Integrated Multi-Model Approach for Assessing Groundwater Vulnerability in Rajasthan’s Semi-Arid Zone: Incorporating DRASTIC and SINTACS Variants

Abstract

Groundwater pollution in Rajasthan, India, poses significant challenges due to the region’s heavy reliance on this resource for drinking and irrigation. Given the increasing water scarcity and overexploitation, this study assesses the susceptibility of groundwater pollution in this semi-arid area. We applied and compared vulnerability mapping methods, DRASTIC and SINTACS, and their modified versions. These methodologies considered various geological and environmental factors such as depth-to-water table, recharge, aquifer conductivity, soil, and topography. The modified versions also integrated land use and temperature data for enhanced sensitivity. Validation was achieved by comparing contaminant data from the Central Ground Water Board (CGWB), India, focusing on primary contaminants such as fluoride, nitrate, chloride, and total dissolved solids (TDS). The results strongly align with the modified methodologies and observed groundwater ion values. Specifically, more than half of the 300 sample points analyzed indicated TDS values exceeding the permissible 300 ppm limit, with over 80 points surpassing 500 ppm. The vulnerability was classified into the following five categories: very low; low; medium; high; and very high. Notably, 30.53% of the area displayed “very high” vulnerability under the modified DRASTIC model. Districts like Jalore, Pali, Sirohi, and Jodhpur emerged as highly vulnerable zones, while areas within Udaipur, Kota, and Jaipur, among others, showed very high vulnerability. This research highlights the importance of conducting groundwater vulnerability assessments, especially for regions grappling with water scarcity like Rajasthan. The findings from this research are pivotal in guiding sustainable ground water resource management, as well as advocating continual monitoring and effective groundwater conservation strategies in the region.

1. Introduction

Groundwater is undoubtedly one of the most crucial natural resources on earth. It plays an integral role in the global hydrological cycle and constitutes a significant water supply source for human consumption and agricultural activities [1,2]. These assertions are particularly relevant for arid and semi-arid regions, where surface water availability is sporadic, and reliance on groundwater is crucial for socio-economic development. Among these regions, Rajasthan in India is a pertinent example, given its high dependence on groundwater for diverse uses. Groundwater contamination in Rajasthan presents a multifaceted challenge, with varying levels of ions, such as total dissolved solids (TDS), fluoride, chloride, and nitrate, contributing to the deterioration of this vital resource [3]. TDS levels in many regions of Rajasthan exceed the permissible limits due to the accumulation of dissolved salts from natural geological processes and agricultural runoff, affecting water quality and making it unsuitable for consumption and irrigation. Evaporation significantly affects the vulnerability of groundwater by diminishing recharge rates, particularly in arid regions. Changes in evaporation patterns due to climate and the influence of land use further compound the overall vulnerability of groundwater systems. Moreover, evaporation plays a role in concentrating contaminants, adversely impacting groundwater quality and making it more susceptible to pollution. A thorough comprehension of these factors is essential for adept groundwater resource management. High fluoride and arsenic found in many aquifers are another pervasive issue, causing dental and skeletal fluorosis and leading to severe health problems like dental fluorosis and arsenicosis [3,4,5]. Industrial and agricultural runoff, improper disposal of hazardous waste, and unregulated mining practices have also contributed to groundwater contamination. Rajasthan’s arid climate amplifies the reliance on groundwater. It is imperative to address this issue promptly through stricter regulations, sustainable water management practices, and increased public awareness to mitigate groundwater pollution’s health and environmental risks [6,7,8]. Chloride contamination is primarily linked to industrial discharges and disinfection byproducts, potentially impacting the health of those consuming such water. Elevated nitrate levels are mainly attributed to agricultural fertilizers and sewage, posing health risks, particularly to infants. Geological factors, agricultural practices, industrial activities, and population density influence the availability of these ions in groundwater. Rajasthan’s arid climate further exacerbates the problem, as heavy reliance on groundwater intensifies the concentration of these contaminants [9].

Addressing groundwater deterioration requires comprehensive measures, including stricter regulation of industrial effluents and agricultural practices, sustainable water management, and promoting safe drinking water sources to mitigate the adverse health and environmental effects of ion contamination in Rajasthan’s groundwater. Rapid industrialization and escalating population pressure have put an enormous strain on groundwater resources in these regions, with over-extraction leading to groundwater depletion. Furthermore, anthropogenic activities have led to water quality degradation through various modes of contamination, including biological, organic, and inorganic pollutants [10]. It is alarming that about 80% of human diseases are waterborne, judiciously emphasizing the importance of managing water resources, especially groundwater [11]. However, managing this essential resource requires a comprehensive understanding of the aquifer system and the hydrologic setting of the area, particularly in terms of its vulnerability to pollution. The term “vulnerability”, in the context of groundwater, relates to the susceptibility of an aquifer to contamination from surface-originating pollutants [12,13]. Variability exists in the exposure of different parts of the land to contamination due to soil type, topography, precipitation, and human activities [14]. Various models and methods have been developed to assess groundwater vulnerability, each with unique strengths, weaknesses, and applicability to specific hydrogeological settings. Two of the most widely used methodologies worldwide include DRASTIC [15] and SINTACS [16]. The DRASTIC model, an acronym formed from the seven parameters it considers, was developed by the National Water Well Association and the U.S. Environmental Protection Agency. The SINTACS model, on the other hand, while sharing several variables with DRASTIC, uses a different weighting and rating system. Both methodologies have been extensively utilized and proven effective in diverse settings. Nevertheless, the applicability of these models in specific geological or hydrogeological settings has necessitated the development of modified versions. These modified models, such as Modified DRASTIC and Modified SINTACS [17,18], aim to enhance the predictive power of the original methodologies by introducing additional parameters or modifying the existing ones to suit specific conditions better.

