Journal of Global Resources
Biannual International Peer-Reviewed Journal
ISSN: 2395-3160 (Print)/2455-2445 (Online)

January 2021
Volume 07 (01)
Crossref DOI 10.46587

DOI: 10.46587/JGR.2021.v07i01.005

05
DETERMINING WATER QUALITY INDEX USING THE PHYSICO-CHEMICALATTRIBUTES FOR GROUNDWATER AND SPRING IN VICINITY OF KAWASING
RESERVE FOREST, ASSAM, NORTH-EAST INDIA
Sangeeta Deka,1 Lal Bihari Singha2 and Om Prakash Tripathi3
1

Department of Forestry, North Eastern Regional Institute of Science and Technology(Deemed to be University) Nirjuli, Arunachal Pradesh, India
2
Department of Life Sciences (Botany), Manipur University, Canchipur, Imphal, India
3
Dept. of Environmental Sciences, Mizoram University, Tanhril, Aizawl, Mizoram, India

Corresponding author Email: deka_sangeeta@yahoo.co.in
Abstract: The current study attempts to assess the physical and chemical attributes andwater quality index (WQI) of spring and groundwater in vicinity of Kawasing Reserve forest(KRF) in Kamrup district of Assam, to understand its suitability for various uses including
drinking purpose. The detailed investigation was carried out in two types of water sources(spring and ground water in form of well). The water samples were collected along a
distance gradient from the mid-range of the forest patch to find out the influence of forest
on water characteristics. It is argued that natural spring water (SWS) could be the key basisof drinking water for populations around the forest vicinity. It was observed that the SWS
possessed pH, dissolved oxygen and total alkalinity beyond the permissible limits of Indian
standards/ICMR standards and other parameters showed values well within the prescribed
limit of standard. On other hand, the ground water system (GWS) possessed dissolved
oxygen, total hardness and magnesium (Mg2+) beyond permissible limit and rest
parameters were within the prescribed limit of standards. The findings reveal that thequality of SWS was better than that of GWS. The WQI indicates that spring water systemfalls under the “excellent” category (WQI: 25.06+6.03) while ground water system denotes“poor” category (154.98+19.03). Moreover, SWS and GWS found 100 percent and 22.5
percent suitable for human consumption. The increase in WQI value with increase indistance suggesting a negative correlation in terms of water quality or water quality
degrades with increase in distance from the mid-range of KRF. The outcome of present
study may be a guiding bacon to the inhabitants in vicinity of KRF with respect to water
resource utilization. Systematic and sustainable water quality management approaches
especially for GWS, to be adopted for clean water in surroundings of Kawasing Reserve
forest.
Key words: Ecosystem Services; Physico-Chemical; Sustainable; Water Quality Index
Introduction
The term “water quality” literally denotes the physical, chemical, and biologicalcharacteristics of water for its suitability for a particular use (Pike et al., 2010). Various
anthropogenic activities are responsible for change in the physical, chemical and biologicalstructure of the water, leading to deteriorated water resource. The major factors causing
alteration of water quality includes change in vegetation cover, construction of various
conveniences on the rivers, use of fertilizers and pesticide in agricultural fields, which
directly affect the micro climate of the water making the water quality unhealthy for aquatic
life as well as human uses. Forests have a multidirectional interaction with the freshwater
systems, and are responsible for regulating the quality of water in various ways- throughsoil stability and sediment load, fishing and hatching activities, presence of various tree41

