Hydrogeochemical analysis of groundwater quality during the pre- monsoon season of Manipur, India

ABSTRACT

The water quality index (WQI) and irrigational index for groundwater were studied in the northeastern section of the Manipur Valley in northeast India. Water samples were collected in 2022 during the pre-monsoon season. To compute the water quality index for drinking water, the basic chemical parameters of total hardness, pH, electrical conductivity, total dissolved solids, Calcium, Sodium, Iron, Magnesium, Manganese, Chlorine, and Hydrogen Carbonate were used. The assessment of bacteriological quality is also done, which is crucial for overall water quality evaluation, alongside physical and chemical analyze. For determining irrigation suitability, irrigational indices such as sodium absorption ratio, sodium percentage, and magnesium hazard were calculated. WQI, %Na+, Sodium Adsorption Ratio (SAR), magnesium hazard, permeability Index and total hardness indicate that most water samples are harmless for irrigation and drinking purpose. They have affirmative relationships indicating that these characteristics are interdependent. Approximately 25% of the Piedmont zone groundwater is found to be unfit for agricultural and drinking usage. The encrustation of gypsum, halite, and evaporation into the Disang shares accelerate the dissolution of ions in Piedmont water, resulting in quality degradation. According to Gibbs plots, Durov Scatter Plot, and Hill Piper Trilinear Diagram of water dominated the rock-weathering process, while hydrochemical facies progressed from the beginning to the intermediate stage of Chadha’s graphical representation illustrates the progression of hydrochemical processes in surface water. Therefore, proper integrated water resource management and development are required for effective water resource utilization, particularly around the Piedmont zone. In recent years, the quality of groundwater has caused a significant deal of alarm, and an increasing number of studies relating to it have been published. The geological, structural, and geomorphological features in the intermontane Imphal Valley in Manipur, India, were identified using SRTM DEM data by QGIS Software. This area has simple geology and structural elements, making it an appropriate site to evaluate the use of remote sensing and GIS tools in geological studies. To prevent a water crisis, groundwater resources must be managed sustainably. The current study also concentrated on a bibliometric examination of groundwater management and access to gauge the state of the field. A bibliometric examination of these papers may offer insight into current research and trends. We are the first to join Groundwater Quality Assessment with bibliometric analysis. This prediction, if taken into consideration strategically during the planning of preventive measures for groundwater quality can help to analyze future evaluation to a great extent.

KEYWORDS:

• Groundwater
• water quality index
• bacteriological quality
• irrigational indices
• hydrochemical processes

Introduction

Groundwater is a valuable and widely distributed resource. It is extensively used across the realm, with every citizen relying on it. Surface water, such as ponds, streams, and rivers, serves as a source for domestic, irrigation, and industrial sectors. Groundwater has emerged as a reliable water source due to its limited resources and increasing water contamination. Rapid urbanization, especially in developing countries such as India, has substantially impacted the supply and quality of groundwater due to overexploitation and improper waste disposal, particularly in metropolitan areas. Mukate et al. (2019) Consequently, the rising demand for water for domestic and agricultural purposes is met through groundwater supply, but excessive use contributes to alarming groundwater lvel depletion. According to the World Health Organization, water is a major source of various human diseases. Once a water source is contaminated, its quality cannot be restored. Therefore, an assessment of water quality is essential for managing and controlling pollution and it also receives a lot of attention in the released research area. Noori et al. (2019) Reviews of studies about the evaluation of water quality are abundant. However, most of these investigations were method and model-focused. Only a small percentage of them conducted thorough analyses of several characteristics like journal, author, citation, and country. Indeed, if the review only concentrates on methodologies and models, a whole picture might not be produced. Roemer and Borchard (2015) QGIS is a strong set of tools for gathering, storing, retrieving, analyzing, integrating, and visualizing spatial data from the actual world for specific applications. Different spatial data, such as land cover, hydrology, and a Digital Elevation Model (DEM), when incorporated into a GIS, enable for more precise and convenient interpretation and study of geomorphologic aspects. Berdimbetov et al. (2020) A helpful tool for quantitatively analyzing the growth and development of any research subject is provided by bibliometric analysis as shown in Figure 1. The dispersed architecture and variation patterns of publications, which in turn reflect the state of the underlying research and technology, can be examined using mathematical and statistical tools. Van Eck and Waltman (2017) Bibliometrics techniques have been used in a variety of environmental-related sectors, such as biosorption technology, wetlands, estuary pollution, and study on sediment, and for the evaluation of water quality. The top two most important topic areas, which primarily concentrate on managing and monitoring water resources, environments, and rivers, are environmental sciences and water resources. Pizzi et al. (2020).

Figure 1. Bibliometric analysis of groundwater worldwide.

According to the results of the current bibliometric examination of groundwater access and management, as shown in Figure 1, India and the USA had a strong network of collaboration Kumar A. and Kumar S. had the most influence and research. Among the different sources of journals, environmental monitoring, and assessment had a high impact on groundwater research. When it came to groundwater research, the water journal outperformed the other sources. Groos and Pritchard (1969) In conclusion, millions of people around the world rely on groundwater as a major supply of water. It is crucial to acknowledge that water sample testing is a fundamental approach to ensure the obtainability of contamination-free water for irrigation and drinking purposes, while also fostering public awareness of sanitation and hygiene. Consequently, this study contributes a valuable database for future reference. Kumar et al. (2019).

The Water Quality Index is a rating that comprehensively reveals the impact of multiple quality factors on water. The WQI is determined based on the suitability of groundwater for human consumption. This study aims to discuss the groundwater quality in Manipur State, focusing on physicochemical and ionic parameters, and water quality index values. This research holds significance due to Manipur’s commercial nature, rapid urbanization, and development, all of which impact groundwater quality. Overexploitation of resources has led to deteriorating quality, exacerbated by the scarcity of documentation, resulting in poor water quality reports for Manipur. Climatic changes significantly contribute to water shortages. Berdimbetov et al. (2020).

Groundwater in Manipur has elevated concentrations of iron (Fe) and fluoride (Fˉ).

