Hydrochemical analysis and evaluation of the suitability of groundwater for irrigation purposes in khariar blocks of Nuapada district, Odisha, India

Introduction

Groundwater and surface water are essential for agricultural irrigation (Worqlul et al.,2017) [25] . Groundwater is an essential source of water for many countries, serving both rural and urban areas (Mansour et al.,2020) [19] . The steady increase in the global population has led to a growing demand for water across agricultural, domestic, industrial, environmental, and recreational sectors. With finite freshwater resources, this escalating need underscores the importance of efficient management and regulation of water supplies, especially when the water is meant for human consumption. (Kumar et al.,2017; Bhardwaj and Sam, 2022) [13,6] . Polluted water can cause numerous serious and long-term health problems, such as gastrointestinal disorders, cholera, and various waterborne infections. (Ali et al., 2021) [1] . In many regions, particularly in developing countries, access to clean water is limited, contributing to high mortality rates, especially among vulnerable populations like children and the elderly. The impacts of inadequate water quality extend beyond immediate health issues; they also affect education, economic stability, and overall community well-being. Efforts to improve water quality such as infrastructure development, water purification technologies, and public health initiatives are crucial for preventing illness and promoting healthier communities (US Environmental Protection Agency (USEPA, 2007, Li & Wu, 2019 and Aly et al., 2015) [24,14,3] . The chemical characteristics of groundwater are shaped by a range of hydrogeochemical interactions and processes occurring within the subsurface environment. (Davis et al., 1966) [8] . Comprehending these processes is crucial for evaluating groundwater quality and its interaction with the surrounding geological formations. Additionally, such geochemical mechanisms play a significant role in causing the spatial and temporal variations observed in groundwater composition. (Ali et al.,2016) [2] . Regular spatiotemporal monitoring and evaluation of groundwater are vital to ensure its safe and sustainable utilization, especially for drinking and irrigation. The hard rock landscape of the Khariar Block, located within the Eastern Ghats and the Chhattisgarh Plateau, depends predominantly on groundwater resources to meet these essential needs. The marginal contributions of fluoride in groundwater primarily arise from the natural dissolution of fluoride-and nitrate-due to excesses use of fertilizer in agricultural land. (Dhakate et al.,2021) [10] . In granitic aquifers, rock-water interactions are the primary source of fluoride contamination (Nakayama et al., 2022) [20] .Moreover, human activities, including the discharge of fly ash from fossil fuel burning, also lead to increased fluoride levels in groundwater (Aslam et al., 2024) [5] . Geographic Information Systems (GIS) are increasingly recognized as a valuable tool for addressing diverse problems and managing geographical data holistically. They effectively capture the spatiotemporal variability that is crucial for assessment and decision-making (Pandey et al., 2020) [21] . The main aim of this research is to evaluate the quality of groundwater for drinking purposes, with a special focus on the use of GIS-based techniques. For this assessment, 15 key water quality parameters were analyzed, including pH, electrical conductivity (EC), total hardness (TH), total dissolved solids (TDS), total alkalinity (TA), sodium (Na⁺), potassium (K⁺), calcium (Ca²⁺), magnesium (Mg²⁺), nitrate (NO₃⁻), bicarbonate (HCO₃⁻), chloride (Cl⁻), sulphate (SO₄²⁻), fluoride (F⁻), and iron (Fe). These parameters were selected to comprehensively assess groundwater quality. Consequently, this study seeks to evaluate the marginal dynamic behaviour of fluoride and nitrate in groundwater using a qualitative approach, alongside statistical analysis and vulnerability assessments related to irrigation.

Materials and Methods

Study area

Khariar Block is situated in the southeastern part of Nuapada District, Odisha, along the southeastern edge of the Chhattisgarh Plateau. The region experiences a tropical monsoon climate with hot and humid summers, where daytime temperatures range from 35 to 40°C, while winter temperatures vary between 12 and 25°C. The average annual rainfall is approximately 1247 mm. Geographically, Khariar Block is bounded by Komna Block to the north, Boden Block to the west, and Sinapali Block to the south, covering a total area of about 412 sq. km (Fig. 1). The average elevation of the study area is around 560 meters above mean sea level (MSL).

