Ensuring water security by reviving selected springs in Kangra region, Himachal Himalaya, India

ABSTRACT

In the Himalaya, availability of fresh water is a need of mankind, but due to numerous unsustainable developments, hill peoplesare witnessing scarcity of potable water. Hence, there is an imperative need for continuous monitoring of different water sources of Himalaya along with sustainable groundwater management practices in the highlands. The present study is based on extensive field visits investigating natural and other anthropogenic influences on mountain springs, locally known as “boweris”. In the undertaken study, eleven boweris were identified in the Salol region of Kangra, out of which two were exclusively selected as representative boweris, for their detailed studies and revival during the year 2021–2022. The physio-chemical characteristics (pH, TDS, and Electrical Conductivity) of the collected water samples from the boweris and hand pumps were found to be within the acceptable limits as prescribed by Bureau of Indian standards. The correlation between the pairs of TDS-EC depicted a strong positive relationship in both post-monsoon and pre-monsoon seasons and was found to be 0.94 and 0.99, respectively. Results of the t-test show a statistically significant difference in the mean concentrations of TDS (p = 0.02) and EC (p = 0.01) compared to pH (p = 0.39) with no significant difference at 5% significance level during both the seasons in the studied area. It was evident from the field investigations that the recharge structures constructed are facilitating the local boweris in maintaining the water level during the dry seasons. In the Bhatlahru region, the water level in the boweris rose from 127 to 159 cm, whereas in the Salol region, a rise from 119 to 142 cm was observed. The obtained results support the effectiveness and suitability of the proposed structures for the sustainable water resource management in the lower Himalaya. However, regular and long-term hydrological monitoring of the existing groundwater sources of the Himalaya is required for a better understanding of groundwater dynamics.

KEYWORDS:

• Mountain Springs
• climate variability
• spring rejuvenation
• remote sensing
• sustainable development

Background

An old saying “Water is life” is almost heard by everyone, which itself demonstrates the significance of water in the existence of living beings. Water can be found as surface water in streams, swamps, marshes, rivers and lakes, or as groundwater in dug wells, hand pumps, and springs. Everyone has the right to consume healthy fresh water, but due to rising pollution levels in the surface water its accessibility is becoming restricted (Bhawan, 2005; Sharma et al., 2020; Walker, Baumgartner, Gerba, & Fitzsimmons, 2019). Groundwater, on the other hand, is considered as an excellent source of fresh water (Carrard, Foster, & Willetts, 2019) after glaciers, and springs in high lands serve as an active source of drinking water for hill communities. However, due to increased human interference and pollution, these sources are rapidly deteriorating, causing a concerning decline in water recharge quantity over time, eventually leading to their extinction (Agarwal, Bhatnaga, Nema, & Agrawal, 2012; Boretti & Rosa, 2019; Liyanage & Yamada, 2017; Negi & Joshi, 2002; Valdiya & Bartarya, 1991).Various initiatives in the form of “Springhed development and rejuvenation” are being undertaken by the Indian government, non-government organizations (NGOs), and other institutions to conserve and sustain these sources of fresh water (Aayog, 2017; Kulkarni, Desai, & Siddique, 2021; Tambe et al., 2012; Tambe, Arrawatia, Kumar, Bharti, & Shrestha, 2009) in the Himalayan high hills. These sustainable sources of fresh water are currently under significant stress as a result of change in the land use land cover (LULC) dynamics, livelihood development, urbanization, increased population expansion, and a lack of public awareness. Additionally, the variables affecting groundwater recharge are also significantly impacted by climatic variability like accelerated or unreliable monsoonal pattern or due to poor quality of surface water (Kumar, Rathod, & Mukherji, 2023; Pandit, 2021; Tarafdar & Dutta, 2023; Vaidya et al., 2014).

Mountain springs are one of the most active fresh drinking water sources for both urban and rural hill communities along the Himalaya. In 2017, Department of Environment, Science and Technology, Himachal Pradesh Government (H.P. Govt.) stated that in Himachal Pradesh more than 60% of the villages depend directly on rain and spring water for their household and irrigation purposes (Ansari, Deodhar, & Kumar, 2019; Thakur, Rishi, Keesari, & Sharma, 2020). In some areas, on the slopes of hills, manmade structures locally called “boweris” are constructed to tap the fresh water seepages in order to be used as a source of water supply. The water supply system becomes defunct in isolated regions of the Himalaya when springs and streams dry up during the lean season, i.e. during the summers. This is a major cause for water scarcity in the rural as well as in the urban areas of Himalaya, which is forcing people to switch over to piped or deep bore well supply of water. Springs, streams, deep bore wells and hand pumps during the monsoon season may yield water, but their reliability during the drier months is uncertain. The region comprises different rock types and experiences distinct seasonal precipitation variations, with summers being dry and winters accompanied by light or no precipitation. This seasonal fluctuation can exacerbate water scarcity issues in the region in near future. As the region is undergoing continuous development, the indiscriminate drilling for groundwater may lead to the depletion of water available in the aquifers and may render their unsuitability for domestic use. To assess potential groundwater recharge zones, numerous research endeavors have utilized a combination of remote sensing, GIS, and the Analytical Hierarchy Process (AHP) technique (Arunbose, Srinivas, Rajkumar, Nair, & Kaliraj, 2021; Das & Pal, 2019; Mukherjee & Singh, 2020; Murmu, Kumar, Lal, Sonker, & Singh, 2019; Nithya, Srinivas, Magesh, & Kaliraj, 2019; Priya et al., 2022). This worldwide technique is essential for the sustainable management of water resources to delineate suitable groundwater recharge sites (Ifediegwu, 2022). The present study is aimed to gain a better understanding of the relationship between spring water yields, water quality, and recharge area characteristics, which is a vital framework for long-term water conservation measures in the hilly region of Himalaya where people mostly rely on spring water for their fresh water needs.

