Quantification of source contributions to the water budgets of the Ganga (Hooghly) River estuary, India

Accepted Manuscript Quantification of source contributions to the water budgets of the Ganga (Hooghly) River estuary, India

Saumik Samanta, Tarun K. Dalai, Sameer K. Tiwari, Santosh K. Rai PII: DOI: Reference:

S0304-4203(18)30012-4 doi:10.1016/j.marchem.2018.10.005 MARCHE 3602

To appear in:

Marine Chemistry

Received date: Revised date: Accepted date:

9 January 2018 25 June 2018 15 October 2018

Please cite this article as: Saumik Samanta, Tarun K. Dalai, Sameer K. Tiwari, Santosh K. Rai , Quantification of source contributions to the water budgets of the Ganga (Hooghly) River estuary, India. Marche (2018), doi:10.1016/j.marchem.2018.10.005

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ACCEPTED MANUSCRIPT Quantification of source contributions to the water budgets of the Ganga (Hooghly) River estuary, India Saumik Samanta 1,*,# , Tarun K. Dalai1,* , Sameer K. Tiwari2 and Santosh K. Rai2 Indian Institute of Science Education and Research Kolkata, Mohanpur 741246, INDIA 2 Wadia Institute of Himalayan Geology, Dehradun 248001, INDIA * Corresponding authors ([email protected], [email protected]) # Presently at Department of Earth Sciences, Stellenbosch University, Stellenbosch 7599, South Africa

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ACCEPTED MANUSCRIPT Abstract

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This study is based on comprehensive data on salinity and  18 O values of the Ganga (Hooghly) River estuary waters sampled during six seasons of contrasting water discharge over two years. In addition, the data for the groundwater collected from areas in proximity to the estuarine transect are also discussed. The  18O values and salinity depict strong positive correlations (r2 : 0.96-0.99) suggestive of efficient mixing in the estuary. The intercepts of the regression lines in the plots of  18 O vs. salinity suggest that the average  18O values of freshwater were the lowest (−8.1 to −8.4‰) in the post- monsoon periods whereas the highest values (−6.2 to −6.6‰) were recorded in the pre- monsoon periods. The results of mass balance calculations carried out using the  18O values of the meltwater and non-melt water (groundwater and rainwater) indicate that meltwater accounts for ~10–25% of the freshwater budget of the Hooghly River in the premonsoon and monsoon periods during two years of the study. In the plot of  18O vs. salinity, several samples plot above the theoretical line of conservative mixing of river water and the seawater; indicating that there is internal source(s) of water within the estuary. The contributions of water from three sources (river water, seawater and groundwater) to the estuary were estimated based on the inverse modeling. The model results of higher fractions of seawater at Gangasagar in the monsoon period compared to the post- monsoon period are consistent with the more intense tidal incursion in the summer months that is driven by the prevalent wind circulation and the surface current in the northern coastal Bay of Bengal. In the upper estuary, the groundwater constitutes ≤10% of the total water flux whereas, in the middle to the lower estuary, the groundwater fractions are typically 20-30%. The observations that the maximum contribution from the meteoric recharge to the Hooghly water flux at Gangasagar is 5-16% and the salinity of shallow groundwater is as high as 4.21; together indicate that there is a component of recirculated saline water in the submarine groundwater discharge to the Hooghly River estuary. Our results of salinity- 18 O covariation over several seasons have implications for the reconstruction of paleosalinity in the estuarine and coastal regions using  18O values of carbonate shells. Keywords: Hooghly River estuary, submarine groundwater discharge, oxygen isotope,

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freshwater sources, paleosalinity

ACCEPTED MANUSCRIPT 1. Introduction Estuaries are regions of physical and biogeochemical processes that are important in modifying the continental fluxes of elements, nutrients and their isotopes to the oceans. While estuaries receive a dominant fraction of their freshwater from the stream flow and rainfall, significant contributions from groundwater to estuaries and coastal oceans are also reported

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(Moore, 1997; Schwartz, 2003; Dowling et al., 2003; Knee and Paytan, 2011; Rengarajan and

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Sarma, 2015). In the trace metal budgets of estuaries and coastal zones, the role submarine

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groundwater discharge (SGD), that has components of both freshwater and re-circulated saline water, is increasingly recognized (Moore, 1997, 1999; Shaw et al., 1998; Dowling et al., 2003;

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Gonneea et al., 2013).

