Introduction

Water is necessary to mankind; however, with dwindling surface water resources, groundwater is presently the principal source of fresh water for domestic and agricultural use. Forever increasing demand for water has accelerated the use of underground water. Especially, in the dry zone where the annual rainfall is low; groundwater (particularly from dug wells and tube wells) acts as the main source of water for agriculture, industry and household uses. Globally, 42% of the total groundwater is used for agricultural purposes (Taylor et al. 2013). Groundwater happens to be an important natural resource for reliable economic growth and drinking water in both urban and rural environment (Agarwal and Garg 2016). Groundwater is known to be a dynamic and renewable natural resource but in hard rock landscape like red and lateritic zones (RLZs), availability of groundwater is limited. In India, water resource improvement is needed as it plays a crucial role in developing the country’s agro-economy (Bhunia et al. 2012). Moreover, in India, more than 90% of the rural and nearly 30% of the urban populations depend on groundwater to meet their drinking and domestic requirements (Reddy et al. 1996).

RLZs of India experience a wide range of temperature and erratic rainfall (Mukherjee and Banerjee 2009). Agriculture in RLZs is mostly rainfed. Due to low water holding capacity, excessive drainage, surface runoff and high soil-erosion, red lateritic zones are highly susceptible to any change of weather parameter (Milly 1994; Milly and Dunne 1994; Sehgal 1998; Mukherjee and Banerjee 2009). Recent studies revealed that the RLZs of West Bengal (Purulia and Bankura districts) India, though experience sufficient but often irregular annual rainfall, are affected by recurrent droughts (Mukherjee and Patil 2013; Ghosh and Jana 2017). In years of below-normal rainfall, RLZs suffer from water stress. In summer months most of the surface water sources like ponds, streams, etc. dry up completely and groundwater stands as the only option for water supply (Nag 1998). Due to the variability of rainfall and lack of irrigational facility, cultivation becomes challenging and gets severely affected (Sehgal 1998; Mukherjee and Banerjee 2009; Mukherjee and Patil 2013). Groundwater resource identification and sustainable use in the RLZ are, therefore, extremely necessary to sustain productivity, remove poverty and to ensure food security in such areas.

The most reliable and standard methods for determining locations, the thickness of aquifers and other subsurface information require test drilling and stratigraphic analysis; however, these approaches are expensive, time-consuming and needs skilled manpower (Todd 1980; Roscoe Moss Company 1990). Numerous techniques for delineating groundwater potential zones (GWPZ) such as frequency ratio (Guru et al. 2017; Al-Abadi et al. 2015), random forest model (Naghibi et al. 2016) and logistic regression model (Pourtaghi and Pourghasemi 2014) have been adopted and implemented by various researchers. In this context, analytic hierarchy process (AHP) based on remote sensing and GIS is considered as a simple, effective, reliable and cost-effective technique (Machiwal et al. 2011; Ishizaka and Labib 2011; Maity and Mandal 2017).

Several studies have been conducted in the world for identifying the groundwater potential zones using remote sensing and GIS for the evaluation of groundwater resources in Central Eastern Desert, Egypt (Abdalla 2012), Burdur, Turkey (Sener et al. 2005), Ghana (Gumma and Pavelic 2013), Maknassy basin, Tunisia (Chenini et al. 2010) and Kurdistan region, Iran (Rahmati et al. 2015). Ferozu et al. (2019) also delineated the groundwater potentiality in the drought-prone area of Bangladesh using remote sensing and GIS approach.

Similar works were conducted in India by Jasrotia et al. (2016) in the sub-mountainous region, Mallick et al. (2015) in New Delhi, Madrucci et al. (2008) in Udaipur district, Rajasthan, Paschim Medinipur District, West Bengal (Bhunia et al. 2012), Theni district, Tamil Nadu (Magesh et al. 2012) and Unnao district Uttar Pradesh (Agarwal et al. 2013). Waikar and Nilawar (2014) used AHP for identification of GWPZ in the Parbhani district of Maharashtra. Ndatuwong et al. (2014) made hydrogeological factors coupled with remote sensing and GIS techniques for demarcation of GWPZs in the Vindhyan basin of Uttar Pradesh. Jaiswal et al. (2003) also emphasized on remote sensing and GIS techniques to define groundwater prospective zones for rural development. Prasad et al. (2008) have considered geomorphology and lineament density (Nalgonda District, Andhra Pradesh) for identification of ground water prospective zones. In India, micro-scale GWPZ evaluation using remote sensing and GIS technique was attempted with considerable success Ibrahim-Bathis and Ahmed (2016) used land use/land cover, geomorphology, drainage density, slope and lineament density for identification of GWPZs in Doddahalla watershed of Krishna basin. Similar parameters were used for GPWZ identification at Bairasagara Watershed, Kolar district, Karnataka by Chandra et al. (2006) and at Kattankulathur block Kancheepuram district of Tamil Nadu (Nagarajan and Singh 2009).