Manipur can be divided into two separate physical regions: the outside area of rough hills and narrow valleys, and the center area of flat plain with all related landforms. These two places have distinct physical characteristics and prominent flora and fauna. Manipur is a state who inhabiting mainly surrounded by Nagas and Kuki-zo conglomerates which includes Gangte, Paite, Hmar, Sukte, Simte, Zou and small other tribes. Kuki-Chin language is dominantly use. According to the Census data, there is 2581 villages in the Manipur. In the field of art and culture, it is the best state in representing classical dance. Bishnupur and Chandel are the most crowded cities of Manipur. Sharma et al. (2021) Water samples were collected from various locations in Manipur and analyzed for iron, manganese, chromium, aluminum, silver, zinc, nitrate, nitrite, phosphate, and fluoride levels, following World Health Organization guidelines. Duraisamy et al. (2019). Sample locations included Bishnupur, Chandel, Kakching, Kamjong, Morch, Nungba, Parbung, Saikul, Senapati, Somdal, and Tamei. Contaminated water significantly contributes to intestinal inflammation, leading to conditions such as diarrhea, parasitic infections, anemia, and gastrointestinal contamination. The Regular evaluation of water quality is essential because of the population’s susceptibility to waterborne infections from consuming contaminated water. Water quality encompasses physical, chemical, biological, and radioactive components, and esthetic qualities. Tripathi and Singal (2019).

Metals such as aluminum, iron, chromium, manganese, and silver, along with physicochemical parameters such as nitrates, nitrites, fluorides, phosphates, and sulfates, are fundamental components requiring investigation and improvement, forming the basis for informed decisions regarding the protection and management of drinking water quality. This research paper focuses on data collection and analysis of water samples collected from the Manipur area to comprehensively understand the procedures and underlying causes of variations in drinking water quality. Eliza et al. (2018) Additionally, the hydrogeochemistry and irrigation capability of groundwater assessments have been conducted in selected regions of Manipur to better comprehend the state of water quality. Wu et al. (2018)

Study area

Samples were collected from 11 different locations in Manipur, India from March to May 2022 during the pre-monsoon season. The present study assessed the geological, geographical, and structural aspects of Manipur, an Indian state. It is located in the north-eastern section of the country. One of India’s most eastern states is Manipur as it shares its entire eastern and a portion of its northern and southern borders with Myanmar, as well as the Indian states of Nagaland and Mizoram in the north and south, and Assam in the west. Manipur is spread over an area of 3312 sq. km. This accounts for around 10% of the state’s overall geographical area, with the remainder being hilly terrain. The Valley is a fluvial-lacustrine plain drained by multiple rivers and dotted with minor hills. The geographical coordinates of the study area lie between latitudes 24.2481° North to 25.3804° North and longitudes 93.1071° East to 94.5283° East. Adimalla and Taloor (2020) The elevation of the research area ranges from 790 m to 2020 m above mean sea level. The climate of the state is subtropical, with an average rainfall of 1989.5 mm. The rainfall is related with the southwest monsoon. In these places, the soil, rock surface, and so on have low vegetation cover, which facilitates clear satellite images and analysis utilizing popular band combinations produces good findings. The research area was chosen for study because it is a hilly region with dense forest cover, and relatively few studies have been conducted there. The area is also unusual due to its basic geological variety. Kumar et al. (2019) The water table refers to the upper surface of this saturated zone. The saturated zone beneath the water table is known as an aquifer, and they are massive reservoirs of water. According to hydrological study reports, the Manipur valley is underlain by a thin veneer of alluvial deposits that are primarily clayey in nature and are supported by Tertiary rocks. Ground water occurs under both unconfined and confined circumstances. Groundwater aquifers and borewells are the sole source of groundwater in many parts of the Manipur. Pizzi et al. (2020) Groundwater is found under water table conditions in shallow excavated well horizons with depths ranging from 1.649 to 12 mbgl. In the foothills, water levels can reach 12 mbgl. Groundwater in Manipur is generally considered appropriate for residential and agricultural use. Groundwater samples were collected from bore wells primarily which are used for domestic purposes (Figure 2). These bore wells are the primarily resource for the consumption and usage of water in their particular areas. People made various arrangements to take water from these wells by digging down bucket, pulled up with the rope or in some developed area uses water through a mechanical system. Wu et al. (2018) The state’s total annual extractable ground water resources as of March 2022 are 4246.51 hectare meters (ham). The provision for domestic uses is 2001.18 ham, whereas the available groundwater resource for future usage is 41,612.43 ham. The net draft for irrigation and industries is negligible throughout Manipur. This area is characterized by hills, plains, and marshes, with drainage provided by the rivers Nambul, Imphal, Thoubal, and their tributaries. The valley lands were previously densely forested, with many swamps and marshes reclaimed for agriculture and urban development. Alluvial rivers are the potential source for the access of groundwater. The region covered by the valley that can be examined for groundwater potential accounts for approximately 70% of the overall geographical state area. In Imphal Valley, superficial alluviums are underlain by Tertiary rocks from the Barail Series. Adimalla and Taloor (2020)

Figure 2. (a) Geological Map and (b) On-Site Map of Groundwater sampling locations.

The Manipur River starts north of Karong in the Senapati district and flows through a 50 Km stretch of steep terrain before meandering through the Manipur valley in a North West-South East direction. Its major tributaries include the Imphal and Nambul River, which disseminates through alluvial plain and flood plain along with the flow path i.e drains into the lakes, ponds which is further use by its population. In Manipur, the Nambul, Imphal, Thoubal, rivers are polluted by sewage. These stretches are primarily found near towns and cities. The chief causes of pollution in this area are sewage discharge, industrial and mining wastewater, and garbage dumping. Hence, There has been a significant increase in demand for freshwater as a result of fast population expansion and industrialization. The majority of Manipur’s rivers are contaminated due to sewerage, washing, solid waste, and sand dredging.

Geologically, the area comprises quaternary formations of older and newer alluvium underlain by tertiary Disang series rocks. The average temperature is 20.4 °C, ranging from 0 to 36 °C, with an annual rainfall of 1,259.5 mm, 60–65% of which falls during the southwest monsoon season of June to September. The district has an annual replenishable groundwater resource of 87.26 mcm, of which 1.35 mcm is currently being used. The district has between 350 and 400 hand-tube wells. The depths of the wells ranged from 32 to 200 feet. The influence of terrain variety, altitudinal variation, and river regime has been emphatic in the seasonal fluctuation of climate from one location to another. The climate in the Barak basin and lower foothills of Manipur’s Western hills is warmer than in the central valley and surrounding hills. Similarly, because of its location on the windward slope of the hills, the western section of the state is moister than the eastern. In general, the state has reasonably excellent climatic behavior with less heat. Ram et al. (2021).

Methodology

During September, 22 samples were collected from 11 different locations in Manipur. All sample bottles were properly cleaned, sterilized, and dried one day before data collection. At the time of collection, the bottles were rinsed with the samples multiple times and appropriately labeled. For the determination of iron content, separate bottles with an acid wash were used to collect water samples. One drop of diluted nitric acid (1:1) GR grade was added as a preservative right away after collection in the iron sample bottle to avoid the formation of any kind of precipitation with oxygen. The GPS model was employed during sample collection to record the latitude and longitude of each collection area, and QGIS was utilized to generate the sampling locations. Digital Elevation Model is employed with the help of QGIS 3.36 software. The collection and preservation of samples were done according to standard practices. The collected water samples were tested for temperature, total hardness, pH, turbidity, dissolved oxygen (DO), salinity, total dissolved solids (TDS), and other physicochemical characteristics.

