1 Introduction

Around the world, there has been a significant influence on the quantity, quality, and accessibility of water due to rapid population increase, urbanization, and water-intensive development patterns combined with climate change [1,2,3]. A significant section of the population in nations like India depends on agriculture for their livelihood, making water management a crucial concern. The majority are modest farmers whose crops are grown solely by the annual monsoon. Therefore, to address the problem and guarantee a sustainable water supply for both human consumption and agriculture, swift and coordinated action must be taken. India is the world's largest groundwater user, with 249 billion cubic meters (BCM) extracted in 2017, more than the combined extraction of the United States and China, according to the latest estimates from the government [4]. The monthly extraction of these assessment units in India is slightly over 17% overexploited, meaning that it surpasses the yearly recharge of their aquifers [4, 5].The country's irrigation well count was 6.2 million in 1986–1987. Two and a half million by 2013–2014. The substantial overexploitation of the groundwater resource has resulted in the depletion of groundwater supplies in many parts of the nation [6,7,8]. After being seen near to the source, rivers usually gradually dry out or lose flow in bigger hydrologic units. Rivers are losing water for several reasons, such as dam construction and water use for agriculture. However, climate change, which is altering rainfall patterns and increasing evaporation owing to rising temperatures, is frequently the cause of the flow drop [9]. When it comes to groundwater replenishment, recharge is the main issue. Recharge can be artificial, coming from human acts that intentionally or unintentionally replenish an aquifer, or natural, coming from precipitation that falls on the earth's surface and flows beneath it [10,11,12]. Artificial recharge replenishes groundwater by speeding the natural penetration of surface water or rains into subsurface formations using a range of methods designed to consider soil, topography, and geological factors [13]. The mass balance approach is the most commonly used to estimate natural recharge [14,15,16]. When groundwater flow in an unconfined aquifer was studied under seasonal artificial recharge schemes with different durations, it was found that the features of the aquifer and the length of the recharge had a significant impact on variations in storage and outflow from the aquifer, except from the silting of the recharge well [17]. According to [18], higher perimeter basin designs led to reduced groundwater build-up when artificial recharge basins of different shapes were analyzed and their effects on the underlying aquifer system evaluated. The amount of groundwater recharge can be increased by building in the appropriate locations, as these structures may impede emergent tributary flow and the natural force behind surface runoff.

Groundwater management studies greatly benefit from the use of geospatial techniques in conjunction with remote sensing and GIS. Remote sensing is an advanced technology that uses data's spatial, temporal, and spectral aspects to cover huge, inaccessible areas quickly and comfortably [19,20,21,22]. Water bodies' ecological and chemical state is evaluated by the Water Framework Directive 2000, which is inherently linked with water security [23]. Cross-border concerns dominate discourse in the Middle East [24]. Water security is influenced by societal disparities, associates with the human right to water and requires a commitment to effective governance [25,26,27]. According to the recently adopted Water Security National Plan, Brazil's primary topic of discussion is large-scale water infrastructure. Due to the Plan's sensitivity to major climatic occurrences, an optimal water security scenario should be carefully planned, dimensioned, implemented, and monitored, considering the equilibrium between supply and demand and contingency eventualities [28, 29]. However, conservation and restoration measures, sometimes referred to as river basin revitalization, are not included in the objectives for water security planning, not even for aquatic zones. The sustainable use of natural resources, the enhancement of socio-environmental conditions, and the availability of water in quantity and quality for various uses are the goals of this concept, which consists of a set of ongoing and integrated actions for preservation, conservation, and environmental recovery [30,31,32]. In light of this, river basin restoration is essential for water security everywhere. With questions like "What role does river basin rejuvenation play in ensuring water security? How do they relate to each other?" needed to be answered. The study's novelty lies in the fact that it combined multi-criteria decision issues for the promotion of recharge structures in the basin with field dataset evaluation. The precise objectives of the project were to (1) create multiple thematic layers using conventional datasets and satellite data products, (2) locate possible groundwater recharge zones, and (3) choose the best sites for the installation of specific artificial recharge structures. Applying scientific technologies like remote sensing, GIS, and multi-criteria decision analysis could solve the water scarcity problem in the study region and the rebirth of the Kanari River.

