sources of major ions and processes affecting the...
TRANSCRIPT
CHAPTER 4
SOURCES OF MAJOR IONS AND
PROCESSES AFFECTING THE
CHEMISTRY OF SUBSURFACE
WATERS IN A TROPICAL RIVER
BASIN, SOUTHWESTERN INDIA
Chapter 4
57
Abstract: River water and groundwater samples were collected seasonally for one year
from Nethravati-Gurupur river basin from ten locations. The major ion and stable isotopic
(δ18
O and δD) composition explain the hydro-geochemistry of groundwater as well as
interaction of surface water with groundwater. The study reveals that intense weathering of
source rocks is the major source of chemical elements to the surface water and
groundwater. In addition, agricultural activities and atmospheric contributions also govern
the major ion chemistry in the basin. There is a clear seasonality in the groundwater
chemistry which is mainly related to recharge and discharge functions of the hydrological
system. On a temporal scale, there is a clear decrease in major cations during the monsoon
which are primarily contributed by the weathering of rock minerals and an increase in
anions which are contributed by the atmosphere, with an increase in water level during the
monsoon. The stable isotopic composition indicates that groundwater in the basin is of
meteoric origin and recharged directly from the local precipitation during the monsoonal
season. Soon after the monsoon, the groundwater and surface water mixes in the
subsurface region. The groundwater feeds the surface water during the lean river flow
season.
4.1. Introduction
The groundwater and the surface water are the major sources of water in India for
domestic, irrigational and industrial purposes. Since utilization of groundwater for drinking
and irrigational purposes has increased drastically over the years, it is important to monitor
the chemistry of groundwater periodically. As a first step in water quality monitoring and
water resource management policy, the groundwater chemistry has to be evaluated at
regional and global scale to identify the sources of chemical elements in water, the
interaction between the broad hydrological compartments and the influence of hydrological
flow conditions on the chemistry of groundwater/surface water. Groundwater chemically
evolves by interacting with aquifer minerals or internal mixing among different source
waters along flow-paths in the subsurface region. In general, the quality of groundwater is
controlled by several factors, viz. climate, soil characteristics, circulation pattern through
various rock types, topography of the area, saline water intrusion and human activity.
Apart from these, the exchanges of groundwater back and forth across channel beds of
rivers have significant impact on the overall water quality (Harvey and Fuller, 1998).
Chapter 4
58
In hard rock terrains of southern India, over exploitation of groundwater for domestic
and/or irrigational purposes and deterioration of water quality due to excessive pumping
has been reported recently by Maréchal et al., (2006a, 2006b), and Dewandel et al., (2007).
In these hard rock terrains, the natural recharge of groundwater is almost equal to
irrigational return flow (infiltration of water which is used for irrigational purposes;
Maréchal et al., (2006a), which has a negative impact on the groundwater chemistry
(Perrin et al., 2011). Similar observations have been made by Rajesh et al., (2005) in their
multivariate statistical study in the Nethravati-Gurupur river basin. However, the authors
(Rajesh et al., 2005) did not attempt to find out the sources of water and contaminants in
their study.
Dakshina Kanada, in particular Mangalore is the hub of many industrial activities and the
source of water for these industries is mainly from the surface and groundwater in the
Nethravati-Gurupur river basin. The excessive withdrawal of water from the groundwater
aquifer and surface water sources from coastal areas poses serious threat of salt water
intrusion into the aquifer system and/or of a general deterioration of groundwater
chemistry. Recent studies report the occurrences of saltwater intrusion and fluoride
contamination in the coastal regions (Chadha, 2000, Durraiswami and Patankar, 2011,
Shaji et al., 2007). Furthermore, Ministry of Environment and Forests, Government of
India, in 2010 has listed Mangalore and Bhadravati regions of Karnataka as critically
polluted cities of India (http://pib.nic.in/newsite/erelease.aspx?relid=65269). Highly porous
laterites are the rock types in the lower region which make the aquifer system more
vulnerable to contamination by anthropogenic activities. This has motivated us to take up a
study on the status of groundwater chemistry of a rapidly developing region (Dakshina
Kanada) on the southwest coast of India.
In the present study, a detailed geochemical investigation of the groundwater based on
major ion and stable isotopes of oxygen and deuterium have been carried out to meet the
set objectives: 1. To determine the sources of major ions and origin of groundwater, 2. To
understand temporal and spatial variation in the subsurface water chemistry and its
response to changing hydrological conditions, 3. To understand the mixing of surface and
subsurface water and hydro-geochemical processes controlling groundwater chemistry, 4.
To generate a baseline major ion chemistry data of subsurface water in the Nethravati-
Gurupur river basin.