To minimize the contamination and maintain the chemical and physical qualities of the water, the sample bottles were transported to the research laboratory and the samples were stored at 4°C for further investigation. Solutions were prepared using a borosilicate apparatus, deionized water, and AR-grade reagents. The pH was measured using a digital pH meter (EuTech pH 610), which is a calibrated instrument and valid upto 25 July 2025. The multiparameter EuTech CD 650, whose calibration valid upto 19 December 2024 and was utilized to measure TDS, electrical conductivity, and salinity. The total hardness was determined through the method of titration (EDTA method) and turbidity was assessed by a turbidity meter (EuTech TN 100), whose calibration valid upto 25 July 2025.

For the determination of cations such as chromium, silver aluminum, manganese, iron, and zinc, as well as anions such as sulfate, phosphate, nitrate, fluoride, and nitrite, the Metrohm 882 Compact IC Plus was employe, whose calibration valid upto 23 October 2024.

Ion exchange chromatography was used to determine the cations and anion concentration present in the water sample and it was done with the help of Metrohm 882 Compact IC Plus, whose calibration valid upto 23 October 2024. Iron was calculated using a UV-Vis spectrophotometer (Analytikjena SPECORD 205), whose calibration valid upto 7 May 2024. The colony forming unit (CFU) per milliliter was calculated using the viable count method, facilitated by a colony counter, which was calibrated internally quarterly. The formula for calculating Cfu/ml is:

$\mathit{Cfu}/\mathit{ml}=\mathit{no}.\mathit{ofcolonies}\ast \mathit{dilutionfactor}/\mathit{volumeofcultureplated}\left(\mathit{ml}\right)$

Water quality was evaluated using the Water Quality Index (WQI). Hydrogeochemistry was analyzed using hydrochemical facies, including Hill – Piper, Durov, Chadha, and Gibbs diagrams. Methods such as magnesium hazard, total hardness, sodium absorption ratio, permeability index, and sodium percentage were employed to assess irrigation parameters.

Results and Discussion

All samples collected from various locations were subjected to physicochemical analysis, and the obtained results were subsequently evaluated. Table 1 shows the different geological locations of the collected water samples. The findings of this investigation exhibit disparities when compared with the standard data provided by organizations such as the Bureau of Indian Standards (BIS) and the World Health Organization (WHO). BIS, I.S.D.W.S., Bureau of Indian Standards. (2012) The turbidity values exceeded the BIS and WHO limits as samples ranged from 1.67 to 16.20 NTU. Over 50% of the samples under examination had levels of manganese that were too high to be consumed by people. Several elements, including turbidity, iron, chloride, sodium, sulfate, and total dissolved solids, were also beyond the acceptable limits for drinking water in several locations. The majority of the sources water is unfit for use in agriculture due to excessive sodium concentrations and sodium absorption ratios (SAR). Wazir et al. (2020) The evaluation of each parameter is mentioned below.

Table 1. Geological Location of the Collected samples.

Sample codes	The Location of the water collection	The location of the GPS
		Latitudes	Longitudes	Altitudes (in feet)
R-1	Bishnupur	24.5625	93.8012	2520
R-2	Bishnupur	24.5625	93.8012	2520
R-3	Chandel	24.3197	94.0210	3294
R-4	Chandel	24.3197	94.0210	3294
R-5	Kakching	24.3890	93.8801	2552
R-6	Kakching	24.3890	93.8801	2522
R-7	Morch	24.8409	94.5283	4409
R-8	Morch	24.8409	94.5283	4409
R-9	Nungba	24.2481	94.3028	584
R-10	Nungba	24.2481	94.3028	584
R-11	Parbung	24.7444	93.4189	1063
R-12	Parbung	24.7444	93.4189	1063
R-13	Saikul	24.2466	93.1071	2543
R-14	Saikul	24.2466	93.1071	2543
R-15	Senapati	24.9035	94.0763	2717
R-16	Senapati	24.9035	94.0763	2717
R-17	Somdal	25.3804	94.0569	3734
R-18	Somdal	25.3804	94.0569	3734
R-19	Tamei	25.1663	94.2834	5572
R-20	Tamei	25.1663	94.2834	5572
R-21	Kamjong	25.1581	93.6799	2946
R-22	Kamjong	25.1581	93.6799	2946

*GPS- Global Positioning System.

Physicochemical and bacteriological analysis

Temperature holds significant importance when assessing water quality because it can affect the physicochemical characteristics of water. Temperature influences the biological activity within water bodies, with activity generally increasing as the temperature increases. S. H. Ewaid et al. (2020) In the present study, the observed temperature of the water samples ranged from 21 °C to 35 °C. The pH level of water is a fundamental criterion for assessing its quality. The pH of groundwater can be influenced by the geological composition of the well surroundings. Low pH levels can lead to gastrointestinal issues and corrosion of metal components, resulting in the release of hazardous metals such as lead, zinc, copper, and cadmium. Sharma et al. (2021) The highest recorded pH value in this investigation was 7.98 (Sample R-15), whereas the lowest was 6.21 (Sample R-5). Approximately 53.3% of the samples fell outside the pH range suggested by BIS, with most samples exhibiting an acidic pH range.

Dissolved oxygen analysis quantifies gaseous oxygen dissolved in a water solution. In this study, the DO concentrations of different water samples ranged from 5.22 to 9.22 mg/L. The majority of sample locations fell within the acceptable range for drinking water quality. Sharma et al. (2021). also determined the concentration of dissolved oxygen (DO) within the desired range (4.75–7.94 mg/L) in their study. Sharma et al. (2021) TDS primarily comprises inorganic salts with minor organic components. As per the BIS guidelines, the permissible TDS limit is 500 mg/L. The TDS levels in the tested water samples ranged from 56.60 to 623 mg/L (Table 2). Although the maximum and minimum TDS values were found in samples R-1(623.00) and R-9(56.60), respectively, all results remained within the BIS and WHO guidelines. Consequently, the TDS level in the drinking water is considered safe. Kumar et al. (2019).

Table 2. Physicochemical parameters of the study area.

