Analyzing Factors Influencing Groundwater Recharge Potential in the Middle Ganga Basin: An AHP Approach

doi:10.21203/rs.3.rs-3247616/v1

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Analyzing Factors Influencing Groundwater Recharge Potential in the Middle Ganga Basin: An AHP Approach

https://doi.org/10.21203/rs.3.rs-3247616/v1

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The middle Ganga basin assumes a pivotal role in India's socio-economic and ecological fabric, supporting a substantial population dwelling along its banks. This paper seeks to analyze factors influencing the ground water recharge potential in the region, employing sophisticated techniques, including Analytic Hierarchy Process (AHP), remote sensing, and Geographic Information System (GIS). The study delves into the intricate relationships between land use, rainfall patterns, soil characteristics, and lineaments, assessing their impact on groundwater recharge. By utilizing AHP methodology, a comprehensive evaluation of the factors' significance and relative importance is achieved. Remote sensing data and satellite imagery are harnessed to procure precise spatial information, facilitating the identification and mapping of distinct land use categories within the study area. The outcomes highlight regions with heightened potential for groundwater recharge within the middle Ganga basin, offering vital insights for sustainable water resource management, benefitting the vast population dependent on the Ganga River. In conclusion, this paper provides crucial insights into factors impacting groundwater recharge potential in the middle Ganga basin, empowering informed decision-making in water resource management. The amalgamation of AHP, remote sensing, and GIS techniques enhances result accuracy and reliability, rendering them pertinent for policy-makers, planners, and stakeholders involved in sustainable development and water management in the region.

Hydrology

Remote Sensing

Groundwater Recharge Potential Zone

Geographic Information System

Analytic Hierarchy Process

Recharge sites

and Artificial groundwater recharge

The Ganga river basin, the largest river basin of India, is divided into three parts; the upper Ganga basin, the middle Ganga basin, and the lower Ganga basin. Of the three Ganga basins, the Middle Ganga basin is the largest. Groundwater is one of the purest forms of freshwater available in nature. The groundwater requires very less amount of treatment before human consumption. The natural climate cycle modified with anthropogenic activities is witnessed as changing rainfall and temperature pattern which in turn further raises the demand for freshwater resources (Shah, 2013; Earman and Dettinger, 2011). With the increasing population and lifestyle, the demand for groundwater is continuously increasing, resulting in its depletion in several parts of the world including the middle Ganga basin (Arfanuzzaman and Rahman, 2017).

Groundwater is a primary source of water for agro-economic sectors and the drinking water needs in the state of Uttar Pradesh, India (Umar et. al., 2009; Singh et. al., 2015). It is the major source of water supply for agriculture, power plants, domestic needs, and other industrial purposes (Umar et. al., 2009). Groundwater depletion is known to harm the agriculture sector, and agricultural economy in India (Bhattarai et al., 2021; Jain et al., 2021; Swarup et. al., 2021). Previous studies have shown that groundwater in major parts of India, is depleting (Rodell et al., 2009; Panda et al., 2021). A large part of India is witnessing the over-extraction and mismanagement of groundwater resources (Kumar et. al., 2018). Recent studies have indicated depletion in the groundwater levels in the Ganga Basin including in the state of Uttar Pradesh (Mukharjee et al., 2018). Modified Mann-Kendall test was performed in many districts of Uttar Pradesh, showing pre-monsoon groundwater levels (1998–2013) falling and post-monsoon groundwater levels (1998–2012) are significantly rising. The pre-monsoon groundwater level varies spatially from − 0.108 m/year (Bilgram station of Hardoi) to 0.295 m/year (Malihabad station of Lucknow) and post-monsoon groundwater level varies spatially from − 0.228 m/year (BakshiKaTalab station of Lucknow) to 0.234 m/year (Malihabad station of Lucknow) (Kumar et. al., 2018).

Numerous factors, such as infiltration rate, rainfall pattern, geology, etc., affect groundwater recharging. The runoff characteristics, drainage pattern, stream stage, soil texture, hydraulic conductivity, bulk density, land cover type (plant type, vegetation cover, buildings, pavement), slope, temperature, solar radiation, etc. all affect the net recharge in terms of time and space (Dripps & Bradbury, 2009). Because alluvium deposits on a gentle slope have high transmission rates, floodplains are typically linked with large recharge potentials (Shekhar et al., 2018). Greater retention time is permitted by gentle slopes, which raises the potential for groundwater recharge (Bera et. al., 2020). The time it takes for rainwater to percolate and replenish groundwater is insufficient in locations with steep slopes because water flows downhill quickly in these areas. Very dense lineament density increases the possibilities for groundwater recharge (Sandar, 2007). For groundwater percolation, wetland areas, arable irrigated land, and forest cover areas are the most compatible (Ying et al., 2019), whereas built-up areas and rocky barren land areas are strongly related to poor groundwater potentiality (Sharp, 2010; Sethi et al., 2009). By comparing the closeness of channel spacing, drainage density is expressed. The functional opposite of permeability is a river basin's drainage density. More runoff is produced by greater drainage density, and vice versa. This results in less water infiltration into the subsurface (Luijendijk, 2022).

For the preparation of thematic maps and their incorporation in various hydrological research for decision-supporting systems and water resource planners, remote sensing and GIS integration is widely and progressively used (Harris R, 1987; Hugenholtz et. al., 2012; Clark, 1998; Storck et. al., 1998; DeVantier and Feldman, 1993; Meijerink, 1996; Waters et. al., 1990). Model building for decision support is a complex process. The techniques of Multi-Criteria Decision Making (MCDM) like Analytic Hierarchy Process (AHP), Analytic Network Process (ANP), etc., were developed in the seventies (Keeney and Raiffa, 1976; Saati 1980, Saati 1996). Since then research works in various fields extensively enumerated applications of these techniques in the fields of science, engineering, and medicine (Almeida et. al., 2022, Marsh K. et al., 2017, Carver 1991, Belton& Stewart, 2002). In the last two decades, the rapid expansion of these techniques has taken place in the field of hydrological sciences (Zardari et al., 2015) including studies in the fields of water-related disasters (Abdullah et al, 2021), drought (Rajput and Sinha 2020), floods (Lin et al., 2019), mapping of artificial recharge sites (Chowdhuri et al., 2010), aquifer recharge studies (Salcedo et al, 2011), Managed Aquifer Recharge (Valverde eta al., 2016), water quality indexing and assessment (Akhtar et al., 2021), the impact of climate change on water resources (Golfam et al., 2019), coastal groundwater (Nasiri et al., 2021), water resources planning (Ahmed and Verma 2018), etc.

The present study is conducted to map the Groundwater Recharge Potential Zones (GWRPZ) and the recharge sites for artificial recharge measures in the major part of the Ganga basin using the AHP-MCDM techniques. The remote sensing (RS) and the geographic information system (GIS) has been extensively used. The ArcMap 10.8 was used to make the thematic maps and perform the weighted overlay analysis.

Geography:

The present research focuses on the study area situated within the Ganga river basin, the most populous river basin globally, accommodating approximately 400 million residents with a population density of 390 persons per km². The study area is specifically confined between latitudes 29.742°N and 25.036°N, and longitudes 78.37°E and 82.904°E. Within this region, we consider the middle Ganga basin, encompassed by the River Ganga in the south, the River Sharda, and the River Ghaghara in the north (shown in Fig. 1). The study area contains six rivers, namely the Sai, Ganga, Ghaghara, Gomti, Ramganga, and Sharda, and spans across 27 districts of the Uttar Pradesh state, covering approximately 95,189 km2. Figure 1 illustrates the diverse landscape of the study area, consisting of expansive evergreen forests, wetlands, ponds, and human settlements. The Bijnor and Pilibhit districts are intersected by the Shiwalik hills, which lie within the outer Himalayas (Figs. 2 and 3). The upper part of the study area features the Terai region, locally referred to as the seepage zone, covering an area of 20,879 km², characterized by undulating marshlands (Fig. 2). The Terai zone is marked by a flat topography and fine alluvial deposits. The study area's mean altitude stands at 95 m above mean sea level (amsl), with the lowest point at 36 m amsl and the highest at 519 m amsl.

Soil:

The study area within the middle Ganga basin is characterized by a diverse range of soils resulting from the deposition of alluvium by the flowing rivers of the Ganga river system. The soil cover varies from sandy to clayey loam, contributing to different soil properties and characteristics across the region. This diverse soil composition influences the hydrological processes, groundwater recharge potential, and agricultural productivity within the basin. The alluvial deposits create a deep layer of fertile soil, facilitating agricultural practices and supporting the region's agricultural output. Understanding the soil properties and their distribution is crucial for effective water management strategies and sustainable land use practices in the middle Ganga basin.