2 Study area

The Ghutehi village (Sihora Tehsil) in the Jabalpur district of Madhya Pradesh is home to the Kanari River basin. The Ghutehi hill region, which is situated at Ghutehi village (Sihora Tehsil) in the Jabalpur district of Madhya Pradesh at an elevation of roughly 490 m, is the source of the non-perennial river known as "Kanari." Geographically, the river's source is situated 62 km northeast of Jabalpur [33]. The basin was geographically extended between (23°33′36.73″N and 80°06′57.49″E) and finally joins (23°29′18.68″N and 79°59′09.20″E), as shown in Figs. 1, 2. The area's spatial extent encompasses a total of 298 km2. The research area is situated between the watershed divides of the Narmada and Son rivers in the Jabalpur district of Madhya Pradesh's Mahakoshal region. However, most of the area is within the Narmada valley, which drops 30 feet down a rocky ledge (the Dhuandhar, or misty shoot).

Fig. 1
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Location map of the Kanari River basin in Central India

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Fig. 2
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Villages in the Kanari River basin in Central India

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3 Material and methods

3.1 Aquifer mapping

The current research area was based on the National Atlas on Aquifer Systems of India on 1: 2,50,000 scale, which was created by the Central Ground Water Board (CGWB) in 2018. Using a variety of ArcGIS 10.3 tools, the National Atlas on Aquifer Systems of India was geo-referenced to extract the different types of aquifers for the Kanari River watershed.

3.2 Aquifer storage volume estimation

The storage of groundwater in an aquifer system, like the one mentioned above that was taken from the National Atlas on Aquifer Systems of India, is the amount of water that might be hypothetically removed in the unlikely event that the aquifer was to be fully depleted. The aquifer's surface area, saturated thickness (b), and specific yield (Sy) of its constituent materials were multiplied to determine the groundwater storage in an unconfined aquifer. This calculation was based on the assumption that the aquifer's surficial extent indicates the lateral extent of the depth aquifer.

$${\text{Groundwater Storage Volume }} = \, \left( {{\text{S}}_{{\text{y}}} } \right) \, \left( {\text{b}} \right) \, \left( {\text{aquifer surface area}} \right)$$
(1)

The distance measured from the top of the water table to the top of the underlying bedrock aquitard is known as the saturated thickness. The ratio of the amount of water that can be released to the volume of material that contains that released water is known as the specific yield, which is also known as the unconfined storavity. Therefore, a specific yield is a dimensionless number representing the amount of water released from storage by an unconfined aquifer per unit aquifer surface area and per unit drop in the water table.

The well locations of nine wells were mapped as point shapefiles using ArcView's ability to connect and link GIS features into tabular data. The database tables were then interlinked with pertinent information. The delineation of the discrete polygons that constitute the unconfined aquifer's coverage area was the next phase in this process. Every discrete polygon had to have a saturated thickness value assigned to it once the acreages, aquifer depths, and precise yield values were established for each polygon.

The Saturated thickness was calculated on the basis of

$${\text{T }} = {\text{Kb}}$$
(2)

where, T is transmissivity; K is hydraulic conductivity (m/day); b is aquifer thickness (m).

The research area's pumping test data were used to calculate transmissivity and hydraulic conductivity (m/day). The particular yield was considered the mean for the kind of aquifer found in the research region. By multiplying the polygon area by the specific yield and the saturated thickness, the groundwater storage volume for each and every polygon was determined.

3.3 Estimation of recharge zones

3.3.1 Identification of recharge zones at Kanari River watershed

The groundwater recharge zone and artificial recharge structures in the Kanari River system were identified by integrating several thematic maps generated from satellite data into the GIS platform. Using RS and GIS techniques, the present study's methodology involves deriving thematic layers essential for identifying and demarcating potential groundwater zones. Next, weights are assigned in accordance with the AHP, a tool for decision-making. The possible groundwater recharge zones in the Kanari River watershed area were identified using weighted overlay analysis in GIS. Major data products used, and their sources are presented in Table 1.