In addition to rainwater and groundwater, the rivers fed by the glaciers in their source

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regions such as the Ganga River (Ramesh and Sarin, 1992), the Yamuna River (Dalai et al., 2002) and the Huanghe River (Zhang et al., 1990) also derive water from snow and glacial melt.

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Thus, detailed understanding of sources of freshwaters and estimation of their relative contributions are essential to quantitatively assess the influence of these water sources in

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regulating the chemical and isotopic composition of estuaries. Furthermore, documenting longterm variations in salinity and streamflow in estuaries is important in understanding,

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management and mitigation of estuarine ecosystems. It is important that the data on the longterm trends for salinity and freshwater inflow are available for estuaries as they help in

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establishing the natural variability that must be understood to determine the impact of anthropogenic activities such as the disposal of industrial discharge, filling of wetlands, water

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development projects such as the dams and barrages. The Ganga River is the largest of the rivers systems in India and splits into two branches at Farakka which is located about 300 km north of the city of Kolkata. The Hooghly River is one of the two branches that flow through India. The Ganga River originates in the Himalaya and integrates water inputs from both rainfall and the meltwater particularly in the upper reaches (Maurya et al., 2011; Siderious et al., 2013; Khan et al., 2017 ). A number of studies have been carried out on the oxygen isotope composition ( 18O) and the source characteristics of waters of the Ganga and its tributaries in the upper reaches (Ramesh and Sarin, 1992; Pande et al., 2000; Dalai et al., 2002; Rai et al., 2009; Maurya et al., 2011). However, detailed studies on 18O

ACCEPTED MANUSCRIPT variation, both on spatial and temporal scales, in the Ganga (Hooghly) River estuary waters and the estimation of relative contributions of water from various sources are lacking. In light of the importance of water flow required for navigation in the Hooghly estuary, the reports of decreasing water discharge and increasing siltation (Parua, 2010) and the reported impact of urbanization and industrialization on water quality parameters such as pH, temperature and salinity (Mitra, 2009; Chaudhuri et al., 2015), it is imperative that the temporal trends in

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streamflow and salinity be monitored systematically.

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This study forms a part of our ongoing investigations on the sources and cycling of

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nutrients, elements and their isotopes in the Ganga (Hooghly) River estuary (Samanta et al., 2015; Samanta and Dalai, 2016; Samanta and Dalai, 2018). Based on the data on salinity and

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18O of waters that were collected during six sampling periods over two years (2012 and 2013), we attempt to determine the relative importance of freshwater (rainfall, river water, meltwater

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and groundwater) and seawater in the overall water budget of the Hooghly River estuary. A specific goal of this study is to evaluate the seasonal variation in the slopes and intercepts of the

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salinity- 18 O covariation trends, determine the underlying causes and assess the significance of such variations. The temporal variation in salinity- 18 O relationships of this study provides a

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base calibration that is essential for using  18 O values of carbonate shells (molluscs and bivalves) as a potential tool in the reconstruction of paleosalinity of estuaries and coastal waters (Rohling

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and Bigg, 1998; Hendry and Kalin, 1997; Dettman et al., 2004; Sampei et al., 2005). In light of the increasingly recognized importance of the groundwater in the trace metal budget of estuaries

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and coastal oceans (Moore, 1997; Moore, 1999; Shaw et al., 1998), the groundwater contribution to the Hooghly River estuary is quantitatively determined based on the inversion modeling of

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data on salinity and  18O. In addition, we assess if the re-circulated seawater component of the submarine groundwater discharge (SGD) influences the water budgets of the Hooghly River estuary.

2. The study area The Ganga River takes its name at Devprayag in the Himalaya where the rivers Bhagirathi and Alaknanda join. The Alaknanda River originates from the snout of the Satopanth and the Bhagirathi Kharak glaciers. The Bhagirathi River originates from Gomukh, the snout of the Gangotri glacier which is located in the Himalaya at an altitude of 3920 m (Maurya et al., 2011).

