Geographical Information System for Groundwater Potential Zoning in a Peninsular Region of Bihar

The groundwater is the primary source of water for domestic and irrigation purposes in the regions where the surface water is not available because of rapid growth in population and pollution. Population growth, improved living standards and economic growth are responsible for increased groundwater exploitation (Magesh et al., 2012, Arumugam et al., 2023). Packialakshmi and Ambujam (2017) found that informal marketing of groundwater by private water suppliers has lead to spatio-temporal changes in quantity and quality of groundwater. Increasing groundwater exploitation and decreasing rainfall has affected the groundwater recharge which is ultimately creating groundwater stress. Therefore, it is important to study the potential zones of groundwater for a sustainable future.
       
The delineation of groundwater can be achieved through the reliable standard methods of test drilling and stratigraphy analysis which however require plenty of time and cost. Multi Influencing Factor (MIF), Frequency Ratio (FR) and Multi Criteria Decision Analysis with Analytic Hierarchy Process (MCDA-AHP) are the popular cost effective techniques. These methods utilise Remote Sensing (RS) and Geographic Information System (GIS). RS and GIS are crucial for delivering data from inaccessible locations and for tracking interventions made in any area in real time (Gaur et al., 2020). The outcomes from MCDA-AHP has been slightly more accurate than the MIF and the FR techniques (Das and Pardeshi, 2018; Senapati and Das, 2022). The MCDA-AHP takes into consideration several factors viz. topography, geology, rainfall, lineament, drainage, land use land cover (LULC) etc. which influence the occurrence and quantity of groundwater in any region. The RS and GIS technique uses surface features prepared from the satellite imageries which act as indicators for GWP. Several researchers globally have succeeded in integrating different factors using RS and GIS techniques to delineate GWP zones (Avtar et al., 2010; Patra et al., 2018; Godif and Manjunatha, 2023). The selection of themes for delineation and assessment of GWP varies from study-to-study and region-to-region (Chowdhury et al., 2009). All factors do not influence the occurrence of groundwater with same intensity and therefore, it is necessary prioritise the factors using a decision-making tool. The AHP is an effective decision making tool in situations involving multiple criteria (Saaty, 1980). Therefore, several researchers have successfully utilized the MCDA-AHP in their studies related to groundwater as well as in other fields like agriculture (Patra et al., 2018; Ghute and Babar, 2020; Sonia et al., 2023; Tiruneh et al., 2024).
       
The groundwater is generally available at shallower depths in the study area. The entire population and agriculture there are dependent on groundwater. The groundwater levels and rainfall in the study area have been decreasing for the last two decades and the problem becomes noticeable particularly in dry seasons (Choudhary and Singh, 2024). It is a notable fact that the depth to groundwater levels in the South Bihar plains region of Bhagalpur closer to the study area, has been the maximum (CGWB, 2023).
       
The topography, surface and sub-surface features, soil and rainfall deeply influence the groundwater in the study area. Thus, it is very important to consider the factors associated with these. Those factors are - geomorphology, lithology, lineament, drainage, soil texture, rainfall, slope, LULC and fluctuations in groundwater level at different locations. The combination of these nine factors is unique in nature and has not been considered together in earlier studies. Further, limited studies have been carried out in general for GWP using the RS and GIS methods in Bihar and particularly in the study area. Therefore, the main objective of this study is to consider the above mentioned themes for mapping of the GWP in the study area using RS and GIS.

Study area
 
The study area (Fig 1) lies between 86°35'E-87°15'E longitude and 25°16'N-25°33'N latitude covering an area of 1157 km². It includes the parts of the bhagalpur and khagaria districts of Bihar (India). It is a peninsular area formed by four rivers- the Budhi Gandak, the Ganga, the Kosi and the Baghmati bounding the study area completely from the south, the east and the north directions and partly in the west direction. A natural drainage channel is present in the remaining west side. The surface elevation ranges 10 to 56 metres above mean sea level. It has hot and humid climate with maximum and minimum temperature of 41°C and 12°C, respectively. It receives on an average 1300-1400 mm annual rainfall. Over 80% of the annual rainfall is received during the monsoon season. Agriculture is the main occupation with around 75% land being used for this. The water for all purposes are primarily extracted from groundwater bore wells (Choudhary and Singh, 2024).
 