Chapter 4
59
4.2. Results
4.2.1. Physicochemical characteristics and hydro-geochemistry
The major ion and stable isotopic composition of groundwater samples at different time
periods of sampling are given in the Table 4.1. The pH of the subsurface samples are
mildly acidic in nature while borewell sample are mildly acidic to alkaline in nature at
different time periods of sampling. The average pH values of post monsoonal and
monsoonal sampling is quite similar (avg. 5.7). The electrical conductivity (EC) of the
water samples ranges from 25 to 338 µS cm-1
at different sampling locations with an
average of 115 µS cm-1
over the sampling period with higher conductivity values during
May and August sampling. The EC is observed to be higher in case of bore well samples
ranging from 145 to 380 µS cm-1
(avg. 288 µS cm-1
). The lesser conductivity values are
observed in the upper catchment (e.g., Shishila hole, Parpikal) where meta-sediments and
granite gneisses are the dominant rock types. The total dissolved solids (TDS)
concentration in the open well samples range from 22 to 272 mg L-1
(avg. 97 mg L-1
)
whereas the bore well samples exhibit higher concentrations with a concentration range
from 144 to 414 mg L-1
(avg. 295 mg L-1
). The TDS and pH in the wells located at the
upper catchment of Nethravati are relatively less (avg. TDS 54 mg L-1
) and more acidic
(avg. pH 5.6) compared to the lower catchment. The samples collected from the middle
reaches are located in a suburban region with intense agricultural activity and has relatively
higher concentrations of TDS (avg. 71 mg L-1
) and pH values (avg. 5.6). Whereas, the
samples from the lower part of the catchment have higher TDS (avg. 94 mg L-1
) than the
upper and middle parts with near neutral pH. The TDS, EC and pH of groundwater, both
openwell and borewell, samples are within the drinking water standards prescribed by the
World Health Organization (WHO). The pollution index estimated as percentage of anion
ratio (Pacheco and Van der Weijden 1996) indicates that the station Uppinangadi,
Mangalore and Kakve are influenced by anthropogenic activity. The order of dominance of
cations and anions in groundwater samples are Ca>Na>Mg>K and HCO3>Cl>NO3>SO4>F
respectively. The percentage contribution of rainwater to the chemistry of groundwater is
calculated using local precipitation chemistry using chloride as a tracer (Négrel et al.,
1993). The rainwater chemistry is presented in Gurumurthy et al., 2012 (Chapter 3). In
brief, the weighted average chloride concentration is 47 µmol L-1
, Na 45 µmol L-1
, Ca 20
µmol L-1
, K 5 µmol L-1
, Mg 7 µmol L-1
and SO4 9 µmol L-1
. The molar Na/Cl ratio (~0.95)
in the rain water is corresponding with the marine ratio suggesting the rain water
composition is dominated by sea salts. However, enrichment of Ca and Mg with respect to
Chapter 4
60
sea water composition is noticed. The per cent contribution of rain water chemistry to the
dissolved major ion chemistry of groundwater is given in Table 4.2. The order of rainfall
contribution to cation composition is Ca> Na> K>Mg and most of the SO4 present in the
groundwater is contributed by rainfall except at few sampling locations.
4.2.2. Isotopic characteristics
The 2008-2009 isotopic results (Tables 4.3) show homogeneity in the rainfall inputs over
Udupi and Mangalore area, with no significant difference between the river water and
groundwater (mean δ18
O = -2.2). Furthermore, the d‐excess (10.4-12.3) for these samples
fall close to the Global Meteoric Water Line (GMWL), i.e., 10, except for a few
groundwater samples near Udupi. The groundwater samples revealed lower d‐excess
values (mean 8.1), indicating low evaporation rates from these wide‐open wells, a
possibility that is supported by the high conductivity values. In contrast, the 2010 low
altitude isotopic values are more negative by around -1.2 ‰ for δ18
O than the August 2010
sampling, whereas the mean d‐excess value range is higher than the 2008-2009 samples,
ranging from 15.2 to 19.1. It is interesting to note that only a bore well with water at
deeper levels reveals isotopic values close to the earlier ones, with a d‐excess at 12.1. The
more negative values in November/December 2010 indicate a more pronounced
fractionation process, showing the possible entry of different air mass moisture. On
Mullayanagiri hills, the isotopic ratios of the samples show negligible altitude gradient.
Samples collected at mid altitude (743-832m above MSL) are from springs that could have
water originating at much higher elevations and thus they reflect high‐altitude ratios.
Samples collected at the highest altitude (1905m above MSL) were from caves, and these
showed less negative values than other high‐elevation samples. This could be because of
an evaporation and recondensation process. The overall decrease in δ18
O was only by
0.5‰, which gives an isotopic gradient of 0.03 ‰ per 100 m. Surprisingly, the samples
from high altitude do not become more negative than δ18
O=−4.1‰. The isotopic gradient
over altitude (0.03 unit/100 m) is very low compared with a classical mountain gradient of
0.2-0.4 units. For the south Indian west coast, Deshpande et al., (2003) reported a general
altitudinal decrease in the δ18
O by 0.42‰ per 100m increase in altitude, but for the
Mangalore area this value is close to zero. Also, they have reported high d‐excess values in
the coastal region of Mangalore but not elsewhere. This low gradient with altitude could be
because of the presence of a fog or mist like atmosphere in the tropical evergreen forests,
which could reduce the δ18
O values (Scholl et al., 2002).
