The study demonstrates the utilization of the Quantum Geographic Information System (QGIS) package, an open-source geographic information system (GIS) tool for evaluating the quantity and quality of groundwater resources. This research employed data from public sources pertaining to several sampling stations in the Indian city of Dehradun as its case study and converted this information into a digitized format. The use of QGIS allows for processing and analysis of huge data, leading to the creation of informative maps that depict the spatial distribution of groundwater characteristics. By employing spatial analysis techniques, the study aimed to gain insights into the state of groundwater resources, including their availability, variations in level, and suitability for drinking and irrigation purposes. By visualizing and analyzing the groundwater data using QGIS, the study contributes to the broader goal of managing water resources efficiently and helps policymakers, water resource managers, and other stakeholders make informed decisions regarding groundwater management, allocation, and conservation strategies.

  • Easily monitor groundwater resources using open-source GIS software, QGIS.

  • Improved data visualization for efficient water resource management.

  • Easy identification of locations requiring water harvesting to increase levels.

  • Determines drinking and irrigation appropriateness by geographical analysis.

  • Research enhances groundwater management and conservation.

Fresh water is an essential component for the preservation of all forms of life; the issue of inadequate access to this resource is one that is felt in every part of the world (Fredriksson 2016; Singha & Singha 2023). As a result of the ever-increasing demand for freshwater that is caused by the rise in population, the focus has shifted to the protection and management of groundwater (Baalousha & Lowry 2022; Polemio & Voudouris 2022). To effectively manage water resources, it is necessary to handle a substantial quantity of data, and the instrument that is currently the most effective and efficient for doing so is geographic information systems (GIS) (Dadhich et al. 2016; Stevović & Nestorović 2016; Kumar & Singh 2018; Habeeb & Weli 2021; Kpiebaya et al. 2022; Radulović et al. 2022; Hosseininia & Hassanzadeh 2023; Noori & Singh 2023; Rukshar et al. 2023). Management of water resources is one of the necessary steps towards effective planning, development, and distribution of water resources, as well as for the most efficient use of water resources (Loucks & van Beek 2017; Criollo et al. 2019). Water resources management, which involves planning, developing, distributing, and managing the optimum use of water resources, needs to adapt well to the current and future need of allocation of water (Criollo et al. 2019). In order to manage groundwater resources, a wide range of physical and chemical parameters must be monitored and evaluated on a regular basis (Kumar et al. 2017). In addition to geology and isotopes, these characteristics, which are used to conceive the behaviour of the environmental system, are commonly stored in various scales and forms, such as maps, spreadsheets, or databases (Criollo et al. 2019). Collecting, preserving, analyzing, and visualizing data are all made easier with the assistance of GIS. In the scientific community as well as the public and corporate sectors GIS software is used widely (Kumar et al. 2022). Platforms based on GIS can be utilized to conduct assessments of local and regional water quality, water supply, zone mapping, and risk (Criollo et al. 2019). Depending on the local water table depth, groundwater quality varies greatly. It is primarily controlled by the amount and content of dissolved solids, although it also changes with the seasons. Managing and protecting groundwater resources depends critically on the groundwater quality assessment made possible by GIS, particularly given their sensitivity to contamination from both natural and human causes (Ram et al. 2021). Groundwater models produced with appropriate groundwater quality data transformed into GIS databases provide an accurate evaluation of the geographical distribution of groundwater quality and how it varies over time and with changes in land use. Information regarding the risk of groundwater contamination may assist in the selection of suitable locations for specific activities, thereby minimizing the adverse effects on groundwater and facilitating the more effective management of groundwater resources (Loucks & van Beek 2017). Researchers utilize several technologies such as ArcGIS (Mahboob et al. 2017; Krishan et al. 2023), QGIS (De Filippis et al. 2019; Azam et al. 2022; Kpiebaya et al. 2022), and Modular Finite-Difference Flow Model (MODFLOW) (De Filippis et al. 2019) for groundwater quality evaluation. ArcGIS is a widely utilized platform for geospatial analysis of groundwater; however, it operates on a subscription model. In contrast, QGIS serves as an open-source alternative, providing a cost-effective solution for geospatial analysis. MODFLOW is used for modeling groundwater flow, sometimes in combination with GIS technologies; yet it necessitates substantial data and is complex. A comparison of several GIS systems for groundwater quality research, together with their unique features, advantages, and limitations, is presented in Table 1. The QGIS programme was chosen for this investigation because it outperformed other GIS systems, even in the most demanding computer environments (Chen et al. 2010). This study uses spatial interpolation techniques to examine the geographical distribution of groundwater quality measurements to identify pollution hotspots, understand contamination sources, and develop enhanced management strategies in the Dehradun district using QGIS, an open-source GIS software. Dehradun relies heavily on its groundwater sources for drinking water supply (National Institute of Hydrology 1997). The contour tool of the QGIS software was employed in conjunction with the inverse distance weighted (IDW) (Ilayaraja & Ambica 2015; Raghav & Singh 2021; Shukla et al. 2021) interpolation technique to enhance the spatial representation of water quality parameters on thematic maps. IDW interpolation is favoured over other geostatistical methods such as Kriging because of its rapid visualizations. simplicity, speed, and computational efficiency, especially for smooth spatial patterns and the ability to capture general trends by emphasizing closeness rather than intricate spatial correlations (Munyati & Sinthumule 2021). There is a scarcity of studies evaluating the quantity and quality of groundwater resources in the Dehradun district using QGIS software. This study enhances the effective monitoring of groundwater levels and quality, hence supporting informed decision-making and superior management in more locations.