Sample collection and physiochemical analysis

Various types of data were utilized to evaluate the groundwater quality of Khariar Block, Nuapada, Odisha. The study area uses the Universal Transverse Mercator (UTM) projection, zone 44N, with the WGS 1984 datum. The research involved both fieldwork and laboratory investigations, including the collection of groundwater samples from hand pumps and dug wells at different locations. A total of 50 groundwater samples were collected following the standard procedures outlined by APHA (1995). The sampling locations were recorded using a Global Positioning System (GPS) and mapped on a georeferenced map (Fig. 2). The collected samples were analyzed for fifteen key water quality parameters according to APHA (1995) standards, and the statistical analysis of these parameters is presented in Table 1. Groundwater samples were collected from 50 locations in Khariar Block, Nuapada District, Odisha, during the premonsoon season. The samples were preserved in precleaned, one-litre high-density polyethylene (HDPE) bottles to maintain their integrity for analysis. (Dupont et al.,2020; Liu et al., 2021) [11,15] . Subsequently, the collected samples were transported to the laboratory for chemical analysis. All chemical parameters were analyzed using the standard methods recommended by the American Public Health Association (APHA, 2012). Sulfate (SO₄²⁻) and nitrate (NO₃⁻) concentrations were determined using a UV-visible spectrophotometer, while chloride (Cl⁻) was measured by the AgNO₃ titration method. Magnesium (Mg²⁺) was calculated using the formula: Magnesium Hardness (MgH) = Total Hardness (TH) -Calcium Hardness (CaH) Mg2+ (mg/L) = MgH × Equivalent weight of Mg2+ × Normality of EDTA. The total hardness (TH as CaCO3) and calcium (Ca2+) were estimated by EDTA titration method. Total hardness (TH as CaCO₃) and calcium (Ca²⁺) were determined using the EDTA titration method, and sodium (Na⁺) and potassium (K⁺) concentrations were measured with a Systronics flame photometer. A standard method using sulfuric acid (H₂SO₄) and methyl orange indicator was employed to determine bicarbonate (HCO₃⁻). Fluoride (F⁻) was measured using the ion-selective electrode technique, specifically an Orion fluoride electrode connected to an Orion electrometer (Ali et al., 2016; Rena et al., 2022). Calibration standards of fluoride (0.1-10 mg/L) were prepared from a 100 mg/L sodium fluoride stock solution. For measurement, 2 mL of total ionic strength adjustment buffer (TISAB III) was added to 20 mL of each sample as required for the analysis.

Statistical Method

Assessing the chemical quality of groundwater for irrigation purposes involves several statistical methods to analyse and interpret water quality data. Here's an overview of key steps and methods; Collect groundwater samples from various locations and depths.Determine key chemical parameters including pH, electrical conductivity (EC), total dissolved solids (TDS), major ions (Na⁺, K⁺, Ca²⁺, Mg²⁺, Cl⁻, SO₄²⁻, HCO₃⁻), and heavy metals. Calculate mean, standard deviation, minimum, and maximum for each parameter. Assess relationships between different chemical parameters (e.g., Na⁺ vs. EC) using correlation coefficient. Based on statistical analysis, provide recommendations for irrigation practices or necessary interventions. Employing these statistical methods allows for a comprehensive assessment of groundwater quality for irrigation purposes, ensuring that agricultural practices are sustainable and safe. It's essential to adapt the methods based on local conditions and specific research goals.