species and its impact on acidification of water, management of downstream water logging
and salinity; influencing the availability of water for irrigation systems and many more
(Dudley and Stolton, 2003). Groundwater systems (GWSs) are the water bodies that rely
on groundwater to maintain their health and vigour. The GWSs are considered vital featuresin the site that necessitate access to ground water to preserve its current composition,
structure and function (Eamus, 2009). Like other systems, GWS also provides ecosystemservices which are valuable at various levels. Provisioning services like drinking water,water for industrial use, irrigation etc. are among the tangible goods while regulating
services such as water retention and drainage, surface water supply, water purifying andfiltering effect of soil and water supporting services as function of biogeochemical cycles
and cultural services such as aesthetical and ethical values of GWS are among theintangible goods essential for sustenance of a healthy environment (Tuinstra andWensem, 2014). Springs are water resources formed in any sort of rock when excavations
on hills and valley bottoms intersect a flowing body of ground water at or below the watertable, below which the sub-surface layer is saturated ( www.usgs.gov). Springs are themain source of water for the people in many parts of the country and worldwide (Taloor andSingh, 2020; Amen, 2019, Barakat et al., 2018; Mofor et al., 2017; Sammoudi et al., 2019;
Ganiyu et al., 2017).
The people depend on springs as a source of potable water and other domestic andagricultural purposes and mostly used without any pre-treatment. Springs are therefore
considered inexpensive and best-quality source of water (Ameen, 2019). The optimum
accessibility and good quality of water in several regions of the world are under serious
threat due to unsustainable use of groundwater, contamination of surface water and theimpact of climate change (IPCC, 2007; Ameen, 2019). This study emphasis theassessment of ground (well) and spring water quality for human consumption, based on
physical and chemical parameters and water quality index (WQI) enumeration of thesewater samples. The WQI is an important model to detect the status of water quality andhas been functional for both ground and surface water system throughout the world since
the last few decades (Ramakrishnaiah et al., 2009; Kawo and Karuppannan, 2018;
Samantray et al., 2009; Bora and Goswami, 2017; Shah and Joshi, 2017; Singh and Kamal,
2014; Seth et al., 2016; Dash et al., 2015; Bhutiani et al., 2014; Krishnan et al., 2016;
Kaviarasan et al., 2016; Vishnu Radhan et al., 2015; Yadav et al., 2015). The WQI model
enables to convert a complex set of water quality data into simple information, making it
easy to understand the status water source (Balan et al., 2012). WQI provides state ofwater with a single value utilizing multi parameters of water quality (Abbasi, 2002). Since
the inhabitants in vicinity of Kawasing forest primarily depends on wells (GWS) and spring(SWS) water, the study aimed to qualify the water from both the sources. The objective of
this research is also to find the effect of the presence of forest stand on water quality of thestudy area.
Study Area
This study is conducted in vicinity of the Kawasing Reserve forest in Kamrup district ofAssam (Fig. 1). The temperature ranges between 10°C and 34°C and relative humidity
accounts for 67- 90 percent with annual precipitation of 120 cm to 230 cm. The forested
catchment is characterized by hilly terrain with natural forest cover and steep slope down
the hill connecting the even land. The even land could be categorised as agricultural lands,
water bodies, human habitations and several stream networks connecting the perennial
springs flowing down the forest. The reserve forest falls under older alluvium
hydrogeological formation (CGWB-Kamrup, 2013). Older alluvium has a suitable prospect
for shallow tube wells, deep tube well up to 100 m depth and dug wells feasible at foot hills.

42

Figure 01: (a) Location of The Study Area (b) Image of Sampling Locations

Sampling Technique and Analysis
Within the study area, the water systems of two types were selected on the basis of
distance gradient from the forest. First category included artificial hand-dug wells andthe second category natural spring flowing down the hill slope through the KFR. Both thecategories of water bodies are largely used for drinking purpose. Water samples werecollected at different locations along a distance gradient up to a distance of 2 km awayfrom the mid-range of the forest patch. GPS points were collected using handheld GPS
device (Garmin) at different locations along a flowing natural spring and also at various
wells set within human habitation areas along a distance gradient from the forest stand to
study the physico-chemical properties of water and to enumerate the WQI of the twodifferent categories of water sources of the study area. A total of 9 wells and 9 springs
from different locations within were surveyed and collected the samples. The wells were
kutcha (entirely hand-dug) or concrete ring- walled. A few wells were later seen unused
due to structural instability. The water samples from selected sites were collected andanalysed for various physical and chemical properties like, temperature, pH, electricalconductivity, total dissolved solids, total hardness, chloride, total alkalinity, Calcium (Ca2+)and Magnesium (Mg2+). The standard methods for the examination of water andwastewater as prescribed by APHA (2005) was followed for examination of water quality
attributes. Temperature was measured using thermometer and expressed as degree
centigrade (°C). Electrode method was used to determine the pH of water. The conductivity
meter of the SWAK was used for the analysis of electrical conductivity (EC) of water andthe results were expressed as micro Siemens. Total dissolved solids (TDS) was estimatedwith the meter inbuilt in the SWAK, and the results expressed in ppm (parts per million) or
mgL-1. The water analysis kit was used to measure the dissolved oxygen content andvalues were expressed in mgL-1 Total hardness was estimated using EDTA titration
method, and values were expressed in mgL-1. Mohr’s Argentometric method was used todetermine chloride content in water, and values were expressed in mgL-1. The Ca2+ andMg2+ were analysed using titrimetric method, and values were expressed in mgL-1.
Water Quality Index (WQI) Analysis
Weighted arithmetic index method formulated by Brown et al. (1970) was followed to
calculate the WQI where all the values of chemical parameters were taken into
consideration with a single expression. The equation used in this method is as follows:

43

𝑛

𝑛

𝑊𝑄𝐼 = ∑ 𝑟𝑖 𝑤𝑖 ⁄∑ 𝑤𝑖
𝑖𝑖

Where n= water quality parameters or variables used
𝑟𝑖 = quality rating of ith water quality variable
𝑤𝑖 = relative unit weight of ith water quality variable
The value of 𝑟𝑖 is computed using the following equation:𝑟𝑖 = 100{(𝑉𝑖𝑜 − 𝑉𝑖𝑝 )}/(𝑉𝑝 − 𝑉𝑖𝑝 )}Where 𝑉𝑖𝑜 = Observed value of ith water quality parameter
𝑉𝑖𝑝 = Ideal value of ith water quality parameter in pure water
𝑉𝑝 =Standard permissible value of the ith water quality parameter
All the ideal values (𝑉𝑖𝑝 ) are taken as zero for drinking water except pH and DO(Tripaty and Sahu, 2005; Boah et al., 2014). The ideal value for pH is 7.0 (for natural/purewater) and a permissible value is 8.5 (for polluted water) and for dissolved oxygen (DO) is
14.6 g/l.
The unit weight ( 𝑤𝑖 ) of the different water parameters are inversely proportional to
the recommended standards for the corresponding parameters. The value is calculated asfollows:
𝑤𝑖 = 𝑘/𝑉𝑝
Where, the constant of proportionality (k) is calculated using the equation:1

k=1⁄∑𝑛𝑖 (𝑉 )𝑝(i=1, 2, 3……n)𝑖Table 01: Water Quality Status Based on WQI Values and their Probable Usage(Ramakrishnaiah et al., 2009; Sahu and Sikdar, 2008; Kawo and Karuppannan, 2018)
WQI
value Water quality inference
Probable usage
range
Less than 50
Excellent
Drinking, irrigation and industrial
51-100Good
Drinking, irrigation and industrial
101-200
Poor
Irrigation and industrial
201-300
Very poor
Irrigation
More than 300
Unfit for drinking and aquaculture Pre-treatment required

Results and Discussion
The pre-requisite condition in calculating WQI is the estimation of relative unit weight (wi)of each parameter taken into account for water quality assessment. To achieve the unit
weights, it is necessary to convert the units of various parameters into a common scale. In
this study, all the parameters were presented in milligram per litre (mgL-1), excluding pH(dimensionless) and electrical conductivity (micro Siemens/centimetre). The Bureau ofIndian Standard (BIS, 2003) and the Indian Council of Medical Research (ICMR, 1975)
standards for drinking water with the relative weights assigned to the respective parameters
were used for calculating the WQI are tabulated in Table 2. Values highlights that dissolved
oxygen (0.50019) contributed the maximum weightage on the WQI followed by pH(0.38476), and total dissolved solids (TDS) contributed the minimum weightage on theindex value.

44

Table 02: Relative Weight of Chemical Parameters and Drinking Water Standards
Recommended by Indian Standard Institute and ICMR
Indian*/ICMR standards#
6.5
300*
500*
5#
300*
250*
120#
30*
75*

Parameters*
pH
Electrical conductivity
Total dissolved solids
Dissolved oxygen
Water hardness
Chloride
Alkalinity
Magnesium
Calcium

Relative weight (wi)0.38476
0.00834
0.00500
0.500190.008340.01000
0.020840.050020.01250∑ 𝑊𝑛 =1.0*Expressed in milligrams per litre excluding pH and EC.