Table 1 Data Products and their sources
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3.3.2 Thematic layers for GIS analysis

A number of layers were developed for the purpose of identifying the appropriate recharging zones using RS and GIS technologies together with other software. Geology, slope, geomorphology, land use/cover, soil, drainage density, and lineament density were the many layers that were examined for the suitability analysis. Lineament maps were also created for the watershed of the Kanari River. Every field on the theme map was given a weight and rank based on how it affected the transportation and storage of groundwater. The Spatial Analyst tool in ArcGIS 10.3 was used to assign the relative ranking for each and every thematic unit inside each theme based on a knowledge-based hierarchy. Following that, the definitive map was categorized into five zones: excellent (5), very good (4), good (3), moderate (2), and poor (1) based on the groundwater potential.

3.3.3 Multi criteria decision analysis (MCDA) using GIS techniques

Determining groundwater recharge zones using multi-criteria decision analysis using the AHP is one of the most often used GIS-based techniques. All of the chosen topic layers are integrated with the aid of this procedure. For this investigation, seven distinct kinds of topic layers were created. The Kanari River watershed's seven thematic levels were thought to regulate the flow and storage of water. The aforementioned contributing elements were combined and given weights based on how they affected the presence of groundwater. A parameter with a high weight indicates a layer with more significant influence, whereas a parameter with a low weight indicates a layer with comparatively less impact on groundwater potential [34, 35]. Based on the relative relevance values, all parameters were allocated a weight based on Saaty's scale (1–9) [36]. In addition, weights based on field expertise and assessments of previous studies were applied. According to Saaty's relative importance scale, a value of 9 denotes extreme importance; an 8 indicates very, very strong importance; a 7 indicates very to extreme importance; a 6 indicates strong plus importance; a 5 indicates strong importance, a 4 indicates moderate plus importance, a 3 indicates moderate importance, a 2 indicates weak importance and a 1 indicates equal importance. All these layers were given weights based on their importance and ability to contain water per the classification. Next, using a pair-wise comparison matrix, all of the theme layers were compared to one another. Using the GIS platform's natural breaks classification technique, the thematic layer subclasses were also classed to assign weights. Based on their respective influence on groundwater development, the subclasses for each thematic layer rank were assigned a number between 0 and 9. For the consistency ratio (CR) calculation, the following steps were adopted:

  1. 1)

    Eigen vector technique was utilised for Principal Eigen value (ʎ) computation and

  2. 2)

    Consistency Index (CI) was computed using equation:

$${\text{CI }} = { }\frac{{{\uplambda }\max - {\text{ n}}}}{{{\text{n}} - 1}}$$
(3)

where, n depicts the number of factors utilised in the analysis.

Consistency Ratio is defined as

$${\text{CR}} = \frac{{{\text{CI}}}}{{{\text{RCI}}}}$$
(4)

where,

RCI = Random consistency Index value, the values were derived using the Saaty’s standard.

Saaty has surmised that the CR of 0.10 or less is acceptable for the analysis continuation. If the value of consistency ratio is greater than 0.10, then it is necessary to revise the judgment and to locate inconsistency causes and then correct it accordingly. If the value of CR is 0; it depicts perfect level of consistency in the pair-wise comparison. If the threshold value is not exceeding value of 0.1, it means the judgments matrix is consistent reasonably.

3.3.4 Weighted overlay analysis

All seven layers were included in the weighted overlay analysis. All of the layers were given weights based on how they behaved, and ranks were then determined by classifying and weighing each layer concerning how it affected the watershed area of the Kanari River to identify the best recharge zones. Utilizing the GIS, a combined groundwater potential zone map was created by integrating the numerous theme maps that describe suitable groundwater zones [34, 35]. One analytical method used to examine geographic phenomena' locations, geographical dimensions, and related characteristics is called spatial data analysis (polygon weight classification, table classification and analysis). Cell width was taken into account when converting all of the theme maps into raster format in order to achieve a high degree of realism. After that, they were classed and given the appropriate weight. A given research area is different based on differences in the occurrence and flow of groundwater in a region and the impact of significant factors. As a result, weights were assigned to each parameter according to how they affected the transportation and storage of groundwater. For instance, the lithological component has less influence over an area containing sedimentary rocks than topographical control. Therefore, the land cover layer, geology, and geomorphology were given greater weights.