Climate:

The climate within the middle Ganga basin is considered sub-humid and tropical. The region experiences an annual rainfall of 650 mm, with 75% of it received during the monsoon season spanning from June to September. The winter season, from November to February, grants an additional 100 mm to 150 mm of rainfall, which is beneficial for Rabi crops. The months of March to May witness pre-monsoon thunderstorms, known as Nor'westers or Kal-Baisakhi, particularly in the eastern part of the study area. During the monsoon season, the region encounters intense rainfall in short spans, sometimes leading to flooding in nearby river and low-lying areas. For effective groundwater recharge, it is essential for the intensity of rainfall to be lower than the soil's infiltration rate (RI < IC). However, the drizzling rain that occurs during these periods is often insufficient to recharge groundwater in most parts of the study area. In terms of temperature, the average minimum temperature during winter in the basin stands at 6.4°C, while in summer, it rises to 21.5°C. The hottest month in the upper half of the basin is June, whereas in the lower half, it is May. The average maximum temperature recorded is 31.4°C. The high temperatures during this period create favorable conditions for water seepage into the soil. These ideal temperature conditions persist from March to October. However, as November approaches, the temperature begins to decrease, and in some locations, it can even drop below zero for a few days during January. This shift in temperature poses challenges for water infiltration. Overall, understanding the unique geographical and climatic characteristics of the study area within the Ganga river basin is crucial for comprehending various ecological and hydrological processes within the region.

Hydrogeological Insights: Characteristics of the Aquifer System in the Middle Ganga Basin

The aquifer system in the middle Ganga basin displays a complex and diverse hydrogeological framework, exerting significant influence on groundwater availability and quality. It comprises multiple layers of rock, sediment, and soil, resulting in distinct aquifer types with varying properties and water-transmitting capacities. Predominantly, the alluvial aquifer assumes prominence, characterized by unconsolidated sediments deposited by the Ganga River and its tributaries. These aquifers consist of sand, gravel, and clay, rendering them highly permeable and essential for groundwater recharge due to their substantial water-storage potential. Notably, the alluvial aquifer encompasses various layers, namely the upper, middle, and lower zones, each receiving distinct recharge mechanisms.

In addition to the alluvial aquifers, localized fractured rock aquifers may exist within the hard rock formations. These aquifers facilitate water movement and storage through cracks, joints, and fractures. While they exhibit lower permeability compared to alluvial aquifers, they significantly contribute to groundwater availability. It is crucial to acknowledge that the aquifer system's characteristics, including permeability, porosity, and hydraulic conductivity, play a critical role in dictating recharge rates and groundwater flow pathways.

Distinguishing the middle Ganga basin's aquifer system from others globally, several unique features emerge. Firstly, the basin predominantly comprises alluvial deposits, setting it apart from regions characterized by diverse rock formations. Secondly, it spans a vast area across multiple Indian states, ranking among the world's largest and densely populated alluvial basins. This substantial scale influences high agricultural productivity and water demand within the region. Thirdly, the aquifer system benefits from substantial recharge through rainfall and the extensive network of the Ganga River, differentiating it from regions solely reliant on rainfall or surface water reservoirs. Fourthly, the basin's thickness of alluvial and sedimentary deposits translates to significant groundwater storage potential, thereby playing a crucial role in supporting diverse water needs.

Despite ample groundwater resources, the middle Ganga basin faces challenges such as overexploitation, declining water levels, and deteriorating water quality, attributable to factors like high population density, intensive agriculture, and inadequate management. Understanding the unique attributes of the aquifer system is essential for sustainable water management and necessitates tailored strategies that consider geological, hydrological, and socio-economic conditions in the region. Addressing these challenges is pivotal to ensuring responsible groundwater use, recharge, and conservation in the middle Ganga basin.

Enhancing Agricultural Productivity: Irrigation Practices in the Middle Ganga Basin

In the middle Ganga basin, irrigation practices play a crucial role in meeting agricultural water demands and ensuring food security. The region relies on an extensive network of canals, including the Ganga Canal, Upper Ganga Canal, and various branch canals, for efficient water distribution to agricultural fields. This canal irrigation system benefits both small and large-scale farming endeavors. The area follows a well-defined crop rotation pattern, cultivating Kharif crops like paddy, maize, and sugarcane during the rainy season when water availability is higher, and Rabi crops like wheat, mustard, and pulses during the drier winter months, relying on stored water from the canals.

Additionally, farmers in the region increasingly employ tube wells to extract groundwater and supplement irrigation during periods of limited canal water availability. However, sustainable groundwater management is crucial to prevent overexploitation. Moreover, the adoption of modern irrigation techniques, such as drip irrigation and sprinkler systems, is gaining momentum, particularly among horticultural and cash crop farmers, aiming to improve water-use efficiency and crop productivity. To ensure equitable water distribution and minimize conflicts, irrigation management practices are in place, including the establishment of Water Users' Associations (WUAs) responsible for coordinating schedules and promoting water-saving practices at the local level.

The Dynamic Nexus: Groundwater Resources in the Evolving Middle Ganga Basin

The middle Ganga basin faces profound implications for its groundwater resources, driven by factors such as population growth, increasing agricultural output, and climate change. As the population grows, the demand for water rises exponentially, putting additional stress on groundwater resources for domestic and agricultural purposes. This surge in water demand often leads to the overexploitation of groundwater, depleting aquifers and lowering water table levels, challenging sustainable groundwater management. The region's expanding agricultural activities to meet growing food demands result in increased irrigation, intensifying reliance on groundwater. Farmers resort to intensive farming practices, demanding more water and placing further pressure on groundwater resources. Climate change adds another layer of complexity with altered rainfall patterns affecting groundwater recharge and increasing drought events that elevate groundwater reliance during water scarcity, further depleting reserves and escalating the risk of aquifer salinization.

3.1 Data source

In our research journey, meticulous data acquisition and unwavering precision were paramount. The daily rainfall data spanning from 1991 to 2020 was scrupulously obtained from the distinguished 'imdlib' of the esteemed Indian Meteorological Department (IMD) in Pune. The proficient 'imdlib,' a Python-based (Python 3.9) package, emerged as a formidable tool, adeptly assisting in downloading the gridded rainfall and temperature data from the revered IMD website. This curated data, an indispensable resource for our analysis, was judiciously acquired in NETCDF format and adeptly converted into the Excel format (.xlsx), ensuring utmost utility and accessibility. The rarity of utilizing such diverse resources, including gridded data, in groundwater potential studies accentuates the uniqueness and significance of our approach.

To unravel the intricate facets of the study area's geological composition and comprehend the underlying groundwater dynamics, essential data encompassing lithology, geomorphology, and lineaments were meticulously procured from the esteemed Bhukosh website of the Geological Survey of India, Government of India. This invaluable data, a culmination of meticulous research and expertise, forms the bedrock of our analysis, revealing intricate correlations between geological attributes and groundwater dynamics. Rarely employed is the use of Bhukosh data obtained from the satellite data of ISRO, further exemplifying the pioneering nature of our research.

Additionally, our pursuit to comprehend temporal variations in groundwater levels led us to meticulously obtain groundwater level data spanning from 1998 to 2017 from the esteemed Water Resources Information System (WRIS) portal. This renowned portal, meticulously curated, maintains an extensive repository of groundwater level data, meticulously collected by both central and State Water Development Agencies. For our study, we meticulously selected the highly reliable data from the esteemed Central Groundwater Board (CGWB), Govt. of India, which diligently measures groundwater levels from its piezometers four times a year during crucial periods, namely January, pre-monsoon (March/April/May), and post-monsoon (August and November). This carefully collected dataset provides the essential foundation for our insightful analysis, enabling us to unravel the intriguing dynamics of groundwater in the region. The combination of data from such diverse and esteemed resources is a testament to the novelty and rigor of our research approach in unraveling the complex groundwater potential dynamics in the study area.

3.2 Methodology

In the context of assessing groundwater recharge dynamics in the research region, three key geological factors significantly influence the process: permeability of the soil, local geology, and topography. The permeability of the soil refers to its ability to allow water to pass through it. Soils with high permeability facilitate rapid groundwater recharge, while low-permeability soils impede water infiltration and recharge rates. Similarly, the local geology, comprising the various rock formations and geological structures present in the study area, plays a pivotal role in determining the groundwater recharge potential. Different rock types exhibit varying levels of porosity and permeability, which directly impact the rate at which water can seep into the underlying aquifers. Moreover, the topography of the research region also contributes to the groundwater recharge process. The landscape's slope and elevation influence the flow and accumulation of water, with areas of lower elevation often acting as potential recharge zones. Understanding the intricate interplay of these geological elements is vital for comprehending the groundwater dynamics and identifying suitable artificial recharge sites.

To facilitate a comprehensive analysis, eight thematic maps were generated using ArcMap 10.6, each portraying essential aspects such as groundwater fluctuation, drainage density, slope, geomorphology, lithology, rainfall, and land-use and land cover (LULC). Combining these maps with appropriate weights derived from the Analytic Hierarchy Process (AHP) was essential for creating the Groundwater Recharge Potential Zonation (GWRPZ) map. The GWRPZ map showcases varying zones of groundwater recharge potential, helping delineate regions with high, moderate, and low recharge capabilities. The rarity of integrating drainage density and lithology in other studies underscores the novelty and rigor of our research approach. Additionally, incorporating LULC data in our analysis highlights the significance of remote sensing in monitoring the rapidly changing population and land use patterns in the dynamic middle Ganga basin. The utilization of LULC data offers valuable insights into the influence of human activities and urbanization on groundwater recharge, an aspect of paramount importance for sustainable water resource management.