Table 1

Comparison of various GIS technologies for groundwater quality studies

TechnologyFeaturesAdvantages and disadvantagesReferences
Remote sensing and GIS 
  • Remote sensing and GIS offer a powerful tool for groundwater mapping, facilitating the creation of groundwater level maps, hydrogeological maps, and groundwater flow models

 
  • High cost of acquiring and processing remote sensing data

  • Technical complexity limits widespread application

 
Arulbalaji et al. (2019)  
Spatial interpolation technique 
  • Techniques for estimating unsampled points

  • Reveals spatial variation in data over time

 
  • Requires large amounts of data sets for accurate prediction

 
Ahmad et al. (2021), Raghav & Singh (2021), Shukla et al. (2021)  
Geostatistical techniques 
  • Analyzes spatial variability and trends

  • Widely used for mapping groundwater quality

  • The most frequently employed interpolation technique is IDW, which assigns a higher weight to points that are closest to the interpolation point

 
  • Straightforward and efficient method for conducting local assessments

  • Limited accuracy in groundwater quality measurement in case of irregular spatial distributions and significant variability in groundwater quality

 
Ilayaraja & Ambica (2015), Mahboob et al. (2017), Polemio & Voudouris (2022), Karim et al. (2024)  
Water quality index (WQI) technique 
  • Composite score representing overall water quality

  • GIS used for mapping and analysing WQI

 
  • Quick analysis of groundwater quality trends

  • Highlights safe areas for drinking, irrigation, and industrial use

  • Accurate interpretation relies on the appropriate weighting criterion

 
Ram et al. (2021), Tefera et al. (2021), Karim et al. (2024)  
Multicriteria decision technique (MCDT) 
  • MCDT integrated with GIS is used to assess groundwater quality by combining multiple water quality parameters

 
  • Comprehensive but complex

  • Complexity in criteria selection and weighting

 
Kpiebaya et al. (2022), Mandal et al. (2023)  
TechnologyFeaturesAdvantages and disadvantagesReferences
Remote sensing and GIS 
  • Remote sensing and GIS offer a powerful tool for groundwater mapping, facilitating the creation of groundwater level maps, hydrogeological maps, and groundwater flow models

 
  • High cost of acquiring and processing remote sensing data

  • Technical complexity limits widespread application

 
Arulbalaji et al. (2019)  
Spatial interpolation technique 
  • Techniques for estimating unsampled points

  • Reveals spatial variation in data over time

 
  • Requires large amounts of data sets for accurate prediction

 
Ahmad et al. (2021), Raghav & Singh (2021), Shukla et al. (2021)  
Geostatistical techniques 
  • Analyzes spatial variability and trends

