwater samples fall in C3S2 and are useful for irrigation in almost all types of soils. Based on Wilcox classification, 36% of the groundwater samples are suitable for irrigation, 40% and 20% groundwater samples fall in permissible to doubtful and doubtful to unsuitable categories. Moreover, 56% of groundwater and all surface water samples belong to permissible limits based on per cent sodium for irrigation utility. Based on the classification of irrigation water according to residual sodium carbonate values, 56% of the groundwater and all surface water samples belong to good for irrigation purposes. The permeability index indicates that the water of the study area is of good quality for irrigation utility.