To ensure water security in the region, the objectives of the present study were accomplished in two stages via GIS to identify the groundwater potential zones (GWPZs) integrated with springshed approach in the Salol region of district Kangra, Himachal Pradesh, India. The first was a preliminary investigation that comprised identification of spring type, the aquifer, the recharge points, and the seasonal variations in the physico-chemical characteristics of spring water, whereas the hydrological and socio-economic effects of spring resurrection were the subject of the second phase. This preliminary study can prove to be a good step toward sustainable water resource management in the hill states of Himalaya.

Material and methods

Study area

Kangra district is the largest (5,739 km²) and one of the most developed regions of Himachal Pradesh with the highest population of about 15,10,075 according to 2011 population census (https://hpkangra.nic.in/demography/). However, these population figures can change due to demographic shifts over time, which can result in an ever increasing demand for fresh water.

The region has many perennial springs having a fresh source of water but due to sheer negligence and unsustainable approach this source of drinking water is losing its charm. The present study was carried out on springs of Salol region, district Kangra, Himachal Pradesh. There is an old phrase “A little goes a long way,” keeping this in mind we carried out our study on spring rejuvenation in a small village named Bhatlahru, which falls within 32°5’28.18“N latitude and 76°12’43.30“E longitude in the Salol region of Kangra district (Figure 1). Bhatlahru region has a total population of 205 with 36 houses. Further during the field visits and local survey it was also found that agriculture is the main occupation of the people of this region, whereas rain water and seasonal surface flow are the only sources of water available for irrigational purpose.

Figure 1. Identified springs in the study area.

Due to scarce rainfall during the summers dug wells and hand pumps run dry during the summer months in the area; springs or boweris then play an important role by meeting the drinking water demands. However, changes in the land use pattern and erratic behavior of rainfall in the region have impacted the flow of these springs, resulting in low discharge rates.

Preliminary study

Extensive mapping of the springs

To identify springs in and around Salol region different approaches and parameters were used. Extensive field visits were undertaken and based on the survey, 11 springs (listed in Table 1) were identified of which, 2 springs were selected for their revival based on the necessity of the villagers. All the identified springs of Salol region represented a variety of geo-physical setups, as well as anthropogenic influences in the catchment area.

Table 1. Identified springs in the Salol region, district Kangra, Himachal Pradesh.

Sl.No.	Name	Sampling Sites	Latitude	Longitude	Geology	Land Use Land Cover	Elevation (masl)	Type of Spring
	Nandrul	S1	32° 5’25.28“N	76°14’36.60“E	Boulder Conglomerate	Grazing land/Bushes/Barren Land	696	Contact Spring
	Nandrul	S2	32° 4’54.26“N	76°14’2.37“E	Boulder, gravel, sand and silt (Alluvium)	Pine forest	619	Seepage Spring
	Madha	S3	32° 4’52.49“N	76°13’34.55“E	Boulder, gravel, sand and silt (Alluvium)	Agricultural Land	636	Seepage Spring
	Madha	S4	32° 4’57.97“N	76°13’30.63“E	Boulder, gravel, sand and silt (Alluvium)	Grassland	617	Seepage Spring
	Rajal	S5	32° 5’58.09“N	76°12’54.72“E	Boulder, gravel, sand and silt (Alluvium)	Cultivated Land	691	Seepage Spring
	Rajal	S6	32° 5’52.12“N	76°12’56.30“E	Boulder, gravel, sand and silt (Alluvium)	Grazing Land/Settlement	694	Seepage Spring
	Rajal	S7	32° 5’46.18“N	76°12’45.31“E	Boulder, gravel, sand and silt (Alluvium)	Agricultural Land	684	Seepage Spring
	Bhatlahru (A)*	S8	32° 5’28.18“N	76°12’43.30“E	Boulder, gravel, sand and silt (Alluvium)	Grazing Land/Settlement	675	Depression Spring
	Bhatlahru	S9	32° 4’55.29“N	76°12’54.47“E	Sandstone with clay	Pine Forest/Settlement	662	Contact Spring
	Pathiar	S10	32° 4’35.74“N	76°12’39.17“E	Sandstone with clay	Pine forest/barren land/Settlement	726	Seepage Spring
	Salol Khas*	S11	32° 6’56.41“N	76°12’3.80“E	Sandstone with clay	Grassland/Bushes	653	Seepage Spring

*Springs marked with asterisks were selected to conduct Spring Rejuvenation Study.

Collection of background information of the area and springs was undertaken in a survey mode from the local inhabitants; different parameters were surveyed like seasonal water availability, land use practices, water dependency, and benefits of reviving seasonal boweris. The study was initiated by creating a base map of the springs of Salol region and delineating the catchment area in Arc GIS 10.4, Survey of India toposheets I43W4 and I43W7 with a scale of 1:50000, surveyed in the year 1969 and updated in the year 2005–2006 were used. The delineated springs were further validated on the ground using GPS.

