Assessment of groundwater at Kurukshetra district

Water plays a crucial role in the human life cycle for livelihood and sustainable development. Water, being one of the most essential resources for mankind, is used for various needs like irrigation, drinking, industrial, domestic, recreation, drinking, and navigation. A total quantity of 1386 M km³ comprising about 75% of the earth's surface area is enclosed by water cover (Kaushik et al. 2004). Of these, oceans comprise 97.5% of total water, which is not suitable for consumption or utilization and 2.5% of fresh water is available for fulfilling mankind's needs and demands out of which 24.4 M km³ lies in the polar region in the form of ice caps and about 10.6 M km³ is in the form of freshwater sources such as groundwater and surface water, i.e. streams, lakes, reservoirs, and rivers (Raheja et al. 2022). Due to the increase in water demand for domestic, irrigation, and industrial needs, the surface water resources are not sufficient. So, an alternative resource like groundwater is required. Groundwater is a vulnerable natural resource, an indispensable and vital resource (Akinrinade & Adesina 2016). About 43% of global groundwater resource is utilized for agriculture irrigation (Siebert et al. 2010; Zhang et al. 2022). It is available as a freshwater resource in terms of good quality and quantity and, mostly in the season of drought, groundwater is preferred for agriculture purposes (Lee et al. 2020). Due to overexploitation of this vital resource, over the past few decades in semi-arid regions the groundwater is depleting drastically and the groundwater level trend is decreasing at alarming levels (Surinaidu et al. 2021). The Ground Water Quality Index (GWQI) from the year 2006 to 2015 in the southwest region of Surat city was determined by Chaudhari et al. (2021). The GWQI is indicated in terms of index number, which shows a representation of quality of water in water quality management (Mehta et al. 2018). In agricultural, arid, semi-arid, and basaltic regions, the advanced DRASTIC model performs better than the classical DRASTIC model (Patel et al. 2022). Chaudhari et al. (2022) studied the intrusion of seawater in the groundwater in the southwest region of Surat city.

For sustainable management of this resource a proper quantification and its declining trend is to be estimated.

Many researchers have identified potential zones in various methods in the form of field-based studies such as test drilling, stratigraphy analysis, electrical resistivity method, Vertical Electrical Sounding technique (VES) which is time, energy-consuming, quite expensive, and tedious work (Jamal & Singh 2020; Gaikwad et al. 2021), and remote sensing techniques (ArulBalaji et al. 2019; Achu et al. 2020; Rajasekhar et al. 2020; Sarwar et al. 2021). Remote sensing (RS) and Geographic Information System (GIS) are effective tools for the delineation of groundwater potential zones. Remote sensing has various advantages concerning spectral and spatial data covering inaccessible areas of a region within a short time for mapping vital groundwater resources (Jha et al. 2007; Das et al. 2019). Some authors also used artificial intelligence techniques for finding prospective areas of groundwater (Shao et al. 2020; Kumar et al. 2021). However, the identification of groundwater resources is based on several factors such as lineament density, land use and land cover, drainage density, rainfall, soil texture, and many demographic features of the region (Senthilkumar et al. 2019). Due to the easy availability of data, many researchers preferred AHP (Analytical Hierarchy Process) in giving weightages to the influencing parameters in finding the GWPZ of the study area (Kaliraj et al. 2014). However, in the present study, the AHP technique is used as an effective method that provides comprehensive information on groundwater potential zone identification through ArcGIS software. Further, the estimation of groundwater is calculated using GEC 2015 (http://cgwb.gov.in/Documents/GEC2015_Report_Final%2030.10.2017.pdf) methodology which is the latest methodology provided by the Central Ground Water Board for estimation (Tiwari et al. 2021). Few researchers quantified groundwater using the water table fluctuation method (Healy & Cook 2002; Joshi et al. 2021) approach by isotopes method (Joshi et al. 2018; Semwal et al. 2020), empirical relations techniques (Kumar 1997; Board 2011), and by water budget method (Maréchal et al. 2006). The assessment of recharge from canals, irrigation return flow, and surface water structures in the Bundelkhand region has been done with the help of the Water Table Fluctuation approach and GEC-97 norms by Joshi et al. (2021).