Chapter 4
63
Table 4.3: Stable isotope (d18
O and δD) characteristics with calculated mean and standard deviation of groundwater and surface waters of
Nethravati-Gurupur river basin.
Sample type S No. Location EC
(µS cm-1
)
Elevation
(m aMSL)
d18
O
(‰)
δD
(‰)
d excess
July, 2008
Seawater
1 Udupi sea 36000 0 0.60 8.53 3.73
2 Suratkal sea 38000 0 0.63 7.41 2.38
Mean
0.61 7.97 3.06
Estuary
3 Nethravati river near sea 1255 0.5 -2.16 -4.62 12.66
4 Mulki river near sea 3466 0.5 -2.15 -7.04 10.16
5 Nethravati/Gurupur confluence near
sea 3806 0 -2.08 -4.57 12.09
Mean±SD
-2.13±0.04 -5.41±1.41 11.64±1.31
Groundwater
6 Mughir GW 234 2 -2.34 -5.57 13.12
7 Mangalore GW 215 3 -2.69 -11.29 10.25
Mean±SD
-2.51±0.25 -8.43±4.04 11.69±2.03
River water
8 Manipur river 59 3 -1.90 -6.46 8.72
9 Udyavara river 325 3 -2.15 -5.93 11.28
10 Nandini river 402 3 -2.27 -8.36 9.76
11 Gurupur river 370 1 -2.17 -5.45 11.91
Mean±SD
-2.12±0.16 -6.55±1.28 10.42±1.45
January, 2009
Groundwater
12 Open well, Parkala, Udupi 88 46 -2.21 -9.59 8.13
13 Borewell, Parkala, Udupi 110 49 -2.06 -8.62 7.88
14 Hand pump, Parkala, Udupi 140 52 -2.13 -8.75 8.26
Mean±SD 113
-2.13±0.08 -8.98±0.53 8.09±0.19
River water
River water
15 BC Road, Bantwala 52 9 -1.25 0.24 10.24
16 Mugera 50 32 -1.79 0.04 14.34
17 Shanthimugeru 51 63 -1.76 -2.34 11.75
18 Gundiahole 54 81 -1.83 -1.09 13.56
19 Shishilahole 35 102 -2.15 -4.89 12.30
20 Neriyahole 44 90 -2.23 -4.39 13.47
21 Dharmasthala 54 96 -1.88 -3.75 11.27
22 Mundaje Hole 51 110 -2.37 -6.81 12.19
Mean±SD 49
-2.16±0.35 -4.98±2.51 12.31±1.35
Chapter 4
64
Sample type S No. Location EC
(µS cm-1
)
Elevation
(m aMSL)
d18
O
(‰)
δD
(‰)
d excess
August, 2010
Groundwater
323 Sangabettu - OW 42
-3.09 -7.81 16.90
324 Bantwala – OW 84
-3.35 -8.62 18.18
325 Melkar/BC Road - OW 134
-3.03 -5.08 19.15
326 Uppinangadi - OW 332
-2.22 -7.33 10.44
327 Kakve – OW 62
-3.03 -9.01 15.27
328 Ichilampadi - OW 37
-1.54 -4.45 7.89
329 Mundaje – OW 153
-3.07 -6.01 18.54
330 Sangabettu - BW 380
-2.98 -4.70 19.15
331 Ichilampadi - BW 137
-2.96 -8.29 15.38
Mean±SD
-2.81± 0.56 -6.81±1.78 15.66±4.01
River water
314 BC Road, Bantwala 32.4 9 -3.14 -7.43 17.67
315 Mugeru – RW 35.4 32 -3.56 -10.29 18.18
316 Shanthimugeru - RW 31.4 63 -2.52 -3.88 16.25
317 Gundya hole - RW 30.9 81 -1.91 -4.49 10.80
318 Shishila hole - RW 32.0 102 -2.95 -6.09 17.49
319 Neriya hole - RW 29.8 90 -3.39 -4.80 22.31
320 Dharmasthala - RW 34.5 96 -3.34 -7.04 19.71
321 Mundaje – RW 27.2 110 -2.83 -6.12 16.51
322 Gurupura – RW 33.2 11 -2.80 -6.05 16.36
Mean±SD -2.94±0.51 -6.24±1.91 17.25±3.10
November/December, 2010
Groundwater
23 Sanghabettu bore well 365
-2.65 -9.12 12.06
24 Sanghabettu well 40
-3.14 -7.94 17.21
25 Bantwal well 83
-3.76 -12.52 17.58
26 Balthila well 44
-3.36 -2.33 24.54
27 Uppinangadi well 296
-2.87 -4.73 18.19
28 Kadaba well 74
-3.67 -9.49 19.89
29 Parpikal well 26
-2.83 -3.81 18.83
30 Mundaje well 104
-3.11 -7.13 17.74
Mean±SD 95
-3.25±0.40 -6.85±3.36 19.14±3.44
River water
31 Bantwal river 46 10 -3.50 -12.68 15.30
32 Mugeru river 44 34 -3.45 -11.77 15.83
33 Shanthi Mogeru river 41 69 -3.33 -11.15 15.45
34 Gundhiya hole river 44 86 -3.19 -13.24 12.30
35 Shishila hole river 39 108 -3.51 -10.06 17.98
Chapter 4
65
Sample type S No. Location EC
(µS cm-1
)
Elevation
(m aMSL)
d18
O
(‰)
δD
(‰)
d excess
River water
36 Neriya hole river 38 94 -3.71 -14.97 14.69
37 Dharmasthala river 48 101 -3.57 -12.22 16.31
38 Mundaje river 46 116 -3.53 -14.99 13.22
39 Gurupura river 37 11 -3.73 -14.46 15.35
Mean±SD 42
-3.50±0.17 -12.84±1.74 15.16±1.66
High Elevation*
40 Charmadi Ghat spring 29 743 -4.09 -11.01 21.70
41 Charmadi Ghat spring 19 832 -3.91 -9.70 21.58
42 Mullayanagiri spring 27 1478 -3.84 -15.96 14.74
44 Mullayanagiri spring 2 high 16 1599 -3.91 -16.15 15.10
45 Mullayanagiri cave 79 1905 -3.62 -17.52 11.47
Mean±SD 39
-3.87±0.17 -14.47±3.47 16.45±4.53
*High elevation samples were collected on December 03, 2010.