Given the unique hydrogeological characteristics and high reliance on groundwater in the semi-arid region of Rajasthan, the need for a comprehensive vulnerability assessment is unquestionable. There is a dire need for the authorities and stakeholders to understand the groundwater contamination risks and employ efficient management strategies. This research intends to conduct a comparative study of the DRASTIC, SINTACS, Modified DRASTIC, and Modified SINTACS models in assessing groundwater vulnerability in Rajasthan. The objective is to discern the most suitable model for this region, offering valuable insights for formulating groundwater management strategies. Technological advancements, especially in geographic information systems (GIS), have remarkably bolstered the capability to conduct detailed and precise vulnerability assessments. GIS enables the manipulation and interpretation of spatial data, significantly assisting in developing vulnerability maps [4,19]. Integrating GIS and groundwater vulnerability models will, thus, contribute to a more holistic understanding of the potential threats to groundwater quality in the semi-arid region of Rajasthan. This study will improve the scientific performance of the underlying hydrogeological processes and provide practical insights for stakeholders, policymakers, and local communities. This research will contribute to the discourse on groundwater protection, preservation, and sustainable utilization by offering a comparative analysis of the selected models. In doing so, this study will address an issue of global concern—water security—through the lens of a specific geographical region, thus ensuring its relevance and applicability. Building upon these advancements, this study aims to (a) assess groundwater vulnerability in terms of quality in Rajasthan’s semi-arid zone using the DRASTIC and SINTACS hydrological model and its variants and (b) validate the groundwater vulnerability map. This study seeks to contribute to sustainable water resource development and planning in the area.

2. Study Area

The study area for this research is the semi-arid region of Rajasthan in the northwest part of the country. It covers 45.4 percent of the Rajasthan state, with an area of about 158,092 km². It lies between 23°06′ to 29°26′ northern latitudes and 74°18′ to 76°90′ east longitudes. It covers the districts of Ajmer, Alwar, Banswara, Baran, Bharatpur, Bhilwara, Bundi, Chittorgarh, Dausa, Dholpur, Dungarpur, Jaipur, Jhalawar, Karauli, Kota, Pratapgarh, Rajasmand, Sawai Modhpur, Tonk, Udaipur, and Parts of Churu, Jhunjhunu, Sirohi, Pali, Nagaur, Sikar, and Small Parts of Hanumangarh (Figure 1). This region is characterized by low rainfall, high evaporation rates, and an extreme climate, with high temperatures during summer, especially from April to June, with scorching heat reaching up to 40 degrees. The winters in Rajasthan are relatively cooler, with an average temperature of 20 degrees during the daytime and dropping significantly during the nights, sometimes reaching 0 degrees centigrade. The primary water sources in this region are groundwater, collected rainwater, and water transported from other areas through canal systems like the Indira Gandhi Canal. The annual average rainfall in this area ranges from 300 mm to 600 mm. The climate, coupled with the underlying geology, makes water scarcity a significant issue in this region.

Regarding geology, this area comprises unconsolidated sandy soil and consolidated rocks, including granites and metamorphic rocks (Figure 2a). The soil in this region is mainly sandy to sandy loam, which allows for rapid water infiltration but poor water retention capabilities. The aquifer systems in this region are typically unconfined with high fluoride concentrations, which is a concern for potable water. Agriculture is practiced under these challenging conditions, often relying on traditional water conservation practices, such as constructing step wells, tanks, and small dams. The study of such an area is crucial for understanding the implications of climatic conditions on water availability and usage, the characteristics of the soil and geological substratum, and the impact on the livelihood of the local population.

Geomorphological landforms in the Rajasthan region, such as aeolian origin, denudational origin, fluvial origin, fluvial plain, hills, structural origin, and waterbodies, significantly impact groundwater levels [12,16,20]. Aeolian landforms like dunes can obstruct groundwater flow, causing water accumulation in dense areas. Denudational landforms formed by erosion affect groundwater levels based on rock types and permeability. Groundwater levels in fluvial areas closely relate to adjacent river water tables, varying with wet and dry periods. Hills function as groundwater recharge zones, replenishing aquifers with rainwater infiltration. Structural landforms, including faults, modify groundwater pathways and enhance storage capacity. Waterbodies serve as both groundwater recharge areas and outlets, influencing local climate and recharge rates (Figure 2b). For a better understanding of the study area’s aspects, such as the drainage of the region and the flow direction map of the region, help us better understand these interactions as they are vital for sustainable groundwater management in Rajasthan, considering the intricate relationships between landforms, precipitation, and hydrogeological processes (Figure 2c). Rajasthan’s groundwater system, a lifeline in this arid region, faces significant deterioration due to a combination of factors. Over-exploitation, driven by agricultural and domestic demands, has led to declining water tables. Additionally, the semi-arid climate amplifies evaporation, further straining groundwater resources. Natural geological processes contribute to high total dissolved solids (TDS) in many areas, rendering water unfit for consumption and irrigation. Furthermore, excessive fluoride, nitrate, chloride, and other contaminants seep into aquifers from agricultural runoff and industrial discharges. As a result, the state grapples with increased salinity, pollution-related health issues, and an urgent need for sustainable water management to safeguard this crucial resource. The ground water well data used for validation is shown in Figure 2d.