In the present study, initially, GWPZ was identified by considering eight influencing factors such as drainage density, slope, lineament density, land use, and land cover (LULC), soil, rainfall, geology, and geomorphology and for these parameters, eight thematic maps were developed using an overlaying technique in ArcGIS software and a GWPZ map was generated by giving weightages to the influencing factors. Further, the data was validated using groundwater levels. Later the quantification of groundwater present beneath the study area surface was estimated using the Ground Water resource Estimation Committee GEC 2015 methodology formulated by the central groundwater resource board (CGWB). At the end the total groundwater draft, total groundwater recharge was quantified. The outcomes of the article could further be used for the successful management of groundwater resources in the Kurukshetra district.

The thematic map which is generated after using the overlaying technique is to be validated for accuracy and sustainable management of resources. Validation of GWPZ was carried out by Rajasekhar et al. (2022) and Saranya & Saravanan (2022) using CGWB groundwater depth levels and Kumar & Krishna (2018) and Kumar et al. (2022) by using well yield data.

From the above equations, in Table 1 net recharge (R_Total) is estimated for the Kurukshetra district.

The eastern part of the district lies within the Upper Yamuna Basin and the western part lies within the Ghaggar Basin. Major drainage occurs in the area via the Markanda River. One of the main concerns in the study domain is groundwater depletion. Due to the seasonal changes and global changes occurring in the climate, the dependence on canal water was decreased by the farmers. As a result, to overcome the water scarcity farmers and people in the study area shifted towards groundwater irrigation. As per the statistics of the census, the population growth is increasing in a tremendous way. Consequently, to meet daily needs and requirements, people in this region are depending on groundwater. People living there have the solitary resource of drinking and domestic water from the ground. Hence, this area is therefore chosen to investigate the groundwater potential zone identification and its computation for sustainable management.

The datasets used in the study for the eight parameters were taken from satellite data and field data. Drainage density, slope, and lineament density thematic maps were developed from the SRTM satellite – digital elevation model data. A LULC thematic map was created from Landsat-8 data. A soil thematic map was developed by the national bureau of soil sciences and land use planning soil data. The rainfall thematic map was generated from IMD (Indian Metrological Department) data. The geology and geomorphology thematic map was prepared from the NRSC Bhuvan data. Initially, the data was downloaded from the respective satellite and after preprocessing the data in ArcGIS software, thematic maps of each influencing parameter were generated.

The dataset for the groundwater estimation was taken from 10 various departments. The crop area of rabi and Kharif were acquired from the agriculture department, Kurukshetra. The canals that are flowing through the study area and the design details were taken from the Irrigation department, Jyotisar, Kurukshetra. Groundwater level data for the period (April 2020–March 2021) was collected from the groundwater cell, Kurukshetra division. The population data was taken from the Census of India. Rainfall data was collected from the IMD website (https://hydro.imd.gov.in/hydrometweb/(S(olotdb55oe2tw53r4tk0la55))/DistrictRaifall.aspx). The data for tanks, ponds and water conservation structures were collected from the NAQUIM report of the Kurukshetra district provided by the Central Groundwater Board (http://cgwb.gov.in/District_Profile/Haryana/Kurukshetra.pdf).

The GWPZ map results were classified into four categories (a) Very low, (b) Low, (c) Moderate, and (d) High. The zones were presented with four different colors as represented in Figure 5. The above result represents that the major part of the Kurukshetra district lies in the moderate potential zone (Shahabad region), low potential zone (Ladwa region, Pehowa region), and the southern part of the study area lies in the high potential zone nearby Kurukshetra region.