Seasonal variations in the physico-chemical properties and water discharge of spring water

All 11 springs in the Salol region were studied to determine the natural and anthropogenic influences on spring water chemistry, as well as the seasonal and spatial hydro-chemical fluctuations. In addition to spring water samples (n = 11), hand pump water samples (n = 05) and surface stream water sample (n = 01) were also collected from existing sources nearby such as streams and wells, along with a few seasonal hand pump samples of the region (APHA, American Public Health Association, 2012).

The samples were collected in good quality, high density polyethylene bottles of one liter. Before sampling, the sample bottles were cleansed three times with distilled water and then rinsed with the same water to be sampled (APHA, American Public Health Association, 2012); water samples were extracted from a depth of 10 to 15 cm below the water surface. On-site measurement of parameters such as pH, electrical conductivity (EC), and Total Dissolved Solids (TDS) of water samples was conducted using portable water analysis kit.

The collected water samples were transported to the laboratory in cold storages and refrigerated at 4 degree centigrade until analysis. In the laboratory, the water samples were filtered through 0.22-micron filter paper (polyvinylidene fluoride PVDF) to separate suspended sediments and then stored for further analysis (S-Springs, H- Hand pumps & R- Surface Stream).

Spring water discharge measurements

Discharge (Q) is the amount of water flowing from the outlet of the spring per unit time. There are various methods for measuring the discharge rate of springs. The method used in the current study for Salol and Bhatlahru regions was meter gauge method (Joshi, 2006), the adopted method being strictly dependent on the type of spring, infrastructure and amount of water flowing from the outlet of these springs. The water levels of boweris were measured from a reference point with a meter scale for pre-monsoon, monsoon, winter and dry seasons.

The measurements were taken twice/month with an interval of 15 days. For better accuracy and error reduction, three readings were taken every time during the sampling procedure and the average was calculated. On the basis of water level and depth further results were prepared.

Hydrological & socio-economical study

The process of delineating, identifying, and mapping potential groundwater zones within the Salol watershed was carried out by collecting the background information in the survey mode from the local residents who heavily rely on the groundwater resources to meet their needs. This procedure had the main goal to determine suitable sites for groundwater recharge and effectively manage the groundwater resources within the region. During the research work, many village people got benefited economically and community awareness on water resource management was heightened through group discussions, particularly engaging women and children within the village.

Groundwater potential zone mapping

The utilization of Remote Sensing and Geographic Information System (GIS) is significant in determining the potential zones for groundwater recharge (Etikala, Golla, Li, & Renati, 2019; Kumari, Poddar, Kumar, & Shankar, 2022) as shown in Figure 2. The mapping was initiated using Resourcesat-2A (LISSIV 5.3 m, 2020), and Advanced Space borne Thermal Emission and Reflection Radiometer (ASTER) DEM having a spatial resolution of 30 meter, freely available at http://earthexplorer.usgs.gov/. A concise overview of the methodology employed for the identification of groundwater potential zones is shown in Figure 3. Additionally, the watershed of the area was extracted and delineated using a digital elevation model (DEM). Six groundwater conditioning factors viz. geomorphology, geology, lineament density, drainage density, slope, and land use land cover were taken into account for the delineation of groundwater potential map of the study area. Further ArcGIS software was used to integrate all the geographical thematic layers and a comprehensive map of groundwater potential zone for the study area was generated (Figure 2). The information obtained from thematic maps was verified through a thorough field visit. Subsequently, different recharge structures were proposed based on the validated data to revive the selected springs.

Figure 2. Groundwater potential zone map of the study area.

Figure 3. Methodology used for groundwater potential zone mapping.

Rejuvenating the springs by rainwater harvesting techniques

There are different methods that have been already implemented in the Indian Himalayan region by various government and non-government organizations for the rejuvenation of springs and conservation of water resources (Aayog, 2017; Rawat, Jose, Chenlak, Raina, & Gurjar, 2022). The eight-step methodology implemented in the mid-hills of Nepal for springshed management approach (Shrestha et al., 2017) was used as a reference/base plan for the present study. Mainly there are two techniques of rain water harvesting: storage of rainwater on surface and recharge to groundwater. Table 2shows recharge zone characteristics of springs at two selected sites (Bhatlahru and Salol Khas).

Table 2. Categorization of factors influencing the groundwater potential zones.