  • Widely used for mapping groundwater quality

  • The most frequently employed interpolation technique is IDW, which assigns a higher weight to points that are closest to the interpolation point

 
  • Straightforward and efficient method for conducting local assessments

  • Limited accuracy in groundwater quality measurement in case of irregular spatial distributions and significant variability in groundwater quality

 
Ilayaraja & Ambica (2015), Mahboob et al. (2017), Polemio & Voudouris (2022), Karim et al. (2024)  
Water quality index (WQI) technique 
  • Composite score representing overall water quality

  • GIS used for mapping and analysing WQI

 
  • Quick analysis of groundwater quality trends

  • Highlights safe areas for drinking, irrigation, and industrial use

  • Accurate interpretation relies on the appropriate weighting criterion

 
Ram et al. (2021), Tefera et al. (2021), Karim et al. (2024)  
Multicriteria decision technique (MCDT) 
  • MCDT integrated with GIS is used to assess groundwater quality by combining multiple water quality parameters

 
  • Comprehensive but complex

  • Complexity in criteria selection and weighting

 
Kpiebaya et al. (2022), Mandal et al. (2023)  

Dehradun, located in the Doon Valley in the Himalayan foothills, is surrounded by two prominent rivers, the Ganges to the east and the Yamuna to the west. The city is positioned between the latitudes of 29°55′N and 30°30′N, and the longitudes of 77°35′E and 78°24′E, as depicted in Figure 1. It encompasses a watershed area of approximately 210 km2, bordered by the Ganges in the southeast and the Yamuna in the northwest. The climate in Dehradun is predominantly moderate, with temperature variations depending on elevation. The region experiences a range of temperatures, from tropical in lower areas to severe cold in higher altitudes. Even in places such as Dehradun, temperatures can drop below freezing when the higher peaks are snow-covered. The annual rainfall in the Dehradun area is approximately 2,000 mm (Kumar et al. 2017). Most of the rainfall occurs from June to September, with the wettest months being July and August. This indicates that Dehradun receives a significant portion of its yearly precipitation during the monsoon season (Kumar et al. 2017). Understanding the climatic and geographic characteristics of Dehradun is vital for assessing water resources and their management. The knowledge of the region's location, topography, and rainfall patterns helps in evaluating the availability and sustainability of water sources, as well as planning for water-related activities and infrastructure development.
Figure 1

An image of the research area's map, displaying Dehradun's groundwater stations (own work).

Figure 1

An image of the research area's map, displaying Dehradun's groundwater stations (own work).

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In the analysis of geographical groundwater data using QGIS, 15 sampling stations were selected for study. The data used for analysis is sourced from India's Central Ground Water Board (CGWB), Ministry of Jal Shakti, Department of Water Resources, River Development, and Ganga Rejuvenation, Government of India. The relevant information extracted from the CGWB site is organized and presented in Tables 2 and 3. To incorporate the geographical data into the analysis, the shape file of the Dehradun map is georeferenced using the georeferencing tool in QGIS. This process aligns the map to its correct spatial location, allowing for an accurate overlay of the groundwater station data onto the base map of Dehradun. The geographical data of the groundwater stations, obtained from the CGWB WRIS, are digitized and superimposed onto the base map of Dehradun. This integration enables a comprehensive investigation of both the level and quality of groundwater in the region. The use of QGIS in this process provides a powerful tool for visualizing and analyzing geographical groundwater data, contributing to a better understanding of the groundwater situation in Dehradun.