Result and Discussion

Hydrochemical results

The Hydrochemical analysis are given in Table-1, which shows pH concentration of the study area varies from 6.49-7.64 and average value is 7.24, that indicates the water is slightly alkaline. TDS varies from 143-1090 mg/l. and Average value is 546.5 mg/l, which indicates fresh water. Electrical conductivity is the measure of dissolved ion and salinity. EC value in water is high due to leaching of aquifer material. The EC value of the area varies from 255-1710 µmho/cm and average value is 871 µmho/cm. Total Hardness of the area varies from 92.07-696.56 mg/l and Average value is 349.43 mg/l, it shows the water is very hard. The fluoride concentration in the study area ranges from 0.1 to 3.04 mg/L, with an average of 0.88 mg/L, primarily originating from granite formations. Nitrate levels vary between 0.08 and 142 mg/L, averaging 50.77 mg/L, largely resulting from the overuse of fertilizers in agricultural fields. All the samples are expressed in mg/l except pH and EC

Sodium Adsorption Ratio (SAR)

The Sodium Adsorption Ratio (SAR) is an important parameter for evaluating water suitability for irrigation, as it reflects the balance of sodium relative to calcium and magnesium in the water. It helps predict the potential for sodium to affect soil structure and permeability ( [16,17,18] . From the analysis it is found that all 50 samples are fall in to excellent category. That means the water is suitable for irrigation.

All values

Percent Sodium (%Na) is a crucial parameter for assessing irrigation water quality, representing the proportion of sodium relative to the total cations in the water. This measure helps determine the potential effects of sodium on soil structure and crop yield. In the present study (Mahanta et al.,2020) [17] , the results show that 18% of the samples are classified as excellent, 46% as good, 28% as permissible, and 8% as doubtful.

All values are expressed in meq/L. The Wilcox (1948) [26] diagram elucidates percent sodium and electrical conductivity to classify groundwater (Fig. 4), can be divided into five divisions (excellent to good, good to permissible, permissible to doubtful, doubtful to unsuitable and unsuitable). A high sodium ratio can indicate potential soil dispersion, reducing water infiltration and harming plant growth. Monitoring Na% helps in making informed decisions about water use in agriculture (Mahanta et al., 2020) [17] . The diagram shows that 8% of the samples fall within the excellent to good category, 54% within good to permissible, 22% within doubtful to unsuitable, and 2% within permissible to doubtful.

Permeability index (PI)

The Permeability Index (PI) is used to assess the effect of irrigation water on soil permeability and to predict the potential for soil degradation, particularly in terms of sodium impact on soil structure. From the data analysis, it is found that 46% samples belong to suitable class and 54% samples belongs to good class.

PI

Here all values are in meq/l. Doneen (1964) [9] irrigation water was categorized according to the Permeability Index (PI).(Fig. 12). it shows that all the samples belong to class -1 type, which is good for irrigation. The soil permeability is affected by the extensive use of irrigation water as it is influenced by Na + , Ca 2+ , Mg 2+ and HCO 3 -.

Monitoring the Permeability Index is crucial for sustainable agricultural practices. High values can indicate that the water may negatively impact soil structure, reducing water infiltration and increasing runoff, which can adversely affect crop growth. Residual Sodium Carbonate (RSC) is an important parameter for assessing irrigation water quality, reflecting the potential for sodium and carbonate accumulation in the soil, which may impact soil structure and crop health. RSC is calculated based on the concentrations of sodium, calcium, and magnesium in the water. Elevated RSC values indicate a higher risk of sodium toxicity and soil dispersion, making it a critical factor in evaluating water for irrigation purposes.

The formula of RSC is given below;

All values are reported in meq/L. 50%of the samples fall below <1.25, making them suitable for irrigation purposes. In contrast, 18% of the samples fall 1.25-2.5 range, which is moderate for irrigation and 32% of the sample >2.5, which is unsuitable for irrigation, (Table 2).

Kelly's Ratio (KR)

Kelly's Ratio (KR) It is a parameter used to evaluate irrigation water suitability based on the sodium and calcium content, calculated using the following formula:

KR =

Here all values are in meq/l.