The respective mean values of all variables from both the water system and therespective contributing scores to the WQI value are presented in the Table 3. The study
revealed that the water characteristics of SWS was superior than that of ground water
system as water quality index value of the former system was found to be quite lower thanthe later (Table 3). In the ground water system, parameters like pH (100.89) and dissolved
oxygen (41.99) were found to be the most influencing factor for a higher value of WQI. But
in case of spring water system dissolved oxygen (39.18) is the only factor found influencing
the WQI score on a higher side. The pH value was seen to have a positive influence on thewater quality of the spring water system as the contributing score of pH to WQI value wasnegligible which compensated and brought back the final WQI value to a very lower range
under the “excellent” category of water quality status (Table 1). As per the categorizationof water quality status based on WQI value, the ground water system (154.98+19.03) falls
under the “poor” category while spring water system (25.06+6.03) under the “excellent”
category.
Table 03: Comparative Account of WQI Values of Ground Water System and Spring
Water System along with the Corresponding Observed Values of the Parameters Used
Water
QualityParameters
pH
Electricalconductivity
Total
dissolved
solids
Dissolved
oxygenWater
hardness
Chloride
Alkalinity
Magnesium
Calcium

Ground water system
Quality
Observed
ratingriwi
values( ri)
5.69
262.22100.8934
70.00

23.33

Spring water system
Quality
Observed
ratingriwi
values( ri)
7.28-68.00-20.0077
40.00
13.33
0.111154

0.194519

120.0024.00

0.120046

6.54

83.95

41.9895

341.87113.96
0.949994
19.89
7.95
0.079584
118.4498.70
2.05711750.48
168.288.417316.97
22.63
0.2829∑ 𝑊𝑛 =1.00000∑ 𝑟𝑖 𝑤𝑖 =154.9845
𝑾𝑸𝑰 = ∑𝒏𝒊 𝒓𝒊 𝒘𝒊 ⁄∑𝒏𝒊 𝒘𝒊 =154.9845

48.00

9.60

0.048018

7.08

76.04

39.18171

17.92

5.97

0.049797

24.00
9.60
0.096037
135.44112.852.351944
15.44
51.47
2.574321
18.04
24.05
0.300782∑ 𝑊𝑛 =1.00000∑ 𝑟𝑖 𝑤𝑖 =25.06088
𝑾𝑸𝑰 = ∑𝒏𝒊 𝒓𝒊 𝒘𝒊 ⁄∑𝒏𝒊 𝒘𝒊 =25.06088

The ground water quality assessment included sampling of 9 wells along a distance
gradient in three classes (W 500-1000 / W 1000-1500 / W1500-2000) i.e., 500 to 1000 meter, 1000 to1500 meter and 1500 to 2000 meter away from the mid-range of the Kawasing Reserve
forest. These wells were selected randomly, three (3) each under each class of distance45

range. Under the GWS, 6 out of 9 wells belong to “poor” category while 2 were under“good” category and only one was reported “very poor” and its respective WQI values arepresented in Table 4. Similarly, a total of 9 locations along the spring flow in three classesof distance gradient (S500-1000 / S1000-1500 / S1500-2000) were sampled for water quality
assessment, each class having three sampling locations. In the SWS, 7 out of 9 possessed“excellent” status of water quality based on WQI values with an exception to location (S7and S9) which fall under the “good” category with a considerable higher value of WQI (>50)
as shown in Table 4.
Classifying the water system (GWS and SWS) on distance gradient and considering
the mean water quality index (MWQI) value of the sampled well and spring locations
respectively under corresponding class of distance range we obtained a significant resultthat water quality index value increases with increase in distance from the mid-range of
Kawasing forest. Under the ground water system, the MWQI values increases with increasein distance (Table 4 and Fig. 2). A similar trend in results was observed for the spring water
system (Table 4 and Fig. 3).
Table 04: Water Quality Index (WQI) of Individual Sampling Locations and Quality
Inferences and Along the Distance Gradient
Sample
ID
W1
W2
W3
W4
W5
W6
W7
W8
W9
Distance
W 500-1000
W 1000-1500
W 1500-2000

WQI value

Water quality
SampleWQI value
Water quality
inferenceID
inference
78.0260
S1
ExcellentGood
11.11723
121.6215
S2
Excellent
Poor
6.656989
98.78181
S3
Excellent
Good
7.891602
196.1628
Poor
S4
Excellent
23.95247
186.3825
Poor
S5
Excellent
12.65996
147.2068
Poor
S6
Excellent
17.79988
195.2440
Poor
S7
Good
56.21569
146.2612
Poor
S8
Excellent
35.38022
225.1735
Very poor
S953.87388
Good
WQI values and inferences along the distance gradient
MWQI
Water quality
MWQI
Water quality
Distance
value
inference
value
inference
99.48
Good
S500-1000
8.56
Excellent
176.58Poor
S1000-1500
18.14
Excellent
188.89Poor
S1500-2000
48.49
Excellent