The GWPZ map was validated by using groundwater level data at four different places in the Kurukshetra district which is provided by CGWB groundwater levels (https://docs.google.com/spreadsheets/d/1eK5P_WBBwN_xVH4lQbyiKWXmJcIzodIk/edit?usp=sharing&ouid=105658342196071492814&rtpof=true&sd=true). The groundwater level at Shahabad region is 41.4 m bgl (moderate potential zone), Ladwa region is 44.24 m bgl and Pehowa region is 44.9 m bgl (low potential zone), Kurukshetra region is 33.22 m bgl (high potential zone).

Table 3 provides the results of 18 canals which are lined canals that are flowing in the Kurukshetra district.

The results from Table 3 are calculated using Equation (1). The results from Table 3 represent that 468.91 ha-m of groundwater is recharged into the ground through seepage action. The seepage factor for the lined canals in normal soil is 3.5 obtained from Annexure 1 of the GEC 2015 methodology.

The mean (μ) of the above-mentioned data in Table 3 was 26.05 ha-m, the standard deviation (σ) was 43.81 ha-m and the coefficient of variation (C_v) was 0.59.

Table 4 presents the irrigation water released to the fields by surface water sources. RFF is calculated using Equation (9) for both paddy and non-paddy fields. The return flow factor for paddy is 0.25 and for non-paddy is 0.1 and was extracted from Annexure 2 of the GEC 2015 methodology. In the present study, the crops data was taken from the Agriculture Department, Kurukshetra.

As per agriculture data (Agriculture Plan: April 2020–March 2021), the monsoon crops are rice, sugar cane, maize and non-monsoon crops are wheat, mustard, and sunflower, cultivated in the Kurukshetra district. The crops cultivated using surface water sources were rice (22,422 ha), sugar cane (2,089 ha), maize (12.96 ha), wheat (2030.58 ha), mustard (559.98 ha), and sunflower (1164.96 ha).

From the data mentioned in Table 4, agriculture data of crops; using Equation (8) the weighted average RFF is calculated as 0.237 for the monsoon season and 0.1 for the non-monsoon season. The results of recharge by applied surface water irrigation are estimated using Equation (2) as 3758.72 ha-m in monsoon season and 796.12 ha-m in non-monsoon season. A total annual recharge by canals seepage action at Kurukshetra district is estimated as 4554.14 ha-m occurring during the assessment period. The mean (μ) of the above-mentioned data in Table 4 was 1323.37 ha-m, the standard deviation (σ) was 2598.71 ha-m and the coefficient of variation (C_v) was 0.59.

From the agriculture data; the crops cultivated using groundwater resources were rice (102,150 ha), sugar cane (9518 ha), maize (59.04 ha), wheat (109,250.42 ha), mustard (2551.02 ha), and sunflower (5307.04 ha). The weighted average RFF is calculated using Equation (9) as 0.19 for the monsoon season and 0.05 for the non-monsoon season. Table 5 shows that the total irrigation draft using groundwater sources was 139,094.72 ha-m in monsoon(M) and 63,236.08 ha-m in non-monsoon (NM).

From the data mentioned in Table (5) and agriculture data; using Equation (3) the recharge by applied groundwater irrigation is 29,428 ha-m in monsoon and 3161.80 ha-m in non-monsoon season. Therefore, a total annual recharge of 29,589.80 ha-m is occurring in the study area by applied groundwater irrigation. The recharge by applied groundwater irrigation in monsoon and non-monsoon season shows a mean recharge (μ) of 14,749.4 ha-m, standard deviation (σ) of 16,459.69 ha-m and coefficient of variation (C_v) as 0.89. It represents that the variation in uncertainty for groundwater recharge during monsoon and non-monsoon seasons is more as it is based on the cultivated area which changes from crop to crop.

The data of recharge from tanks, ponds, and water conservation structures were taken from the Kurukshetra groundwater information booklet, CGWB (http://cgwb.gov.in/District_Profile/Haryana/Kurukshetra.pdf). A total recharge of 79.72416 ha-m is occurring in the study area).