Conversely, though, these themes were given less weight because the area's drainage density and slope had less of an impact. The ArcGIS 10.3 software's spatial analyst tool was used to transform all of the thematic layers into raster format after each theme and feature had its weights assigned. The ArcGIS 10.3 software's spatial analyst tool was used for the final analysis and raster conversion characteristics. Using this method, the weights allocated to the different layers according to their suitability were added together or multiplied to determine the overall weights of the final integrated map. After that, each theme's individual units were given a knowledge-based hierarchy ranking ranging from 1 to 3. Based on significance, a groundwater recharge zone with a score of 1 denotes poor prospects, while a score of 3 denotes outstanding possibilities.

3.3.5 Analytical hierarchy process

AHP was utilized for demarcating the potential groundwater recharge zones, and the whole procedure was suggested by [34,35,36,37,38]. In this method, the Analytical Hierarchical Process pair-wise matrix was refined using the input values of the parameter scale's weight based on numerous direct or indirect relationships. Pairwise comparisons, consistency matrix and classification of parameters for AHP are presented in Tables 2, 3 and 4.

Table 2 Pairwise comparisons matrix for AHP
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Table 3 Consistency matrix and computation of the principal eigen value (λmax)
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Table 4 Classification of parameters controlling the GWRZs in the Kanari River watershed
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3.3.6 Estimation of surplus water for artificial recharge and conservation for water security

Water can be artificially recharged by spreading or impounding it on the ground to increase soil infiltration, aquifer percolation, or water injection by wells straight into aquifers,any type of additional available water can be used to achieve artificial recharging. The results of the SWAT model of groundwater recharge and the aquifer storativity obtained from the assessment of the aquifer storage volume were used to calculate the excess water required to revitalize the Kanari River watershed on a volume basis [33].

3.4 Water harvesting structure sites selection for recharge zones

Combining remote sensing data with a GIS and theAHP analysis technique identified a suitable location for water-collecting structures by considering seven levels. Sites suitable for rainwater gathering were selected using a multi-criteria evaluation (MCE). The slope, land cover/use, drainage, and soil maps were created using satellite photos and DEM data. Eight land use classes and a hydrological soil group map were also created to choose a good location for water collection. The indicators for appropriate water harvesting sites were categorized into three comparable units based on suitability: good, moderate, and poor. In order to determine the volume of water storage in the proposed water harvesting structure, the water spread area, which was determined using GIS software, as well as the height of the structure and the streams that contribute water to a given structure, were taken into account. This allowed for the simultaneous recharge calculation based on the assumption that a given amount of water can be recharged if the storage volume is known.

3.5 Water budgeting of additional water supplied through recharge structures for ensuring water security

3.5.1 Estimation of water demand for domestic, livestock, and agriculture

The district statistics data book included demographic information. Water requirements for humans, animals, and crops were taken into account. Based on crop evapotranspiration (ETc) from the output of the SWAT model and district statistical data, the agriculture demand was computed for both the rabi and kharif seasons. The WHO estimates that each person needs 135 L of water per day for residential use. This was used to compute the total amount of water needed for household use. Overall methodology of the study is depicted in Fig. 3 and rainfall map is presented in Fig. 4.

Fig. 3
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Flowchart illustrating the precise approach used in the current study

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Fig. 4
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Map showing variation of rainfall in Kanari River Basin

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4 Results and discussion

4.1 Determination of fluctuation of depth to water level for the Kanari River watershed

Well-formatted data was supplied by the State data centre. Water level, well identification number nine, and well coordinates in UTM were tabulated individually for use in the GIS. With the use of satellite photos, well locations were confirmed. The UTM coordinate system aligned satellite photos, and vector point files were made from the well using inverse distance weighing method (Fig. 5).

Fig. 5
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Groundwater level fluctuation map

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4.2 Aquifer mapping and aquifer storage volume estimation

4.2.1 Aquifer mapping

The National Atlas on Aquifer Systems of India, created by the Central Ground Water Board and scaled to 1: 2,50,000, served as the foundation for the current aquifer mapping. The Kanari River watershed has four primary significant aquifers, which are shown in Fig. 6. Schist, and quartzite have found to be possessing good groundwater potential, while granite has medium groundwater potential. Therefore schist, and quartzite is preferred for recharge followed by granite aquifer [33, 39, 40].