Figure 02: Graphical represantation of individual water quality index (IWQI) of the sampled
wells and the mean water quality index (MWQI) along distance (in meter) gradient of groundwater system

46

Figure 03: Graphical represantation of individual water quality index (IWQI) of the sampledspring locations and the mean water quality index (MWQI) along distance (in meter)
gradient of spring water system

The findings on the quality of water are in conformity with the works of several
authors (Lalchhingpuii et al., 2011; Lalparmawii and Mishra, 2016; Thasangzuala et al.,2014; Mishra and Chenkual, 2014; Chenkual and Mishra, 2016; Sunar and Mishra, 2016;
Laldinpuii and Mishra, 2019; Lalhmangaihzuali et al., 2019). Mishra and Lalhruaizeli (2009)
also reported a similar result in a study on spring water quality status in Aizawl, Mizoram,
India.
The findings on WQI is supported by the work of Sunar and Mishra (2018) who
studied WQI of Serlui river of Mizoram. Based on distance gradient, the WQI values
increased with increase in distance which suggests a positive correlation between WQI
value and the dimension of distance, while it suggested a negative correlation with respect
to water quality. In other words, results reveal that water quality degrades with increase indistance from the mid-range of Kawasing forest, supporting the statement that tropicalforest cover act as a good indicator of water quality (Mello et.al 2018). In the present days,
tropical forests have been facing tremendous threat due to land use change, deforestationand fragmentation like activities and causing degradation of water quality. Over extractionof timber, mis-utility and severe pollution were recognised as the major drivers for
degradation of the water resource (Calder, 2007). Therefore, it is important to study the roleof forest cover as an indicator of water quality in different landscapes.
Conclusions
The present study is an effort to assess quality of drinking water sources prevalent in thevicinity of Kawasing reserve forest, and to make aware the people settled in vicinity who
are using such water for various purposes. The assessment of water quality was carriedout from 18 different locations of two different water system viz., ground water system (9locations) and spring water system (9 locations). The only physical parameter analysed in
the study was temperature which was not included in the WQI score computation. It was
found that 11.11 percent, 22.22 percent and 66.67 percent of water samples wereconsidered as ‘very poor’, ‘good’ and ‘poor’ water quality, respectively under the groundwater system. On the other hand, 22.22 percent and 77.78 percent of water samples wereconsidered as ‘good’ and ‘excellent’ water quality under the spring water system. Of water
samples analysed, only 22.22 percent of GWS and 100 percent of SWS may be considered47

suitable for human use. Based on findings, it can be argued that natural spring water could
be the primary source of drinking water for the inhabitants in vicinity of forest instead of thewells (ground water source). ‘Poor’ or ‘very poor’ water quality of the GWS might be due tostructural instability of wells from where water samples were collected. Based on on-sightobservation, the sampled wells were found mostly hand-dug kutcha (without concrete
walls). Sanitation and domestic sewage outflows found unmanaged and improper.
Moreover, it also facilitates easy runoff from surroundings and contamination of groundwater through percolating water, making water unhealthy and unfit for human consumption.
On the contrary, the spring water system is still pristine. There exists very little humaninterference to the SWS. Analysis of individual water quality parameter depicts that GWS
possessed all the parameters were within the permissible limits of the chosen standards
except for dissolved oxygen, total hardness and magnesium (Mg2+) which were closer to or
exceeded the permissible limit of Indian Standard Institute/ICMR standards. Similarly, SWS
possessed pH, dissolved oxygen and total alkalinity beyond permissible limits. The findingsof present study are not only important as research data but also has a tremendous
significance as ground reality. The outcome of present study may act as guiding bacon to
the inhabitants settled in vicinity of the Kawasing forest. For maintaining a healthy
ecosystem and a hazard free health, systematic and sustainable water quality managementof GWS and necessary pre-treatment of water are pre-requisite.
Acknowledgements
Authors thankfully acknowledge the University Grants Commission, New Delhi for financial
assistance through National Fellowship for Higher Education. The authors are also verymuch thankful to the Department of Forestry, NERIST for providing all necessary facilities
for the research work.
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