 
Data for thematic maps
 
The satellite data for geomorphology (1:250000 scale) and lithology were obtained from Geological Survey of India, Kolkata to prepare their thematic maps. The SRTM 30m × 30m resolution DEM data were used to generate lineament density, drainage density and slope maps. The rainfall map was prepared using the 0.25°×0.25° resolution gridded daily rainfall data (Pai et al., 2014) collected for the period 1996-2020 from the India Meteorological Department, Pune. The LULC map was generated using the Sentinel-2 10 m LULC world map produced by Impact Observatory, Microsoft and Esri for the year 2020. The soil texture map was extracted from the digital soil map of the world published by the food and agriculture organization, rome. The groundwater level (GWL) data were obtained from the Central Ground Water Board (CGWB). All themes were projected to WGS 1984 UTM Zone 45N coordinate system and resample to 10 m × 10 m cell size using ArcMap 10.4.
 
Assignment of weights
 
The themes were compared pair-wise in a matrix using the MCDA of the AHP technique (Saaty 1987) on a scale of 1 to 9 suggested by Saaty (1980). Thereafter, the normalized weights to each theme were computed. The consistency ratio (Saaty (1980)) of the normalized weights of the matrix of order n is checked using the equation (1):
 

Where,
R.I. depends upon the order of the matrix. In this case of 9×9 matrix, n=9 and R.I.= 1.45 (Saaty, 1980).
The C.I. is calculated using the equation (2):                                                                                                                                                                                                                  
Where,
λmax= Largest eigen value of the matrix.
       
Saaty (1980) suggested that C.R. value less than or equal to 0.10 is positive evidence for a good judgement.

Geomorphology (Gy)
 
The study area has five classes of geomorphologic features namely active flood plain, river, older flood plain, pond and younger alluvial plain as shown in Fig 2(a). The active flood plain and younger alluvial plain are spread over 99% of the study area with other three features, which are less than 1% combined. The presence of these features is suitable for availability of groundwater. The plains are generally alluvial deposits from the Ganga-Kosi plains.
 

 
Lithology (Ly)
 
Lithology influences permeability and porosity of aquifers which affect the occurrence as well as distribution of groundwater. The study area has newer alluvium of the Holocene and the late Holocene age as shown in Fig 2(b). The Kosi-Ganga formation is spread across 59% of the study area, followed by the formation from the present-day deposits in 38% and the Purnea formation in the remaining 3% area.
 
Lineament density (LD)
 
Lineaments represent the natural linear features, fractures, faults and joints through which water can percolate. Higher lineament density represents higher potential of groundwater in any area and vice-versa. The lineament density is presented in five different classes as shown in Fig 2(c). The distribution of lineament density is found to be good in the eastern as well as well central parts of the study area.
 
Drainage density (DD)
 
Drainage pattern of an area reflects its surface and sub-surface characteristics. The better is the drainage, the more is the runoff and the lesser is the infiltration in an area. Thus, drainage has a vital role in groundwater potential of an area. Similarly, a lesser drained area will have more infiltration and thus are more suitable for development of groundwater. The drainage density in the study area was classified in five groups as shown in Fig 2(d). The drainage density in the western part is comparatively more in comparison to the remaining parts of the study area.
 
Soil texture (ST)
 
The infiltration of water into the ground depends upon the soil texture. It has a vital role in groundwater recharge. The study area has following types of loam textured soil- type 1 (40% sand, 36% silt, 24% clay), type 2 (40% sand, 40% silt, 20% clay), type 3 (38% sand, 44% silt, 18% clay) and type 4 (44% sand, 35% silt, 21% clay). Soils with higher sand content have lower water holding capacity, which is favourable for occurrence of groundwater. The soil texture map is shown in Fig 2(e).
 
Rainfall (Rf)
 
The groundwater gets recharged primarily from the rainfall. Overall, the study area receives a good amount of annual rainfall. The spatial distribution of the average annual rainfall for the period 1996-2020 is presented in Fig 2(f) with five classes of rainfall. It can be noted that the western part receives relatively lesser rainfall as compared to other parts in the study area.
 
Slope (Sl)
 
Slope controls the infiltration rate. The surface runoff is slower in a gentle slope where as it is faster in steeper slope. The slow rate of flow allows more time to water to percolate into the ground. The gentle slope is favourable for groundwater recharge and it’s potential. The slopes have been categorized in five different classes with 97% area having gentle slope in the range 0-3.6% as shown in Fig 2(g). Therefore, slopes in the study area are quite favourable for infiltration and thus for GWP.
 
LULC
 
Land uses of different types have different effects on runoff and infiltration which in turn have crucial roles in groundwater potential. Water bodies, vegetation, forests etc. increase infiltration whereas built up areas, bare grounds etc. facilitate runoff. 75% of the study area is used for agricultural purposes, 10% is built-up area and the remaining 15% includes water bodies, trees, flooded vegetation, bare ground and range land as shown in Fig 2(h).
 