Fig. 6
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Principal aquifer systems of the Kanari River watershed

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4.2.2 Aquifer storage volume estimation

The district resources of Madhya Pradesh used the findings of four pumping tests conducted in 2018 on open wells in the research area to evaluate the aquifer's properties. The aquifer's characteristics were assessed using the splitter method of pumping tests. Table 5 shows the distilled outcome of the pumping test.

Table 5 Summarised result of pumping tests
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4.3 Recharge zones identification at Kanari River watershed

The weighting of several criteria for potential groundwater recharge was determined in the current study, and the scores under various characteristics were evaluated based on the features of the study area. Land use, geology, and geomorphology were used in this study. The most significant variables influencing the possible recharge of groundwater are land cover, slope, soil, lineament density, and drainage density (Fig. 7). Geographic and hydrologic data were digitalized using the GIS technique, and a primary database was ultimately produced. For several parameters, appropriate scores were fixed. Lastly, the possible groundwater recharge zone of the Kanari River watershed was identified using the spatial analystfunction.

Fig. 7
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Different thematic layers for groundwater recharge mapping

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4.4 Groundwater recharge zoning

Creating a viable groundwater recharge potential zone map in raster format involved systematically examining AHP techniques on weighted parameters. The weight allocated to each parameter was divided by the geometric mean of the relevant stratum to produce the parameter's normalized weight. The Government of India has established guidelines for CGWB standards that state that surfaces with good permeability and deep soil depth and those with a moderate slope and aquifer connectivity linked to towns and agriculture are appropriate for groundwater recharging. For the groundwater recharge zone, the normalized weighted raster was reclassified into high, moderate, and poor categories based on the previously illustrated notion (Fig. 8).

Fig. 8
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Potential zone for groundwater recharge in the Kanari River watershed

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The resultant map of groundwater recharge was classified into three classes (good, moderate, and poor), depicting the suitable artificial recharge sites (Table 6).

Table 6 Resultant output showing the percentage of the zone-wise area of coverage
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4.5 Computation of surplus recharge possible at the site

Aquifer storativity from aquifer storage volume calculation previously described, along with the results of the SWAT model of groundwater recharge, were used to compute the surplus water required to revive the Kanari River watershed on a volume basis. Table 7 shows the excess water required.

Table 7 Computation of surplus recharge possible at the site
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4.6 Selection of water harvesting structure sites for recharge zones

A few artificial recharge techniques were applied in order to improve the average surface water flow into subterranean systems. Percolation tanks, farm ponds, concrete Nallah bunds, artificial flooding to trigger re-energizing techniques, and the development of other impounding and infiltration structures are examples of structures that have been successfully implemented around the world; however, this method of creating structures can also be used in the study area to increase the groundwater yielding capacity. In the Kanari River watershed, several methods of water conservation, such as terracing, contour trenching, Nulla bunding, etc., can also be recognized. These kinds of systems can be adopted, and various problems with inadequate precipitation and errant water supplies can be set up. Selecting appropriate places for the application of appropriate artificial recharge procedures is one of the critical conditions for successful recharge, and it is based on several criteria grouped in a GIS context. The aquifer’s unsaturated zone penetration capacity determines the topographical region's capacity to recharge itself. It also depends on the hydro-geomorphological and geographic boundaries that are close by, the terrain's slope, the land use or land cover such as the presence or development of vegetation, and the accessibility and thickness of the available drainage. Finally, recharge structures were suggested to be built in the Kanari River watershed. These structures, which include a check dam, farm pond, DSM (Dry Stone Masonary) pond, percolation tank, gully plugs, subsurface dykes, staggered trenches, and contour trenches, are presented in Fig. 9. These structures enhance the soil's specific yield and water level in this area. Table 8 shows the criteria for choosing a structure, which include subsurface dykes, contour trenches, staggered trenches, gully plugs, farm ponds, DSM ponds, and check dams.