3. Materials and Methods

3.1. Datasets

The current study employed DRASTIC and SINTACS with their modified versions to assess groundwater vulnerability zones in the semi-arid region of Rajasthan. The 9-parameter maps of the DRASTIC and SINTACS MODELS are prepared by using the available data of the specific parameters such as depth-to-water table map, net recharge map, aquifer map, soil map, topography map, impact of vadose zone map, hydraulic conductivity map, land use land cover, and temperature map of the region. The data necessary for preparing parameter maps are collected and extracted from the surveys and websites given in

Table 1. Data used in this study.

Name of Dataset	Source	Spatial Resolution	Temporal Resolution	Purpose
Landsat-8	USGS Earth Explorer	30 m	2021	LULC Map
Groundwater data	CGWB Rajasthan	30 m	2010–2020	Depth-to-water table map
Rainfall data	CHIRPS Data	5.3 km	2000–2020	Net recharge map
Aquifer data	Geological Survey of India	1 km	-	Aquifer map
Soil media	FAO-UNESCO Soil Map	5 km	-	Soil map
ASTER-DEM	NASA EARTH DATA	15 m	-	Slope, flow direction, and drainage maps
Geology and Geomorphology data	Geological Survey of India	500 m	-	Impact of the vadose zone map
Temperature data	IMD	-	2010–2021	Temperature map
Contaminants concentration data	CGWB Well Data	-	2010–2021	Validation

.

After acquiring the data, it is necessary to pre-process them according to the requirements of the models. This could involve georeferencing, rasterization, interpolation, normalization, etc., based on the specific needs of the DRASTIC, SINTACS, and modified models. For each model, specific ratings and weights were assigned to the respective parameters (depth-to-water table, net recharge, aquifer media, soil media, topography, impact of the vadose zone, conductivity for DRASTIC, depth-to-water table, effective infiltration, unsaturated zone, soil media, terrain slope, hydraulic conductivity, and land cover for SINTACS). Multiply each layer’s value by weight and then sum up all layers to generate the vulnerability index. To account for the influence of temperature and land use land cover (LULC), ratings and weights were assigned to these two parameters and added to the original DRASTIC and SINTACS models. As before, the product of the rating and weight was computed for each layer, including the new layers, to create the modified vulnerability index. The original and modified DRASTIC and SINTACS models were validated using the ground well contamination data. A common approach is to divide the study area into regions of low, moderate, and high vulnerability based on the vulnerability index and then compare the actual contamination levels in these regions.

3.1.1. Depth-to-Water Table

The depth-to-water table plays a crucial role in assessing groundwater vulnerability to contamination as it determines the extent and time contaminants take to reach the aquifer, influencing their dispersion and dilution characteristics [21]. Accurate knowledge of this parameter is vital for effective groundwater management and protection. In this study, well logs from the Central Ground Water Board (CGWB) in Rajasthan were used to construct a depth-to-water table map using the Inverse Distance Weighting (IDW) method known for its effectiveness in spatial interpolation. The DRASTIC approach was then applied, utilizing surveyed well data, to derive the depth of the water table. The results showed a pattern where the depth-to-water table decreased progressively with increasing elevation, indicating the susceptibility of the study area to potential groundwater contamination. This analysis highlights the importance of considering the vertical distance to groundwater resources in groundwater vulnerability assessments, strengthening the reliability of the findings [8,19] (Figure 3).

3.1.2. Net Recharge

Net recharge, which represents the amount of water infiltrating the ground surface and reaching the water table, is a crucial parameter for assessing groundwater vulnerability (Figure 4). It plays a vital role in diluting contaminants within unconfined aquifers, as it primarily occurs through vertical infiltration from the surface. Higher recharge rates indicate greater dilution potential for pollutants. To create a net recharge map, rainfall data and a permeability map of the study area are combined using Inverse Distance Weighting (IDW) interpolation. This approach estimates the potential infiltration for aquifer recharge, providing insights into the spatial variability of groundwater recharge and enhancing the understanding of recharge potential in the region [22,23,24].

3.1.3. Aquifer Media

Aquifer media refers to the characteristics and properties of the geological materials that comprise the aquifer [25]. It represents the nature of the saturated zone and plays a significant role in determining the route and path length of pollutants within the aquifer [24]. The properties of the aquifer media, such as permeability, porosity, and hydraulic conductivity, influence the movement and transport of contaminants through the aquifer system. The study area’s aquifer map is prepared using the surveyed data and ArcGIS software (Figure 5).

3.1.4. Soil Media

Soil plays a critical role in groundwater recharge as it is the initial layer through which water infiltrates the subsurface. Finer soil textures like clay have smaller spaces between particles, resulting in slower infiltration rates. In contrast, coarser textures like sandy soil have larger spaces, leading to faster infiltration rates [6]. The soil media, which refers to the upper portion of the vadose zone with significant biological activity, also plays a crucial role in groundwater recharge [25]. It encompasses the materials between the weathered unsaturated zone and the depth reached by plant roots and soil biotic activities [26]. Understanding the characteristics of the soil media is essential for assessing groundwater recharge and considering factors such as land use practices, vegetation cover, and soil management techniques. In this study, data on soil types and their associated characteristics were obtained from the Food and Agriculture Organization (FAO, Rome, Italy) of the United Nations, specifically utilizing the FAO’s Soil Map of the World, which provides comprehensive soil classification at a global scale. The soil types considered in this study’s area included alluvial, clayey, silty, fine sandy, and loamy soils, contributing to a comprehensive groundwater vulnerability assessment (Figure 6).