Chapter 4
66
4.3. Discussion
4.3.1. Major ion composition in subsurface water and their sources
The relationship between the pH and TDS varies at different parts of the catchment. For
instance, the middle catchment shows exponential increase in the concentration with
increase in the pH (R2 = 0.90), whereas the lower and upper catchment are showing
polynomial (degree-2) relationship with a R2 value of 0.70 and 0.68 respectively (Fig. 4.1).
This suggests that as the groundwater flows through the porous media, the groundwater
composition is altered due to interactions with the mineral phases present in the weathered
mineral matrix. The samples collected from Uppinangadi open well are isolated from rest
of the samples with relatively higher concentration of TDS (avg. 242 mg L-1
) and mildly
acidic pH (avg. 6.1). This could be due to anthropogenic sources, particularly agricultural
activity, contributing to higher TDS in the well. Lesser concentrations of TDS in the upper
catchment could be due to the abundant presence of weathering resistant rock types such as
granite-gneisses and meta-sedimentary rocks. Whereas, the lateritic wells of lower
catchment (Bantwala, Melkar and Mangalore) shows higher TDS which could be due to
marine aerosol deposition as the stations are close to the Sea. Siva Sowmya et al., (2009)
has demonstrated that the chemistry of the rainwater could be enriched with major ions and
the concentration of major ions decreases from coast to inland.
The chloride concentrations are not affected by any biological or geochemical reactions,
though its concentration can vary with evaporation. If the evaporation is the dominant
process and uniform throughout the catchment (considering small catchment size), the
concentrations of chloride should progressively increase with an increase in electrical
conductivity (Fig. 4.2). The scattering of few samples having higher conductivity suggests
there is a strong influence of anthropogenic chloride in the catchment particularly at
sampling station Uppinangadi and Mangalore. This enrichment could be due to
contamination by agricultural fertilizers and domestic waste. This is also evident from the
observed higher concentrations of NO3 and SO4 in the in the subsurface waters. There are
two possibilities to explain the observed concentrations of NO3 and SO4 in the catchment.
Firstly, the middle and upper reaches of the river Nethravati catchment is extensively used
for agricultural activity and the crops are fed with groundwater and/or surface water. The
extensive irrigation in the catchment leads to infiltration of water (Rajesh et al., 2005)
along with agricultural effluents to the shallow subsurface regions. Secondly, there are
Chapter 4
67
reports of enrichment of anthropogenic NO3 and SO4 in the winter and summer monsoon
rains (Praveen et al., 2007). These chemical constituents could be added to the subsurface
through soil infiltration (Hegde, 2007). Possibility of atmospheric contribution may be
insignificant as no enrichment of SO4 and NO3 were observed in the Nethravati River
(Gurumurthy et al., 2012). Thus, irrigational return flow could be the reason for
enrichment of SO4 and NO3 in the groundwater. Similar instances of contamination of
groundwater in agricultural catchments are documented at several places across the world
(e.g., Bohlke, 2002).
Figure 4.1: pH vs TDS for the groundwater samples (open wells) of Nethravati and
Gurupur river basin.
Chapter 4
68
Figure 4.2: Electrical conductivity and Cl for the groundwater (open well) samples of
Nethravati-Gurupur river basin.
