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A Simple Indexing Approach to Classify the Groundwater Quality for Drinking and Irrigation Purposes in and around Koppal City, Karnataka State, India

Madhu K. N, K. Lokesh, Manjappa S, Suresh B*

Department of Civil Engineering, Bapuji Institute of Engineering & Technology, Davangere-577 005, Karnataka, India

Abstract: Advanced Mathematical Tool (AMT) is a user approachable, open source, result support tool for the appraisal and reporting of groundwater quality data. Groundwater quality of the selected regions needs great attention since it is the main water exporter for household and irrigation needs. In this study, the AMT like GWQI and IWQI were applied to monitor the suitability of groundwater quality for drinking and irrigation purposes respectively in and around Koppal city, Karnataka state, India. To attain aim of the work twenty five groundwater samples were collected from different places and the total 12 physico-chemical variables were carried out to monitor the suitability of groundwater for drinking needs. Total eleven parameters have been subjected to calculate the GWQI for drinking testes. The obtained results were compared with WHO guideline values. Also, seven variables were selected for irrigation testes for calculating the IWQI were selected. The results revealed that the ground waters of most samples were fit for drinking purposes according to WHO (AMT). However, the calculated GWQI for drinking propose showed that 16 % and 12% of samples are comes under poor category during pre-monsoon and monsoon respectively. 72 % and 80% are comes under permissible category and only 12 % and 8% of samples are comes under very poor category. For irrigation needs, most of monitored samples were acceptable for irrigation purposes (AMT). The computed IWQI showed that 15% of water samples were in excellent category and 85% were in good category.

Keywords: advanced mathematical tool, SAR, RSC, GWQI, IWQI format

Received August 15, 2021; Revised September 20, 2021; Accepted September 28, 2021

Citation: Madhu K. N, K. Lokesh, Manjappa S, Suresh B, A Simple Indexing Approach to Classify the Groundwater Quality for Drinking and Irrigation Purposes in and around Koppal City, Karnataka State, India. Applied Ecology and Environmental Sciences, 9 (9). 832-837. January 2021. doi:10.12691/aees-9-9-7

1. Introduction

Groundwater is available beneath the Earth’s surface in soil through pore spaces through cracks of rock formations. Reporting of Ecological variables of groundwater is regularly examined in areas where the high risk of pollution and effects on human beings. Monitoring of ground water quality using advanced mathematical tool (AMT) approaches are designed to encourage the existing conditions and trends of ecological variables to know the risk to human beings and the environment. The water quality monitoring gives clear picture of the web layer of the geologic conditions where the availability of ground water [1]. Kaushik et al., [2] reported the groundwater quality of Ambala and Nilokheri Cities in Haryana. Sarath Prasanth et al., [3] Appraise the groundwater quality and its acceptability for drinking and irrigational needs in the coastal branches of Alappuzha district in Kerala.

Most excellent mathematical tools for ground water quality monitoring and interpretation like GWQI. IWQI, Statistical approach, cation anion calculation, multivariable analysis and also GIS surprisingly, only a limited number of geo-statistical tools are available. In common with number of ecological applications, the AMT was recognized that there would be an advantage in using the mathematical tool is an open and clear since policy makers and ecological regulations prefer these type of techniques which are fully apparent and used by previous scientist and sound science [4].

GWQI and IWQI are mathematical tools which can be convert number of results of water quality into a single technical representation of Ground water quality condition Many researchers are have been adopted and established these two tools to represents the quality of groundwater [5,6,7,8,9,10,11,12,13,14,15].

In Koppal city in and around the area, the groundwater quality is in a deteriorating trend since over exploitation and other man made activities. So, ground water quality monitoring of current trends is needed. The objectives of the current work is to use the advanced mathematical tools to conduct an reporting and interpretation of the groundwater quality in and around Koppal city and to draw the areas where the groundwater is acceptable / not acceptable for both domestic and irrigational needs using GWQI and IWQI approach.