Sample Codes	Temp.	pH*	Dissolved Oxygen*	TDS*	Salinity*	Electrical Conductivity*	Total Hardness*	Turbidity*
BIS specification	(°C)	6.5–8.5	6.5–8.5 mg/L	500–2000 mg/L	>600 mg/L	50–800 uS/cm	200–600 mg/L	1–5 NTU
WHO	(°C)	6.5–8.5	6.5–8.0 mg/L	300–1200 mg/L	>1000 mg/L	50–400 uS/cm	200–600 mg/L	1–5 NTU
R-1	24 ± 0.03	6.54 ± 0.02	7.90 ± 0.02	623.00 ± 0.11	593.00 ± 0.21	63.32 ± 0.02	24.00 ± 0.02	16.20 ± 0.23
R-2	24 ± 0.01	6.53 ± 0.01	8.00 ± 0.01	621.42 ± 0.09	60.60 ± 0.02	64.35 ± 0.02	25.00 ± 0.02	15.21 ± 0.18
R-3	25 ± 0.03	6.45 ± 0.04	7.68 ± 0.05	431.20 ± 0.01	67.34 ± 0.03	56.78 ± 0.01	28.00 ± 0.23	14.83 ± 0.16
R-4	25 ± 0.02	6.45 ± 0.04	7.45 ± 0.04	562.70 ± 0.03	82.43 ± 0.03	66.78 ± 0.02	45.00 ± 0.03	15.34 ± 0.32
R-5	28 ± 0.01	6.21 ± 0.02	7.69 ± 0.05	255.20 ± 0.01	249.00 ± 0.09	268.00 ± 0.06	175.00 ± 0.32	13.50 ± 0.24
R-6	28 ± 0.01	6.23 ± 0.01	6.78 ± 0.05	231.70 ± 0.01	245.56 ± 0.08	256.22 ± 0.05	176.00 ± 0.28	12.34 ± 0.19
R-7	22 ± 0.03	6.98 ± 0.05	5.22 ± 0.01	123.70 ± 0.02	243.12 ± 0.08	222.43 ± 0.04	187.00 ± 0.02	11.67 ± 0.02
R-8	22 ± 0.02	6.34 ± 0.02	5.66 ± 0.03	134.60 ± 0.03	243.66 ± 0.08	212.67 ± 0.01	198.00 ± 0.24	13.56 ± 0.26
R-9	23 ± 0.02	7.10 ± 0.09	7.50 ± 0.02	56.60 ± 0.01	56.91 ± 0.01	59.20 ± 0.02	25.00 ± 0.31	1.57 ± 0.02
R-10	23 ± 0.02	7.12 ± 0.03	9.22 ± 0.06	89.23 ± 0.02	59.23 ± 0.01	57.89 ± 0.02	34.00 ± 0.29	1.78 ± 0.01
R-11	19 ± 0.01	6.23 ± 0.01	8.98 ± 0.05	96.22 ± 0.02	76.67 ± 0.02	63.67 ± 0.03	78.00 ± 0.35	2.96 ± 0.01
R-12	19 ± 0.01	6.80 ± 0.05	9.23 ± 0.06	93.23 ± 0.02	87.45 ± 0.03	89.22 ± 0.02	67.00 ± 0.04	1.84 ± 0.01
R-13	35 ± 0.01	6.91 ± 0.02	8.44 ± 0.02	99.45 ± 0.03	98.56 ± 0.03	67.78 ± 0.02	56.00 ± 0.25	1.67 ± 0.01
R-14	35 ± 0.11	7.65 ± 0.03	8.20 ± 0.02	100.00 ± 0.05	95.33 ± 0.02	101.90 ± 0.03	50.00 ± 0.26	6.91 ± 0.02
R-15	21 ± 0.02	7.98 ± 0.07	8.44 ± 0.04	122.56 ± 0.03	94.56 ± 0.02	104.22 ± 0.04	45.00 ± 0.27	6.78 ± 0.17
R-16	21 ± 0.01	7.44 ± 0.10	7.32 ± 0.02	145.56 ± 0.07	97.22 ± 0.03	709.67 ± 0.06	67.00 ± 0.04	6.12 ± 0.02
R-17	29 ± 0.02	7.63 ± 0.02	7.56 ± 0.03	102.11 ± 0.02	98.21 ± 0.02	104.56 ± 0.02	345.00 ± 0.19	6.45 ± 0.16
R-18	29 ± 0.02	7.63 ± 0.02	8.00 ± 0.03	101.80 ± 0.02	100.00 ± 0.02	105.20 ± 0.02	50.00 ± 0.27	7.26 ± 0.21
R-19	24 ± 0.01	7.61 ± 0.01	8.60 ± 0.02	102.45 ± 0.04	98.45 ± 0.01	123.66 ± 0.03	67.00 ± 0.28	7.89 ± 0.24
R-20	24 ± 0.01	7.13 ± 0.01	8.44 ± 0.01	123.66 ± 0.05	99.72 ± 0.02	112.78 ± 0.01	56.00 ± 0.17	7.44 ± 0.02
R-21	25 ± 0.02	7.89 ± 0.03	8.12 ± 0.02	123.44 ± 0.05	96.22 ± 0.02	132.89 ± 0.02	89.00 ± 0.02	7.87 ± 0.23
R-22	25 ± 0.02	7.38 ± 0.02	8.23 ± 0.04	134.66 ± 0.03	98.34 ± 0.01	145.66 ± 0.03	102.00 ± 0.27	7.11 ± 0.19

*Means are statistically significant by 0.05 (Standard Error Value).

**TDS- Total Dissolved Solid, WHO- World Health Organization, BIS- Bureau of Indian Standards, NTU- Nephelometric Turbidity Unit.

Salinity refers to the concentration of dissolved salts in a water sample. Shil et al. (2019) Groundwater quality is categorized into freshwater ranges from 0 to 1%, salinized water ranges from 1 to 3.5%, and saline water ranges from 3.5–35.7% based on salinity levels. Electrical Conductivity (EC) is measured in s/cm at 25 degrees Celsius and serves as an indicator of water salinity. A. K. Taloor et al. (2020) It is influenced by cations (potassium, sodium, magnesium, and calcium) and anions (carbonate, sulfate, chloride, and bicarbonate). In our analysis, the maximum and minimum EC values were recorded in samples R-22 and R-9, ranging from 145.66 s/cm to 57.89 s/cm, respectively. In the study of Sharma et al. (2021) the sample EC ranges from 140 to 900 s/cm. The hardness of drinking water significantly affects consumer acceptance. No specific recommended value exists for drinkable water hardness. C. Zanotti et al. (2019) The overall hardness of the samples ranged from 24.00 to 345.00 mg/L which is under the permissible limit of 500 mg/L according to BIS. Turbidity measures the optical dispersion of light in water and indicates water clarity. It is usually measured in nephelometric turbidity units (NTU), with a preferred value of less than 5 NTU indicating clearer water. Higher turbidity signifies an increased presence of suspended particles, which can carry heavy metals, microorganisms, and organic chemicals. The turbidity values in the collected samples ranged from 1.67 to 16.20 NTU. Cotruvo (2017)