ACCEPTED MANUSCRIPT Thus, the Ganga River integrates water inputs from both rainfall and the meltwater in the upper reaches (Kumar et al., 2010; Maurya et al., 2011). The Ganga River is also fed by the tributaries that draw water from the extra-peninsular (e.g., the Yamuna and the Kosi) and peninsular India (e.g., the Son, Fig. 1a). At Farakka (Fig. 1a), the Ganga River branches off into two channels: one that flows through India is called the Hooghly River and the other that flows through Bangladesh is called the Padma River. The catchment area of the Hooghly River and its estuary

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experiences monsoonal climate. About 80% of the annual rainfall in the catchment areas is

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derived from the summer- monsoon precipitation (June-September). The annual rainfall recorded

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in the catchment areas of the Hooghly River estuary were ~1310 mm and ~2300 mm in the year 2012 and 2013, respectively (IMD, 2013). The Farakka Barrage was constructed in 1975 to

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divert water from the Ganga River to the Hooghly River. Adequate water flow in the Hooghly River is required to minimize the silt accumulation downstream, a condition which is a requisite

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for the estuary to be used as a navigating waterway for the Kolkata and Haldia ports. The Hooghly River, thus, accumulates water from the Ganga River upstream of Farakka, rainfall in

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its catchment area and the water from a few tributaries (e.g., the Damodar and the Rupnarayan) along its course before draining into the Bay of Bengal (Fig. 1b). Also, the Hooghly River

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estuary receives significant contributions of industrial effluent and urban wastewater which are estimated at ~1150 million liters per day (~13 m3 /sec, Sadhuram et al., 2005).

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3. Sampling and Methodology

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The sampling of the surface water of the Hooghly river estuary was carried out during the pre-monsoon (April-May), monsoon (July-August) and post- monsoon (October-November)

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periods in the years 2012 and 2013. The samples were collected from the upper ~50 cm of the water surface using a plastic bucket after rinsing it several times with the ambient water. The groundwater samples were collected from both shallow and deep aquifers. The shallow samples were collected from the domestic wells and tube wells in the year 2013 at a depth of ~15 m to ~76 m. The deep samples were collected at a depth of ~300 m from the pumping stations of Public Health Engineering Department (PHED, West Bengal) during the post-monsoon period of the year 2012. About ~30 mL water was filtered using a 0.45 m PTFE syringe filter and was stored in pre-cleaned Amber bottles (Tarson®). The filtered samples were poisoned by adding 10 L saturated solution of Sigma-Aldrich® HgCl2 to prevent the biological growth.

ACCEPTED MANUSCRIPT The salinity was measured in situ using the multi-electrode probes (EutechPCSTestr 35). The average accuracy of the measurement of salinity was ±0.01 per mil. The oxygen isotope ratio (18 O/16 O) measurements were carried out by an Isotope Ratio Mass Spectrometry facility at Wadia Institute of Himalayan Geology (WIHG). Towards this, ~ 500-700 L water sample was transferred into a 15 mL borosilicate LabcoExetainer® vial which was then flushed with a HeCO2 gas mixture (99.5% He + 0.5% CO 2 ) for 10 minutes. After flushing, the samples were left at

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32ºC for 16 h for equilibration with a reference tank CO 2 gas. The CO2 was purified from the

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equilibrated gas before being introduced into the mass spectrometer (Thermoscientific® Delta V

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plus). Along with every batch of samples, a laboratory standard (Milli-Q water) that was calibrated against the international standard (VSMOW) was analyzed.

The isotopes ratios

18 O

O 18 O

− 1] × 1000

(1)

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 18 O (‰) = [

( 16 )sample

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(18 O/16 O) were expressed as  18 O values using the following relation

( 16 )VSMOW O

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The average instrumental precision of  18 O measurement was better than 0.06‰.