3.1.5. Topographical Map

The topography or slope of an area has a significant influence on groundwater vulnerability to contamination. Slopes determine the runoff and retention of pollutants on the land surface. Areas with steeper slopes tend to have increased runoff and reduced infiltration, making them less vulnerable to groundwater contamination [27]. Conversely, regions with gentle slopes retain water for longer durations, allowing more water to infiltrate the ground and increasing their susceptibility to contamination [5]. To assess slope variability, ASTER DEM Satellite Data were utilized to generate a slope percentage map with a spatial resolution of 30 m. This study’s area exhibited slopes ranging from 0% to 50% and was categorized into six classes: 0–5%; 5–10%; 10–20%; 20–30%; 30–40%; 40–50%; and above 50%. Most of the area fell within the 0–10% slope range. Based on the classification by [22], areas with gentle slopes received the highest rating of 10, while lower ratings were assigned to extremely steep slopes. This spatial representation of slope variability provides valuable information on the vulnerability of different areas to potential groundwater contamination (Figure 7).

3.1.6. Impact of Vadose Zone Map

The vadose zone, also known as the unsaturated zone, assesses groundwater vulnerability and contamination. It refers to the region between the land surface and the water table, characterized by unsaturated or discontinuously saturated conditions [5,28,29]. The vadose zone’s properties, such as depth, soil type, porosity, permeability, and preferential flow paths, significantly influence the movement and attenuation of pollutants [20]. Its depth can impact the travel time of contaminants to the water table, with deeper vadose zones allowing for longer attenuation processes. Different soil types within the vadose zone exhibit varying permeabilities and adsorption capacities, affecting the speed and extent of pollutant migration [30]. Preferential flow paths in the vadose zone can expedite water and pollutant movement. The vadose zone’s biological and chemical activities contribute to pollutant decomposition and neutralization, dependent on pollutant type and specific conditions [30]. Parameters related to depth-to-water table, net recharge, and soil media in groundwater vulnerability models, such as DRASTIC and SINTACS, account for the vadose zone’s impact [20]. Understanding the vadose zone’s characteristics and behavior is essential for accurate groundwater vulnerability assessments [20] (Figure 8).

3.1.7. Hydraulic Conductivity Map

Hydraulic conductivity is a crucial parameter in groundwater vulnerability assessments as it determines the ability of rocks or soils to allow for water movement under a pressure differential. It is calculated based on the rate of water flow across a unit cross-section over a given distance [31]. Meinzer defined it as the volume of water flowing through a 1-square-foot cross-section with a 1-foot hydraulic gradient per day. Hydraulic conductivity is influenced by intergranular porosity, fractures, and bedding planes. Hydraulic conductivity is vital in determining an aquifer’s ability to transport the fluid through its pore spaces. It controls the water flow rate through the soil for a given hydraulic gradient. In groundwater vulnerability assessments, hydraulic conductivity maps are constructed using the soil map of the study area. Ratings and ranges are assigned to different land cover types based on the approach of [32] (Figure 9). The study area exhibits a range of hydraulic conductivity values from <0.002 to 5 m/day. According to [1,19,28], regions with high hydraulic conductivity are more susceptible to pollution due to their increased potential for fluid transport.

3.1.8. Land Use Land Cover Map

Anthropogenic activities, such as industrial waste, sewage, and agriculture, significantly contribute to the degradation of groundwater quality [27]. In groundwater vulnerability assessments, land use and land cover (LULC) are crucial factors in determining potential contamination sources and the vulnerability of groundwater resources. LULC data help identify areas with specific land uses that may introduce environmental contaminants, such as industrial areas, urban development, and agricultural practices. By analyzing LULC patterns, vulnerability assessments can identify regions where contaminants are more likely to infiltrate the soil and impact groundwater. Different land use types have varying infiltration rates, surface runoff characteristics, and potential for pollutant transport. Integrating LULC data with hydrogeological properties allows for classifying areas into zones based on their vulnerability to contamination. This zoning approach assists in prioritizing management and protection strategies, focusing on areas with higher contamination risks due to specific land uses (Figure 10).

3.1.9. Temperature Map

Temperature changes in the subsurface environment can significantly impact physical, chemical, and microbial processes, leading to changes in groundwater quality [33,34]. Studies, have concluded that temperature changes can affect groundwater quality [35]. While temperature may not be a primary factor in groundwater vulnerability assessments for pollution, it can indirectly influence vulnerability in certain cases. Higher temperatures can reduce dissolved oxygen levels, alter microbial activity, and disrupt the ecological balance of aquatic species, potentially making groundwater more vulnerable to pollution. Temperature variations can also impact the rate of chemical reactions in groundwater, affecting the mobility and fate of contaminants. Microbial populations in groundwater play a crucial role in natural attenuation processes, including the biodegradation of contaminants. Changes in temperature regimes can influence microbial activity, potentially influencing the vulnerability of groundwater to pollution. In the study area, the temperature reaches a high of up to 45 degrees Celsius in the summer season and drops to a low of 1 or 2 degrees Celsius in winter. The average temperature of the region is 36 degrees Celsius. Temperature data can be incorporated into broader groundwater vulnerability assessments, considering other factors such as hydrological information, land use patterns, geological data, and contaminant sources. A more comprehensive vulnerability assessment model or map can be developed by integrating temperature measurements to assess groundwater vulnerability to contamination (Figure 11).