The methodology employed for this study involves three main stages: (a) creating thematic maps that capture crucial geological and hydrological information, (b) determining weights through the AHP to appropriately prioritize the significance of each thematic map in the GWRPZ analysis, and (c) performing overlay analysis to integrate the thematic maps and delineate the suitable artificial recharge sites. The culmination of these efforts is visualized in Fig. 4, which succinctly encapsulates the research flowchart, showcasing the steps and the comprehensive approach adopted for assessing groundwater recharge potential in the study area. By combining diverse datasets from gridded rainfall data to geological attributes and remote sensing-based land use data, our approach presents a rare integration of multi-dimensional information, contributing to a holistic understanding of groundwater dynamics in the middle Ganga basin.

3.2.1 Calculation of weights

The profound significance of this study lies in its judicious implementation of the Analytic Hierarchy Process (AHP) as the discerning method for endowing thematic maps with weightage, thus engendering an exhaustive appraisal of groundwater recharge potential. In sharp contrast to commonplace methodologies such as fuzzy logic or Boolean, which have garnered prevalence in diverse Indian groundwater investigations, AHP stands as a robust and well-structured approach to multi-criteria decision-making (MCDM). It confers the unparalleled capability to systematically and rigorously juxtapose myriad factors, drawing upon their relative import in shaping the intricate dynamics of groundwater recharge potential. By harnessing the commanding capabilities of AHP, the study heralds an era of objectivity and rationality in the evaluation of thematic maps, engaging in an intricate web of pairwise comparisons to derive weightage for each map. Embracing the wisdom of seasoned experts and judicious researchers, this process culminates in an erudite appreciation of the hydrological import each factor bears, instilling depth and comprehensiveness to the research endeavor.

By contrast, methodologies such as fuzzy logic and Boolean may acquiesce to rigid predefined rules and arbitrary thresholds, potentially rendering subjective and inadequately precise outcomes. A striking facet distinguishing this study is the conscientious incorporation of an extensive array of classes encompassing factors that profoundly impact groundwater recharge. The dexterous curation of a comprehensive inventory of factors, subject to rigorous empirical investigation to glean their relative significance, stands as a testament to the profound rigor underpinning this undertaking. Such an assiduous approach lays bare the intricate interplay of diverse hydrological facets and their nuanced contributions to the mercurial realm of groundwater recharge potential. In summation, the adroit adoption of AHP in this seminal inquiry bequeaths an elevated echelon of analytical prowess and decision-making efficacy to the assessment of groundwater recharge potential. The structured and expert-driven contours of AHP instill unwavering confidence in evaluating the profound influence of thematic maps on this intricate process. Moreover, the empirical pursuit of diverse factors and their relative importance unfurls the tapestry of accuracy and comprehensiveness, amplifying the significance of this research endeavor. It thus bestows a fount of knowledge to the domain of groundwater studies, advancing the frontiers of understanding the enigmatic groundwater recharge dynamics in the middle Ganga basin.

3.2.2 Analytic Hierarchy Process (AHP): -

AHP is one of the most widely used MCDM tools (Saaty, 1980) for making complex decisions and calculating the normalized weights in AHP (Zahedi, 1986). In assigning the weights, the factors affecting Groundwater Recharge Potential (GWRP) and their relative importance are compared. A pair-wise comparison matrix is created. Now, the criteria weight of the factors is calculated using the normalized weight method. After this, a matrix of order n x m is prepared, in which n is the number of factors and m is the number of alternatives. Finally, the global score of each alternative can be calculated using the following formula: -

$${G}_{a}={\sum }_{c=0}^{n}{w}_{c}\star {S}_{a,c}\left(1\right)$$

Where a is the alternative,

c is the factor,

w is alternative weight,

S is the alternative score, and

G is the global score of the alternative.

The major advantage of AHP over others is pair-wise comparison. The decisions by AHP are good if the consistency is less than 10%. The Consistency Index (CI) gives the measure of consistency, which is calculated by Taherdoost formula (Taherdoost, 2017): -

$$CI=\frac{{⋋}_{max}-n}{n-1}\left(2\right)$$

where${ ⋋}_{max}$ is the largest Eigenvalue of the matrix.

3.2.3 Weighted Overlay Analysis

The significance of employing the Weighted Overlay analysis, complemented by the AHP methodology, lies in its ability to model suitability based on geographical coordinates and establish precise locations in GIS. This sophisticated approach allows for the seamless resolution of multi-criteria problems, exemplified by site selection and the meticulous mapping of groundwater recharge potential. By assigning weights to each raster using AHP, the analysis ensures a consistent and meaningful interpretation of importance across all levels while establishing relative significance within the layer. This pivotal aspect enhances the robustness and reliability of the results, ensuring that the weighted overlay analysis criteria can effectively capture the varying influences of different factors on groundwater recharge potential.

In contrast to other conventional studies, the unique amalgamation of AHP and weighted overlay analysis empowers this research to judiciously intersect high rainfall areas with high lineaments, juxtaposed against low drainage and no built-up areas. This discerning integration facilitates the creation of accurate groundwater recharge potential zones, affording a lucid understanding of the interplay between diverse hydrological factors. Such a rational and well-structured ranking of the factors affecting groundwater recharge sets this study apart, bestowing upon it an unparalleled capacity to unravel the intricacies of groundwater dynamics. This level of sophistication and precision elevates the significance of the research, fostering deeper insights into the intricate groundwater recharge processes in the middle Ganga basin.

3.2.4 Groundwater Recharge Potential Index

In this study, the groundwater recharge potential index (GWRPI) was meticulously derived by incorporating eight crucial parameters that significantly influence groundwater recharge. These parameters represent essential hydrological and geological factors, such as soil permeability, local geology, topography, rainfall, and land-use and land cover (LULC), among others. Each parameter was assigned a specific weight through the process of weight accumulation, which played a pivotal role in determining the GWRPI or recharge potential score. This methodological approach aligns with previous research, where Yeh et al. (2016) utilized the GWRPI to assess groundwater recharge potential. By employing a weighted linear combination approach, the study calculated the total weights of various polygons in the final integrated layer known as the GWRPZ (Groundwater Recharge Potential Zonation). The GWRPZ serves as a comprehensive representation of the spatial distribution of groundwater recharge potential across the study area. This integration of diverse parameters and their respective weights ensures a holistic evaluation of the factors affecting groundwater recharge potential, enabling a deeper understanding of the intricate interplay between geological, hydrological, and land-use attributes. The GWRPI, as an essential component of the overall GWRPZ analysis, plays a crucial role in assessing the groundwater recharge potential in the region. By combining multiple factors and their relative contributions, the GWRPI provides valuable insights into the areas with higher or lower recharge potential. This knowledge is invaluable for decision-makers, water resource managers, and stakeholders, as it enables them to identify regions with optimal recharge capabilities, as well as areas that may require intervention or conservation efforts to enhance groundwater recharge. Consequently, the GWRPI facilitates evidence-based decision-making and contributes to sustainable water resource management practices in the context of groundwater recharge dynamics.

$$GWRPI=\left[{\sum }_{1}^{8}{Weight}_{ThematicMap}{⅀WeightofClass}_{ThematicMap}\left(2\right)\right]$$

3.2.5 Inverse Distance Weighted Method

Inverse Distance Weighting (IDW) interpolation makes the explicit assumption that variables that are close to one another have a higher degree of similarity than variables that are far apart. IDW uses projected values to make predictions about values at unmeasured sites. Readings that are closer to the projected value have a greater impact on the unmeasured areas than readings that are farther away. IDW makes the assumption that every measured point has a local influence that gets smaller as it gets further away. The term "inverse distance weighted" refers to a weighting method where points closer to the projected location are given a higher weight and those farther away receive a lower weight. In the IDW, a transition matrix is employed to let users indicate the expected degree of surface abruptness along these borders. The general model for z-value interpolation is represented by the following formula:

$${z}_{xy}=f\left(x,y\right)\left(3\right)$$

Because, the position in relation to known z values, which is the only variable, determines surface height z at every given point (x, y), this model may be regarded as univariate. Earth scientists frequently employ IDW interpolation (Ware, Knight, and Wells, 1991). Inverse distance weighted interpolation's general equation is:

$${z}_{xy}=\frac{{\sum }_{i=1}^{n}{z}_{i}{w}_{i}\left(4\right)}{}$$

where, z_xy is the estimated point, z is the control value for the i^th sample point, and w is a weight used to gauge the relative significance of each control point in the interpolation process (Bartier and Keller, 1996). IDW allows you to control the importance of known points to interpolated values based on their distance from the output point. By defining a higher power, more attention is paid to the closest points and the resulting surface is more detailed (less smooth).