Factors	Geomorphology	Geology	Lineament Density	Slope	LULC	Drainage Density	Weight
Geomorphology	6	5	4	3	2	1	0.40
Geology	6/2	5/2	4/2	3/2	2/2	1/2	0.20
Lineament Density	6/3	5/3	4/3	3/3	2/3	1/3	0.13
Slope	6/4	5/4	4/4	3/4	2/4	1/4	0.10
LULC	6/5	5/5	4/5	3/5	2/5	1/5	0.08
Drainage Density	6/6	5/6	4/6	3/6	2/6	1/6	0.06

Suitable recharge structures for spring rejuvenation adopted for Bhatlahru and Salol region

In the present study, artificial recharge structures were constructed in Salol and Bhatlahru regions of Kangra district (Table 3). The constructions were based primarily on the hydro-geological features, such as geologic parameters, geomorphology, slope, lineament density, lineament, drainage pattern, drainage density, LULC and availability of water through rain fall and natural springs (Amineh, Hashemian, & Magholi, 2017; Prabhu & Venkateswaran, 2015; Sargaonkar, Rathi, & Baile, 2011; Senanayake, Dissanayake, Mayadunna, & Weerasekera, 2016; Singh, Panda, Kumar, & Sharma, 2013). Contour trenching, recharge pits, and percolation ponds are some of the suitable methods for the natural augmentation of water in the identified springs (see in Supplementary Material). These constructions aid in replenishing groundwater (aquifer), which helps to maintain the water flow of surface streams and other groundwater sources in addition to revival of dry springs

Table 3. Recharge zone characteristics of the selected springs.

Name	Physiography and Structures	Rock type	Land use	Land cover	Slope (degree)	Spring type
Bhatlahru	Spring is located at the center of a grazing land of an elevation of 675 m	Boulder, gravel, sand and silt (Alluvium)	Grazing land and settlement in smaller fraction	shrubs	Slope ranges from 0–40 degree	Perennial spring
Salol Khas	Spring is located at the base of a hill at an elevation of 653 m	Sandstone with clay	Wasteland	Shrubs and bushes in down slope	Slope ranges from 0–30 degree	Perennial spring

Results and discussions

Physico-chemical characteristics of spring water

The physical parameters of springs of the Salol region were observed for two seasons (post-monsoon and pre-monsoon) for the years of 2021 and 2022, respectively.

pH

The pH defines the nature of water whether it is acidic or alkaline. A total of 17 water samples (groundwater and surface water) were collected from the Salol region during both post-monsoon (year 2021) and pre-monsoon (2022) seasons. Figure 4 shows the pH values observed during the two sampling seasons. The average values of pH in post-monsoon and pre-monsoon seasons recorded were 7.04 and 6.55 respectively, which are within the acceptable limit i.e. 6.5–8.5 according to (IS10500, 2012). Site sampling locations of S3 and H5 were dry during pre-monsoon, so the values of pH are missing in Figure 4.

Figure 4. Observed pH level in the years of 2021(post monsoon) and 2022 (pre monsoon).

The maximum values of pH were recorded at the locations of S11 and R1 during the pre-monsoon season. While the minimum value of pH was detected at location of S3 during the post-monsoon season. The maximum values of pH during the pre-monsoon season might be due to disposal of waste material and decomposition of organic matter in the vicinity of the area (Niwa et al., 2007), while the lowest pH value observed during the post-monsoon season might potentially be attributed to the dilution effect caused by rainwater.

TDS

The present study reflects that the value of TDS in post-monsoon season varied from 96 to 549 ppm while in pre-monsoon season it varied from 168 to 809 ppm as shown in the Figure 5. In pre-monsoon season, the concentration of TDS was high, however, the values for majority of springs in the Salol region were below the acceptable limit (IS10500, 2012) (500 ppm) except for the locations of H2, S6 and H3. Similar to (Kupwade & Langade, 2013; Taloor et al., 2020) and (Kausher et al., 2023), the evaporation effect might be the main cause for increasing the value of TDS. In post monsoon season the values of TDS were below the threshold permissible limits except for the location of S11, which might be contributing to monsoonal surface erosion in a vegetation free land. Similarly, the main contributors for rise in groundwater TDS are chemical weathering of rocks, evaporation, and vegetation degradation (Dandwate, 2012).

Figure 5. Observed TDS concentration in the years of 2021(post monsoon) and 2022 (pre monsoon).

Electrical conductivity

Electrical conductivity (EC) of water is a measure of the ability of water to pass an electric current, which is dependent on the dissolved salts/ions and other inorganic compounds/chemicals. The acceptable range of EC in drinking water falls between 200 to 800 micro Siemens per centimeter (μs/cm). In the pre-monsoon season, the present result showed that the value of EC at the location of S6 was the highest, 1212 μs/cm. While, in the post-monsoon season, the location of S11 showed the highest conductivity (818 μs/cm) as shown in Figure 6. Also, the obtained results show that most of the samples have comparatively high conductivity in pre-monsoon season as compared to post-monsoon season. It is clear that evaporation was primarily responsible for the seasonal change in conductivity levels as precipitation-induced dilution lowers those values (Aksever, Davraz, & Bal, 2016; Trivedy, Shrotri, & Khatavkar, 1990; Umarani, Ramu, & Kumar, 2019).

Figure 6. Observed electrical conductivity in the years of 2021(post monsoon) and 2022 (pre monsoon).

The general characteristics of in-situ parameters (pH, TDS and Electrical Conductivity) for both post and pre monsoon season water samples are summarized in Table 4 and Table 5 with minimum, maximum, mean, and standard deviation values. Table 6 and Table 7 show a strong positive relationship between TDS-EC whereas pH remains almost unchanged during post-monsoon to pre- monsoon seasons. The strong positive correlation between EC and TDS is well-known as EC is determined based on the amount of total dissolved solids in the water (Subramanian & Baskar, 2022). A strong positive correlation (correlation coefficient = 0.94) during the post-monsoon season can be seen between the pairs of TDS-EC. Similarly, the results summarized in Table 7 show a strong positive relationship during the pre-monsoon season between TDS and EC (Kamble, Machiwal, & Bhakar, 2016). It is evident that the distribution of TDS was significantly correlated with EC in the water samples during both the seasons indicating the high mobility of ions into the water (Sharma & Chhipa, 2016). As for the hand pump water samples the mean values of the measured in-situ groundwater quality parameters such as TDS and EC exhibit higher concentrations than the surface stream water (Thomas, 2021).