3.2. Methodology Adopted

To utilize the methodology of the models, the factor data were converted into a raster data format within the ArcGIS platform. This conversion allowed the data to be represented in a consistent spatial resolution. Using the converted data, the final vulnerability maps of the four index maps were created by performing weighted overlay operations in ArcGIS. This process involved assigning weights to each factor based on its relative importance and combining factors to generate the vulnerability index (

Table 2. Rate assigned to different parameters.

Parameter	DRASTIC	SINTACS	Modified DRASTIC	Modified SINTACS
Depth-to-water table	5	5	5	5
Net recharge	4	4	4	4
Aquifer media	3	3	3	3
Soil media	2	3	2	3
Slope Media	1	3	1	3
Impact of vadose zone	5	5	5	5
Hydraulic Conductivity	4	3	4	3
LULC	--	--	5	5
Temperature	--	--	3	3

). The weighted overlay operation in ArcGIS facilitated the integration of the various factors. It produced the final maps, providing valuable insights into the study area’s groundwater vulnerability and contamination risks (Figure 12).

Step-wise methodology:

• Acquire the necessary data for the analysis. This includes groundwater data, digital elevation data, soil data, aquifer data, precipitation data, geology and geomorphology, land use, and temperature;
• Determine weights: assign relative importance weights to each input layer based on their relevance to the analysis. Weights can be assigned based on parameters, their role in vulnerability analysis, and their importance;
• Performed weighted overlay analysis by giving the assigned weights and ratings to the parameters and the aspects of the parameters individually and ran weighted overlay analysis. This gives us the DRASTIC AND SINTACS vulnerability zone maps;
• Then, we performed a modified weighted overlay analysis using the land use and temperature parameters, giving us the Modified DRASTIC and Modified SINTACS vulnerability zone maps;
• Categorize results into different risk levels. As in the present study, the vulnerability zones were categorized into five zones: very low; low; medium; high; and very high zones;
• The validation of the results was performed by using the well data and the four major ion data, such as the concentration of fluoride, chloride, nitrate, and TDS in the groundwater.

3.2.1. Assigning Rate and Weight to the Parameters Used

Each DRASTIC factor has been compared to the others to identify the relative significance of each factor [7,9]. To each DRASTIC, a relative weight between 1 and 5 was assigned. The important factors are rated at 5, while the minor factors are rated at 1. The Delphi technique was used to accomplish this (consensus). This tariff is fixed and unchangeable. Each range is for each DRASTIC and SINTACS [36]. The relative importance of each range about the possibility of pollution has been assessed relative to the other factors [20,37]. The DRASTIC and SINTACS range for each element has a weight that ranges from 1 to 10. Seven parameters, or seven input parameters for modeling, form the foundation of the DRASTIC and SINTACS models [34,38,39]. The following are the data sources listed in Table S1.

3.2.2. DRASTIC Vulnerability Index

The DRASTIC vulnerability index, which assesses the inherent vulnerability of aquifer systems, is calculated using the following symbols:

D_r: Ratings assigned to the depth of the water table;

D_w: Weights assigned to the depth of the water table;

R_r: Ratings for ranges of aquifer recharge;

R_w: Weights for aquifer recharge;

A_r: Ratings assigned to aquifer media;

A_w: Weights assigned to aquifer media;

S_r: Ratings for the soil media;

S_w: Weights for the soil media;

T_r: Ratings for topography (slope);

T_w: Weights assigned to topography;

I_r: Ratings assigned to the vadose zone;

I_w: Weights assigned to the vadose zone;

C_r: Ratings for rates of hydraulic conductivity;

C_w: Weights given to hydraulic conductivity.

The DRASTIC Index is then computed by applying a linear combination of all factors according to the following equation:

DRASTIC vulnerability Index = (D_r × D_w) + (R_r × R_w)+ (A_r × A_w)+ (S_r × S_w)+ (T_r × T_w)+ (I_r × I_w)+ (C_r × C_w)

The subscripts “r” and “w” represent the appropriate ratings and weights, respectively, and D, R, A, S, T, I, and C are the seven parameters. The initials of DRASTIC criteria are ranked from 1 to 5 in Table 2 based on how important they influence the contamination potential. Each parameter rating is multiplied by its weight and then added to generate the DRASTIC index number. Each characteristic is rated between 1 and 10, with a score of 10 indicating a high level of pollution potential.

3.2.3. SINTACS Vulnerability Index

The initial seven factors used to assess the inherent vulnerability of aquifer systems were used to create the name SINTACS [40,41]. The SINTACS vulnerability index is computed using the symbols listed below. The SINTACS vulnerability index for the study area is calculated using all these parameters with weights and ratings:

ISINTACS = ∑ Pi × Wi,

where I is the vulnerability index; Pi is the parameter rating, and Wi is the weight of the parameter.

S, I, N, T, A, C, and S are the seven parameters represented by the subscripts P and W, which match ratings and weights. The SINTACS parameters are ranked from 1 to 5 based on how significant a role they play in the contamination risk.

The SINTACS index number is calculated by multiplying each parameter by weight and averaging the results. Each characteristic is rated between 1 and 10, with a score of 10 indicating a high level of pollution potential [39,41,42].