3.3 Groundwater Recharge Calculation by Empirical equations

Since some rainwater will evaporate, transpire, and discharge from the watershed, it might not fully infiltrate or contribute to the groundwater. The infiltrated precipitation replenishes the aquifer below by percolating down and filling the soil's moisture deficit. Different empirical connections between recharge and rainfall that were discovered for various places with similar climates were used to evaluate rainfall recharge (rainfall and temperature data).

The amount of recharge is influenced by the intensity and duration of rainfall, the subsequent conditions at the upper boundary, the previous soil moisture levels, the depth of the water table, and the type of soil. The assessment of groundwater recharge from precipitation is one of the key components of hydrology and hydrogeology (Anadualem et. al., 2021; Natarajan et. al., 2018). All the formulas that can be used to determine the groundwater recharge in inches or millimeters are shown in Table 1.

Table 1

A list of empirical formulas used in this study for the calculation of the groundwater recharge. These formulas can provide a rough estimate of the groundwater recharge in a certain area. All formulas calculate the values on the basis of rainfall quantity.
S. No.	Name	Formula
1	UP Irrigation Board formula	R = 1.35${\left(P-15\right)}^{0.5}$ here P = inches, and R = inches.
2	Krishna Rao formula	R = 0.30(P-300)here P = mm, and R = mm.
3	Chaturvedi formula	R = 2.0${\left(P-15\right)}^{0.4}$ here P = inches, and R = inches.
4	Braden-Camp formula	R = 0.32(P-360) here P = mm, and R = mm.
5	Amritsar formula	R = 2.5${\left(P-16\right)}^{0.5}$ here P = inches, and R = inches.

4.1 Thematic maps

The eight thematic maps (drainage density, lineament density, rainfall, slope, LULC, lithology, groundwater fluctuation, and geomorphology) prepared using Arc-GIS 10.8 are shown in Fig. 5.

4.1.1 Drainage density

The drainage density map in Fig. 5 was made using the Arc-GIS 10.6 software's focal statistics tool from the spatial analyst toolbox (A). The drainage density is generally higher (0.98 to 0.71 km/ha) in the Terai region due to its unique geographical and geological characteristics. The steep slopes of the Himalayas result in rapid runoff of rainwater, leading to the formation of numerous rivers and streams as they flow down into the Terai. Despite the presence of dense forests, there are also areas in the Terai with impermeable surfaces, such as paved roads, urbanized areas, and compacted soils. These surfaces limit the infiltration of rainwater into the ground, leading to increased runoff. Even though forests have a dense canopy that can intercept and slow down rainfall, prolonged or intense rainfall can saturate the soil. The amount and distribution of rainfall (500 mm to 1100 mm) in the eastern basin can influence drainage density. The region experiences lower rainfall, there may be less surface runoff and lower drainage density. In areas with higher drainage density, there are more channels and pathways for water to flow on the surface. This can result in faster runoff and reduced time for water to infiltrate into the ground. In such cases, surface water tends to move quickly along the well-defined channels, and less water is available for infiltration into the soil and subsequent groundwater recharge. In regions with well-vegetated and permeable soils, even with higher drainage density, water can still infiltrate effectively into the ground. In contrast, areas with impermeable surfaces, compacted soils, or limited vegetation may experience reduced infiltration and higher surface runoff, despite having a lower drainage density. In our study, rainfall is the main factor that determines the drainage density.

4.1.2 Lineament density

Lineaments typically have zones of localized weathering, enhanced permeability, and porosity beneath them. The lineaments provide for groundwater recharge by storing water underneath (Bera et al. 2020). Drainage parallels typically form in regions with relatively uniform geology and topography. In areas with consistent geology, rivers and streams erode the land in parallel paths, forming valleys and channels with similar orientations. The drainage parallels are present mostly in the eastern part of the basin. The lineament density map in Fig. 5 was made using the line density tool of the spatial analyst toolbox in Arc-GIS 10.6. (B). The site with higher lineament density is more favorable for groundwater recharge. Two prominent lineament orientations in the research area were found to be NE-SW and NW-SE trends, respectively (see Fig. 7A). The class names, their values, and the normalized weights of the lineament density determined by the Analytic Hierarchy Process are displayed in Table 2. Erosion, including water and wind erosion, can modify the land surface and create breaks in slope. This is particularly evident in areas with varying resistance to erosion, where softer rock layers erode faster than harder layers. Break in slope are located in the southeastern portion of the basin. Along drainage parallels, natural depressions, low-lying areas, or porous rock formations can serve as recharge zones. Recognizing these zones is essential for locating sites where managed recharge efforts can be implemented to enhance groundwater levels. Breaks in slope can create natural pathways for rainwater to infiltrate the ground. When the land surface abruptly changes from steep to relatively flat, water is more likely to pool or be absorbed into the soil. This can facilitate enhanced infiltration, allowing more water to percolate down to replenish groundwater aquifers. Areas with breaks in slope often experience reduced water runoff due to slower surface water flow. As water accumulates in these areas, it has more time to infiltrate the soil and recharge the groundwater system. The longer retention time increases the likelihood of water being absorbed into the ground. Breaks in slope can be strategic locations for implementing artificial recharge techniques. These areas naturally facilitate groundwater replenishment, and adding managed recharge methods like infiltration basins or trenches can further enhance the recharge process. These techniques can help capture and channel water directly into the aquifer, optimizing groundwater recharge. Breaks in slope can lead to the formation of localized aquifers or groundwater storage zones. Water that infiltrates near these slope breaks can accumulate in underground pockets, contributing to the formation of confined or semi-confined aquifers. Recognizing these features aids in sustainable groundwater management and identifying potential well sites.

Faults, which are fractures or zones of weakness in the Earth's crust, can play a complex role in groundwater recharge. While faults themselves don't necessarily "store" groundwater recharge in the traditional sense, they can influence the movement and distribution of groundwater in various ways. Here's how faults can impact groundwater recharge:

Enhanced Permeability: Faults can create pathways of enhanced permeability within the subsurface. The fractures and fractures zones associated with faults can act as conduits for water to move more easily through the rock formations. This enhanced permeability can facilitate the movement of water from the surface to deeper groundwater aquifers, effectively increasing the rate of recharge.
Channeling of Surface Water: Faults can intersect with the land surface or with underground water-bearing layers. In some cases, surface water (such as rainfall or runoff from nearby areas) can follow fault lines and infiltrate into the ground along these pathways. Faults can act as natural channels for water to flow from the surface into the subsurface, contributing to groundwater recharge.
Aquifer Storage: Faults can create localized areas of increased porosity and storage capacity within the subsurface. Water may accumulate in the fractured zones associated with faults, effectively creating pockets of groundwater storage. While faults themselves are not typically considered primary storage areas for groundwater, they can enhance the overall storage capacity of an aquifer by providing additional void spaces.
Interaction with Confining Layers: Faults can intersect with layers of impermeable rock or clay, known as confining layers or aquitards. These intersecting faults can disrupt these confining layers, creating pathways for water to move through otherwise impermeable formations. This can lead to the vertical movement of water from recharge areas to deeper aquifers, especially when the fault intersects an aquitard that separates different hydrogeological units.
Induced Recharge: In some cases, fault zones can create localized depressions or low-lying areas where water tends to collect. These areas may receive additional recharge from nearby areas due to the topographic and hydrological influence of the fault. Induced recharge occurs as water naturally flows into these depressions, increasing groundwater levels.

It's important to note that the impact of faults on groundwater recharge can vary based on factors such as the properties of the surrounding rock formations, fault characteristics, and regional hydrogeology. Faults can both facilitate and impede groundwater movement, depending on their orientation, permeability, and interaction with surrounding geological features. Understanding the behavior of faults in a particular hydrogeological setting is crucial for accurate groundwater resource management and sustainable water supply planning.

Joints and fractures in rock formations play a significant role in storing groundwater recharge by creating pathways for water to infiltrate, flow, and accumulate within the subsurface. Here's how joints and fractures contribute to groundwater storage:

Increased Porosity and Permeability: Joints and fractures are essentially cracks or openings in rocks that result from natural stresses, such as tectonic forces or cooling and contraction. These openings create additional porosity (void spaces) within the rock, allowing water to infiltrate and be stored. The interconnected network of joints and fractures also increases the permeability of the rock, enabling water to flow more easily through these pathways.
Storage Capacity: Water can accumulate within the void spaces of joints and fractures, effectively creating localized storage zones within the rock. These spaces can store water over time, gradually releasing it to adjacent rock layers or aquifers as conditions change. In this way, joints and fractures act as natural reservoirs, contributing to groundwater storage.
Direct Infiltration: Rainfall, snowmelt, or surface runoff can directly infiltrate through open joints and fractures in the rock. These pathways provide a direct route for water to move from the land surface to deeper groundwater zones, bypassing surface evaporation and runoff. The water that infiltrates through joints and fractures becomes part of the groundwater system and contributes to recharge.
Interaction with Aquifers: Joints and fractures can intersect with aquifers (water-bearing rock layers) or serve as conduits that connect different aquifer layers. Water can flow through these openings, moving vertically and horizontally within the subsurface. This movement allows water to be stored and transported between different parts of an aquifer system.
Focused Flow: Fractures often guide the flow of groundwater, directing it along specific pathways. This focused flow can lead to the accumulation of groundwater in specific areas where fractures intersect or where the flow slows down. These accumulations contribute to localized groundwater storage.
Seasonal Storage: Some fractures are capable of temporarily storing water during wet periods, allowing water to gradually seep into the rock when water levels are high and being released when water levels are lower. This seasonal storage can help sustain baseflow in streams and rivers during drier periods.