Table 4. Descriptive statistics analysis of water quality parameters pH, TDS, EC for the post-monsoon season (2021).

Parameters	Sample Number	Minimum	Maximum	Mean	Standard Deviation	Standard Error
pH	17	6.46	7.62	7.05	0.32	0.07
TDS	17	96	549	272.35	119.32	28.94
EC	17	145	818	396.35	177.63	43.08

Table 5. Descriptive statistics analysis of water quality parameters pH, TDS, EC for the pre-monsoon season (2022).

Parameters	Sample Number	Minimum	Maximum	Mean	Standard Deviation	StandardError
pH	17	0	8.76	6.50	2.49	0.60
TDS	17	0	809	357.52	196.82	47.73
EC	17	2	1212	536.11	294.74	71.48

Table 6. Correlation analysis for in-situ water quality variables for the post-monsoon season (2021).

	pH	TDS	EC
pH	1
TDS	0.291233	1
EC	0.290304	0.941615	1

Numeric figures in bold indicate very strong correlation between the variables.

Table 7. Correlation analysis for in-situ water quality variables for the pre-monsoon season (2022).

	pH	TDS	EC
pH	1
TDS	0.672726	1
EC	0.672692	0.999918	1

Numeric figures in bold indicate very strong correlation between the variables.

Results of the t-test indicate significant/non-significant changes in the in-situ water quality parameters for the post and pre monsoon seasons. It is revealed that for pH the t-test with p value is found to be 0.39 which is greater than the significance level i.e. p = 0.05, which concludes that there is no significant difference between the means of pH concentrations during both the seasons. However, the t-test for TDS and EC with p-values of 0.02 and 0.01, respectively, concludes that the mean concentrations of both TDS and EC have changed significantly between the post-and pre- monsoon seasons in the area. Thus, the results from TDS and EC levels further indicated that the water quality undergoes a noticeable change between both the post and pre monsoon seasons.

Identification of groundwater potential zones

An estimation of groundwater availability by identifying the groundwater potential zone (GWP) in the Salol region, district Kangra was done using remote sensing data in geographic information system (GIS) platform with Analytical Hierarchy Process (AHP) method. The AHP is an effective tool for reducing complex decisions to a series of pair-wise matrix comparisons and then synthesizing the results (Saaty, 2001).

Geology and geomorphology

The occurrence and distribution of groundwater are significantly influenced by geologic and geomorphologic settings of any terrain (Yeh, Cheng, Lin, & Lee, 2016). The Salol region comprises different geological sequences, ranging from quaternary, plio-pleistocene, upper Miocene to Pliocene which predominantly consists of rocks of upper and middle shiwaliks (https://bhuvan-app1.nrsc.gov.in/gwis/). This rock formation consists of alluvium, boulder, and conglomerate sandstone with clay (Figure 7). In the undertaken study area, the region with alluvial (boulder, gravel, sand, silt and clay) deposits shows very high potential of groundwater, whereas moderate to high groundwater potential is found in sandstone and conglomerate deposits (Figure 2). Geomorphologically, the region consists of older river terraces, piedmont alluvium, dissected denudation hills, and moderately dissected structural hills. Highly dissected denudation hills and hard nature of structural hills act as good runoff zones (Roy, Keesari, Sinha, & Sabarathinam, 2019) with little infiltration (Rajasekhar, Upendra, Raju, Anand, & 2022). Entisols type of soil is found in the Salol region; it eases water percolation. The region shows structural hills which are slightly divided, consisting of fractures and faults that facilitates the groundwater movement. The hills are mainly composed of massive sandstone, shale, and limestone with noticeable joints and fissures showing a good recharge potential of the region. On the other hand, older river terraces, alluvium and water body account for good groundwater storage (Singh, Anand, & Chattopadhyay, 2022) capacity. With respect to the groundwater potentiality and the relative importance of different landforms with different geological setups, the highest to lowest weightage was assigned to older river terraces, piedmont alluvium zones and ridge type structural hills respectively (Table 8).

Figure 7. Thematic spatial maps of study area: (a) Geology; (b) geomorphology.

Table 8. Classification of weighted factors and their ratings influencing the potential zones in the study area.