Micro-level GWPZ was also assessed in Purulia and Bankura District, West Bengal using integrated approach of remote sensing and GIS techniques in the hard rock terrain of Kashipur Block, (Nag and Kundu 2016), Baghmundi block in Purulia District (Nag 2005) Dwarakeswar watershed, Bankura district, (Nag and Lahiri 2011) and Chhatna Block, Bankura District (Nag and Ghosh 2012). They have mainly used three basic parameters (hydrogeomorphology, slope and lineament density) to identify the groundwater potentiality. However, recent studies (Patra et al. 2018; Nsiah et al. 2018; Magesh et al. 2012; Singh et al. 2018; Ferozu et al. 2019) indicate that drainage density, land use and fractional impervious surface (FIS) are very important parameters to effectively recognize GWPZ. The drainage pattern indicates runoff and infiltration capacity to recharge the groundwater (Yeh et al. 2016; Ferozu et al. 2019). FIS serves as an indicator of the availability of groundwater (Patra et al. 2018) and land use/land cover can influence the groundwater recharge (Leduc et al. 2001). Many studies have also integrated drainage density, land use/land cover and FIS to identify a potential groundwater recharge zone (Singh et al. 2019; Ferozu et al. 2019; Patra et al. 2018). Due to the paucity of studies involving an integrated approach to identifying GWPZs in the RLZ of West Bengal, India, the present study was conducted to delineate the GWPZs in the study area using the parameters like hydro-geomorphology, slope, lineament, drainage density, land use/land cover and FIS.

Study area

RLZ of West Bengal under National Agricultural Research Project (NARP) includes the districts of Purulia, Bankura, West Medinipur, Burdwan (part) and Birbhum (part). Kashipur block (~ 434 km2) of Purulia district and Chhatna block (~ 449 km2) of Bankura district were chosen as representatives of the RLZ (Fig. 1) which lie between 23°10ʹ33.2ʺ (N)–23° 30′40.3ʺ (N) and 86°34′19.97ʺ (E)–87°00′55.59ʺ (E). The study area is largely a Pre-Cambrian gneissic terrain comprising crystalline gneiss, schist, intrusives and recently deposited alluvium (Nag and Ghosh 2012). The Dwarakeswar is the largest river in the area and flows from northwest to southeast. The area experiences subtropical climate and the average temperature ranges between a maximum 43–47 °C (summer) and minimum 7–12 °C (winter), respectively. The annual rainfall (1200–1400 mm) is distributed throughout the year as 100–150 mm during the pre-monsoon season, 900–1100 mm during the monsoon season and 80–110 mm during the post-monsoon season. The land surface of the area is characterized by hard rock uplands, undulating laterite and flat alluvial area (Nag and Kundu 2016). Elevation, in general, varies between 150 and 300 m in the area, the master slope being towards the east and south-east (Ray 1982).

Fig. 1
figure 1

Location map of the study area

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Data used

Six different types of thematic maps, respectively, for geomorphology, lineament, slope, land use/land cover, drainage density and FIS, were prepared from analysis of satellite data and existing maps for the present study area. Elevation, slope and drainage density maps were prepared using ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) Digital elevation model (DEM) at 30-m spatial resolution downloaded from United States Geological Survey Earth Explorer (earthexplorer.usgs.gov). The geological map was acquired from the Geological Survey of India (GSI). Topographical maps (No. 73 I/11, 73I/12, 73 I/15 and 73I/16) were collected from the Survey of India. Land use/land cover and FIS maps were generated from LISS-IV (Linear image sensing sensor) images at 5.8-m spatial resolution.