Here, Na⁺ represents the concentration of sodium ions, while Ca²⁺ and Mg²⁺ denote the concentrations of calcium and magnesium ions, respectively. KR value of less than 1 suggests that the water is suitable for irrigation, as it indicates a lower proportion of sodium relative to calcium and magnesium. A KR value greater than 1 may indicate a higher risk of sodium accumulation in the soil, which can lead to soil dispersion and reduced crop yields. This ratio is an important factor in assessing the potential impact of irrigation water on soil health. Eightyfour percent of the samples fall below <1.0, making them suitable for irrigation purposes. In contrast, 16% of the samples exceed >1 which is unsuitable for irrigation, (Table 3).

Potential Soil Salinity (PS)

Potential Soil Salinity (PS) indicates the estimated concentration of soluble salts in the soil, which can influence crop growth and soil fertility. Its levels are affected by irrigation practices, rainfall distribution, and evaporation rates.PS is often measured in terms of electrical conductivity (EC), with higher values indicating higher salinity levels. Elevated salinity can lead to issues such as reduced water uptake by plants, nutrient imbalances, and toxicity. Managing PS is crucial for sustainable agriculture, as it helps in determining suitable crops for specific soils and guiding irrigation practices to minimize salinity build-

PS

All values are given in meq/L. 88% percent of the samples fall below <5 which fall under excellent to good category. In contrast, 14% of the samples fall 5-10 range which is good to injurious for irrigation (Table 4). All values are expressed in meq/L. Seventy percent of the samples fall below 50, making them suitable for irrigation purposes. In contrast, 30% of the samples exceed 50, rendering them unsuitable for irrigation (Table 5).

Gibbs Diagram (Mechanism controlling groundwater quality)

The Gibbs diagram (Gibbs, 1970) is widely employed to examine the relationship between water chemistry and the lithological characteristics of aquifers. As illustrated in Fig. 6, the diagram is divided into three distinct zones: evaporation-crystallization, weathering or rock-water interaction, and precipitation dominance. (Mahanta & Sahoo, 2016) [16] . In this research work it is concluded that all sample under the rock dominance category.

Correlation

Correlation of water quality involves analyzing relationships between various chemical constituents in water to understand their interactions and impacts on overall water quality. This analysis can help identify potential sources of contamination, predict water behaviour, and assess suitability for various uses, including agriculture. Correlation between SAR, PI, PS, KR, % NA and MR shown in Table 6. SAR has high positive correlation between KR (r = 0.92) and % Na (r = 0.89). KR has strong positive correlation with % Na (r = 0.93). PI has negative correlation with PS (r = -0.11). RSC has negative correlation with PS (r = -0.1).

Conclusion

The recent groundwater study has highlighted the dynamics of fluoride in the area, which significantly affect the health of humans, and animals, among other factors. Analyses using Piper and Gibbs diagrams, correlation studies, statistical methods. The key conclusions are summarized as follows.

 From piper diagram, The dominant hydrochemical facies are Ca 2+ -Cl -type followed by Na + -Cl -type  Average value of pH is 7.24, which shows the water is alkaline in nature. Average value of Total Hardness is 349.43mg/l, most of sample comes under moderate to hard type. Fluoride concentrations range from 00.1to 3.24 mg/l, with enriched zones noted in the the far western and central regions of the study area. According to BIS [7] standards, 8% sample exceed the permissible limit of 1.5 mg/l, placing them in the highrisk zone.  In permeability index diagram all samples comes under Class I type, which is very suitable for agricultural system.  The statistical analysis shows SAR has high positive correlation between KR and % Na KR has strong positive correlation with % Na PI has negative correlation with PS). RSC has negative correlation with PS.  From Gibbs diagram it concluded that all samples belong to rock dominance type.  The area primarily consists of Khandalite, gneiss, and gabbro, along with small patches of Charnockite and quaternary sediments. It features diverse geomorphology, including pediments, structural hills, denudational hills, and valley fills. Fluoride dissolution in this region is significantly influenced by the interaction between rock and water.

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