3.2.4. Modified-DRASTIC Vulnerability Index

In the modified DRASTIC model, the conventional or the traditional method of DRASTIC is limited either by changing the weights or by adding the other parameters to the traditional way as per the need or the research criteria [29,43,44]. This research adds land use, land cover, and temperature maps to perform a modified DRASTIC analysis. The DRASTIC Index is then calculated using a linear combination of all factors using the equation below:

Modified DRASTIC Index (Mod-DVI) = IDRASTIC + LU_rLU_w + TE_rTE_w,

where LU_r = ratings to the land use land cover; LU_w = weights assigned to the land use land cover; TE_r = ratings to the temperature; TE_w = weights assigned to the temperature. In the modified DRASTIC model, we have also used the land use landcover parameter and temperature parameter to perform the DRASTIC vulnerability analysis; these additional parameters can assess the groundwater vulnerability more precisely.

3.2.5. Modified-SINTACS Vulnerability Index

In the modified SINTACS model, the conventional or the traditional method of SINTACS is limited either by changing the weights or by adding the other parameters to the traditional way as per the need or the research criteria [7,37,40]. This research adds land use, land cover, and temperature maps to perform a modified SINTACS analysis. Then, using a linear combination of all components by the following equation, the Modified SINTACS Index is calculated:

Modified SINTACS Index= ISINTACS + P_LU × W_LU + P_TE × W_TE,

where P_LU = ratings to the land use land cover; W_LU = weights assigned to the land use land cover; P_TE = ratings to the temperature; W_TE = weights assigned to the temperature. In the modified SINTACS model, we have additionally used the land use landcover parameter and temperature parameter to perform the SINTACS vulnerability analysis; by using these additional parameters, we can assess the groundwater vulnerability more precisely.

4. Results and Discussion

4.1. DRASTIC Vulnerability Map

The result map and weights for each element in DRASTIC were used to create the vulnerability map for the semi-arid region of Rajasthan, which is further separated into five zones known as very low, low, medium, high, and very high vulnerability zones. The areas show how easily the water table can become contaminated. Higher vulnerability areas exhibit greater susceptibility to water table pollution. The grades and weights assigned to the following variables directly impact the map results. Influence of the aquifer’s hydraulic conductivity and vadose (unsaturated) zone media. Water depth, recharge (net), soil, aquifer, and topography (slope of the surface, for instance; if the range of values is limited, there will be fewer values, and if the content is larger, there will be more classes that may be created from the same range of values (Figure 13).

This map’s shallow and low–shallow vulnerability zones indicate vulnerable areas less sensitive to pollution. In contrast, the very high and high vulnerability zones indicate weak areas more sensitive to pollution. The DRASTIC method primarily relies on hydrogeological factors; we observed distinct vulnerability zones within the middle to the eastern part of Rajasthan. The “very low” vulnerability zone covers 9.02% of the study area, while 37.89% falls into the “low” category. Additionally, 28.77% is categorized as “medium”, with 15.30% in the “high” vulnerability zone. Notably, 9.02% of the region exhibits a “very high” vulnerability to groundwater contamination (

Table 3. The area under different vulnerability zones based on the DRASTIC vulnerability map.

DRASTIC Vulnerability Zone	Area (sq. km)	Percentage (%)
Very Low	14,257.9	9.02
Low	59,893.9	37.89
Medium	45,490.9	28.77
High	24,191.9	15.30
Very High	14,257.4	9.02

). These findings reveal a relatively balanced distribution of vulnerability zones, with a significant portion of the area categorized as “low”.

4.2. SINTACS Vulnerability Map

The semi-arid region of Rajasthan’s vulnerability map, which is further divided into five zones known as very low, low, medium, high, and very high vulnerability zones, was prepared using the results map and weights for each factor in SINTACS. The regions demonstrate how sensitive the water table is to contamination. Greater susceptibility to water table pollution is seen in higher vulnerability locations (Figure 14). The grades and weights given to the following parameters directly impact the map’s outcomes. Water depth, net recharge, soil media, topography (surface slope), effect of the vadose (unsaturated) zone media, and hydraulic aquifer conductivity. For instance, a limited range of values would result in fewer values, whereas a more extensive range would allow dividing the same content into more classes. The shallow vulnerability zones on this map indicate vulnerable areas less sensitive to pollution. In contrast, the very high and high vulnerability zones indicate weak areas more sensitive to pollution.

The SINTACS method, which combines hydrogeological and hydro-chemical factors, yielded distinct vulnerability zones within the study area. Here, 4.53% of the region is classified as a “very low” vulnerability, while 28.25% falls into the “low” category. The “medium” vulnerability zone encompasses a substantial 41.89%, and 17.26% is designated as “high.” Additionally, 8.07% exhibit a “very high” vulnerability. Notably, this method emphasizes the “medium” vulnerability zone, suggesting areas of potential concern for groundwater quality (

Table 4. The area under different vulnerability zones based on the SINTACS vulnerability map.

SINTACS Vulnerability Zone	Area (sq. km)	Percentage (%)
Very Low	7157.8	4.53
Low	44,653.2	28.25
Medium	66,229.7	41.89
High	27,288.5	17.26
Very High	12,762.8	8.07

).