Factor	Weight	Rank	Overall
(A) Geomorphology
Structural Hills Moderately Dissected	40	2	80
Denudational Hills Highly Dissected		3	120
Piedmont Alluvium		4	160
(B) Geology
Sandstone with Clay	20	2	40
Boulder,Gravel,Sand,Silt and Clay (Alluvium)		4	80
Boulder Conglomerate		4	80
(C) Lineament Density
Very Low	13	1	13
Low		2	26
Moderate		3	39
High		4	52
Very High		5	65
(D) Slope
0–10	10	5	50
10–20		4	40
20–30		3	30
30–40		2	20
Greater Than 40		1	10
(E) LULC
Agricultural	08	3	24
Barren Land		3	24
Forest		4	32
Ravinous Land		2	16
Settlement		1	08
Water		5	40
(F) Drainage Density
Very Low	06	5	30
Low		4	24
Moderate		3	18
High		2	12
Very High		1	6

LULC

The land use and land cover (LULC) map delineates the distribution of water bodies, forests, vegetation, settlements, and other features across a region (Arulbalaji, Padmalal, & Sreelash, 2019). The LULC pattern is one of the major controlling factors used to determine the groundwater replenishment potential zone in the present study. The study area exhibited a diverse land use and land cover pattern, encompassing agricultural land, forest land, grazing land, and different types of rural settlements. In the present study the LULC of the region is classified into six class i.e. agricultural land, barren land, forest, raven land, settlement and water. Most of the study region is covered with forest or trees (72 %), followed by agricultural land (11.45 %) where 10% is covered by settlement and rest of the land encompasses barren land, raven land and water. The landform characteristics of the present study area not only aid in the identification of groundwater potential zones but also helps to identify suitable sites for the construction of groundwater recharge structures.

Slope

The gradient of the slope significantly controls the surface runoff pattern, water infiltration rate, and consequently, the movement of groundwater within a specific region (Condon & Maxwell, 2015; Singh, Anand, & Chattopadhyay, 2022). The slope gradient map of the study area (Figure 8) is divided into five classes, flat (0–10°), gentle (10–20°), medium (20–30°), steep (30–40°) and very steep (greater than 40°). High slope gradient results in less aquifer recharge condition because most of the precipitated water is lost due to surface runoff during rainfall. In the present study the class with the highest weight was assigned to flat and gentle slopes whereas slopes that are extremely steep to very steep were given the lowest weight due to the relatively high run-off possibilities. The majority of the study area falls in the gentle (10–20°) slope to steep (30–40°) slope (Figure 8), whereas high degree of slope gradients was noticed in the north-eastern part of the area. Salol and Bhatlahru springs are situated in the region having slope greater than 30°. Hence, to augment the water storage capacity of these springs, artificial recharge structures were constructed in the area, which most likely helps to reduce the surface runoff during monsoon months.

Figure 8. Thematic spatial maps of study area: (a) Landcover/land use; (b) Slope; (c) drainage density; (d) lineament density.

Drainage density

For groundwater potential zonation in the present study, high and low weight is assigned for low and high drainage density patterns respectively. The study area shows highly variable drainage densities, from very low to very high, with the low drainage density pattern representing higher infiltration as compared to high drainage density, consequently contributing to greater groundwater potentiality. The regions with favorable water infiltration conditions are located in the south-western and south-eastern part of the studied region, while the majority of the region exhibit moderately favorable conditions (Figure 8) for water infiltration and hence provide valuable insight for the identification of suitable groundwater recharge sites.

Drainage pattern, which results from stream erosion, explains the features of rocks and other geological structures in a drained region (Srivastava, Denis, Srivastava, Kumar, & Kumar, 2014). Land gradient, dominance of hard or soft rocks and amount of rainfall are the main factors responsible for a particular type of drainage pattern. The study region exhibits dendritic drainage pattern (Figure 1) which indicates the geomorphic and geological homogeneity of the area (Ganie et al., 2022). Dendritic drainage pattern is one of the most common patterns formed, having various branches as that of tree roots. Usually it is formed in areas having homogenous material. The drainage is structurally influenced by the region’s geology, topography and erosional processes (Sreedevi, Subrahmanyam, & Ahmed, 2005). The availability and contamination of groundwater are significantly influenced by the drainage density (Krause, Jacobs, & Bronstert, 2007). High drainage density indicates lower infiltration, thus limiting groundwater potential in the area and vice versa (Saravanan, Saranya, Abijith, Jacinth, & Singh, 2021).

Lineament density

The lineament density map of the study area is classified under five categories as shown in Figure 8. Within the study area, the lineament density varies between very low to very high. The major lineaments are present in NW to NE direction, respectively. Studies show an inverse relationship between the distance of lineaments and groundwater potential (Prasad, Loveson, Kotha, & Yadav, 2020). The moderate to high groundwater potential is associated with the area of high lineaments, while low lineament zone is characterized by very high groundwater potential (Figure 2), which also serves as good groundwater recharge locations. The highest rank is assigned to the high lineament density and similarly the lowest rank for the low lineament densities. Lineaments are typically associated with zones of faults and fractures that are responsible for increased permeability in the area (Arulbalaji, Padmalal, & Sreelash, 2019). Therefore, the regions with high lineament density are indicative of substantial groundwater potential zones in the study area (Rajasekhar, Upendra, Raju, & Anand, 2022).

Table 2 shows the categorization of factors from 1 to 6 influencing the groundwater potential zones. The influence and importance of each factor were defined by making a pair wise matrix, and the factors were valued on a scale ranging from 1 (very low) to 5 (very high) as shown in Table 8. All the factors were classified into sub-classes and were ranked based on their impact on groundwater flow dynamics. Finally, overall weightage was calculated by multiplying the weight with the ranks of each sub-class, as shown in Table 8. The final results are categorized into five different classes namely “Very High, High, Moderate, Low and Very Low” groundwater prospects (Figure 2), which shows the groundwater availability in the study area based on the hydro geomorphological conditions of the region. As evident from the map (Figure 2), moderate, high, and very high zones are uniformly distributed throughout the region, particularly in areas dominated by alluvium. The study area exhibits promising groundwater potential, as majority of the region categorized, have high water infiltration capacity.