The concentration of iron varies with the depth of the sampled water table. Typically, the iron concentration increases with increasing water depth. In this study, the primary sources of sample collection ranged in depth from 32 to 200 meters. Notably, 40% of the collected samples exhibited elevated iron content, rendering them unsuitable for direct consumption without appropriate treatment. It was observed that the initial iron content was relatively high, particularly in the northeastern states where significant levels of iron contamination were found in Arunachal Pradesh, Assam, Mizoram, Meghalaya, and Tripura. The permissible limit of iron is 0.3 mg/L. S. I. Abba et al. (2020) Additionally, it is anticipated that nearby states would also be at risk of pollution, underscoring the urgency of taking swift preventive action. Manganese concentrations below 0.1 mg/L are generally considered safe for consumption, whereas levels exceeding this threshold can lead to adverse effects. Given its chemical characteristics similar to iron, manganese is often considered a close relative (Abba et al., 2020). High concentrations of manganese and iron were observed in specific samples R-14(0.42 mg/L and 0.91 mg/L respectively) and R-13(0.48 mg/L and 0.33 mg/L respectively) which exhibit similar patterns in this analysis. More than half of the examined samples contained elevated manganese levels, making them unsuitable for human consumption. Figure 3 illustrates the varying manganese concentration levels across different oxidation states.

Figure 3. The concentration of cations in water sample.

The BIS standard specifies a maximum aluminum level of 0.2 mg/L. C. Tokatli (2019) However, the samples analyzed in this study exceeded this limit, rendering them unsuitable for human consumption without prior filtration. The BIS standard specifies a maximum permissible zinc level of 15 mg/L. Anyanwu and Emeka (2020) Fortunately, the samples in this study remained within this limit, with zinc concentrations ranging from 0.00 to 0.16 mg/L. Magnesium and calcium concentrations in water play a crucial role in assessing water suitability and are correlated with water hardness. The concentration of Ca²⁺ ranged from 11.91 to 89.02 mg/L, whereas the concentration of Mg²⁺ ranged from 9.5 to 84.7 mg/L. Potassium, a naturally occurring element, exhibits significantly lower concentrations than calcium, magnesium, and sodium. The average potassium concentration was 11.93 mg/L, with a minimum of 0.57 mg/L and a maximum of 68.56 mg/L. Sodium concentrations ranged from 11.94 to 131.05 mg/L. In most natural waters, sodium is the dominant ion among cations and plays a pivotal role in Hydrogeo-chemistry. Khatri et al. (2020) The concentrations of heavy metals such as silver and chromium were not determined in the samples, as per Indian standards (IS:10500) and WHO guidelines.

High levels of fluoride in water are harmful to human health. However, Figure 4(a) shows fluoride concentrations in the study region generally remained below the ideal limits set using the WHO guidelines. Nitrate contamination in drinking water, often sourced from private wells, arises from groundwater hydrology, natural nitrate addition, and surface pollution. Mukherjee and Singh (2020) Although high nitrate concentrations can lead to microbial contamination, the nitrate levels in this study remained substantially below the permissible limit of 45 mg/L according to IS:10500. Notably, the presence of significant nitrite levels indicates oxygen deficiency and sewage waste contamination. Phosphate, a component found in fertilizers, can contribute to water pollution. High phosphate content can trigger eutrophication and algae blooms. Ustaoğlu et al. (2020) The BIS standard does not specify a maximum phosphate limit, but the WHO recommends a tolerable level of 0.1 mg/L. Consequently, water with elevated phosphate levels is unfit for human consumption without proper filtration. Wazir et al. (2020) analyzed the samples of Chandel district, Manipur for parameters such as temperature, pH, EC, TDS, salinity, cations, and anions, and their study concluded that the pH ranges from 5.97 to 8.67. The TDS values range from 70 to 460 mg/l, which indicates that lithophilic ions have dissolved into the groundwater samples. EC values vary from 140 to 900 S/cm. Exceeding EC values in some samples shows the presence of geogenic inorganic ions, which are released during the weathering of rocks and minerals. Sodium (Na+) concentrations are increased (96.6%) compared to the WHO permitted limit, ranging from 21.64 to 472.2 mg/l (average: 119.1 20.72 mg/l) and exhibiting larger geographic variability. The permitted limit of sulfate is 200 mg/l and the sample concentration ranges from 6.65 to 145.22 mg/l which is under the permissible limit. The authors hypothesized that sulfate mineral dissolution or sulfur oxidation is the cause of the higher concentration of sulfate in groundwater samples. Fluoride was found in groundwater samples between 2.30 mg/l and 1.65 mg/l with about 27.1% of those samples under the WHO-permitted limit of 1.5 mg/l.Dubey et al. (2020).

Figure 4. The concentration of anions in the water samples.

Sulfate concentrations should range between 100 and 200 mg/L according to the BIS guidelines. The tested water samples exhibited sulfate concentrations within the allowable limit, ranging from negligible quantities to 80 mg/L. Chloride ions, derived from various sources, including weathering and leaching, were found within the range of 2.05 to 269.07 mg/L for the water samples. Carbonate and bicarbonate concentrations, which are influenced by factors such as dissolved carbon dioxide, pH, and cations, remained below 200 mg/L in surface waters. Kumari and Rai (2020).

The assessment of bacteriological quality is crucial for overall water quality evaluation, along with physicochemical properties. As per the WHO recommendations, drinking water should be free from disease-causing microorganisms. Groundwater classified as “below risk” by WHO in terms of bacterial contamination, aligns with the findings of this investigation. Nonetheless, certain water samples in this study exhibited bacteriological contamination that renders them unsuitable for consumption, based on BIS standards. The bacteriological evaluation involved plating samples on nutrient agar, followed by incubation and colony counting. Ramesh et al. (2019).

Water quality index assessment

Several international and national organizations have developed numerous water indices to check water quality. For instance, the American Water Quality Index (AQI) was introduced by the United States National Sanitation Foundation in 1970. D. Mridha et al. (2021) This term is commonly used to describe the availability and suitability of potable water supplies for domestic use. The mean values of the 15 investigated parameters (EC, pH, TDS, turbidity, salinity, Cl⁻, NO), NO, SO₄, PO₄, Br⁻, Ca²⁺, Mg²⁺, Na⁺, and K⁺) from 22 samples were used for analysis. For each criterion, a weight value (AW) was assigned based on the impact on water quality. In the first step, the relative weight (RW) was calculated using Eq. (1)

(1) $\mathit{Wr}=\mathit{Wi}/\sum \mathit{Wi}$(1)

In the succeeding step, the Qi (quality rating) was determined by dividing the measured parameter (Ci) by the permissible water value (Si) (as per the WHO) and multiplying by 100, as shown in Eq. (2)

(2) $\mathit{Qi}=\left(\frac{\mathit{Ci}}{\mathit{Si}}\right)\ast 100$(2)

The sub-indices (SI) were obtained using Eq. (3) in the third phase, and the water quality index (WQI) was derived using Eq. (4)

(3) $\mathit{SIi}=\mathit{Wr}\ast \mathit{Qi}$(3)

(4) $\mathit{WQI}=\sum \mathit{SIi}$(4)

The Water Quality Index (WQI) aids in assessing the overall water quality. WQI data were used to compute WQI at various water sample locations, providing a quick and straightforward interpretation of water quality parameter values in Manipur. Table 3 lists the respective water quality metrics.