4.3. Modified DRASTIC Vulnerability Map

The Semi-arid region of Rajasthan’s vulnerability map was created using the results map and weights for each element in Modified DRASTIC. It is divided into five zones: very low, low, medium, high, and very high vulnerability zones. These regions demonstrate how sensitive the water table is to contamination. Greater susceptibility to water table pollution is seen in higher vulnerability locations (Figure 15). The grades and weights given to the following parameters directly impact the map’s outcomes. Depth-to-water table, recharge (net), aquifer conductivity (hydraulic), soil conductivity, topography (surface slope), the impact of the vadose (unsaturated) zone media, as well as land use and local temperature, for instance. A limited range of values would result in fewer values. In contrast, a larger capacity would allow the division of the same content into more classes. The shallow vulnerability zones on this map indicate vulnerable areas less sensitive to pollution. In contrast, the very high and high vulnerability zones indicate weak areas more sensitive to pollution.

Different vulnerability zones emerge when land use/land cover (LULC) and temperature data are integrated into the analysis using the modified DRASTIC method. The “very low” vulnerability zone encompasses 7.82% of the study area, with 22.50% in the “low” category. Furthermore, 19.81% fall into the “medium” vulnerability zone, and 19.34% are categorized as “high.” A significant 30.53% of the region exhibits a “very high” vulnerability, suggesting areas that may require immediate attention for groundwater protection (

Table 5. The area under different vulnerability zones based on Mod-DRASTIC vulnerability map.

Mod- DRASTIC Vulnerability Zone	Area (sq. km)	Percentage (%)
Very Low	12,357.0	7.82
Low	35,577.7	22.50
Medium	31,313.2	19.81
High	30,578.6	19.34
Very High	48,265.3	30.53

).

4.4. Modified SINTACS Vulnerability Map

The semi-arid region of Rajasthan’s vulnerability map was created using the results map and weights for each element in modified SINTACS. It is divided into five vulnerability zones: very low; low; medium; high; and very high. These regions demonstrate how sensitive the water table is to contamination. Greater susceptibility to water table pollution is seen in higher vulnerability locations (Figure 16).

The grades and weights given to the following parameters directly impact the map’s outcomes. Depth-to-water table, recharge (net), aquifer conductivity (hydraulic), soil conductivity, topography (surface slope), the impact of the vadose (unsaturated) zone media, as well as land use and local temperature, for instance. A limited range of values would result in fewer values. In contrast, a larger capacity would allow the division of the same content into more classes. The shallow vulnerability zones on this map indicate vulnerable areas less sensitive to pollution. In contrast, the very high and high vulnerability zones indicate weak areas more sensitive to pollution. Incorporating LULC and temperature data into the analysis using the modified SINTACS method reveals unique vulnerability zones. The “very low” vulnerability zone covers 9.32% of the study area, while 15.84% falls into the “low” category. Additionally, 32.29% is categorized as “medium,” and 34.07% is designated as “high.” A notable 8.47% exhibits a “very high” vulnerability. This method emphasizes both the “high” and “medium” vulnerability zones, indicating regions where groundwater quality and sustainability may be at risk (

Table 6. The area under different vulnerability zones based on the Mod-SINTACS vulnerability map.

Mod- SINTACS Vulnerability Zone	Area (sq. km)	Percentage (%)
Very Low	14,738.3	9.32
Low	25,042.2	15.84
Medium	51,049.7	32.29
High	53,869.8	34.07
Very High	13,392.1	8.47

).

4.5. Validation

The outcomes of our analysis were juxtaposed with empirical data sourced from wells, aiming to validate the groundwater vulnerability assessments conducted via the DRASTIC, SINTACS, modified DRASTIC, and modified SINTACS methodologies. This investigation primarily focused on detecting contaminants in groundwater, such as fluoride, nitrate, chloride, and total dissolved solids (TDS). The well data were meticulously scrutinized and compared with the vulnerability assessment results to initiate the validation process. The point data from these wells offered precise insights into the presence and concentrations of the pollutants above in the groundwater (Figure 2d).

The data were plotted according to the provided coordinates and subsequently analyzed to ascertain if the points aligned with the designated zones based on contaminant levels (Figure 17, Figure 18, Figure 19 and Figure 20). Later, a map was constructed utilizing the outcomes of the vulnerability assessment, with each vulnerability zone delineated by a distinct color. The zones colored sky blue, yellow, and orange denoted areas with lower susceptibility, while the red zone indicated regions with a heightened probability of contamination. The analytical precision can be gauged by juxtaposing the depicted susceptibility zones on the map with the empirical well data.

The vulnerability assessment, employing DRASTIC, SINTACS, modified DRASTIC, and modified SINTACS methodologies, consistently pinpointed zones from high to low pollutant concentrations, corroborated by an in-depth examination of the validation outcomes. A robust congruence was observed between the assessment findings and the actual observations, incredibly when validating using the mentioned methodologies in conjunction with well-point data and specific contaminants (chloride, TDS, NO₃, and fluoride) [42,43,44,45,46,47]. The precise boundary of regions with varying pollutant concentrations through the spatial vulnerability zones offers valuable insights. This, in turn, aids in informed decision-making and paves the way for the formulation and execution of strategic measures to safeguard groundwater assets.