Table 2

Groundwater levels at various sampling stations in Dehradun

S. No.Ground water stationsLatitudeLongitudeBasinLevel (m)
Lal tapar 14.640 30.120 Ganga 16.95 
Kanwali 12.800 30.315 Ganga 11.48 
Chhorba 21.010 30.419 Ganga 21.50 
Kuanwala 5.730 30.245 Ganga 5.15 
Ramgarh 6.440 30.331 Ganga 6.02 
Motichur 11.030 30.013 Ganga 11.03 
Rishikesh 6.490 30.105 Ganga 5.32 
Jhajra 13.110 30.340 Ganga 7.91 
Nanda ki Chauki 10.620 30.347 Ganga 13.68 
10 Redapur 7.520 30.404 Ganga 6.43 
11 Rampura 5.260 30.370 Ganga 9.34 
12 Selakui 15.740 30.354 Ganga 14.19 
13 Majra 4.430 30.292 Ganga 24.20 
14 Sabhawala 7.730 30.369 Ganga 10.14 
15 Singhniwala 9.090 30.331 Ganga 7.53 
S. No.Ground water stationsLatitudeLongitudeBasinLevel (m)
Lal tapar 14.640 30.120 Ganga 16.95 
Kanwali 12.800 30.315 Ganga 11.48 
Chhorba 21.010 30.419 Ganga 21.50 
Kuanwala 5.730 30.245 Ganga 5.15 
Ramgarh 6.440 30.331 Ganga 6.02 
Motichur 11.030 30.013 Ganga 11.03 
Rishikesh 6.490 30.105 Ganga 5.32 
Jhajra 13.110 30.340 Ganga 7.91 
Nanda ki Chauki 10.620 30.347 Ganga 13.68 
10 Redapur 7.520 30.404 Ganga 6.43 
11 Rampura 5.260 30.370 Ganga 9.34 
12 Selakui 15.740 30.354 Ganga 14.19 
13 Majra 4.430 30.292 Ganga 24.20 
14 Sabhawala 7.730 30.369 Ganga 10.14 
15 Singhniwala 9.090 30.331 Ganga 7.53 
Table 3

Qualitative data at various sampling stations in Dehradun

S. No.Ground water stationsCa (mg/L)Cl (mg/L)F (mg/L)K (mg/L)Mg (mg/L)Na (mg/L)EC at 25 °C (μmhos/cm)pHTotal hardness (mg/L)
Lal tapar 3.5 0.06 38 391 170 
Kanwali 24 14 – 36 74 713 210 
Chhorba 32 11 – 0.4 26 18 430 190 
Kuanwala 24 7.1 0.08 1.5 12 6.9 270 8.03 110 
Ramgarh 56 – 26 482 250 
Motichur 40 3.5 0.2 7.2 23 334 130 
Rishikesh 28 11 0.1 14 275 130 
Jhajra 28 0.1 14 274 130 
Nanda ki Chauki 28 14 0.1 15 15 330 130 
10 Redapur 3.5 – 2.4 14 112 30 
11 Rampura 32 11 – 2.4 10 210 90 
12 Selakui 20 3.5 0.01 14 14 204 80 
13 Majra 76 0.09 14 14 541 250 
14 Sabhawala – 47 11 403 200 
S. No.Ground water stationsCa (mg/L)Cl (mg/L)F (mg/L)K (mg/L)Mg (mg/L)Na (mg/L)EC at 25 °C (μmhos/cm)pHTotal hardness (mg/L)
Lal tapar 3.5 0.06 38 391 170 
Kanwali 24 14 – 36 74 713 210 
Chhorba 32 11 – 0.4 26 18 430 190 
Kuanwala 24 7.1 0.08 1.5 12 6.9 270 8.03 110 
Ramgarh 56 – 26 482 250 
Motichur 40 3.5 0.2 7.2 23 334 130 
Rishikesh 28 11 0.1 14 275 130 
Jhajra 28 0.1 14 274 130 
Nanda ki Chauki 28 14 0.1 15 15 330 130 
10 Redapur 3.5 – 2.4 14 112 30 
11 Rampura 32 11 – 2.4 10 210 90 
12 Selakui 20 3.5 0.01 14 14 204 80 
13 Majra 76 0.09 14 14 541 250 
14 Sabhawala – 47 11 403 200 