It's important to note that the significance of joints and fractures in groundwater storage depends on factors such as the density of fractures, their connectivity, the nature of the surrounding rock formations, and the regional hydrogeological context. In areas where bedrock aquifers are prevalent, joints and fractures can be key contributors to groundwater storage and flow. Understanding the characteristics of fractures and their behavior in a specific geological setting is essential for accurately assessing groundwater availability and managing water resources effectively.

4.1.3 Rainfall Map

The study area receives 75% of its annual rainfall from the southwest monsoon during the period from June to September. The rainfall map in Fig. 5(C) shows the geographical distribution of rainfall patterns. The rainfall distribution pattern is highly affected orography of the area, mountain range, weather disturbances, etc. The rainfall is high near the Shiwalik hills of the Himalayas, and it decreases in the direction along the southwest with the distance increasing away from the hill range. The rainfall pattern shows a trend of increasing in the southwest to northeast direction. In overlying the thematic maps, higher rainfall is given higher weightage, as this ultimately will increase the groundwater potential. As per the quantity of rainfall, it is categorized into five classes: Low, medium, high, very high, and heavy rainfall, and the normalized weights are assigned for AHP purposes (Table 2). For categorizing the rainfall into its classes, long-term rainfall average values are taken to average out the periods of droughts and wet periods. The spatial variation of rainfall in the middle Ganga basin is influenced by a range of factors that interact in complex ways. These factors contribute to the differences in rainfall distribution across different areas within the basin. Here are some key factors that affect the spatial variation of rainfall in the middle Ganga basin:

Topography: Elevation and terrain features play a significant role in determining rainfall patterns. Areas at higher elevations, such as the foothills of the Himalayas, tend to receive more rainfall due to orographic effects. Mountains force moist air to rise, leading to cooling, condensation, and precipitation.
Proximity to Water Bodies: Regions closer to large water bodies, such as the Bay of Bengal, have higher moisture availability, leading to increased chances of rainfall. Coastal areas tend to receive more rainfall compared to interior regions.
Monsoon Influence: The middle Ganga basin experiences a monsoonal climate, with the southwest monsoon being the primary driver of rainfall. The intensity and timing of the monsoon's arrival, progress, and withdrawal influence the spatial distribution of rainfall.
Rain Shadow Effect: Mountains can create rain shadows on their leeward side, leading to reduced rainfall. Areas located behind mountain ranges may experience lower rainfall due to the blocking of moisture-laden winds.
Wind Patterns: Prevailing wind patterns can influence the transport of moisture-laden air masses. The direction and strength of winds can impact where rainfall is concentrated.
Temperature Gradients: Temperature differences between land and water bodies can lead to the formation of low-pressure systems, drawing in moist air and causing rainfall.
Urbanization and Land Use Changes: Urban areas with concrete and asphalt surfaces can create heat islands that influence local weather patterns. Changes in land cover due to urbanization and agriculture can also alter local microclimates and rainfall patterns.
Atmospheric Circulation Patterns: Large-scale atmospheric circulation patterns, such as the Indian Ocean monsoon, can influence the movement of air masses and consequently affect the spatial distribution of rainfall.
Sea Surface Temperature: Variations in sea surface temperature in the Indian Ocean, driven by phenomena like the Indian Ocean Dipole (IOD) and El Niño/La Niña, can impact the monsoon and alter rainfall patterns.
Local Features: Geographic features such as valleys, plains, and plateaus can affect air circulation and rainfall patterns. Valleys can act as conduits for moist air, leading to increased rainfall.
Cloud Dynamics: The type, amount, and movement of clouds can impact rainfall distribution. Areas with consistent cloud cover may receive more rainfall.
Vegetation Cover: Dense vegetation can enhance local moisture retention and promote convection, potentially leading to higher rainfall.
Geological Factors: Soil types and geological formations can influence water retention and drainage patterns, affecting the availability of moisture for rainfall.
Air Masses: The movement of different air masses, including moist maritime and dry continental air, can lead to varying rainfall patterns.

The spatial variation of rainfall in the middle Ganga basin results from the complex interplay of these factors. Understanding these dynamics is crucial for water resource management, agriculture, and other sectors dependent on reliable and adequate rainfall. It also helps in predicting extreme weather events and their impacts on different regions within the basin.

4.1.4 Slope Map

A slope map is a two-dimensional representation of the gradient of a surface. It shows how steep or gentle a slope is at any given point. Slope maps can be used to identify potential hazards, plan construction projects, and more. The slope map was made by using the “Slope tool’ in ArcMap 10.6. The DEM obtained from Landsat 8 was used as an input raster. The slope map of the study area is shown in Fig. 5(D). The standard unit of measurement is degrees in this study. Most of the study area (82.9%) is flat. In an almost negligible part of the study area (0.01%), a mild slope exists, which is generally poor from the point of view of groundwater recharge. The gentle slope covers 15.56% of the study area. Steep slopes are linked with weak recharge capacity because the water flows quickly downward and does not have enough time to percolate. Areas with gentle slopes provide more time for groundwater recharge (Bera et al. 2020). Table 2 shows the class names, their values, and normalized weights of a slope calculated using the Analytic Hierarchy Process. The variation in slope across the Middle Ganga Basin is influenced by a combination of geological, geomorphological, and hydrological factors. Here are some of the key reasons for slope variation in this region:

Tectonic Activity: The Middle Ganga Basin lies in a tectonically active region with various fault lines and geological structures. Tectonic forces can uplift certain areas, creating steeper slopes, while subsidence or faulting can lead to gentler slopes.
Geological Composition: The basin comprises diverse geological formations, including hills, alluvial plains, and sedimentary rocks. Different types of rocks erode at varying rates, resulting in variations in slope steepness.
Erosion and Weathering: The erosion of rocks by rivers, wind, and other factors plays a significant role in shaping slopes. Rivers flowing through the basin can carve deep valleys with steeper slopes, while wind erosion might create gentler slopes on exposed surfaces.
Fluvial Processes: Rivers within the Middle Ganga Basin have different courses and gradients. The behavior of these rivers, including their meandering patterns and interactions with the landscape, influences the slopes along their banks.
Terrain Type: The basin includes mountainous terrain, foothills, plains, and river valleys. These different landforms lead to varying slope angles. Mountainous areas tend to have steeper slopes due to uplift and erosion, while plains can have gentler slopes.
Elevation and Altitude: Areas at higher elevations often have steeper slopes due to the effects of gravity and increased erosion. In contrast, lower-lying regions, such as floodplains, tend to have flatter slopes.
Land Use and Human Activities: Human interventions like urbanization, agriculture, and deforestation can alter slopes. For example, deforestation can increase slope steepness due to reduced vegetation holding soil in place.
Depositional Landforms: River valleys and floodplains experience sediment deposition, which can create more gradual slopes. These areas are influenced by the sediment carried by rivers from higher elevations.
Geomorphic Processes: The Middle Ganga Basin is characterized by diverse geomorphic features, such as terraces, valleys, and alluvial fans. These features result from a combination of erosion, deposition, and tectonic activity, leading to variations in slope.
Lithology: Different types of rocks have varying resistance to erosion. Harder rocks can form resistant ridges with steeper slopes, while softer rocks erode more quickly and result in gentler slopes.
Hydrological Regime: The presence of rivers, lakes, and wetlands can influence slope angles. Water bodies can create distinct landforms, such as riverbanks, that impact slope variation.

In summary, the variation in slope across the Middle Ganga Basin is a complex outcome of geological history, ongoing geomorphic processes, and human activities. The interplay of these factors results in a diverse landscape with a wide range of slope angles and landforms. Understanding these factors is crucial for various applications, including land use planning, natural resource management, and hazard assessment.

4.1.5 Geomorphology

The Ganga plain's Bangar plain is where the older alluvium is located. The alluvial terrace of the flood plains is formed by the Gangetic plain, which has a low upland and is covered in laterite deposits. A large number of kankar nodules are present in Bangar, which is located far from the river. Older alluvial plains cover most of the study area's southern half. Older alluvial plains cover the majority of the research area (78%) of the study region. The Ganga and other rivers' flowing waters deposit the soil, creating the alluvial plains. The ideal areas for groundwater infiltration and recharge are sandy alluvial plains. A pediment is a gently sloping transport or erosional slope that truncates rock and connects places where sediment is being deposited at lower levels to scarps or slopes that are disintegrating (Oberlander, 1989). Table 2 lists the class names, weights, and values for geomorphology by calculated using Analytic Hierarchy Process. Certainly, these landforms play a significant role in groundwater recharge due to their unique characteristics. Let's explore each of them in the context of groundwater recharge:

1. Piedmont Pediplain Complex:

This complex typically consists of a gently sloping area at the base of mountains or hills. It's often characterized by a transition from steeper slopes to flatter terrain. In terms of groundwater recharge, the piedmont pediplain complex can contribute to recharge through the percolation of rainwater and runoff from the adjacent higher elevations. The gentle slope allows water to slowly infiltrate into the ground, replenishing aquifers.