Table 3. The Relative weight of each parameter.

Water quality Parameters	Standards of Water Quality Parameters	AW (Assigned weight)	RW (Relative weight)
pH	8.5**	4	0.095
DO	5.0*	4	0.095
Total Hardness	300*	2	0.047
Electrical Conductivity (µS/cm)	50*	3	0.071
TDS (mg/L)	500**	3	0.071
Salinity(mg/L)	600***	3	0.071
Zinc	3.0*	1	0.023
Manganese	0.2*	4	0.095
Phosphate(mg/L)	40***	3	0.071
Iron	0.3*	1	0.023
Aluminum	0.03*	1	0.023
Nitrite (NO3^−) (mg/L)	50*	2	0.047
Fluoride(mg/L)	1.5*	3	0.071
Nitrate (NO2^−) (mg/L)	50*	2	0.047
Sulfate (SO4) (mg/L)	500*	1	0.023
		∑ n i= 1 AW = 37

*WHO (2017), ** BIS (1991), ***US EPA (1998).

#TDS- Total Dissolved Solid.

DO- Dissolved Oxygen.

In this study, the findings of the computed WQI are reported in Table 4 for the water samples that were taken in the autumn. According to the aggregate WQI, the drinking water quality was evaluated and classified as unsuitable (greater than 300), very poor (200–300), poor (100–200), good (50–100), and excellent (less than 50). Ravikumar et al. (2015) The WQI results for most samples fell within the range of 90–120, showing that 31.81% of the samples were in the range of good quality water. In terms of WQI, Manipur state exhibited good water quality, with a few samples classified as having medium water quality. Ramesh et al. (2019) conclude in their study that the WQI spans from 32.5 to 106.1, with approximately 21.2% of samples falling into the excellent water category, followed by samples with 75.8% good water quality and samples with 3.1% poor water quality, respectively. Higher EC values and concentrations of dissolved ions like F⁻, Cl⁻ and NO₃⁻ have an impact on the WQI of samples for habitations. Additionally, samples with greater F⁻ concentrations have higher WQI values and are therefore deemed unfit for potable use. D. Mridha et al. (2021).

Table 4. WQI and Bacterial analysis of Manipur samples collected from different sites.

Samples Codes	WQI	Quality of the water	CFU/ml Count	Presence of bacteria
R-1	100.09	Good	0.00	No
R-2	124.04	Bad	200.00	Yes
R-3	71.66	Good	0.00	No
R-4	80.69	Good	0.00	No
R-5	110.70	Bad	190.00	Yes
R-6	137.52	Bad	140.00	Yes
R-7	192.80	Bad	200.00	Yes
R-8	103.69	Bad	0.00	No
R-9	90.27	Good	0.00	No
R-10	89.67	Good	0.00	Yes
R-11	118.01	Bad	200.00	Yes
R-12	111.22	Bad	210.00	Yes
R–13	235.07	Very Bad	350.00	Yes
R-14	107.02	Bad	180.00	Yes
R-15	118.60	Bad	350.00	Yes
R-16	87.66	Good	0.00	No
R-17	120.25	Bad	98.00	Yes
R-18	139.79	Bad	100.00	Yes
R-19	130.21	Bad	200.00	Yes
R-20	99.77	Good	0.00	No
R-21	103.24	Bad	200.00	Yes
R-22	313.16	Unsuitable	400.00	Yes

*WQI- Water Quality Index.

CFU- Colony forming unit.

Hydrogeochemistry of Manipur water samples

Hydrochemical data were subjected to several typical graphical plots to know and identify the central water types and ionic constituents in the study area’s aquifer. The graphical plots were used to validate the effectiveness of data in assessing drinking water quality. Ravikumar et al. (2015).

Hill-piper trilinear diagram

Figure 5 depicts the distribution of the ions plotted in the Hill-Piper Trilinear diagram. This diagram showcases the key cations and anions that influence surface water or groundwater characteristics. The diagram includes two triangles at the bottom and a diamond-shaped triangle at the top (Piper, 1994). Jain C. et al. (2018) It classifies surface water and groundwater into six categories: Na⁺ - Cl⁻ type, Mixed Ca²⁺ - Mg²⁺ - Cl⁻ type, Mixed Ca²⁺ - Na⁺ - HCO₃⁻ type, Na⁺ - HCO₃⁻ type, Ca²⁺ - HCO₃⁻ type and Ca²⁺ - Cl⁻ type. Analysis of the Hill-Piper diagram indicates that 35% of the samples fall into the Ca²⁺-Cl⁻ type. Additionally, the study reveals that samples are predominantly distributed into Ca²⁺-Cl⁻ and Na⁺-HCO₃⁻ types. Cations are dominated by Ca²⁺ > Na⁺ whereas anions primarily consist of CO32- - HCO3- The graph suggests anion dominance over alkaline earth, possibly due to the presence of sodium and potassium in the environment. Uddin et al. (2021) Moreover, Ravikumar et al. (2015) study concluded that according to the hydrochemistry of the examined samples, the primary cations are present in the following order: Na⁺ > Ca²⁺ > Mg²⁺ > K⁺ while the major anions are present in the following order: HCO₃⁻ > NO -) > Cl⁻ > SO₄ - > F⁻. According to the study, groundwater quality is affected by rock-water interactions, with sodium being the most dominating alkali and calcium and magnesium being the most prevalent alkaline earth metals leached in the aquafer while Kumar et al. (2020) studied hill piper diagrams in the semi-arid region of India and their research revealed that in the pre-monsoon period, 16% of samples were Ca²⁺ type, 56% were Mg²⁺, and the remaining 28% fell into no dominant cation zone, whereas in the post-monsoon period, 44% are Mg²⁺ type, 33% are in no dominant zone, and 23% are Ca²⁺ type. In both the pre- and post-monsoon, the anion triangle shows that HCO₃⁻ (100%) is the dominant ion. As a result, the concentration of ions such as Na⁺, K⁺, and Cl⁻, as well as SO₄-), is very low and inconsequential in both seasons. From the above findings it might be concluded that the dominant water facies were Ca²⁺-Cl⁻ and Na⁺-HCO3- type. Analogous research has been done to determine the hydrogeochemistry and water quality of various groundwater in the Lesser Himalayas, and it has revealed that alkaline earth is more abundant than alkaline metal and weak acid is more prevalent than strong acid. Kant et al. (2018).