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4. Results

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The data on salinity and  18 O values have been provided in Table 1. Note that salinity data were reported earlier (Samanta et al., 2015; Samanta and Dalai, 2016). The salinity of the Hooghly

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River estuary water samples varies in the range of 0.12‒25.92‰ during two years of the study. At the mouth of the estuary (Gangasagar), the estuary exhibits the highest salinity (25.92‰) during the pre- monsoon and the lowest salinity (14.46‰) during the post- monsoon period. The

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18O values vary from –0.8 to –6.6‰ during pre- monsoon, –1.9 to –7.9‰ during monsoon and – 3.8 to –9.1‰ during post- monsoon periods (Table 1, Fig. 2). For any given sampling period, the freshwaters (S≤0.3‰) are characterized by the lowest  18O values with a range of–6.2 to –9.1‰. The  18O values at the mouth of the estuary vary from –0.8 to –4.9‰, which are up to ~4‰ lower compared to those reported for the Bay of Bengal water (Somayajulu et al., 2002; Achyuthan et al., 2013). At any given location, the highest  18O values are observed during the pre-monsoon (April- May) period whereas the lowest  18 O values are observed during the postmonsoon period (October-November). The largest seasonal variation of  18O-water at any

ACCEPTED MANUSCRIPT particular location is as high as ~4.4‰ (Fig. 3, Table 1). For locations where sampling was carried out during both the high and low tide periods of the same day,  18 O values of the low tide period samples were lower by as much as ~0.5‰. The variation of  18 O observed in this study is larger than that reported for the Hooghly River estuary (–4.45 to –7.97‰) by Somayajulu et al. (2002). The smaller range of  18O values reported by Somayajulu et al. (2002) can be explained in terms of lower and less variable discharge owing to the limited temporal coverage given their

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sampling span was confined to December in the year 1991. The magnitude of  18 O variation in this study is marginally higher than that (–3.1 to –8.6‰) reported by Ghosh et al. (2013). The

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sampling of Ghosh et al. (2013) differs significantly than ours in that they sampled at only one location in the Muriganga channel over several months and that their samples covered a sa linity

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range of 0.7 to 13.7‰, much lower than the range of 0.12 to 25.92‰ observed in this study. For the groundwater samples, salinity vary in the range of 0.39 to 4.21‰, and  18O

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values depict a variation from –6.5 to –3.3‰. The numbers of groundwater samples are not enough to discern any spatial and temporal correlations for  18O values. For shallow

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groundwater samples,  18 O values increased with depth up to a depth of ~50 m. The shallowest

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sample (HGH13/SGW-6, 15 m) depicted the lowest  18 O value (-6.5‰).

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5. Discussion

5.1. Mixing in the Hooghly estuary

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The variation of  18 O as a function of salinity is plotted in Fig. 2. The regression statistics (regression coefficients and slopes of the regression lines) with their standard errors have been

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given in Table 2. Note that the regression lines are not plotted in Fig. 2. It is observed that  18O and salinity exhibit strong positive correlations (r2 : 0.96‒0.99) for all the sampling periods. Such strong correlations are suggestive of efficient mixing of river water and seawater irrespective of seasonal variation in the freshwater discharge. The  18O and salinity covariation trends, however, do not exactly conform to the theoretical lines defined by conservative mixing of seawater and freshwater (Fig. 2) as some of the data points are off the mixing lines. The causes and implications of deviation of data points from the conservative mixing lines are discussed in detail in section 5.4. The inference of near-perfect mixing is consistent with the knowledge that there is

ACCEPTED MANUSCRIPT insignificant variation of salinity with depth in the Hooghly River estuary and that the tidal reach is at least up to Diamond Harbour (Sadhuram et al., 2005; Mukhopadhyay et al., 2006) that is located ~100 km upstream of the mouth of the estuary (Fig. 1b). The influence of tidal mixing on 18O distribution is also evident from the observation that the rate of increase of  18 O as a function of distance (Fig. 3) is much higher in the lower estuary starting from the point at ~100

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km downstream of Kolkata, whereas in the upper estuary  18O variation with distance is

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relatively less significant. It is noteworthy that the saltwater intrusion in a well- mixed estuary depends on its shape and geometry (Savenije, 2005). Estuaries that are relatively narrow in the

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upper reaches and funnel-shaped at the mouth show a gentle change in salinity in the upper estuary and a steep change in salinity in the middle to the lower estuary. Given that the Hooghly

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River estuary is funnel-shaped and macro-tidal (Mukhopadhyay et al., 2006; Rudra, 2018), a steep variation of  18O in the middle to the lower estuary (Fig. 3) is expected. The salinity of the