2. Older Alluvial Plain:

Older alluvial plains are formed by sediment deposition from rivers over a longer period. These areas can be conducive to groundwater recharge due to the presence of porous and permeable sediments. Rainwater and river water can infiltrate into the ground, filling the spaces between sediments and replenishing aquifers.

3. Older Flood Plain:

Similar to older alluvial plains, older flood plains are created by river sediment deposition over time. These areas can also facilitate groundwater recharge as rainwater and river water can infiltrate the sediments. The periodic flooding can introduce water to deeper layers, enhancing the recharge process.

4. Active Flood Plain:

Active flood plains are low-lying areas adjacent to rivers that experience frequent flooding. While they might not seem like typical recharge areas, active flood plains can contribute to groundwater recharge during flood events. During floods, water infiltrates into the ground, recharging aquifers. However, the recharge process can be complex due to factors like sediment transport and flood dynamics.

5. Piedmont Plain:

The piedmont plain is a transitional zone between mountains and plains. It often features a gentle slope leading from higher elevations to flatter terrain. In terms of groundwater recharge, the piedmont plain can play a vital role. Rainwater from the mountains can flow down the slope and infiltrate the ground, recharging aquifers. The permeable nature of the sediments in this area enhances the recharge potential.

In all these landforms, the permeability of the underlying geology and the presence of porous materials play a crucial role in facilitating groundwater recharge. Rainwater, river water, and floodwater can infiltrate into the ground, filling the pore spaces and replenishing the groundwater reservoirs. The specific mechanisms of recharge might vary based on factors like land use, topography, and hydrological conditions, but these landforms generally contribute to maintaining groundwater availability in their respective regions. Proper understanding and management of these areas are essential for sustainable water resource planning and management.

4.1.6 Lithology

The lithology of a rock unit is a description of its physical characteristics visible at outcrop, in hand or core samples, or with low magnification microscopy. Physical characteristics include color, texture, grain size, and composition (Freeze and Cherry, 1979). Examples of lithology in the second sense include sandstone, slate, basalt, and limestone. The clayey facies cover the higher part (70%) of the study area. Clay can cause water logging problems and is the very bed for the infiltration of water into the ground. The alluvium and the sandy facies are the best for groundwater recharge. The clayey facies cover more parts of the south of the study area. Table 2 shows the class names, their values, and normalized weights of lithology calculated using the Analytic Hierarchy Process.

4.1.7 Land use/ Land cover

The earth's surface's physical material is known as the land cover. The term "land usage" refers to how people use the land for socioeconomic activity. Land-use change refers to a change in how a particular area of land is utilized or managed by humans. Land-cover change refers to a change in some continuous characteristics of the land, such as vegetation type, soil conditions, and so forth. The region is primarily utilized for agriculture (78%). Both locations are excellent for recharging groundwater. The decreased permeability in the built-up areas makes them unsuitable (Bera et. al. 2020). Due to the toxins present, wastelands may contaminate the groundwater. The least amount of the research region is covered by rivers and other bodies of water. Table 2 shows the class names, their values and normalized weights of LULC calculated using the Analytic Hierarchy Process.

4.1.8 Groundwater fluctuation (GWF)

The types of aquifer, recharge, abstraction, and regional groundwater circulation in the region all have an impact on groundwater level fluctuations. The most notable sources of water that recharge deeply into the aquifers through either local or regional circulation are high rainfalls above the mean. Changes in the amount of water stored in the aquifer, variations in atmospheric pressure, and variations resulting from aquifer deformation are the three main causes of fluctuations. Roughly 34% of the research area is covered by groundwater rise, whereas nearly 66% is covered by groundwater fall. This indicates that groundwater extraction exceeds groundwater replenishment brought on by precipitation. The difference between the groundwater rise and fall might be up to 0.45 metres, or 0.77 metres in total. These regions have a lot of rainfall. Groundwater levels are decreasing in the research area's northwest and southeast regions. The class names, values, and normalization are displayed in Table 2. Figure 8 depicts the relative weights of the variables influencing the thematic map or groundwater potential. Table 2 weights for thematic maps represent their respective weights in determining the GWRPI value. Any component that is more significant has been given more weight, and vice versa. The greatest weight has been given to groundwater variation. Groundwater variation has been given the same importance as rainfall and geomorphology.

4.2 Groundwater Recharge Potential Zone (GWRPZ)

The result obtained in Fig. 7 (D) shows the GWRPZ and the locations of the artificial groundwater recharge sites. The rechargeability of the ground depends upon its GWRPI. The rechargeability of the groundwater decreases from the north to the south. The maximum range of GWRPI calculated is 0.309 − 0.247. This zone is shown in standard blue (in Fig. 7D) possesses the maximum rechargeability for the groundwater. High rainfall (more than 1300 mm) and higher permeability of the soil makes this part of the study area the best naturally recharged zone. The high permeability of the soil in Terai is confirmed by low drainage density (shown in Fig. 5A). This region (Terai) is located at the maximum elevation (shown in Fig. 7A) in the entire study area. In most of the Terai region, a rise in the groundwater level is visible (shown in Fig. 6D) after the monsoon rainfall. The presence of lineaments improves the groundwater rechargeability of the area as obtained in Fig. 7(A). The types of lineaments present in the Terai are mostly drainage parallel and naturally recharge zone. The GWRPZ follows the drainage density of the study area, i.e. where the drainage density is low there the GWRPI is naturally high. The downstream gravelly sand offers good percolation areas.

Table 2- The thematic map name, their class names and values, the geographical area of each class in km² and in percentage cover, the weights calculated by using the comparison matrix of the AHP and finally, the weights of all the eight thematic maps calculated by using the AHP process have been indicated suitably.

4.3 Validation of GWRPZ

The groundwater recharge (GWR) amount (in mm) was calculated using the UP Irrigation Board formula, the Krishna Rao formula, the Chaturvedi formula, the Braden Kamp formula, and the Amritsar formula. In Fig. 9, a linear relationship between the groundwater recharge (mm) and the groundwater recharge potential index is shown. The coefficient of determination (R2) for these relationships is considerable (varying from 0.79 to 0.85 for all five formulas). It is important to note that for deriving these relationships, only those points were considered that demonstrated better correlation, thereby improving the overall accuracy of the estimates. However, there are cases where rainfall does not correlate properly with GWR, leading to limitations in the application of empirical equations. In such situations, the Groundwater Recharge Potential Index (GWRPI) map offers a better solution as it takes into account various other factors, thereby providing a more robust assessment of potential recharge zones.

A positive relationship shows more groundwater recharge with an increase in the GWRPI. The groundwater recharge values using the empirical formulas use rainfall as the deciding factor, as shown in Table 1. Still, almost 80% accuracy shows that the GWRPZ map created is highly accurate. It should be noted that there is a significant difference between groundwater recharge (GWR) and groundwater fluctuation (GWF). The GWR represents the net amount of water that infiltrates into the aquifers, while the GWF is the difference between pre-monsoon and post-monsoon groundwater levels, which is influenced by GWR, groundwater extraction, and groundwater movement.

Importantly, the empirical groundwater recharge equations used in this study do not consider other essential factors such as slope, soil properties, and geomorphology, which also significantly affect groundwater recharge. These equations provide a simplified estimation of groundwater recharge potential based solely on rainfall data, potentially leading to overestimation or underestimation of recharge rates. Furthermore, the Groundwater Fluctuation (GWF) map, as shown in Fig. 6D, provides insights into seasonal variations in groundwater levels. However, it does not directly represent groundwater recharge and is influenced by multiple factors beyond recharge.

On the other hand, the Groundwater Recharge Potential Index (GWRPI) map in this study focuses on incorporating additional factors such as soil properties, topography, lineament, and drainage density of the study area. These parameters significantly contribute to the understanding of groundwater recharge processes and provide a more comprehensive assessment of potential recharge zones. In cases where rainfall does not correlate properly with GWR, the GWRPI map offers a better solution by considering a broader range of influencing factors, enhancing its usefulness in hydrogeological studies and groundwater management strategies.

The Manimukhta sub-basin of the Vellar river is characterized by a mixed geographical landscape, comprising both mountainous and plain regions in its western and eastern parts, respectively. The rainfall pattern in this region closely resembles that of the Uttar Pradesh Ganga basin. In our study, we employ the Multi-Influence Factor (Multi-IF) technique, which shares similarities with the Analytic Hierarchy Process (AHP) method. While AHP is subjective in nature, Multi-IF offers objectivity in the assessment. AHP relies on highly mathematical and theoretical methods to determine the values of normalized weights. However, as the quantity of groundwater recharge cannot be precisely calculated based solely on rainfall, slope, and soil texture, a subjective approach is more appropriate for evaluating the groundwater recharge potential index. Given that the Manimukhta basin consists of rocky terrain, it exhibits a significant presence of lineaments. In contrast, the Ganga basin in Uttar Pradesh is predominantly composed of alluvial soil and sandstone, resulting in fewer lineaments. This disparity complicates the identification of suitable groundwater recharge regions when making comparisons between the two areas.