To visually understand the level and quality of groundwater, heat maps are generated. Heat maps use colour gradients to represent the severity of the problem, indicating areas with higher or lower groundwater levels and highlighting variations in groundwater quality across the study area. Valuable insights can be gained regarding the level and quality of groundwater in the Dehradun region by creating heat maps and analyzing the spatial distribution of groundwater data. This analysis helps in identifying areas with critical groundwater issues, supporting effective decision-making and management of groundwater resources. The validation procedure for heat maps and spatial interpolation methodologies is of paramount importance for accurate analysis. The validation process for a heat map entails assessing whether the visual representation faithfully corresponds to the underlying data. This includes ensuring that significant patterns and trends are appropriately emphasized, as well as confirming that the colour gradients, legend nomenclature, and contextual data are suitable for interpretation (Vacanti 2019; Sibrel et al. 2020). This validation is performed by means of comparisons with data obtained from the CGWB, the Ministry of Jal Shakti, the Department of Water Resources, River Development, and Ganga Rejuvenation, Government of India. Adhering to the guidelines outlined below facilitates a deeper understanding of heat maps and enables the extraction of insights from patterns, trends, and anomalies within the data.

Identification of the data

Identify the variable and the kind of data being represented, specifying whether it is numerical or categorical. Numerical data are quantitative, but categorical data are qualitative in character. Ascertain the objective of the visualization, whether it seeks to illustrate correlation, distribution, density, or another metric.

Comprehend the data context

Comprehend the context of the data, regardless of whether it is performance-related, spatial, or time-series data. A heat map's interpretation can be altered by the context of the data. If the heat map displays time series data, it is important to observe time-related trends, including seasonality, surges, or periodic patterns.

Examine the axes

Identify the representations of the x and y axes, which may include time, categories, spatial locations, or continuous variables. Familiarization with each axis facilitates a better interpretation of the correlations or comparisons depicted by the heat map.

Examine the legend and its colour

The heat map employs a colour gradient to denote values. Darker or more intense legend's colours often signify greater values, whereas lighter colours denote lower values. Custom colour schemes may even be employed for particular data categories. Examining the legend's colour is crucial for comprehending accurate mapping.

Identify clusters and patterns

Focus on regions with comparable colour intensity. Similar-coloured clusters can be used to identify patterns or groupings within the data. Symmetric patterns or colour repetitions on the map might draw attention to recurring patterns or relationships in the data.

Observe any annotations

Annotations are intended to draw attention to critical points, clarify unusual values, or direct readers to areas of interest. Locate any text, numerals, or symbols that are superimposed on the thermal map.

Detecting anomalies

It is possible to identify substantial deviations from the norm by examining the anomalies, which may be crucial for decision-making or additional research. Outliers frequently manifest as isolated colour blocks that exhibit a stark contrast to their surroundings. These may be anomalies, rare occurrences, or data errors.

Spatial interpolation method

The contour tool of the QGIS software was employed in conjunction with the IDW interpolation technique to enhance the spatial representation of water quality parameters on thematic maps. IDW interpolation is favoured over other geostatistical methods due its rapid visualizations. Simplicity, speed, and computational efficiency, especially for smooth spatial patterns and the ability to capture general trends by emphasizing closeness.

Current level of groundwater

The analysis of groundwater levels in different seasons (May 2020, August 2020, November 2020, and January 2021), as depicted in Figures 25, provides insights into the temporal behaviour of water levels over time. The temporal geographical distribution of water levels reveals that a majority of the Dehradun district has water levels exceeding 15 mbgl (metres below ground level). Shallow water levels, varying from 5 to 10 m beneath ground level, are in small regions in the northwestern part of the Sahaspur block in Doon Valley. The water level at a depth of 10–15 mbgl is seen in the northwestern part and the southern section of the Doon Valley. To assess if there were any changes in the groundwater regime throughout the seasons, a comparison of water levels was conducted for each season from May 2020 to January 2021. The spatial distribution of groundwater levels in May 2020 (pre-monsoon) was compared with that of August 2020, indicating an improvement in water levels due to rainfall. The visual comparison of Figure 2 with Figures 3 and 4 indicates that a significant seasonal increase of 2–4 m is prevalent in most of the Doon Valley, particularly encompassing substantial areas within the Doiwala and Raipur blocks of the district. The Doon Valley predominantly exhibits a seasonal trend of rising water levels. However, as the year progressed, the water levels subsided, as evidenced by the comparison of the spatial distribution of water levels between May 2020 and January 2021, as shown in Figures 2 and 5. These findings highlight the dynamic nature of groundwater levels in the Dehradun district. The impact of rainfall is evident in the improvement of water levels, but over time, the water table tends to decline. This temporal analysis can yield important insights into variations associated with seasonal changes in precipitation and evapotranspiration; it is typically inadequate for accurately capturing long-term trends in groundwater dynamics. This inadequacy arises from the potential for significant changes to occur within a single season, which may be overlooked if monitoring is conducted solely at seasonal intervals. Higher temporal resolution, such as monthly, weekly, or even daily data, tends to be essential for conducting reliable trend analyses over extended periods that will be addressed in forthcoming research. The stakeholders and policymakers can make informed decisions regarding water conservation and usage by monitoring and analyzing the temporal behaviour of groundwater levels and evaluating potential interventions to sustain groundwater resources in the Dehradun district.
Figure 2