Fig. 9
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Site suitability map for Kanari River Watershed

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Table 8 Criteria for selection of structures [41]
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4.7 Water storage and recharge through the proposed structure as per the water spread area, bed slope, and height of the structure

Table 9 shows the recharge through the water harvesting structures, which included farm ponds, check dams, DSM ponds, percolation tanks, gully plugs, subsurface dykes, staggered trenches, and contour trenches. The recharge was calculated based on the water spread area, bed slope, and structure height.

Table 9 Water storage in the proposed structure as per the water spread area, bed slope, and height of the structure
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The additional recharge through proposed structures was estimated as 554 MCM based on recharge through proposed structures and possible surplus recharge in the aquifers, which can be further utilized for domestic purposes, industrial use, agriculture purposes, and to compensate the over-drafting of the water and is presented in Table 10. Primary purpose of extensive pumping operations is agricultural use, making up about 60% of the overall water demand [42, 43]. Based on that the pumping overdraft of the Kanari River watershed has been determined to be 423 million cubic meters (MCM), and it is recommended that 859 MCM increase the recharge by implementing a planned conservation structure.

Table 10 Computation of additional recharge through proposed structures (MCM)
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The total water demand of the Kanari River watershed, calculated based on agriculture, livestock, and domestic use, is presented in Table 11.

Table 11 Water demand of Kanari River watershed
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Utilizing a combination of integrated maps including geology, slope, geomorphology, land use/cover, soil, drainage density, and lineament density data, we identified groundwater recharge zones and suitable locations for artificial recharge structures within the Kanari River system. This was accomplished through the use of hydrogeological data, GIS, and AHP based methodologies with MCDA. Additionally, we conducted estimations of domestic water demand, agricultural water use, pumping, and livestock water demand to facilitate water budgeting and calculate water availability. This approach provides a comprehensive understanding of the groundwater potential zone and the installation of recharge structures, which is crucial for achieving sustainable development in the region.

While we made every effort to develop a comprehensive database and utilized local data, there is still room for improvement in addressing the limitations of the data sources and methodologies. Regional planning that focuses on the development of local high spatial–temporal resolution datasets based on regional data will greatly benefit the planning and implementation of groundwater recharge projects and water resource planning [34, 35, 44, 45]. Furthermore, studying the potential impact of climate change on groundwater recharge and availability in the Kanari River basin, and how this may impact the suitability of the identified locations for artificial recharge structures, would be an interesting area of future research [46].

5 Conclusion

A pragmatic methodology was suggested in this study for implementing water harvesting structures for river revival and estimation of water demand, pumping, and recharge. The geometric mean and the normalized weight for individual features were specified using the AHP in a GIS environment. All the different features/datasets were overlaid, and possible groundwater zones were uncovered using AHP. Integrated maps were used to identify the groundwater recharge zone and locations for establishing artificial recharge structures within the Kanari River system. Ultimately, the domestic water demand, agriculture water use, pumping, and livestock water demand were estimated for water budgeting, and based on this data, the water availability was calculated. The aquifer storage volume was calculated based on area, thickness, and sp. Yield and was found to be 1901 MCM. The water harvesting structures, including check dam, farm pond, DSM pond, percolation tank, gully plugs, sub-surface dykes, staggered trenches, and contour trenches, were proposed, and the recharge through them was calculated based on water spread area, bed slope, and height of the structure. An estimated sum of 1002 MCM can be recharged through the proposed structures. The additional recharge through the proposed structures was estimated at 859 MCM. Estimating the demand for crops was performed and found to be 70533 ha m, while the domestic water demand was found to be 1641 ha m. Similarly, the livestock water demand was estimated as 595 ha m. The water demand of the Kanari River watershed was estimated as 7312 MCM. The pumping overdraft of the Kanari River watershed was calculated. It was found to be 423 MCM, and the proposed additional recharge through the planned conservation structure is 859 MCM, through which it can quickly be concluded that if over-drafting through pumping is also considered, then this additional recharge can fulfill the requirement and can maintain the flow in the river. It can be suggested to quantify groundwater recharge by using conservation structures. Water table data of piezometer should also be collected and analysed for assessing impact on lower aquifer which is becoming major source of pumping water for irrigation. Ground water could be used for predicting scenarios in future and planning effectively strategy.