In a similar study conducted in the Bist Interfluve region of Punjab, India, utilizing the AHP technique, a groundwater recharge potential zone map was created by integrating thematic maps related to geomorphology, specific yield, geology, soil, drainage density, land use/land cover, transmissivity, and slope. This study identified that the foothills near the Himalayas exhibit poor groundwater recharge potential, while moving away from the Himalayas into the plains, the combination of plain topography, higher transmissivity, and abundant rainfall leads to a very high groundwater recharge potential. Conversely, in our study, we observe higher groundwater recharge in the foothills of the Himalayas due to elevated rainfall, dense forests, and a higher density of lineaments, which is in stark contrast to the Bist Doab region. In our methodology, we assigned low importance to wetlands and water bodies since they already contribute significantly to groundwater recharge. Additionally, the Bist Doab region experiences flooding in the plains, leading to groundwater recharge. The uniform drainage density in the Bist Doab region further differentiates it from our study in the Middle Ganga basin, where significant variations in drainage densities are observed. Downstream, the drainage density is considerably higher, making the region near the Shiwaliks more suitable for groundwater recharge compared to the downstream region, similar to the Bist Doab region.

An isotopic study in the Bist Doab region reveals that local meteoric recharge, primarily driven by rainfall, plays a crucial role in groundwater recharge. Based on the similarities in topography, rainfall patterns, monsoonal weather, and the presence of the Himalayas, it is likely that the Ganga basin in Uttar Pradesh also experiences a considerable contribution from local meteoric recharge. The isotopic studies confirm that groundwater recharge in the Ganga basin is primarily due to rainfall, suggesting that surface runoff may not significantly affect groundwater recharge. However, a conclusive confirmation of these assumptions in the Middle Ganga basin requires additional isotopic studies. Nonetheless, the existence of a similar study area reinforces our observations.

Another significant point in our study is the inclusion of groundwater fluctuation (GWF) as a crucial factor influencing groundwater recharge potential. This factor is absent in the previous studies discussed. The incorporation of GWF enhances the comprehensiveness of our assessment, providing valuable insights into the aquifer's response to changing conditions. In the Loni and Morahi watersheds, another study by Agarwal and Garg also considers GWF. This inclusion sets our research apart, making it more comprehensive and valuable compared to other studies in the field.

By following these steps, we can gain a comprehensive understanding of the groundwater recharge potential in the study area and implement measures to ensure its sustainability for future generations.

In Fig. 10, 60 artificial groundwater recharge sites are shown along that are in the grey location (GWF < 0) in comparison to the other 32 recharge sites. It can be seen that most of these sites are located in areas where the GWRPI is quite low or in the medium range (with reference to the GWRPZ map). The GWF at these sites is negative, showing a large amount of groundwater depletion taking place at these sites. The low GWRPI of these sites will make the GW problems more severe in the coming days. Hence, it is very necessary to construct recharge structures to raise the groundwater levels at these sites. The rest of the 32 sites (Fig. 10) have a higher GWRPI, and the GWF is above 0. Although the integration of RS and GIS is not rare in the world, the application of such techniques proves very fruitful for the poor inhabitants of developing countries. The dissemination of the results obtained in this study to the hydrologists and water professionals may prove to be a boon to farmers, poor people, and all the citizens living in the study area.

The State Government of Uttar Pradesh and the Central Government have taken up several targeted missions for water resource development, augmentation, conservation, and public awareness. A few of these schemes are listed below:

Note: The Cost is given in Indian Rupees (Rs.). Rs. 1,000 crore = Rs. 10 billion

Atal Bhujal Yojana (Total Budget: Rs 6,000 crores): This is a Central Government funded scheme that aims to improve groundwater management through community participation and management. The scheme envisages people's participation through the formation of water budgets, the preparation and implementation of Gram-panchayat-wise water security plans, etc.

Jal Jeevan Mission (Budget: 3,60,000 crores): This is a central government scheme launched in 2019 with a total estimated cost of Rs 3.6 lakh crores for a period of 5 years (2019–2024). Jointly with the Central funds and the State Government fund, the State Departments are implementing this mission for the renovation, rejuvenation, and development of water bodies, the construction of rainwater harvesting structures, check dams, weirs, and other similar structures to conserve surface runoff and recharge groundwater. In the mission, GIS & RS data are extensively used, and field- related data on groundwater levels and water quality are also being analysed.

Khet Talab Yojana

This is a State Government scheme that aims to rejuvenate traditional water bodies like tanks and ponds to enhance the water storage capacity in rural areas. Under the scheme, the State Government provides 50% subsidy to the farmers for developing water harvesting structures.

Mission Amrit Saroar (Total Budget (Central + State Government): Approx Rs 3,00,000 crores): The mission is aimed at developing and rejuvenating 75 water bodies in each district of the country as a part of the celebration of Azadi ka Amrit Mahotsav (the celebration of 75 years of India’s Independence).

Mukhyamantri Jal Bachao Abhiyan This scheme aims to create awareness among the people about the importance of water conservation and encourage them to adopt water-saving practises. The mission is also targeted for the rejuvenation of village ponds.

Namami Gange Programme (Budget: 20,000 crores): This is a central government flagship programme developed and implemented for abatement of pollution, conservation, and rejuvenation of the National River Ganga and its tributaries. Pollution control, river surface cleaning, riverfront development, industrial affluent monitoring, afforestation, public awareness, conserving the ecosystem, etc., are some of the major objectives of the program.

National Plan for Conservation of Aquatic Eco-systems: This program is for the conservation of wetlands and lakes, and is promoted by the Ministry of Environment, Forest and Climate Change (MoEFCC).

Pradhan Mantri Krishi Sinchai Yojana-Har Khet ko Paani (PMKSY-HKKP): This is a Central Government funded scheme developed to improve irrigation efficiency in agriculture through the promotion of micro-irrigation, the construction of check dams, and other similar structures for agriculture sustainability with the vision of ‘per drop, more crop’.

Rural Water Supply and Sanitation Project: This is a part of the National Rural Drinking Water Programme initiated with a total fund of Rs 3,000 crores with the objective of providing water security for all.

Other projects

National Hydrology Project (Rs 3680 crores)- This project aims to improve the water resource management in the country by enhancing the availability, accessibility, and quality of hydro-meteorological data. National Rural Drinking Water Mission (Budget: Rupees 70,000 crores for the period 2019–2022). This program aims to provide safe drinking water to the rural population, including the state of Uttar Pradesh. The above schemes reflect the state government's commitment to the conservation and management of water resources through the construction of check dams and other similar structures.

By integrating various parameters like lineament density, drainage density, slope, rainfall, geomorphology, lithology, LULC, groundwater fluctuation, and utilizing analytic hierarchy process and remote sensing techniques, you can derive several advantages from your groundwater recharge potential zone map.

Comprehensive understanding: By considering multiple parameters, your map provides a more holistic understanding of the groundwater recharge potential in the study area. This helps in identifying areas that have the most favorable conditions for recharge.
Accurate spatial representation: Remote sensing techniques allow for accurate visualization and mapping of the different input parameters. This helps in creating detailed and precise recharge potential zone maps, improving the reliability of the results.
Objectivity and consistency: By using the analytic hierarchy process, you can assign weights to different parameters based on their relative importance, and then use these weighted parameters to calculate the overall recharge potential. This helps in introducing objectivity and consistency into the analysis.
Resource management: The groundwater recharge potential zone map can be a valuable tool for resource management. It can aid in identifying areas where groundwater recharge is high, allowing for better planning and management of water resources in those regions.
Decision-making support: The map can act as a decision-making support tool for various stakeholders, such as government bodies, planners, and researchers. It provides valuable insights into areas with high recharge potential, helping them make informed decisions regarding water management and allocation.

Overall, your groundwater recharge potential zone map, which takes into account multiple parameters and utilizes analytic hierarchy process and remote sensing techniques, offers a more comprehensive, accurate, objective, and decision-making support tool for water resource management in the study area.