The concentration of bicarbonates in groundwater reflects degree of water rock interaction,
oxidation of organic matter or respiration by plants and soil organisms in the groundwater
system (Zheng et al., 2004). In Nethravati river system the bicarbonates are believed to be
derived partly from atmosphere and partly from the oxidation of organic matter as most of
the samples belong to shallow waters (<10m) and having less dissolved oxygen
concentration (~3.5 mg L-1
). The organic carbon could be oxidised to soil carbon dioxide
which subsequently dissolves the rock mineral. The water rock interaction in the
subsurface region is illustrated in Fig. 4.3a. Most of the samples are showing the general
silicate mineral weathering trend as explained by Garrels (1967); decrease in Na/Ca ratio
with increase in HCO3/SiO2. Few samples from Uppinangadi do not fit to the general
weathering trend, suggesting the contribution of major elements from another element-
mobilizing process. Similarly, another sample from the Mangalore site (coastal region;
~3 km from the coast) is clearly out of the trend (Fig. 4.3a), which could be explained by
the presence of carbonate bearing recent alluvial deposits (Fig. 2.2). In general,
kaolinization could be the dominant mineral formation process in the river catchment (Fig
4.3a and 4.3b). This suggests intense mineral weathering in the river basin being located in
the tropics. It is consistent with the previous reports on chemical weathering in the basin
based on dissolved major ion composition of river water (Chapter-3; Gurumurthy et al.,
2012). The major cations are primarily coming from the weathering of primary silicate
Chapter 4
69
minerals, secondary soil minerals and leaching of carbonate fluid inclusions in the
charnockite rocks (Santosh et al. 1991). This interpretation is supported by our observation
in the Fig. 4.4. The molar ratio of Ca*/Na* and Mg*/Na* (corrected for atmospheric input)
in the groundwater plotted along with molar ratio of Ca/Na and Mg/Na measured in the
major rock types and laterites in the catchment. Most of the groundwater samples are
clustered around the weathered, partially weathered bedrock composition and are far from
the lateritic end member ratio. This suggests that as the groundwater flows through the
porous media, the groundwater composition is altered due to interactions with the mineral
phases present in the weathered mineral matrix. The weathering component of major
cations for the subsurface water is estimated following the method explained in the
previous Chapter (Chapter 3; Gurumurthy et al., 2012). The samples suspected for
agricultural contamination and the bore wells which are having higher concentrations are
excluded while calculating the average. Therefore, the below mentioned values represent
only the open wells with natural weathering source. The range of weathering component is
Na 3-197 µmol L-1
, K 2-127 µmol L-1
, Ca 3-204 µmol L-1
, Mg 5-108 µmol L-1
.
Figure 4.3a: Plot of HCO3/SiO2 (molar) vs Na/Ca (molar) for the groundwater and surface
waters of Nethravati and Gurupur River.
Chapter 4
70
Figure 4.3b: Mineral stability diagram for the plagioclase, gibbsite, smectite, kaolinite and
metastable aluminosilicate such as halloysite minerals.
Ca*/Na* (molar)
0.01 0.1 1 10
Mg
*/N
a*
(mo
lar)
0.1
1
10
Groundwater
Charnockite
Biotite Gneiss
Felsic Gneiss
Mafic Gneiss
Amphibolite
Laterite
Ch-BR
Ch-PW
Ch-W
GG-BR
GG-PW
GG-W
Figure 4.4: Mixing diagram of atmospheric input corrected Ca/Na and Mg/Na molar ratios
measured in the ground water. The bed rock composition is taken from Sharma and
Rajamani 2000, Braun et al. 2009, and weathered rocks and laterite composition is taken
from Narayanaswamy, 1992. Ch-BR:Charnockite bedrock; Ch-PW: Charnockite Partially
Weathered; Ch-w: Charnockite weathered; GG-BR: Granite Gneiss bed rock; GG-PW:
Granite Gneiss Partially Weathered; GG-W: Granite Gneiss Weathered.
Chapter 4
71
4.3.2. Temporal and spatial variation of groundwater chemistry and its response to
hydrological functioning
The hydrological and hydro-geochemical processes governing the temporal and spatial
variations of water chemistry in the subsurface region involve recharge and discharge,
hydrological flow path characteristics, mixing of different water sources, interaction with
aquifer material etc. The fluctuation of water table level in a watershed is often associated
with recharge and discharge of groundwater and hydrological flow conditions of
watershed. Further, in hard rock terrains the water table generally follows the surface
topography (Perrin et al., 2011). Therefore, the comparison of fluctuation in water level
with water chemistry would explain the control of surrounding lithology on water
chemistry in shallow aquifers.