5. Conclusions

The comprehensive study on groundwater pollution susceptibility in Rajasthan’s semi-arid region provides invaluable insights into the pressing issue of water contamination in the face of increasing water scarcity and overexploitation. By employing a range of sophisticated techniques and models, the research effectively maps vulnerability zones, shedding light on areas at high risk of groundwater pollution. The validation of these assessments through real contaminant data underscores their accuracy and reliability. Importantly, this study emphasizes the adaptability of groundwater vulnerability models, making them crucial tools for sustainable resource management in water-scarce regions like Rajasthan. It also underscores the ongoing need for monitoring and evaluation to secure water supplies and inform effective conservation policies. In the semi-arid region of Rajasthan, the methods of DRASTIC, SINTACS, and their modified models by using LULC and temperature are used to assess the groundwater’s susceptibility to contamination [16,41,43]. According to the features of the location, the results appear to be practical and satisfactory. The parameters that we used to conduct the investigation helped with the examination of vulnerabilities. Groundwater vulnerability assessment using the DRASTIC, SINTACS, modified DRASTIC, and modified SINTACS techniques in Rajasthan’s semi-arid region has shed light on the state and sustainability of the area’s water resources. The evaluation and classification of groundwater vulnerability into five separate zones—very low, low, medium, high, and very high—has been accomplished using these approaches. The strength of these methods rests in their capacity to consider a wide range of geological and environmental variables, providing a full picture of the subsurface conditions. This study has successfully identified contamination-prone zones through the integration of various models, demanding targeted conservation and management actions. In this analysis of groundwater vulnerability in the middle to the eastern part of Rajasthan, we applied various assessment methods to gauge the susceptibility of aquifers to contamination. The DRASTIC method, predominantly reliant on hydrogeological factors, yielded the following vulnerability distribution after adjustments to match the study area size: The “very low” vulnerability zone covers 9.02% of the study area. A substantial portion of 37.89% falls into the “low” category. Additionally, 28.77% is categorized as “medium,” with 15.30% in the “high” vulnerability zone. Notably, 9.02% of the region exhibits a “very high” vulnerability to groundwater contamination. These findings reveal a relatively balanced distribution of vulnerability zones, with a significant portion of the area categorized as “low.” On the contrary, the original SINTACS method, which considers both hydrogeological and hydro-chemical factors, produced a somewhat different vulnerability distribution after adjustments. A more modest 4.51% was labelled as “very low,” while 28.34% was characterized as “low.” Of significance, 41.93% fell within the “medium” vulnerability category, with 17.28% identified as “high” and 7.71% as “very high.” SINTACS specifically emphasized the “medium” vulnerability zone, signifying potential areas of concern for groundwater quality. Incorporating data on land use/land cover (LULC) and temperature, the modified DRASTIC method presented a unique vulnerability distribution: “very low” occupied 7.63%; “low” encompassed 22.47%; “medium” constituted 19.71%; “high” was at 19.22%; and “very high” covered a substantial 30.48%. This method highlighted a higher proportion in the “very high” vulnerability category, suggesting areas warranting immediate attention for groundwater protection. Similarly, the modified SINTACS method, incorporating LULC and temperature data, emphasized different zones: “very low” accounted for 9.27%; “low” made up 15.82%; “medium” encompassed 32.53%; “high” represented 34.76%; and “very high” stood at 8.61%. This method underscored both the “high” and “medium” vulnerability zones, indicating regions where groundwater quality and sustainability could potentially be at risk. The modified DRASTIC and SINTACS techniques also showed improved sensitivity in spotting possible weak spots. These models’ accuracy for Rajasthan’s semi-arid environment and distinctive hydrogeological structures was improved by the changes, which considered region-specific factors. As the data of the contaminants at the locations likewise reveal relatively high and low levels as per the zones of vulnerability determined from the study, the validation demonstrates that the vulnerability analysis results are generally accurate. Additionally, it is concluded that the modified SINTACS model is more accurate than the other models because of the fact that the modified SINTACS vulnerability map’s ground data on the contaminants in the well was largely accurate. This work emphasizes the significance of employing reliable, flexible, and thorough models to guide sustainable groundwater management techniques. It also emphasizes the importance of ongoing groundwater resource evaluation and monitoring, particularly in semi-arid areas like Rajasthan, where water scarcity creates serious difficulties. The original DRASTIC method presented a balanced distribution, while the original SINTACS method leaned toward the “medium” vulnerability zone. The inclusion of LULC and temperature data in the modified methods unveiled distinct patterns, with the modified DRASTIC method emphasizing the “very high” vulnerability zone and the modified SINTACS method focusing on the “high” and “medium” zones. These findings offer valuable insights for groundwater management and resource planning. Priority should be given to “very high” and “high” vulnerability areas for immediate groundwater protection and monitoring. At the same time, ongoing vigilance is essential in the “medium” zones to prevent any deterioration in water quality. Further research and data collection will contribute to refining these assessments, facilitating sustainable groundwater resource management in the region. This investigation underscores the imperative of adopting sustainable groundwater management paradigms, especially in regions like Rajasthan, where water scarcity poses formidable challenges. As evinced through this research, the adaptability and applicability of groundwater vulnerability models signify their pivotal role in underpinning informed conservation stratagems. While the current findings demarcate heightened contamination susceptibility zones, they underscore the necessity for sustained monitoring and iterative data acquisition. Areas delineated as bearing “very high” and “high” vulnerability ought to be accorded precedence for immediate interventional measures and rigorous monitoring, with “medium” zones also warranting meticulous oversight. Through its systematic approach and findings, this study provides a foundation for future endeavors to augment groundwater conservation strategies. It is quintessential that, moving forward, efforts are persistently directed toward evaluation, innovation, and adaptive systems to ensure the prudent stewardship of our precious groundwater reserves.