The results further offer effective information for the selection of suitable groundwater recharge sites (natural or artificial) in the region. Out of the identified 11 boweris, two were taken for their revival; the degree of revival was further validated with the results obtained through isotopic studies.

The regional climatic conditions

For understanding the regional climatic conditions better, forty-one years (1981–2021) long-term annual maximum temperature (TMAX), minimum temperature (TMIN), and corrected precipitation data were analyzed for Bhatlahru region, given that the Salol region experiences similar climatic conditions, therefore it is presumed to exhibit comparable climatic trends as that of Bhatlahru region. The highest TMAX (42.38°C) was recorded in 1995, thereafter the temperature following a decreasing trend (Figure 9), whereas TMIN depicts linearity with bimodal nature in temperature. The years 1984, 2008, and 2020 recorded a minimum temperatures of-0.76°C, −0.32°C and-1.37°C respectively (Figure 10). The long-term time series of temperature demonstrates climatic variability with the passage of time. As for the precipitation data, an increasing trend in frequency and intensity of rainfall has been documented from 2013 to 2021 (Figure 11). The arithmetic mean and standard deviation are indicators of central tendency and dispersion, respectively, and was utilized to assess the significance of statistical data (Table 9). The skewness coefficient quantifies the degree of asymmetry in a frequency distribution relative to the mean, which varied between −0.57 (TMin) to 0.41 (rainfall). The negative value observed for TMax and TMin suggests an asymmetric distribution skewed to the left of the mean (Riju & Linda, 2021). However, positive skewness has been observed for the rainfall through the period. The peakedness of a symmetrical frequency distribution varied from −0.48 (TMax) to 0.57 (TMin) within the region. The coefficient of variance (CV) was computed for studying variability in temperature (TMax, TMin), and rainfall over the study area. The CV varied between 3.89 % (TMax) to 58.15% (TMin), suggesting that the variability in maximum temperature across the study area is relatively low as compared to the TMin, which indicates a much higher variability through time.

Figure 9. Time series TMAX (ºC) data from 1981–2021 for Bhatlahru region.

Figure 10. Time series TMIN (ºC) data from 1981–2021 for Bhatlahru region.

Figure 11. Time series precipitation (mm) data with effect from 1981–2021 for Bhatlahru region.

Table 9. Computed climate data for the study area from 1981–9021.

Climate variables	Arithmetic mean	SD	Coefficient of skewness	Coefficient of kurtosis	CV%
TMax	39.66	1.54	−0.01	−0.48	3.89
TMin	2.22	1.29	−0.57	0.57	58.15
Rainfall	892.11	311.95	0.41	−0.73	34.96

SD-Standard Deviation; CV-Coefficient of variation.

Observed impact of constructed recharge structures on salol boweri and bhatlahru boweri

The present study finds that the rainfall pattern of the two sites, Salol and Bhatlahru, was different from the other parts of the Kangra district; rainfall patterns show a shift that may be due to different LULC and topography. Thus it may induce somewhat different seasonal changes in the water levels at these springs. Rainfall data was recorded by installing rain gauge at Bhatlahru, whereas the rainfall data for Salol region was downloaded from https://power.larc.nasa.gov/data-access-viewer/. Figure 12 shows the fluctuation in water level of the Salol boweris (with respect to rainfall and seasons). The present results showhow rainfall pattern and recharge structure affects the water level of Salol boweri. At Bhatlahru spring, rainfall data were collected by installing the rain gauge; the collected results show that the highest rainfall was recorded during the monsoon from June 2021 to the end of September 2021 and the lowest rainfall was recorded in the dry seasons of March, April and May 2022 (Figure 13). The rainfall ranged from 315 mm to 694.69 mm in the month of July and August, it was also observed that there is a good relationship between rainfall and water level of boweris in these monsoonal months, whereas in the dry seasons rainfall received was the lowest. It ranged from 1.01 mm to 3.04 mm. It is clear that the water level of the boweris follows an annual, periodic rhythm that is strongly dependent on the rainfall pattern with a distinct time lag after rainfall.

Figure 12. Hydrograph of salol boweri with respecte to the impact of artificial recharge and rainfall pattern.

Figure 13. Hydrograph of bhatlahru boweri with respect to the rainfall pattern.

In the year 2021, the water level of Bhatlahru boweri during the dry season was recorded between 127 cm to 132 cm. After the construction of recharge structures, in the year 2022 during the dry season the water level increased to148–159 cm. From the study it was found that the implemented rain harvesting technique was partially successful in increasing the water level of the boweris during the dry seasons. According to the downloaded data of the region from https://power.larc.nasa.gov/data-access-viewer/ Figure 12 shows that the highest rainfall received during the month of July, August and September, the highest rainfall recorded was between 232.38 mm to 503.09 mm, whereas the lowest rainfall recorded was during the dry season i.e. in the month of March and April, ranging from 11.88 mm to 169.56 mm. After constructing the recharge structures, it was observed that water level of Salol boweri incrementally raised. The water level before constructing recharge structure ranges from 119 cm to 135 cm, wheras after constructing the recharge structure the water level of boweri rose, and varied between 139 cm to142cm and persisted up to February. It was observed that during the dry seasons, March and April the water level decreased due to reduced frequency of rainfall, indicating that rainfall directly affects the water level of Salol boweris.