In Fig. 4.5a, 4.5b and 4.5c, the water level and major ionic composition at different time
period of sampling at three locations each (Bantwala, Uppinangadi and Mundaje) is shown
in per cent considering total well depth as 100% (X-axis) whereas the sum of ions
(∑Ci=CJan+CMay+CAug+CNov; where ‘C’ is concentration and ‘i’ is an ion) at all sampling
period as 100% (Y-axis). Higher percentage of water level corresponds to monsoonal
sampling (August 2010), whereas lesser percentage corresponds to peak dry season (May
2010). The percentage scatter plot of major ions against water level in groundwater at three
different locations shows increase in the concentration of major anions (SO4, NO3, Cl) and
K
with increase in the water level. The higher concentration of these major ions
corresponds to higher water level, which in turn corresponds to higher rainfall months,
suggesting addition of major anions to the groundwater through rain water
(marine/terrestrial origin salts)and/or fertilizers (onset of agricultural activity). Whereas,
the major cations (Ca, Mg, Na), HCO3 and SiO2 shows decrease in concentration with
increase in water level. This indicates that these ions are having different sources. The
weathering of bed rocks, secondary soil minerals and carbonate fluid inclusions in
charnockite rocks are the source of major cations in the groundwater. The variation in the
leaching process controls the major cation variation in subsurface water. Another
possibility which would contribute to major cation variation is higher evaporation during
the dry period. Since, these major ions are abundant in the bed rocks, the weathering of
rock minerals could be predominant source. The abundance of major anions at different
sampling periods are more scattered than cations particularly for SO4, NO3 and Cl which
Chapter 4
72
clearly shows that these two group of ions have different sources. Furthermore, the data
plot at different sampling point shows that the variation of major ion abundance at
different stations are less when compared to variations at different time periods of
sampling.
Figure 4.5: Variation in major ion composition with water level at (a) Bantwala (OW), (b)
Uppinangadi (OW) and (C) Mundajehole (OW).
4.3.3. Sources of groundwater and its interaction with surface water
Stable isotopes of oxygen (δ18
O) and hydrogen (δD) in groundwater and river water can be
used to identify the sources of water and processes such as evaporation and mixing (Lloyd
and Heathcote, 1985). Figure 4.6 summarizes all the isotopic data in the form of plot of
δ2H versus δ
18O values. The sampling periods as well as the water type (river or
groundwater) are in different symbols, showing clearly two sets of data. The 2008 samples
are close to the local meteorological water line 1 (LMWL1), which is quite similar to the
GMWL. The groundwater samples from 2009 are located under the GMWL, showing the
same isotopic behaviour, whereas the river water samples are spread between LMWL1 and
LMWL2, showing a possible shift in response to different air masses. All the first group of
δ18
O values range from -1.3 to -2.6‰. The second group (from 2010) display more
Chapter 4
73
depleted values of -1.54 to -4.09‰. The more negative values correspond to the higher
latitude sampling. Furthermore, all the points of this second isotope group are more centred
on the LMWL-2 position, revealing a different climatic condition with a higher d‐excess.
The plot shows that the river water and groundwater of Nethravati and Gurupur catchment
is of meteoric origin, i.e., direct recharge of local precipitation, as evident from the close
spacing of isotopic ratios near Local Meteoritic Water Line (Warrier et al., 2010). The
Local Meteoric Water Line-1 (LMWL-1) is defined by Warrier et al., (2010) for local
rainfall at Kozhikode (200 km south of the study area) whereas LMWL-2 corresponds to
North East Monsoon isotopic ratio with an intercept of 14. In the Nethravati-Gurupur River
catchment, the water level falls drastically soon after the withdrawal of monsoon and rivers
start getting fed with groundwater. This observation is supported in the Nethravati-Gurupur
river catchment during the January sampling where the isotopic ratio of both groundwater
and surface water are quite similar. The influence of northeast monsoon on the
groundwater could be minimal on account of two reasons. Firstly, in 2010 there was
minimum influence of northeast monsoon in the study area (200 mm). Secondly, the δ18
O
and δD ratios of the northeast monsoon rains (δ18
O = -8.64‰ and δD = -53.2‰; Warrier et
al., 2010) and groundwater samples are not matching (δ18
O = -3.35‰ and δD = -10.15‰),
being heavier in the latter. Therefore, the slightly depleted isotopic ratio (compared to
monsoonal sampling) during this period could be due to mixing of subsurface water with
surface water. This suggests that there is an exchange/mixing of surface water and
groundwater during the post monsoonal period in addition to the monsoonal and pre-
monsoonal period when the groundwater recharges the surface water. The mixing of
stream water and subsurface groundwater is also explained from the plot of δ18
O vs EC
(Fig. 4.7). In Figure 4.7, the isotopic composition of groundwater and river water
belonging to monsoon and post-monsoon sampling are forming a cluster with a change in
the conductivity caused by addition of ions by weathering. Whereas, groundwater samples
belonging to pre-monsoon are having depleted isotopic composition compared to river
waters. The heavier isotopes in river waters during pre-monsoon could be due to
evaporation effect. The above observations are consistent with the observations made by
Rajesh et al., (2002) in their multivariate statistical study. Because of rapid
interaction/mixing of groundwater and surface water in the subsurface region,
contamination of any of the water compartment (surface or groundwater) would affect the
connected compartment and thus, imbalances the geo-biological, ecological and
environmental functioning.