Materials and methods

The processes of delineating the groundwater potential zones have been represented in Fig. 2. Six thematic layers (Hydrogeomorphology, Slope, Lineament Density, Drainage Density, Land Use/Land Cover and FIS) having significant control on groundwater availability (Mukherjee et al. 2012; Agarwal et al. 2013) were prepared. The GWPZs were acquired by superimposing all the thematic layers in terms of weighted overlay technique (Waikar and Nilawar 2014) using the spatial analysis tool in ArcGIS 10.3 software.

Fig. 2
figure 2

Flow chart of methodology

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Generation and classification of the thematic layers

Hydrogeomorphology

Collected hydro geomorphological map of the study area was scanned, rectified and digitized in ArcGIS 10.3 software.

Slope

The slope map was created from the digital elevation model (DEM) using the spatial analysis tool in ArcGIS10.3 software.

Lineament

Lineaments were interpreted from a high-resolution satellite image (LISS-IV). At first, Principal Component Analysis was conducted for image enhancement in ERDAS14, followed by automatic line extraction in PCI Geometica 9.1. Lineament density map (km/km2) was prepared in ArcGIS10.3.

Drainage density

Drainage was derived using the DEM and toposheets. Using ArcGIS10.3 software, the drainage density map was composed taking into account length of drainage per sq km area.

Land use/land cover

Land use/land cover map for the year 2017 was composed using high-resolution (5.8 m) satellite image (LISS-IV) and knowledge-based classification technique using the ERDAS Imagine (14) platform.

Fractional impervious surface

Impervious surface indicates the environmental quality of any region. Satellite-derived NDVI data (from LISS-IV image) were used to derive fractional vegetation cover (FVC) (Kasperson 2015).

Ridd (1995) and Owen et al. (1998) showed the relation between the fractional vegetation cover (FVC) and fractional impervious surface area (FIS) flows as:

$$ {\text{NDVI}}_{\text{S}} = {\text{NDVI}} - {\text{NDVI}}_{\text{low}} /{\text{NDVI}}_{\text{high}} - {\text{ NDVI}}_{\text{low}} , $$
(1)

where, NDVIlow and NDVIhigh values were obtained from bare soil and dense vegetation, as proposed by Carlson and Ripley (1997).

$$ {\text{FVC}} = \, \left( {{\text{NDVI}}_{\text{S}} } \right)^{ 2} , $$
(2)
$$ {\text{FIS}} = { 1}{-}{\text{FVC}} . $$
(3)

Assigning rank and weight

The groundwater potential zones were evaluated by integrating all the spatial layers using weighted overlay approach. Before the overlying operation, individual spatial layers were reclassified to a uniform rank of 1–4, where 1 represents poor groundwater potential and 4 represents excellent groundwater potential. Weights have been assigned through pairwise comparisons matrix based on AHP (Table 1).

Table 1 Normalized Pairwise comparison matrix (six layers) developed for AHP based groundwater potential zoning
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The ranks were assigned to the respective parameters considering the field survey experiences, stakeholder consultation, and expert opinion surveys as well as consulting the existing literature (Krishnamurthy et al. 1996; Saraf and Choudhury 1998; Waikar and Nilawar 2014). Hydrogeomorphology was assigned the highest weight; whereas slope, lineament density and drainage density were assigned moderate weight and land use/land cover was assigned low weight (Table 2). After assigning weights to the respective parameters, individual ranks were given for sub-variables (Butler et al. 2002; Asadi et al. 2007; Yammani 2007). The maximum value was used to characterize the highest groundwater potentiality and vice versa.

Table 2 Weights assigned for different ground water control parameters in the present study
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Results and discussion

Hydrogeomorphology

Hydrogeomorphology, controlled by landform, lithology and underlying rock structure (Patra et al. 2018) in turn imparts a significant control over the groundwater potential and prospect (Kumar et al. 2008). The study area is characterized by dominant rocky terrain, undulating surfaces, erosional and depositional hydro-geomorphic features (Fig. 3).

Fig. 3
figure 3

Hydrogeomorphological map of Kashipur and Chhatna block

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Structural hills

These are rocky broad upland with a perceptible rise in elevation. Very shallow coarse loamy soil was observed. It is mostly covered by open to dense forest and plantation and is not suitable for agriculture or orchards. From the groundwater point of view, the structural hills serve as high run-off zones, leading to poor infiltration mainly due to moderately steep to very steep hill slopes.