Spatial distribution of level of groundwater (own work).

Figure 2

Spatial distribution of level of groundwater (own work).

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Figure 3

Spatial distribution of level of groundwater (own work).

Figure 3

Spatial distribution of level of groundwater (own work).

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Figure 4

Spatial distribution of level of groundwater (own work).

Figure 4

Spatial distribution of level of groundwater (own work).

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Figure 5

Spatial distribution of level of groundwater (own work).

Figure 5

Spatial distribution of level of groundwater (own work).

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Quality of groundwater

In assessing groundwater quality, parameters, such as pH, calcium, sodium, absorption ratio, total dissolved solids (TDS), electrical conductivity (EC) at 25 °C, and nitrate concentration (NO3), are crucial as they provide valuable insights into the water's overall chemistry, often reflecting the geological formations it passes through and potential issues related to water hardness, salinity, and its suitability for drinking and agricultural use, particularly in specific regions (Singh & Hussian 2016; Kumar et al. 2022). It becomes possible to assess the quality of the groundwater, identify potential contamination sources, monitor changes over time, and make informed decisions regarding water resource management and treatment processes by digitizing and analyzing groundwater wells using these parameters. Industrial waste, sewage, fertilizers, and pesticides from urbanization and agriculture pollute groundwater. Groundwater management is needed to provide drinking water and safeguard ecosystems. Inadequate urban waste management and excessive agricultural pesticide usage can severely harm groundwater quality (Pradhan et al. 2023). The analysis results can help determine the suitability of groundwater for various purposes, such as drinking water, irrigation, and industrial uses, and guide actions to ensure the protection and conservation of this vital resource.

Calcium

The analysis of calcium concentration distribution reveals that most wells located in the Dehradun district exhibit calcium concentrations within the allowed range (Figure 6), which falls below the acceptable threshold of 75 mg/L as specified by the Bureau of Indian Standards (BIS), IS 10500, 2012. This finding suggests that the groundwater in the region is predominantly fresh and appropriate for potable use. Calcium ranks as the fifth most prevalent element within the Earth's crust and holds significant importance in both human cellular physiology and skeletal structure. Approximately 95% of the calcium present in the human body is mostly kept inside the skeletal system, encompassing bones and teeth. The presence of a significant calcium deficit in the human body can lead to many health issues such as rickets, impaired blood coagulation, and bone fractures. Conversely, an excessive intake of calcium can contribute to the development of cardiovascular illnesses (Kumar et al. 2017; Raghav & Singh 2021).
Figure 6

Spatial distribution of Ca (own work).

Figure 6

Spatial distribution of Ca (own work).