Chapter 4
74
Figure 4.6: Relationship between the δ18
O and δD values. The first solid line (LMWL-1)
corresponds to the Local Meteoric Water Line as defined by Warrier et al., (2010) [δD=
(7.6 ± 0.13× δ18
O) + (10.4 ± 0.81)]. The second line, LMWL-2, has the same slope but
with an intercept of 14 and corresponds to the winter north‐east monsoon conditions (RW-
River water, GW- Groundwater, SW- Spring water).
R2=0.6739
Chapter 4
75
Figure 4.7: Scatter plot of δ18
O vs electrical conductivity (EC) suggesting mixing of
surface water with subsurface waters soon after offset of monsoon (RW-River water, SW-
Spring water, GW- Groundwater).
4.3.4. Statistical analysis of groundwater data
For groundwater and surface water, the sources of chemical elements are weathering of
rock minerals, marine aerosol deposition and anthropogenic activity. Sources of chemical
elements and their importance can be interpreted with interspecies relationship and using
chloride, bicarbonates/silica and nitrates as tracer for marine, weathering and agricultural
sources respectively (Singh et al., 2005).
Factor analysis: R-mode factor analysis is performed considering physicochemical
parameter, major ion and minor ion composition in water to identify major factors
controlling the groundwater chemistry of subsurface region. The number of significant
factors within the data are derived by Principal Component Analysis and Pearson
Correlation method considering an Eigen value greater than one (>1) using SPSS v19
statistical package. The extents of influence of each variable on the factors are given by its
Chapter 4
76
loading on that factor. The rotated component matrix (Varimax) and factor loadings are
given in Table 4.4.
For January and May sampling (considered as pre-monsoon) four factors having an Eigen
values >1 are selected which explains about 87% of total data variance of groundwater
chemistry at that particular time of sampling. Factor 1, accounts for about 52% of data
variance and the parameters involved in this factor are EC, TDS, Cl, SO4, HCO3, Na, K,
Ca, and Mg. This factor indicates the contribution of these elements from the weathering of
bed rock minerals in the catchment along with atmospheric contribution (particularly for
Cl, Na, SO4), which makes up the overall ionic composition of the water. The factor 2
accounts for 17% of total data variance. The parameters involved in factor 2 are pH, SiO2,
F and Fe. Both silica and iron are dominant species in the secondary soil minerals. The
fluoride is known to be adsorbed on to the clay minerals after their release from the source
minerals. The correlation between Fe, SiO2 and F indicates the desorption of F from the
clay mineral surface. The factor 3 accounts for 11 % of the total data variance and it
includes T, pH, Ca and Al, and negative loadings of DO that means the decrease in the
concentration of DO reduces the soil organic matter to carbon dioxide which in turn
decreases pH. Acidic pH could have control over the aluminium concentration in the
groundwater (Drever 1997). The fourth factor accounts for 6% of total data variability and
this factor is loaded with nitrates and sodium, which are known to contribute through
agricultural fertilizers and/or anthropogenic activity.
In the August (monsoon) sampling, three factors were selected based on the Eigen value
and these factors together accounts for 92% of the total data variance. The factor 1
constitutes EC, TDS, Cl, NO3, HCO3, Na, K, Ca, and Mg and this factor accounts for about
67% of total data variability. This factor loading suggests the dominance of weathering
processes along with leaching of agricultural and sea salt derived chemical elements. The
factor 2 is loaded with pH, HCO3, F, SO4, Ca and the factor accounts for 16% of the total
variance. The summer monsoon in the Arabian Sea and its coastal region is having higher
concentration of sea salts and non-sea salt originated Ca and SO4 ions. These enrichments
would originate from continental dusts and/or anthropogenic sources (Hegde 2007,
Praveen et al., 2007, Satyanarayana et al., 2010). The correlation between Ca and SO4
forming the second cluster in factor 2 suggests that Ca and SO4 are partly derived from the
rain water. This is also supported by rainwater contribution calculation, which suggests
Chapter 4
77
most of the SO4 and ~50% of Ca is contributed from the rains. The factor 3 is composed of
T, SiO2, Fe and negative loadings of DO. The silica and iron are the dominant in the
resistant secondary minerals of soil because of the least mobility during weathering and
transportation. Iron is known to form insoluble oxyhydroxides at higher oxygen
concentration and there by decrease the solubility. The negative loading with dissolved
oxygen suggests the solubility control of dissolved oxygen over the Fe.
In the month of November sampling, four factors were selected based on an Eigen value
which together accounts for 93% of data variance. The factor 1 is loaded with T, EC, TDS,
Cl, NO3, Na, K and Mg and this factor accounts for 41% of the total data variance. The
factor could be contributed by weathering of primary rock minerals along with atmospheric
sources such as marine aerosol deposition. Whereas the factor 2 accounts for 23% of the
total data variability is composed of pH, TDS, HCO3, SO4 and Fe. During post-monsoonal
months, the fertilizers and pesticides are being applied for the Arecanut and paddy fields to
prevent the damping off in seedlings. These pesticides include copper sulphate and
ammonium carbonate which could be contributing to the chemistry of groundwaters. The
factor 3 is composed of EC, HCO3, Ca and Al which accounts for 23% of data variability.