Valley fills

These are accumulation zones of unconsolidated sediments and colluvium derived from surrounding uplands. Soil characteristics in this region are fine loamy to clayey soil with fine texture, and moderately well-drained having moderate wetness. Valley fills are suitable for single crop and that too for mainly terrace cultivation. This region has very good porosity and permeability but sometimes the presence of clay may make it impermeable.

Buried pediment (moderate)

The slope of moderate buried pediment is gentle. Moderately deep clay to fine loamy soil with fine texture was observed over this landform. Buried pediment (moderate) is suitable for a single crop with marginal Rabi crops. Groundwater prospects are also moderate in this region.

Buried pediment (shallow)

This region shows nearly flat to gently sloping topography. It is characterized by shallow to moderately deep loamy soil followed by weathered zone. Soil texture is coarse with the presence of weathered rocky outcrops. This region is also suitable for a single crop. The groundwater prospects in this region are moderate to poor.

Hydrogeomorphology provides information about the distribution of various landform and topography of an area and is one of the main factors used widely for the delineation of groundwater potential zones (Rajaveni et al. 2017; Thapa et al. 2017).

The structural hills and inselberg region of the study area are having sharp but with rugged tops depicting that the high surface runoff of the upper stretches of the hills is affected by erosion. Very shallow coarse loamy soil is originated. However, the lateritic lower plateau with valley fill occurs in midland and lowland areas of the Dwarakeswar river basin, with fine-textured, moderately well-drained loamy to clayey soil. Hence, valley fill is the best landform (highest rank) and structural hill is poor (lowest rank) for high groundwater potential.

Slope

Generally, flat and gently sloping areas have high infiltration and are capable of more groundwater recharge; whereas, steeply sloping grounds promote high run-off and little or no infiltration (Adiat et al. 2012; Rahman et al. 2012). The slope of the study area ranges between 0° and 54°, with maximum at Shusunia Hill area in Chhatna block, Bankura (Fig. 4). Gentle to moderate (0–10°) and steep (> 20°) slope covered 70% and 30% area of the blocks, respectively.

Fig. 4
figure 4

Slope map of the study area

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The class having less slope value is given the highest rank due to an almost flat or gentle slope which associated high infiltration and low runoff, while class having maximum slope value is given the lowest rank due to relatively high runoff and low infiltration.

Lineament

Geological linear features are mainly expected to be the fractured zone with good porosity and permeability (Das et al. 1997; Rao et al. 2001; Magowe and Carr 1999; Hardcastle 1995; Devi et al. 2001). The lineament disposition of the area gives important information about subsurface fractures that may influence the movement and storage of groundwater. Mainly ESE–WNW/E–W, NE–SW and NW–SE, N–S/NNE–SSW trending fractures, joints or lineaments were found in the study area. Areas with very high lineament density (2.5–3.5 km/km2) have good groundwater potentiality and assigned higher rank due to good porosity and infiltration; whereas, the areas with very low lineament density (0–0.5 km/km2) are considered to have poor groundwater potentiality and assigned lower rank. The entire area is classified into four categories according to lineament density as shown in Fig. 5.

Fig. 5
figure 5

Lineament density map of the study area

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Drainage density

Drainage density reflects the proximity of spacing of channel as well as surface characteristics (Manap et al. 2013). Runoff, infiltration, relief and permeability-related information are acquired by quantifying drainage density and type of drainage. Drainage pattern gives information related to surface materials and subsurface formation, such as dendritic drainage mostly indicates homogenous rocks; the trellis, rectangular and parallel drainage patterns are indicative of structural and lithological controls (Horton 1945). Observations from various geologic and climatic zones indicate that low drainage density is more likely to occur in a flat region with highly permeable subsoil under dense vegetation. High drainage density is developed in mountainous relief, regions with sparse vegetation and impermeable subsurface. Low drainage density characterizes coarse drainage texture and high drainage density leads to fine drainage texture (Waikar and Nilawar 2014). A high drainage density region causes lower infiltration leading to poor GWPZs as compared to a low drainage density region (Murasingh 2014). River or water bodies are generally considered as the vital sources of recharge of the groundwater table. However, if too many rivers flow in an area increasing the drainage density, it means high surface runoff and eventually promotes limited infiltration and reduced groundwater recharge (Dinesh Kumar et al. 2007; Magesh et al. 2012). Drainage density has an inverse effect on permeability. Therefore, it is an important feature in evaluating groundwater potential zone. High drainage density value is favorable for runoff and low groundwater potential. Hence, high rank is given the low drainage density area. The highest drainage density was found to occur in the northern and south-western part; whereas, the lowest drainage density occurs in the eastern part of the study area (Fig. 6).