Based on the rainfall data for the past five years (2016–2020) the annual normal rainfall is calculated as 784 mm, normal monsoon rainfall as 543.9 mm, normal non-monsoon rainfall as 240.1 mm, maximum threshold rainfall as 289.5 mm, and minimum threshold rainfall as 0 mm. (https://hydro.imd.gov.in/hydrometweb/(S(olotdb55oe2tw53r4tk0la55))/DistrictRaifall.aspx). The rainfall infiltration factor is considered as 22% from Annexure-IV of the GEC 2015 methodology, as the study area has a principal aquifer in the older alluvium of Quaternary age. Using Equation (5), the groundwater recharge by rainfall is estimated as 19,488.25 ha-m.

Evapotranspiration is a cumulative effect of evaporation and transpiration. As per GEC 2015 methodology, if water levels are shallow, that is groundwater levels <3 feet (0.9 m), then the evapotranspiration effect on groundwater recharge can be neglected as mentioned in Equation (6).

Table 1 represents the parameters that are considered in the assessment of groundwater estimation such as canals, surface water irrigation, groundwater irrigation, water conservation structures, rainfall, and evapotranspiration. From the statistical data, an uncertainty was observed in terms of coefficient of variation (Cv) for recharge by canals, recharge by surface water irrigation and groundwater irrigation as 0.59, 0.51 and 0.89. The summary of total groundwater estimation computation results at the Kurukshetra district is mentioned in Table 6.

From Table 6, it is shown that about 0.16284361 million ha-m of net groundwater was depleted in the Kurukshetra district during the assessment period (April 2020–March 2021).

The present research work mainly aims at the exploration of groundwater potential zones and the computation of net groundwater recharge occurring in the study area. From the results, the following conclusions were made:

• 1.

  Remote sensing data can be acquired for a remote location in an efficient and effective way. It decreases the cost, work force and time.

• 2.

  In the Kurukshetra district, a groundwater potential map was created and categorized into four different zones: extremely low, low, moderate, and high.

• 3.

  From the groundwater potential zone resultant map (GWPZ) (Figure 5), the southern region of the Kurukshetra district was observed to have a high potential for groundwater, while most of the district is in the moderate potential zone.

• 4.

  From Table 6 results of net groundwater recharge, it was estimated that 93% of groundwater is utilized for irrigation facilities, 6% is used to meet the industrial demand and 1% is utilized to meet the domestic demands of the region.

• 5.

  The net groundwater recharge shows that the groundwater in the study area is depleted by about 0.16284361 million ha-m.

• 6.

  From the statistics on groundwater, it is necessary to construct artificial recharge structures.

• 7.

  The research can be further extended for augmented studies of moderate and poor potential zones.

• 8.

  Strict regulations are to be implemented in the agriculture sector to reduce the groundwater draft and initiation has to be taken for the change of cropping pattern.

• 9.

  The research can further be extended towards groundwater modeling techniques and the construction of water conservation structures in critical zones.

• 10.

  The results help government agencies and global engineers in predicting the future condition of the groundwater in the Kurukshetra district.

There are various limitations of the present study including comparatively lesser size, range of the datasets, and deficient parameters like chemical characterization and water mobility that have been gathered by various sources. Therefore, future research could extend these findings by using more parameters and relatively more datasets to examine if better estimation can be obtained for arriving at more concrete conclusions. Besides, the present results may also be compared with other methodologies like the DRASTIC model.

The first author (Gandikota Rakesh) is thankful to MHRD, the Government of India (GOI) for the MTech scholarship grant (2K20/NITK/MTECH/32012504), the irrigation department of the Kurukshetra district for providing the data and to the website (https://kurukshetra.gov.in) in making the data available for research work.

Data cannot be made publicly available; readers should contact the corresponding author for details.

The authors declare there is no conflict.