This factor could be representing the leaching of resistant mineral such as garnet group
minerals which is dominant in Ca and Al. The factor 4 is composed of DO and F with
negative loadings of SiO2 which accounts for about 9% of the data variability. This factor
could be representing the secondary soil minerals in the basin.
The statistical analysis of the major ions and physicochemical parameters on a seasonal
basis showed three source contributions in common i.e., weathering/marine aerosol, soil
secondary mineral leaching and agricultural/anthropogenic activities.
Chapter 4
78
Table 4.4: Multivariate factor analysis scores (rotated component matrix) for pre-monsoon, monsoon and post-monsoon months of sampling.
Rotated Component Matrix
Component (Jan & May)
Component (Aug)
Component (Nov)
Fact: 1 Fact: 2 Fact: 3 Fact: 4 Com Fact: 1 Fact: 2 Fact: 3 Com Fact: 1 Fact: 2 Fact: 3 Fact: 4 Com
T 0.314 0.306 0.691 -0.112 0.682 0.03 -0.363 0.837 0.833 0.862 0.118 -0.205 -0.32 0.902
pH 0.223 0.619 0.569 0.065 0.76 0.266 0.866 0.392 0.974 -0.074 0.816 0.35 0.216 0.841
EC 0.831 0.16 0.262 0.443 0.981 0.841 0.539 0.003 0.997 0.526 0.361 0.763 0.096 0.998
DO -0.475 -0.203 -0.645 0.077 0.689 -0.63 -0.122 -0.661 0.849 0.091 0.172 0.251 0.897 0.906
TDS 0.853 0.358 0.252 0.279 0.998 0.823 0.554 0.112 0.995 0.517 0.582 0.602 -0.121 0.984
SiO2 0.444 0.827 0.049 -0.233 0.938 0.535 0.335 0.727 0.927 0.251 0.242 -0.286 -0.767 0.792
HCO3 0.591 0.253 0.429 0.486 0.834 0.78 0.548 0.225 0.959 -0.26 0.654 0.697 -0.056 0.984
F 0.059 0.943 0.042 0.113 0.907 0.357 0.89 -0.229 0.972 0.363 0.67 0.227 0.593 0.983
Cl 0.942 -0.021 -0.053 0.121 0.905 0.864 0.429 -0.2 0.97 0.761 0.05 0.613 0.181 0.989
SO4 0.964 0.077 0.087 -0.13 0.96 0.438 0.723 -0.285 0.795 0.159 0.805 0.104 -0.431 0.87
NO3 0.292 -0.17 -0.092 0.822 0.798 0.966 0.251 -0.029 0.997 0.815 -0.234 0.366 0.372 0.991
Na 0.747 0.179 0.073 0.619 0.978 0.942 0.33 0.038 0.998 0.686 0.197 0.347 -0.52 0.9
K 0.834 -0.03 0.269 0.245 0.828 0.814 0.356 0.11 0.801 0.496 0.75 0.163 -0.216 0.883
Ca 0.662 0.041 0.540 0.327 0.839 0.534 0.838 -0.086 0.994 -0.1 0.241 0.849 0.438 0.981
Mg 0.909 0.207 0.043 0.307 0.964 0.936 0.279 0.198 0.994 0.963 0.111 -0.188 0 0.975
Al -0.265 -0.297 0.825 0.081 0.846 0.961 0.218 -0.138 0.989 0.032 -0.168 0.901 0.29 0.926
Fe -0.1 0.974 0.019 -0.037 0.96 -0.24 -0.001 0.749 0.619 -0.039 0.893 -0.262 0.117 0.881
Initial Eigen
Value 8.86 3.028 1.88 1.082 11.54 2.73 1.4 6.98 4.07 3.12 1.59
% of variance 52.17 17.81 11.09 6.36 67.88 16.04 8.23 41.07 23.97 23.97 9.39
Cumulative % 52.17 69.99 81.08 87.44 67.88 83.91 92.14 41.07 65.05 83.46 92.85
Chapter 4
79
4.4. Summary
The study on hydrogeochemistry of surface and subsurface waters along the Nethravati-
Gurupur catchment reveals intense weathering of source rock as the major source of
chemical elements to the river and groundwater; agricultural and atmospheric constituents
are the additional sources of chemical elements.. There is a clear seasonality in
groundwater chemistry which is mainly because of hydrological functioning of the
watershed i.e., recharge and discharge functioning of the aquifer. The seasonality explain a
clear decrease in major ions like Ca, Na, Mg, K, HCO3 and SiO2 and an increase in anions
like Cl, SO4 and NO3 during the monsoon. The study shows that the groundwater is
meteoric in origin and recharged directly from the local precipitation during the monsoonal
season whereas the mixing of groundwater with surface water is observed soon after the
withdrawal of monsoon. The groundwater feeds the surface water during the lean river
flow season. Thus, the study concludes the mixing of closely related two hydrological
compartments, river and groundwater in the subsurface regions of the study area..
Chapter 4
80
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