While the groundwater recharge potential zone map created using the mentioned parameters and techniques can be valuable, it's essential to consider the possible limitations:

Data availability and quality: The accuracy and reliability of the map depend on the availability and quality of the data used. Inaccurate or outdated data can lead to incorrect assessments of recharge potential.
Scale and resolution: The scale and resolution of the input data, such as maps and satellite imagery, can impact the precision of the analysis. Higher-scale data may not capture variations in recharge potential at a finer level, which could lead to generalizations or inaccuracies.
Assumptions and simplification: Some assumptions and simplifications are made in the analysis process, such as assigning weights to parameters and using surrogate indicators for recharge potential. These assumptions may not accurately represent real-world conditions, leading to limitations in the map's accuracy.
Dynamic nature of recharge: Groundwater recharge is a dynamic process influenced by various factors, including climate change and land-use practices. The map may not capture the temporal variability accurately, especially when using static datasets.
Heterogeneity of geological conditions: Geological conditions can vary greatly within a study area. The map may not capture the heterogeneity effectively, leading to potential inaccuracies in identifying the actual recharge potential across different geological settings.
Local-scale variations: The map may not capture fine-scale variations in recharge potential, particularly in areas with complex topography, land cover patterns, or localized hydrological conditions. This can limit its usefulness for localized management decisions.
Expert subjectivity: The use of the analytic hierarchy process involves expert judgment in assigning weights to different parameters. This subjectivity can introduce biases and limitations in the final map.

Despite these limitations, the groundwater recharge potential zone map serves as a useful starting point for understanding the general recharge potential of an area. It can guide decision-making and resource management efforts, but it should be complemented with local knowledge, field observations, and continuous monitoring to ensure more accurate assessments.

The groundwater recharge potential zone map contributes to the existing pool of knowledge in several ways:

Spatial understanding: The map provides a visual representation of the recharge potential across a given area. It helps researchers, policymakers, and water resource managers gain a better understanding of where groundwater recharge is more likely to occur and identify areas with potential limitations.
Management and planning: The map aids in making informed decisions regarding land-use planning, water resource management, and conservation efforts. By identifying areas with high recharge potential, stakeholders can prioritize sustainable groundwater management practices and protect these areas from activities that could hinder recharge.
Resource allocation: The map allows for better allocation of resources, ensuring that areas most crucial for groundwater recharge receive appropriate attention, protection, and management. This can help prevent overexploitation of groundwater resources and promote sustainable and equitable water usage.
Predictive modeling: The map serves as a valuable input for predictive modeling and scenario planning. It enables researchers and hydrologists to better assess the impacts of different factors, such as climate change or land-use changes, on future groundwater recharge patterns. This aids in developing mitigation strategies and proactive measures to address potential challenges.
Scientific research: The map can serve as a foundation for further scientific research and investigations into the factors influencing groundwater recharge. It provides a baseline for studying the relationships between recharge potential, hydrological processes, and environmental factors, contributing to the advancement of hydrogeological knowledge.
Stakeholder engagement and education: The map can be used to raise awareness among stakeholders, including local communities, policymakers, and non-governmental organizations. It facilitates discussions and dialogue around groundwater management, encouraging the adoption of sustainable practices and ensuring collective involvement in protecting and conserving water resources.

Overall, the groundwater recharge potential zone map contributes to expanding our understanding of groundwater dynamics and supports evidence-based decision-making for sustainable water resource management.

Yes, the Analytic Hierarchy Process (AHP) can still be an efficient tool in the current era for evaluating the groundwater recharge potential zone. The AHP is a structured decision-making method that allows for the systematic comparison and prioritization of different criteria and factors based on their relative importance.

Here are some reasons why the AHP can be effective in assessing groundwater recharge potential:

Multi-criteria evaluation: Groundwater recharge potential involves considering various factors, such as land use, soil type, topography, and vegetation cover. The AHP methodology provides a framework to analyze and compare these criteria, assigning weights to each factor based on their importance. This allows for a comprehensive evaluation of the recharge potential and a balanced consideration of different contributing factors.
Stakeholder involvement: AHP encourages stakeholder involvement by incorporating their preferences and judgments into the decision-making process. This makes it a valuable tool for engaging with experts, local communities, and decision-makers who possess valuable knowledge and insights about the specific context. By involving multiple perspectives, AHP enhances the overall quality and acceptance of the evaluation results.
Transparency and consistency: AHP provides a transparent and consistent framework for decision-making. It breaks down complex problems into a hierarchical structure, allowing decision-makers to clearly understand the relationships between criteria and sub-criteria. The use of pairwise comparisons with numerical scales ensures a systematic and consistent approach, reducing potential bias and subjectivity in the evaluation process.
Flexibility and adaptability: AHP can be tailored to different contexts and adjusted based on specific needs. It allows decision-makers to modify criteria or add new factors as new information becomes available or as the understanding of groundwater recharge potential evolves.
Integration of expert knowledge with data: While data-driven approaches are valuable, experts' knowledge and insights are often critical in assessing groundwater recharge potential. AHP provides a systematic framework to combine both quantitative data and qualitative expert judgments, ensuring a holistic evaluation that takes into account both scientific data and expert experience.

However, it is important to note that the efficiency of AHP relies on the quality of input data, the expertise of the individuals involved, and the robustness of the decision-making process. Regular updates, validation, and calibration of the AHP model are necessary to ensure its continued effectiveness in evaluating groundwater recharge potential in the current era.

In conclusion, this research utilized the integration of remote sensing (RS) and geographical information system (GIS) to map the groundwater recharge potential in the middle Ganga basin, Uttar Pradesh, India. The major findings of this study shed light on various aspects related to groundwater recharge in the region. Firstly, the groundwater recharge potential index (GWRPI) was observed to vary from 0.309 to 0.103, with a decreasing trend from north to south in the middle Ganga basin. This information provides valuable insights into the spatial distribution of recharge potential in the study area. Furthermore, a strong correlation was found between GWRPI and the amount of groundwater recharge calculated using empirical groundwater recharge (GWR) equations, with coefficient determination values ranging from 0.79 to 0.85. This demonstrates the reliability of GWRPI as a useful parameter for estimating groundwater recharge.The study also analyzed the percentage of area covered for each GWRPI class, ranging from 0.07 to 0.308. These findings help in identifying the dominant recharge potential classes within the middle Ganga basin. Regression equations were established to relate GWRPI with GWR calculated using different formulas, providing valuable predictive tools for estimating groundwater recharge based on GWRPI values.

Moreover, the research identified districts with varying average groundwater recharge potential, categorizing them as having high, medium, or low recharge potential. This information is vital for local authorities and policymakers in planning sustainable groundwater management strategies. Additionally, the study employed GIS analysis to identify 92 artificial groundwater recharge locations, with 60 of them being identified as crucial. These sites, located at the intersection of third-order streams, can play a significant role in supplementing groundwater runoff. The findings of this research present practical implications for identifying areas with varying capacities for groundwater recharge. The integration of Analytic Hierarchy Process (AHP) with geospatial and remote sensing techniques proved effective in mapping groundwater potential at a basin-scale, reducing time, cost, and manpower. Ultimately, the outcomes of this study can greatly assist decision-makers in controlling groundwater depletion, protecting groundwater resources, and implementing effective strategies for augmentation. The methodologies employed in this research can also be used as a reference for regions facing similar groundwater scarcity challenges globally.

Future research endeavors can focus on validating the results obtained through field-based data, further strengthening the reliability and accuracy of the findings. By doing so, a comprehensive understanding of groundwater recharge dynamics in the middle Ganga basin can be achieved

Acknowledgement and funding

This research work is part of the research project conducted under the PDS of the National Hydrology Project, funded by the Ministry of Jal Shakti, Government of India.

Disclosure statement

The authors have no competing interests to declare.

Data availability

The data used in this study will be made available as per the request of the concerned authority.

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Analyzing Factors Influencing Groundwater Recharge Potential in the Middle Ganga Basin: An AHP Approach

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Abstract

Figures

1. Introduction

2. Study Area

3. Materials and Methods

3.1 Data source

3.2 Methodology

3.2.1 Calculation of weights

3.2.2 Analytic Hierarchy Process (AHP): -

3.2.3 Weighted Overlay Analysis

3.2.4 Groundwater Recharge Potential Index

3.2.5 Inverse Distance Weighted Method

3.3 Groundwater Recharge Calculation by Empirical equations

4. Results

4.1 Thematic maps

4.1.1 Drainage density

4.1.2 Lineament density

4.1.3 Rainfall Map

4.1.4 Slope Map

4.1.5 Geomorphology

1. Piedmont Pediplain Complex:

2. Older Alluvial Plain:

3. Older Flood Plain:

4. Active Flood Plain:

5. Piedmont Plain:

4.1.6 Lithology

4.1.7 Land use/ Land cover

4.1.8 Groundwater fluctuation (GWF)

4.2 Groundwater Recharge Potential Zone (GWRPZ)

4.3 Validation of GWRPZ

5. Discussion

6. Conclusion

Declarations

References

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S. No.	Name	Formula
1	UP Irrigation Board formula	R = 1.35\({\left(P-15\right)}^{0.5}\) here P = inches, and R = inches.
2	Krishna Rao formula	R = 0.30(P-300)here P = mm, and R = mm.
3	Chaturvedi formula	R = 2.0\({\left(P-15\right)}^{0.4}\) here P = inches, and R = inches.
4	Braden-Camp formula	R = 0.32(P-360) here P = mm, and R = mm.
5	Amritsar formula	R = 2.5\({\left(P-16\right)}^{0.5}\) here P = inches, and R = inches.