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Electrical conductivity

EC is a crucial parameter for assessing water quality, as it indicates the ability of water to conduct electrical current. EC is intrinsically linked to TDS since the solubilized substances in water affect its conductivity. Water in its pure state generally exhibits low conductivity owing to the lack of impurities. However, when water is polluted or includes impurities, its conductivity rises. It is influenced by the presence of inorganic dissolved particles, such as chloride, nitrate, sulphate, phosphate, sodium, magnesium, calcium, iron, and aluminium ions. Additionally, temperature plays a role, with higher temperatures leading to increased conductivity. To standardize the measurement, conductivity is often specified at 25 °C. Based on World Health Organization (WHO) standards, water with an EC within an acceptable limit of 400–2,000 μS/cm is considered suitable for drinking. In the case of the Dehradun district, the spatial distribution of EC reveals that most of the wells exhibit conductivity within the 400–2,000 μS/cm range (Figure 7). This indicates that the groundwater in Dehradun has low levels of dissolved mineral content. The low EC levels in the groundwater of Dehradun suggest that it is indeed suitable for drinking purposes, in accordance with WHO standards. This finding is significant for water resource management and reinforces the region's ability to meet the drinking water needs of its population. The availability of groundwater with low EC not only ensures access to potable water but also reduces the potential risks associated with high mineral content in drinking water, such as adverse health effects or the need for additional treatment processes. This information is invaluable for policymakers, water resource managers, and stakeholders involved in the planning and development of water supply systems in Dehradun. It confirms the suitability of groundwater as a reliable and safe drinking water source, contributing to sustainable water resource management practices in the region. However, it is important to note that while EC is an important indicator of water quality, it is just one aspect of a comprehensive assessment. Other parameters, such as pH, specific ions, and microbiological contaminants, should also be considered to ensure a comprehensive understanding of groundwater quality.
Figure 7

Spatial distribution of electrical conductivity (own work).

Figure 7

Spatial distribution of electrical conductivity (own work).

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Chlorides

Chloride itself is generally not considered toxic at typical concentrations found in drinking water. However, high chloride levels can contribute to increased saltiness, affect the taste of water, and impact its palatability. Individuals with specific health conditions, such as high blood pressure or certain kidney disorders, may need to monitor their chloride intake. High chloride concentrations in water can accelerate the corrosion of metal pipes, fittings, and fixtures within the distribution system. This can result in infrastructure degradation and potentially lead to increased levels of other metals (e.g. lead) in the water, which can have adverse health effects. The spatial distribution of chloride concentration shows that most wells in the Dehradun district have chloride concentrations less than 250 mg/L (Figure 8), which is below the acceptable limit of 250 mg/L according to BIS, IS 10500, 2012. This indicates that the groundwater in the area is primarily fresh and suitable for drinking purposes. Monitoring and maintaining the chloride concentration within acceptable limits is crucial for ensuring the quality of drinking water and protecting public health. It's important to continue regular monitoring and testing of groundwater to ensure that the chloride concentrations remain within the acceptable range.
Figure 8

Spatial distribution of chloride (own work).

Figure 8

Spatial distribution of chloride (own work).

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Magnesium

Magnesium is an essential mineral for human health and is involved in various physiological processes. Drinking water with moderate levels of magnesium can be beneficial, as it contributes to daily magnesium intake. However, excessive magnesium in drinking water may have a laxative effect and can also affect the taste and hardness of the water. According to the BIS in their publication 10500, 2012, the established acceptable level for magnesium is 30 mg/L, while the allowed limit is set at 100 mg/L. The findings indicate a noticeable rise in contamination levels in groundwater at a few well sites (Figure 9). This increase can be attributed to reasons such as urbanization, industrialization, anthropogenic activity, and several other contributors. In regions where the magnesium concentration in groundwater is excessively high, water treatment methods such as ion exchange, reverse osmosis, or lime softening can be used to reduce magnesium levels to an acceptable range for both consumption and other uses.
Figure 9

Spatial distribution of magnesium (own work).

Figure 9

Spatial distribution of magnesium (own work).

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Fluoride

The acceptable limit of fluoride concentration, according to BIS, IS 10500, 2012, is up to 1 mg/L (BIS 2012). The spatial distribution of fluoride concentration shows that the majority of wells in the Dehradun district have fluoride concentrations less than 1 mg/L (Figure 10), indicating that it is safe to drink and poses no health risks.
Figure 10

Spatial distribution of fluoride (own work).

Figure 10

Spatial distribution of fluoride (own work).

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Sodium

For most people, consuming moderate levels of sodium in drinking water is not a health concern. In fact, sodium is an essential electrolyte that plays a crucial role in maintaining fluid balance, nerve function, and muscle contraction. However, individuals with specific health conditions, such as hypertension or kidney issues, may need to be cautious about their sodium intake. Water containing high levels of sodium is not suited for agricultural use due to its tendency to degrade soil quality. The WHO has established guidelines for the permissible concentration of sodium in drinking water, which is set at a maximum limit of 200 mg/L. Most wells in the Dehradun area have sodium concentrations below this threshold (Figure 11), making them safe for human consumption and use in agricultural irrigation.
Figure 11

Spatial distribution of sodium (own work).