Fig. 6
figure 6

Drainage density map of the study area

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Land use/land cover

Land use/land cover of an area is largely governed by the groundwater resources and, at the same time, plays an important role in controlling the resources. It influences many hydrogeological processes in the water cycle like evapotranspiration, infiltration, surface runoff, etc. (Kaliraj et al. 2014). In the forest and agricultural land, runoff is generally less and infiltration is more, whereas, in pediment and settlement areas, the rate of infiltration usually decreases. Therefore, agricultural land, vegetation cover area is assigned high rank, and pediment and settlement are assigned low rank. In the RLZ understudy, major portion in land use is cropland, covering 516.14 km2 (59.99%) area, forest & vegetation covering 129.52 km2 (15.05%), pediment covering 128.31 km2 (14.91%), fallow land covering 50.33 km2 (5.84%) and settlement covers 36.06 km2 (4.19%) area (Fig. 7).

Fig. 7
figure 7

Land use/land cover map of the study area

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Fractional impervious surface

Impervious surfaces, either natural or manmade, are hard surfaces that prevent percolation of rainwater and groundwater recharge. Analysis of impervious surface, therefore, has an important contribution in the identification of GWPZ. Many researchers (Fohrer et al. 2001; Lee et al. 2003; Zhou et al. 2010; Weng 2012) have deliberated the effect of the impervious surface on hydrology and environment. Impervious surfaces impede percolation, infiltration, subsurface water availability and encourage overland flow, larger volumes of run-off and shorter time of absorption (Brun and Band 2000). Thus, a higher amount of impervious surface restricts groundwater potentiality in a region. Hence, low FIS area is considered as high groundwater potential zone. In the study area, the coverage of such an impervious surface is around 42% indicating low to poor groundwater potential (Fig. 8).

Fig. 8
figure 8

Fractional impervious surface of the study area

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Ground water potential zones

All the six thematic layers (hydrogeomorphology, slope, lineament density, drainage density, land use/land cover and fractional impervious surface) were assimilated in a GIS platform and a single groundwater potential map was produced illustrating the favorable groundwater zones (Fig. 9). Four different classes, namely, ‘Excellent’, ‘Good’, ‘Fair’ and ‘Poor’ GWPZs were categorized in 1–4 scale (Table 3).

Fig. 9
figure 9

Ground water potential zone of the present study area

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Table 3 Groundwater potential zones of the study area
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The ‘Fair’ areas of groundwater potential zones are found to be randomly distributed over the study area. It encompasses an area of 265 km2 in Chhatna and 278 km2 in Kashipur, which are about 56.72% and 59.81% of the total area of the administrative blocks in the RLZ, respectively. The north, north-eastern, south and south-western parts of the study area fell under the category of ‘good’ GWPZ of about 170 km2 (38.45%) and 139 km2 (31.81%) in Chhatna and Kashipur block, respectively. ‘Good’ GWPZ is characterized by a gentle slope, low drainage density, high lineament density and favorable hydro-geomorphological form. ‘Poor’ GWPZ has low recharge capacity and steeper slope as compared to good and moderate GWPZ (Patra et al. 2018). The southern part of the Kashipur covers an area of about 18.27 km2 ‘poor’ GWPZ zone because of its steep slope and unfavorable geomorphological condition.

Ground water potential zones have been identified with the help of remote sensing and GIS-based AHP process in different parts of the world (Sener et al. 2005; Gumma and Pavelic 2013; Rahmati et al. 2015; Ferozu et al. 2019). Results of these studies indicated that out of the total study area, 30–40% have fair to good potentiality of groundwater, as in Bangladesh (Ferozu et al. 2019), in Iran (Rahmati et al. 2015) or in central Eastern desert Egypt (Abdalla 2012). Similar study at Ghana (Gumma and Pavelic 2013) could identify 50% of the total area to be of fair to good groundwater potentiality.