Groundwater level fluctuation (GWLF)
 
The GWLF map is shown in Fig 2(i). The average fluctuations ranged between 1.907 to 3.705 m. The increase in fluctuation values indicates increase in outflow of groundwater, whereas the decrease in fluctuation values indicates decrease in outflow of groundwater. From the Fig 2(i), it can be said that the outflow of groundwater is more in the eastern side as compared to the rest of the study area. The more outflow of groundwater can be seen as an indication of its more availability.
 
Groundwater Potential Zoning
 
The thematic maps-geomorphology, lithology, lineament density, drainage density, soil texture, rainfall, slope, LULC and GWLF were compared pair-wise in a matrix using the MCDA-AHP technique as shown in Table 1. The normalized weights for each theme were estimated and consistency ratio was computed and checked.
 

       
Appropriate ranks were assigned to the individual features of each theme based on their relative influence on groundwater occurrence. The features are shown as legends in Fig 2(a) to 2(i). All the themes were overlaid in ArcMap 10.4 with the ranks of their individual features to produce the GWP zone map.
       
The map produced from weighted overlay presented the GWP zones on a scale of 1 to 4 with lower to higher values representing low, moderate, high and very high potential zones as shown in Fig 3. 0.5 km2 (0.004%), 497.2 km² (44.04%), 622.5 km² (55.14%) and 9.3 km² (0.82%) of the study area have low, moderate, high and very high GWP zones, respectively. Fig 3 shows that the study area has predominantly moderate to high GWP zones. The moderate GWP zones are mainly spread across the western parts whereas the eastern parts have majority of the high GWP zones. The extremely small patches of low potential zones (magnified view 1 and 2 in Fig 3) lie entirely in the western part of the study area, whereas pockets of very high potential zones fall entirely in the eastern part of the study area.
 

 
Validation
 
The GWP zones obtained from integrating thematic layers were validated using the pre- and post-monsoon GWL data of the CGWB Hydrograph Network Stations (HNS) (Fig 3). The spatial variations in GWLs of pre- and post-monsoon seasons for the years 2000, 2005, 2010, 2015 and 2020 are shown in Fig 4(a) and 4(b), respectively through depth to GWL maps prepared in GIS environment.
 

       
The depth to GWLs are related to the topography under natural conditions (Avtar et al., 2010). The HNS in the east and west sides are at lower and higher elevations, respectively. It can be observed from Fig 4(a) that the depth to GWLs in the eastern parts were in the range of 4-6 m and 5-7 m bgl in 2000 and 2005, respectively and 6-7 m from 2010 to 2020. Further, it can be noticed from Fig 4(b) that the depths to GWL were in the ranges 2-4, 1-3, 3-5, 2-4 and 3-5 m in the years 2000, 2005, 2010, 2015 and 2020, respectively. Comparing these two figures, it can be noticed that the GWLs in the post-monsoon showed good recovery due to recharge except in the year 2010. Similarly, on comparing the central part, it can be observed that the GWLs have attained very good recharge in the post-monsoon season except in the year 2010. Further, by comparing GWLs in the west part, it was found that the recharge is lesser as compared to the other parts. The rainfall in the eastern parts is more than the western parts, which is reflected in the GWLs of the post-monsoon season. In the year 2010, the rainfall was lowest during the period 1996-2020, which is reflected in the depth to GWLs of the post-monsoon season in 2010 as shown in Fig 4(b). Saranya and Saravanan (2020) obtained similar results in Tamilnadu, India. From this discussion, it can be concluded that the eastern part has high GWP whereas the western part has comparatively moderate GWP. Thus, Fig 3 is closely representing the GWP zones in the study area.

The RS and GIS are powerful tools for GWP mapping in regions with poor data accessibility like this peninsular study area in Bihar, India. The themes selected for this study together had a great influence on the occurrence of groundwater in the study area. The geomorphology, lithology and soil texture of the study area are very favourable for groundwater occurrence. The lower lineament and higher drainage densities, higher slopes and lesser rainfall hamper the recharge in the west part whereas higher lineament and lower drainage densities, lower slopes and higher rainfall favour the recharge in areas located in the central and east parts of the study area. Further, the presence of trees near the built-up areas, mostly in the central part hampers the runoff. This is evident from the GWP zone map which shows the zones of high potential in the east part of the study area even after higher fluctuations in GWLs. The low and very high potential zones are spread in only 1% area whereas 55% areas have high and 44 % areas have moderate GWP. This suggests that there should be controlled extraction of groundwater in the areas with moderate GWP. It is worth mentioning that the study area is in developing phase and is continuously growing in terms of population, economy and living standards, which are the major reasons behind the increase in water demand. Therefore, the findings of this research would provide a base to the decision makers while planning for future groundwater development.

Authors declare no conflict of interest.