Based on the geomorphological analysis and weighted values in this study, suitable recharge structures for recharging the aquifer with estimated storage capacity were chosen as shown in Table 10. At Salol region, staggered contour trenches were chosen as artificial structures, whereas recharge pits and percolation tanks were found to be appropriate for the Bhatlahru region. The primary goal of constructing artificial recharge structure was to collect and store excess rain water lost due to surface runoff and to facilitate groundwater recharge. The constructed artificial recharge structures at Salol and Bhatlahru region of Kangra district facilitated the important task of collecting and storing rainfall for groundwater recharge; it showed a positive impact on the water level of the studied springs.

Table 10. Estimated storage of water in constructed recharge structures.

Sr. No.	Location	Type of Recharge structures	Dimensions	Capacity	Total constructed recharge structures
	Bhathalru	Recharge pits	$1\mathrm{m}\times 1\mathrm{m}\times 0.6\mathrm{m}$	$0.6{\mathrm{m}}^3$	100
	Bhathalru	Percolation tank	$9\mathrm{m}\times 6\mathrm{m}\times 1\mathrm{m}$	$54{\mathrm{m}}^3$	01
	Salol	Contour trenches	$2\mathrm{m}\times 0.3\mathrm{m}\times 0.6\mathrm{m}$	$0.36{\mathrm{m}}^3$	150

Correlation between spring water level and rainfall

Values close to 1 or −1 indicate a strong linear relationship between the variables, the correlation coefficient between the observed rainfall and Bhatlahru spring water level was found to be 0.02, indicating a very weak positive linear relationship. Similarly, a very weak positive correlation coefficient of 0.05 was obtained between the Salol spring water level and rainfall (Table 11). Moreover, a correlation coefficient of −0.06 has been observed between secondary rainfall data and Bhatlahru spring water level. In the undertaken study, spring water level has no linear relationship with the rainfall; this condition might favor the role of artificially constructed recharge structures, because a clear time lag is seen between rainfall and spring water level. But definite conclusions can not be drawn merely on the basis of analytical relationship between spring water level and rainfall to the efficiency of recharge structures for rejuvenating springs, it is imperative to consider additional variables such as evapotranspiration rate, surface runoff dynamics, and potential data limitations into account. These different factors play a crucial role in the mountain hydrological processes that govern groundwater recharge and spring discharge dynamics.

Table 11. Correlation matrix for Bhatlahru and salol spring water level with rainfall.

The correlation matrix for Bhatlahru spring water level and rainfall
	Rain Gauge	Bhatlahru water level
Observed Rainfall from installed rain gauge
Rain Gauge	1
Bhatlahru water level	0.029995495	1
Secondary data
	Data access viewer	Bhatlahru water level
Data access viewer	1
Bhatlahru water level	−0.066328709	1
The correlation matrix for Salol spring water level and rainfall
	Data access viewer	Salol water level
Data access viewer	1
Salol water level	0.058240014	1

Conclusion

Geologically the area of Salol is represented by sedimentary deposits such as unconsolidated rocks, boulders, conglomerate, gravel, sandstone, silt and clay, which aids percolation and thus most suitable for any type of ground-water recharge system. Interactions with the local people reflect an urgent demand for fresh water sources along with improvement of water supply system of the area especially during the summer months. During field visits, seasonality of boweris and struggle for daily water needs has already been witnessed. The present studies in the Bhatlahru and Salol region show that the springs that have gone seasonal can be revived using artificial recharge structures. During the implementation of management practices in the area, the groundwater potential zone map proved to be quite useful in delineating and demarcating the recharge points for the selected representative boweris. With respect to long-term water conservation in the hilly region it is highly recommended and expected that the maintenance of constructed recharge structures is a necessity. In order to understand the hydrological behavior of the springs with respect to changing environment and micro-climate, long-term monitoring of springs should be carried out considering the rainfall pattern along with different aspects of hydrology such as evapotranspiration rate, infiltration rate and other components. These measures, if implemented and practiced, a large population may get benefited in the Himalaya.

This study will add to the current understanding of the spring recharge sources and aid in planning sustainability of springs. The generated baseline data at a micro level can be used for proper planning and management of these water resources in the district Kangra. It was found that there is a need of tailored design structures for the management of water resources in the Himalaya. Finally, it will create awareness about the sustainability of natural water resources among the young researchers and local inhabitants.

Acknowledgments

The authors are thankful to the Dean, Department of Environmental Sciences, Central University of Himachal Pradesh and to the Vice-Chancellor, Central University of Himachal Pradesh, Dhramashala (H.P.) for providing all the necessary facilities to execute and run the research work. The Divisional Forest Officer, Dharamshala, H.P. Forest Department is also gratefully acknowledged for his collaboration and support at various stages of the research work.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/23570008.2024.2333600

Additional information

Funding

This work was funded/supported by Himachal Pradesh Council for Science, Technology & Environment (HIMCOSTE) Shimla under Sanction letter F.No. STC/F(8)- 6/2019/(R&D 2019-20)-420 Dated 29.06.2020.