In contrast, GWPZ assessed using three parameters of hydrogeomorphology, slope and lineament density in the Kashipur Block, Purulia District (Nag and Kundu 2016) and Chhatna Block, Bankura District (Nag and Ghosh 2012) identified significantly larger area under ‘excellent’ and ‘good’ categories of GWPZ. These previous studies identified about 30–35% of the Chhatna block and 2% of the Kashipur under ‘excellent’ category, while 55–60% of the area of both the blocks under ‘good’ category of GWPZ. However, ground validation of GWPZ in the present study did not reveal such an encouraging proposition.

Recent studies (Patra et al. 2018; Nsiah et al. 2018; Magesh et al. 2012; Singh et al. 2018; Ferozu et al. 2019) indicate that drainage density, land use and fractional impervious surface (FIS) are most important parameters to effectively recognize GWPZ. The present study using six basic parameters namely hydrogeomorphology, slope, lineament density, drainage density, land use/land cover and FIS in an integrated remote sensing GIS framework appears to be more in tune with the state of the art method to delineate the GWPZs, particularly in the RLZ of West Bengal. Moreover, previous studies in this area did not offer any ground validation of the remote sensing-derived GPWZs. Thus, the findings from the present study are distinguished from the earlier ones in two aspects; firstly, in the total number of parameters employed for the analysis and secondly, in the better accuracy in ground water potential assessment as evidenced by the validation from field data discussed in the subsequent section.

Validation of groundwater potential zones

To validate the potentiality of the groundwater, the present status of several dugwells was considered as a proxy of groundwater availability. It was assumed that regions having good to fair GWPZ must be accompanied by perennial dugwells and the dugwells of poor GWPZ should show the characteristic of drying up, especially in summer. Field surveys were conducted and the majority of dugwells in good/fair GWPZs were found to be perennial indicating the existence of permeable reservoir with substantial water storage at subsurface. Conversely, majority of the wells in the poor zone was found to dry up during the summer season. Out of the total 180 perennial wells in the present RLZ, 81% were found in good GWPZ and 19% in fair GWPZ confirming the first part of the hypothesis. Conversely, among the 76 non-perennial wells, 62% falls in the fair category and all the surveyed wells (10 wells) in the poor GWPZ were found to be non-perennial. This observation not only proves the high accuracy of the assessment but also signifies that the approach taken in the present study to characterize the GWPZs was apt for such kind of RLZ.

Conclusion

Sustainable use of groundwater is necessary to promote long-term sustainability of agriculture as well as for socio-economic development in any area. In the present RLZ, groundwater is being extensively used to the domestic and agricultural needs of the people. The agriculture of the RLZ area under study depends largely on rainfall and rainwater harvesting, mostly through ponds and dugwells with limited river lift irrigation. As the onset of monsoon and quantum of rainfall in the month of July and August has become irregular in recent time, the demand of groundwater is increasing to fill up the water deficit not only in the Rabi (winter) season but also during the monsoon months. We have delineated the GWPZs in the RLZ of West Bengal (Kashipur and Chhatna blocks) by the integrated RS and GIS-based AHP methodology. The GWPZs were derived for the present RLZ and the results revealed that poor, fair and good potential zone covered 4.18%, 56.72% and 31.81% of the Kashipur and 1%, 59.81% and 38.45% of Chhatna, respectively. It was also observed from the study that good groundwater recharge zone is located only in the peneplained portion of the study area with favorable hydrogeomorphology, slope, lineament density, drainage density and land use/land cover. Rainwater is mainly responsible for the groundwater recharge. However, moderate to steep slope area is considered as fair zones for groundwater recharge processes. These areas can be selected for the construction of recharge structures such as check dam, water absorption trench and farm ponds to store the rainwater and to arrest excessive surface runoff. The GWPZ map as an outcome of the present study is envisaged to be useful for locating suitable locations for extraction of water, sustainable groundwater utilization, further land-use planning and water resource management in Bankura and Purulia region and can be extended to other RLZs of West Bengal, and India. This integrated remote sensing–GIS framework-based analysis has been used at the micro-scale in the present study but this method can further be scaled up in the RLZ of India and the world to facilitate better watershed management practices, which can be used for agricultural and drinking water purposes. The present research reaffirms the efficacy of integration of remote sensing with AHP in terms of being a cost-effective method requiring a reduced workforce and eliminating the time constraints of conventional methods for groundwater prospecting.