1.1. Study Area

The area selected for study is situated in Karnataka State, Koppal city southern end of India. Koppal is surrounded on three borders by hills. It consists historical landmarks such as the Koppal Fort, the Gavimath and the Malle Mallappa Temple. The region covers about 7,190 km² area in and around Karnataka state and lies between the longitudes 15’09′00″ to 16’03′30″ North Latitude and 75’47′30″ to 76’48′10″ East Longitude (Figure 1). In the south, the Tungabhadra reservoir present in a distance of about 23 km from the study area. Koppal town and its surroundings commonly called as ‘‘Kopan Nagara’’ has an average elevation of about 529 m above the mean sea level, city is surrounded by hills and lush green paddy field. The average annual normal rainfall of this district is 572 mm. A general overall view of rainfall noticed in the different rainfall locations indicate that the precipitation varies from 584.50 to 218.50 mm. Most of the rainfall occurs during NE and SE monsoon seasons. The temperature data shows higher and lower temperatures prevailed during monsoon season. The average maximum temperature during May is 34.59°C. The average minimum temperature recorded is 22.82°C during January. The annual average minimum and maximum temperatures are 22.80 and 32.98°C, respectively (CGWB 2008). The population density in this city is very less compare to other district. It is about 250 peoples per sq.km, according to 2011 census of India. Mostly, on hard rock areas, the presence of weathered size is sporadic both in space and depth. Hence, the groundwater recharge is encouraged by the strength of weathering. The depth of the wells in the study area varies from 2 to 200 m depth ground level (CGWB 2008).

Figure 1. Location Map of the Koppal district (study area)

2. Materials and Methods

A total of twenty five groundwater samples are collected from bore wells from January 2020 to December 2020. The samples were collected in the thoroughly washed with acid polyethylene bottle of one litre. During sampling analysis and transported water samples to the laboratory, all required precautions were taken (APHA, 1999). Electrical conductivity (EC) and hydrogen ion concentration (pH) were determined on the field itself using digital meters. Water samples were estimated at the laboratory for chemical constituents like anions and cations, by using standard methods as recommended by APHA, 1989 [40]. Total hardness and Calcium was measured using EDTA methods and used equation to find out Total hardness, Ca²⁺, Mg²⁺, Total dissolved solids (TDS) were assessed by calculation method. The analyzed data was showed in the graphical plots such as Wilcox’s salinity plots and US salinity plots to show the hydro-geochemistry of the groundwater and to represents their accessibility for agricultural uses and Gibb’s plots were also created. GWQI was deliberated by considering 10 of the chemical variables. GWQI is a combined and advanced tool for ground water quality monitoring. It gives a clear condition about the overall quality of water. We adopt the formula to determine the GWQI as used by Chaurasia, et al., [16,41].

3. Result and Discussion

Sustainable of ground water in the study area, it is significant to appraise the quality of ground water for various purposes. In the present work an effort has been made to apprise the ground water for Ground water quality index (GWQI) and Irrigational water quality Index (IWQI) in newly formed Koppal district, hard rock aquifer and sustainable use.

3.1. GWQI (Ground Water Quality Index)

GWQI contains one calculated value, describes the entire chemical reactions and effects of chemical substances on ground water properties which are used for human consumption [17]. GWQI have been used to apprise the quality of water by many researchers [17,18,19,20,21]. It consists three continuous successive footsteps, hence it is called as Advanced Mathematical Tool (AMT) [3,11,22,23].

The GWQI for 16 ground water samples ranges from 2.71 to 121.94 with an average of 48.73 and standard deviation of 36.83 during pre-monsoon, post-monsoon and monsoon periods. The calculated GWQI categorized the groundwater into excellent to unsuitable category depends on the values given in Table 1. The GWQI technique looks to be more accurate for appraising water quality at different locations. The maximum value of GWQI of these wells has been found to be primarily from the maximum values of EC, TDS, hardness, sulphate and potassium. As per that, 44%, 56% and 44% of wells water comes into the poor category and 56%, 44% and 52% comes into the very poor category during three seasons respectively. No one sample is comes under Excellent, Good and unsuitable category (Table 1). The same trends of GWQI was identified in their work and reported sum of carbonate and bi-carbonate in groundwater over the sum of Ca2+ and Mg2+ also encourages the quality of water used for other activities [24]. Many other researchers GWQI also correlate our results [18,25,26,27,28,29,30,31].

3.2. Suitability for Agriculture

IWQI measures to determine the quality of water for agricultural activities. The anthropogenic activities and industrial activities are deteriorates the geological sources of water. Many other factors are also changes the geological sources of water like unregulated drainage waste through system form residential area condition in the study area [32]. The IWQI was calculated are given in Table 1. As per the two hazards group of cumulative effect [33]. The calculated IWQI for a period of one year are varied from (2019-2020).