Figure 5. Hill piper trilinear diagram.

Durov scatter plot

The Durov Scatter Plot proposed by Lloyd and Heathcoat in 1985, documents the hydrochemical facies observed in the Hill-Piper plot. Kumar P. et al. (2020) The cation field in this plot is enriched with Na⁺ and K⁺, whereas the anion field is dominated by HCO₃⁻. The prevalence of mixed water types in the Durov diagram data suggests the influence of reverse ion exchange and dissolution as the primary hydrochemical mechanisms altering groundwater. The Durov diagram reveals that 81.2% of the samples plot within the fifth area along the dissolving or mixing line. This pattern indicates a simple dissolution or mixing pattern with a dominant cation but no significant dominant anion. Moreover, the plot shows that 55% of the samples exhibit Ca²⁺ dominance in cation and anion distribution (Figure 6). R Dubey et al. (2020) also showed in their study that the Durov plot of the water samples shows that the origin of water in the research area is primarily influenced by two geochemical processes. Hydrogeochemical properties and other chemical parameters of the Parbati River were evaluated in recent research. The findings of this study’s Durov plot are consistent with the current investigation.

Figure 6. Durov class scatter plot diagram.

Gibbs’s diagram

The Gibbs diagram is a valuable tool for establishing the relationship between water composition and the lithological properties of aquifers. Gibbs (1970) It illustrates three distinct fields: rock-water interaction dominance, evaporation dominance, and precipitation dominance. The diagram is plotted between TDS vs Na⁺/(Na⁺ + Ca²⁺) and TDS vs Cl⁻/(Cl⁻ + HCO₃⁻), with all ionic concentrations expressed in meq./L. Figure 7a indicates that the samples fall between evaporation and precipitation, while Figure 7b suggests that rock weathering dominates evaporation and precipitation. The rock-water interaction dominant field demonstrates how rock chemistry interacts with percolating fluids beneath the surface through processes such as silicate weathering, where rock forms soluble silica, cations, and clay minerals through hydrolysis.

Figure 7. Gibbs diagram (a) TDS vs Na+/(Na++Ca2+) (b) TDS vs Cl-/(Cl-+HCO3-).

Chadha’s plot

Chadha’s Plot (Figure 8) represents an advanced version of Piper’s trilinear diagram and an expanded Durov diagram. Chadha’s graphical representation illustrates the progression of hydrochemical processes in surface water. Chadha D. (1999) The X-axis shows the difference in mill equivalent percentage between alkali and alkaline earth metals, whereas the Y-axis displays the difference between strong and weak acidic anions. Analysis of the Chadha Plot is based on the following groups: 1 (Ca²⁺ – Mg²⁺ – Na⁺ – K⁺), 2 (Na⁺ – K⁺ – Ca²⁺ – Mg²⁺), 3 (HCO₃⁻ – Cl⁻ – SO₄-), 4 (SO₄-) – HCO₃⁻ – Cl⁻), 5 (Ca²⁺ – Mg²⁺ - HCO₃⁻), 6 (Ca²⁺ – Mg²⁺ – Cl⁻– SO₄-), 7 (Na⁺ – K⁺ – Cl⁻ – SO₄-), and 8 (Na⁺ – K⁺ – HCO₃⁻). Maximum samples falling into groups 1, 2, 5, and 8 exhibit Cl⁻ dominant Na⁺ type, HCO₃⁻ dominant Ca²⁺ - Mg²⁺ type, Na⁺ - Cl^—type, Na⁺ dominant Cl⁻type, Ca²⁺ - Mg²⁺ dominant HCO₃⁻ or Na₂SO₄⁻ - Ca²⁺ + Mg²⁺ - HCO₃⁻ type water. The plot indicates that surface water varies over time due to high bicarbonate ion concentration, leading to the precipitation of Ca²⁺ and Mg²⁺.

Figure 8. Chadha’s Plot.

Relative statistical analysis

Figure 9 presents the relative statistical analysis of certain parameters to understand the hydrological process (Pizzi, Caputo, Corvino, & Venturelli, 2020). The concentration of Ca²⁺ (R2 = 0.0276), Na⁺ (R2 = 0.0423), and Mg²⁺ (R2 = 0.0003) in water displays a weak association with the concentration of HCO₃⁻. Similarly, the concentration of HCO₃⁻ + Cl⁻ (R2 = 0.3913) weakly associates with Na⁺ + Mg²⁺ + Ca²⁺. The concentration of Mg²⁺ (R2 = 0.1806) demonstrates a weak association with Ca²⁺, whereas the concentration of Ca²⁺ (R2 = 0.071) weakly associates with Na⁺. However, the concentrations of Na+ (R2 = 0.0171), Ca2+ (R2 = 0.1305), and Mg2+ (R2 = 0.0025) show a weak association with the concentration of Cl-. Additionally, the weak association between the cations in the surface water with Cl- was detected. Surface water and groundwater in the river Munda Basin have been researched in a manner similar to this one, and the results are consistent with the current study. Barik and Pattanayak (2019).

Figure 9. Relative statistical analyses of correlation between (a) Ca2+ vs. HCO3- (b) Na+ vs. HCO3- (c) Na+ vs. Cl- (d) Mg2+ vs. Ca2+ (e) Ca2+ vs. Cl- (f) Ca2+ vs. Na+ (g) Mg2+ vs. HCO3- (h) HCO3- + Cl- vs. Na+ + Mg2+ + Ca2+ (i) Mg2+ vs. Cl-.

Water suitability for the irrigation purpose

Magnesium hazard (mH)

Tracking water quality parameters is essential for maintaining soil fertility and crop quality. Poor-quality water can negatively impact irrigation. If mH is less than 50 meq./L, the water is suitable for irrigation. However, if it exceeds 50 meq./L, the water is not suitable for irrigation purposes. Barik and Pattanayak (2019) Figure 10 illustrates that 31.8% of the water samples fall within the suitable range.

Figure 10. Diagram Show Magnesium Hazard.

Total hardness (TH)

Most of the samples fall into the category of “hard water,” according to the classification of groundwater’s total hardness (TH). Kant N. et al. (2018) Hardness values ranged from 123.28 to 412.12 mg/L, with an average value of 232.06 mg/L. The maximum acceptable limit for TH is 500 mg/L for drinking water, and the most desirable limit is 100 mg/L according to WHO standards. Water sample with a concentration exceeding 300 mg/L is considered to be very hard. Figure 11 shows the total hardness of the water sample. Samples 4, 5, 18, and 22 exhibited 41.2, 310.46, 341.83, and 312.71 mg/L, respectively, indicating a hard water type. The hardness of the water is attributed to the occurrence of alkaline earth elements such as magnesium and calcium.