Figure 11

Spatial distribution of sodium (own work).

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pH

Water's acid–base balance can be evaluated using pH as a key metric. It is also an indicator of the water's acidity or alkalinity (Meride & Ayenew 2016). The acceptable limit of pH range, according to BIS, IS 10500, 2012, is 6.5–8.5. Overall, the Dehradun water source falls within the desired and appropriate range. The research focused on evaluating the acid-base balance of the water in the Dehradun water source using pH as a key metric. The pH of water serves as an indicator of its acidity or alkalinity. According to the acceptable limit specified by BIS, IS 10500, 2012, the pH range for drinking water should be between 6.5 and 8.5. The research findings indicate that the water in the Dehradun water source falls within the desired and appropriate pH range (Figure 12). This suggests that the water is well-balanced in terms of acidity and alkalinity, making it suitable for consumption. Maintaining the pH within the acceptable range is crucial because extreme acidity or alkalinity can affect the taste and safety of drinking water. Water with a highly acidic pH may corrode pipes and potentially leach metals into the water, while highly alkaline water can have a bitter taste and potentially cause gastrointestinal issues. Therefore, the research findings provide reassurance that the water in the Dehradun water source is within the acceptable pH range, indicating a balanced acid-base profile. This is crucial for ensuring the quality and usability of the water for drinking purposes. Regular monitoring and periodic testing of the water's pH levels are still important to ensure that it remains within the acceptable range. Such monitoring helps identify any potential changes in water quality and allows for appropriate actions to be taken to maintain the water's pH balance and overall suitability for consumption.
Figure 12

Spatial distribution of pH (own work).

Figure 12

Spatial distribution of pH (own work).

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Total hardness

The presence of divalent ions, including calcium, magnesium, and iron, in water is a contributing factor to its hardness. The term ‘water hardness’ refers to the presence of magnesium and calcium ions in water. The presence of magnesium and calcium carbonates and bicarbonates results in transitory hardness, whereas the occurrence of magnesium and calcium sulphates and chlorides leads to permanent hardness. The phenomenon of scaling in utensils and boilers, as well as the incrustation and corrosion of pipes, can be attributed to the property of hardness (Chabuk et al. 2023). According to the BIS in their publication 10500, 2012, the established acceptable level for total hardness is 200 mg/L, while the allowed limit is set at 600 mg/L. The findings indicate a noticeable rise in total hardness levels in the Raipur and Doiwala areas of Dehradun (Figure 13).
Figure 13

Spatial distribution of total hardness (own work).

Figure 13

Spatial distribution of total hardness (own work).

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The research indicates that the water table is in a state of decline, with most of the Dehradun district experiencing water levels that exceed 15 mbgl. The spatial distribution of groundwater levels before and after the rainy season indicates that there has been an increase in water levels in numerous locations because of rainfall. This assists in the identification of areas that require special consideration for water harvesting to enhance the water level. The spatial distribution of qualitative parameters including pH, EC, total hardness, and calcium, chlorides, magnesium, fluorides, and sodium major ion concentrations, indicates that the most of area except a few patches in Doiwala and Raipur areas of Dehradun, the water is suitable for human consumption and irrigation purposes. This study highlights the importance of regular groundwater monitoring to ensure sustainable water resource management. The study's accuracy increases as the number of datasets increases. QGIS aids in visualizing and analyzing the groundwater data and contributes to the broader goal of managing water resources efficiently and helps policymakers, water resource managers, and other stakeholders in making informed decisions for sustainable groundwater resource management, pollution control, and land use planning in the region.

No funding was received to assist with the preparation of this manuscript.

A.M. conceptualized and investigated the study, manuscript preparation, reviewed and edited the article; N.A.S. conceptualized and reviewed the process; P.M. reviewed and edited the article; G.P. reviewed the work; N.S.M. reviewed and editing. The final manuscript was read and approved by all authors.

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.

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