Many variables like pH, EC, Na percentage, SAR, permeability index, RSC and magnesium hazard are used for appraising the suitability of groundwater for irrigational activities. Groundwater pH values varied from 6.5 during post monsoon to 7.8 during monsoon periods 7.45, 7.27 and 7.28 during three monsoon, post and pre-monsoon season correspondingly. With reference to average values during the study period 8.0 for Oligocene aquifer and between 7.2 and 8.5 with a mean value of 7.9 for Mio-Plio-Quaternary aquifer [34,35]. Hence, the study area comes under safe category.

The water salinity is directly proportional to the quantity of dissolved solids it gives TDS and EC. With reference to the EC and TDS the calculated values indicates that most of the water samples are come into the more salinity and low Na+ content, these type of water may be used for irrigation in all type of soil but little hazard in excessive Na+ content soil [36].

Table 1. Classification of water based on GWQI value

Table 2. Statistical description of the IWQI in and around Koppal City

Extreme Na+ in water may affect undesirable changes in soil characteristics and modify in the permeability property. For Oligocene (13.2 – 62.3%) and Mio-Plio-Quaternary (14.1 – 45.3%) [34,35]. In the current study, groundwater categorization indicates that 16 % and 12% of samples are comes under good category during pre-monsoon and monsoon respectively. 72 %, 80% and only 20% are comes under permissible category and only 12 % and 8% of samples are comes under unsuitable category (Table 3).

Na+ content is significant variable in categorizing water purpose for irrigation as it also changes the property of permeability of the soil and encourages infiltration problem. According to Richards [37], SAR values of water is < 10 are deliberated as excellent, 10 - 18 as good, 18 - 26 as fair, and > 26 are unsuitable for irrigation purpose. In the current work, SAR values showed 3.08 to 10.38, indicates except KGW-17 all most all the water samples are suitable for irrigation use and excellent category (Table 3) in the entire study.

The application of the permeability index (PI) help in appraising the soil permeability, which changes in the soil quality due to long term usage. PI values ranged between 54.0 to 85.47, 50.55 to 85.64 and 46.3 to 86.15 during three period (Table 2). These values predicts that most of the water samples comes into class III categorized also called as unsuitable (28%, 24% and 16%) for irrigation in Table 3 [38].

Table 3. Categorization of ground-water quality and its suitability for irrigation

Figure 2a. Occurrence of Cation during monsoon period

Figure 2b. Occurrence of Anion during monsoon period

Figure 2c. Occurrence of Cation during pre-monsoon period

Figure 2d. Occurrence of Anion during pre-monsoon period

Figure 2e. Occurrence of Cation during post-monsoon period

Figure 2f. Occurrence of Anion during post-monsoon period

In order to understand the occurrence of cation and anions during the study period is given in Figure 2. Kumara, et al., [36] Reported Na+ is the more significant cation in their study. In the present study average Na+ is also predicts same trends (53%) during entire study period. In the present study, maximum and minimum Na+ content during monsoon, pre-monsoon and post-monsoon season are 380.70 mg/L, 524.20 mg/L (KGW-21) and 295.08 mg/L and 118.58 mg/L 96.23 mg/L (KGW-08) and 95.46 mg/L respectively. The current Na values showed a chief reason for increasing in the ground water may cause salty taste and this due to irrigational practices in and around the study area [39].

4. Conclusion

In this study, a valuable tool that can be used to any region was applied to apprise to verify different groundwater quality categories. Simple and easily analysed groundwater quality variables can be apprised as input in the tool. These tool could be used as a groundwater quality indicators before establishment water supplies and irrigational activities. However, addition to these AMT quality variables will further increase the value of data. AMT can also be used for grouping the water samples to drinking and irrigational purposes in the same or any other area. On the basis of SAR, RSC, Na% and PI, all the groundwater samples were observed to be suitable for irrigation purpose. Dominance of cations such as magnesium and calcium in the groundwater indicated contamination due to man-made activities. All the groundwater samples indicated simple mixing of ions as no major ion present. Future research should participate the analytical values analyze them at a large scale under varied ecological condition with variables. The computed IWQI showed that 15% of water samples were in excellent category and 85% were in good category. The approach of these AMT expected values will contribute to possible facilities to help to take decision and help to policy makers. It is expected that these analytical and calculated using tool values will progress the water quality management.

Conflicts of Interest

The authors declare no conflict of interest.

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