Figure 11. Diagram showing total Hardness.

Permeability index (P.I)

The use of Na⁺, Ca²⁺, Mg²⁺, and HCO₃⁻ enriched water primarily affects soil permeability. The permeability index is classified mainly into three classes: Class 1, Class 2, and Class 3.Only Class 1 and Class 2 water are appropriate for irrigational use with 75% maximum permeability, whereas Class 3 water, with only 25% maximum permeability, is unsuitable for irrigation. In this study, 27.2% of the samples fall into Class 1, and 63.6% fall into Class 2, indicating suitability for irrigation (Figure 12). However, 4.5% of the samples fall into Class 3, indicating water unsuitability. Kant N. et al. (2018) reported that in their study PI values indicate that approx. 21.2% of samples show suitability and 78.8% of samples show unsuitability for irrigational uses.

Figure 12. Classification of suitability for irrigation purposes based on permeability index.

Sodium percentage

Sodium is considered a crucial cation for irrigation because it can reduce soil fertility. The Wilcox diagram was employed to plot the computed percentage of Na versus EC values. The diagram reveals that the majority of groundwater samples fall within the “excellent to good” category, followed by “good to permissible.” In addition, three samples fall within the “permissible to doubtful” range, and four samples are plotted in the “doubtful to unsuitable” category. Approximately 36.6% of samples are categorized as excellent to good, whereas 27.2% fall into the good to permissible range, indicating suitability for irrigation according to Figure 13. Conversely, the remaining 13.4% of the samples are deemed unsuitable for such use. Cotruvo etal. (2017) reported that their Wilcox graph shows that 84.8% of samples fall into the excellent to good range for irrigational water and 15.2% of samples fall into the good to permitted range.

Figure 13. Wilcox plot for sodium percentage in water samples.

Sodium adsorption ratio (SAR)

The sodium adsorption ratio is a critical parameter in irrigation water analysis, serving to determine the suitability of groundwater for agricultural purposes. Wilcox (1955) It quantifies the level of salt or alkali exposure to crops. High SAR values in irrigation water indicate elevated Na+ concentration and reduced Ca²⁺ concentration. The SAR values range from 0.26 to 2.24, with a mean value of 0.97, underscoring its suitability for irrigation (Figure 14). Kumar and Sharma (2019) reported that in their study SAR concentration shows that approximately 78.8% of samples fall in the category of low alkali hazard (SAR), whereas 18.2% and 3% of samples fall in the category of increasing problem and severe problem of alkali hazards, respectively.

Figure 14. Wilcox plot for the sodium adsorption ratio.

Digital elevation model

The elevation map derived from the SRTM QGIS data of the Imphal Valley and its surrounding region displays the maximum and least elevation. Low elevation locations are represented by the valley, while high elevation areas are represented by the valley’s hillocks and surrounding hills. The Imphal Valley is essentially flat, with little fluctuation in elevation. The valley’s height ranges from 768 to 939 m above mean sea level. However, the valley contains many hillocks with elevations of up to 1800 m above sea level, which are largely exposed on the valley’s northern and southern sides. These little hills follow the NE-SW trend and are referred to as structural hills in the literature. The mountain ranges that run parallel to the valley on both the western and eastern sides reach a maximum elevation of 2357 meters above sea level. The longitudinal profiles revealed three distinct altitude levels in the valley. The valley has the lowest altitude, followed by the second and third altitude levels on the eastern side of the valley, which is divided by hills and small hillocks in the region. The slope map of the Imphal Valley and its catchment area is also extracted based on SRTM-DEM as shown in Figure 15, which shows that the slope of the area varies from 0° to 69°. Further the slope has been subdivided into five equal classes viz; very gentle (0° to 13°), gentle (13° to 25°), moderate (25° to 38°), steep (38° to 50°) and very steep (50° to 69°) slopes. Major part of the valley has very gentle slope (0° to 13°), whereas the isolated hills present in the valley and the surrounding mountains has moderate to steep slopes. These areas show the slope ranging from 25° to 50°. The area which is very adjacent to the valley scattered in the whole catchment’s area shows gentle slope (13° to 25°). However the north-western and south-eastern parts of the catchment’s area show very steep slope (50° to 69°)

Figure 15. Digital elevation model (DEM) of the area.

Conclusions

Except for heavy elements such as lead, the dataset indicates that all samples collected from various locations conform to both the WHO and Indian Standards in terms of physicochemical, cationic, and anionic properties. Notably, the concentrations of iron, manganese, and phosphate exceed permissible limits, rendering the water unsuitable for drinking or domestic use. However, effective water treatment can improve water quality before use. Bacterial contamination was also detected in some sample sources. This study has illuminated groundwater contamination within the region, which likely necessitates further testing to identify additional contaminated aquifers. The water quality index was calculated to be 126.59, with 31.8% of the samples falling within the acceptable range for consumption. Both the Hill-Piper and Durov diagrams indicate that alkaline earth elements dominate alkali metals, a finding supported by Chadha’s plot. The Gibbs diagram and the relative statistical analysis diagram highlight the significant roles of rock weathering and ion exchange in hydrogeochemistry. Parameters such as mH, TH, P.I, SAR, and sodium percentage confirm the suitability of water samples for irrigation and crop management. EC values suggest moderate to high saline suitability for irrigation, whereas TDS values classify the water as freshwater. The results from the Piper plot and Chadha’s classification predominantly identify the Ca²⁺-Mg²⁺-HCO₃^– water type, indicative of temporary hardness, with a smaller subset classified as Ca²⁺-Na⁺- HCO₃^– or Na⁺- HCO₃^–, likely due to ion exchange processes. In conclusion, ion exchange processes are observed to be influenced by the predominance of weak acidic anions over strong acidic anions and alkaline earth metals over alkali metals within the studied area. The morphometric parameter provided by the SRTM digital elevation model (DEM) may be used to delineate the valley’s large fan deposits. Lineaments based on SRTM demonstrate spatial diversity in direction; on the western side of the valley, they trend NE-SW, whereas on the southern side, they trend NW-SE. The south-eastern half of the valley showed a swing in the direction of lineaments, which follow the northern elongation direction of the Indonesian island, which has a westward convexity. The valley’s south-eastern section is part of the convex system’s bottom component. The analysis emphasizes the importance of periodically measuring various water quality parameters to enhance water treatment processes.

Acknowledgments

The authors want to acknowledge Banasthali University for their support during sample collection.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

No funding is provided for this research work.