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sample collected at Kolkata is as low as 0.16‰ (Table 1) during the pre- monsoon period when the tidal influx is expected to be higher compared to the monsoon and post- monsoon periods

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(Sadhuram et al., 2005; Mukhopadhyay et al., 2006). This observation suggests that the tidal influx is unlikely to change the freshwater characteristics at Kolkata. The inference that the tidal

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mixing is insufficient to smooth out the heterogeneity of the freshwaters draws support from the observed variation of  18 O values in the freshwaters: –6.6 to –6.2‰ during pre- monsoon, –7.9 to

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–7.0‰ during monsoon and –9.1 to –8.0‰ during the post- monsoon period (Table1). A part of this observed variation can be attributed to different age and origin (e.g., rainfall and streamflow)

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of freshwater and addition of groundwater.

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5.2. Freshwater in the Hooghly River: sources and processes The largest variation of  18 O (~1‰) is observed for freshwaters of the post- monsoon period of the year 2012 and the monsoon period of the year 2013. The variation of  18 O in the freshwaters of the Hooghly River is a collective result of the composition ( 18 O) and proportion of various sources: meltwater from the upper reaches, rainfall in the catchment, probable groundwater contributions and the water supplied by tributaries that join the Hooghly River in the lower reaches.

ACCEPTED MANUSCRIPT The  18O-intercepts obtained from regression of salinity and  18 O data provide a measure of the average  18O values of the freshwater end member (Table 2). We consider the estimates of freshwater  18 O values obtained based on such an approach to be better than those obtained by averaging the  18 O values of the individual freshwater samples. This is because the freshwater 18O values obtained by averaging are likely to suffer from the uncertainties due to factors such

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as the bias of spatial coverage of sampling and the unusual  18O values of a sample due to

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specific local process(es) (e.g., the addition of groundwater). However, extrapolation of the regression lines to the  18O axis ensures that the effect of the uncertainties such as those

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mentioned above is minimized as the  18 O values of the freshwaters (i.e., the intercepts) are statistically determined by the scatter of the continuously changing salinity and  18O values

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resulting from mixing of freshwater and seawater. Based on the regression analysis (Table 2), it is estimated that  18 O values for the freshwater are the lowest (–8.1 to –8.4‰) during the post-

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monsoon and the highest (–6.2 to –6.6‰) during the pre-monsoon periods with intermediate values during the monsoon periods. The determination of freshwater  18 O values from the

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regression of salinity and  18O data (Table 2) is based on the assumption that the  18 O values of

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the estuary water are insignificantly influenced by evaporation and mixing with water from sources other than river water and seawater. We discuss the role of these processes in the

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following.

The effect of isotopic fractionation due to evaporation on  18O of waters is governed by a

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number of environmental parameters, the most important being the ambient relative humidity such that higher the humidity, the smaller the change in  18 O values of water undergoing

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evaporation (Kendal and Caldwell, 1998). The effective change in  18 O of water is due to the combined effect of both equilibrium and kinetic fractionation. The estimated rate of evaporation in the Hooghly estuary, (1.74–4.36) × 106 m3 /day (Banerjee, 2013), constitutes only 0.5–3.6 % of the freshwater discharge to the estuary. The relative humidity of the estuary region remains in the range of 70–90% throughout the year (Sen and Naskar, 2003). Owing to high relative humidity in the area and the turbulence associated with the tidal influx and monsoonal discharge, we contend that the influence of evaporation on  18 O of the estuary water is negligible (cf. Craig and Gordon, 1965; Gat, 1996). Such a contention draws support from the observation that the

ACCEPTED MANUSCRIPT observed slope of 6.8 for the D– 18 O regression line of the Hooghly estuary waters (Ghosh et al., 2013) is only marginally lower than the slope of the local rainwater. In addition to the evaporation, the water contribution in the lower reaches can also result in the change of  18 O of the estuary water. The two major tributaries in the lower reaches, the Rupnarayan and the Damodar, join the Hooghly River at a location upstream of Diamond

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Harbour and together they contribute ~12% of water to the annual water discharge of the

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Hooghly River (Maity and Maiti, 2013; GRDC, 2012). Also, some small tributaries drain into the

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Hooghly River before the estuarine transect. However, water contributions from these small tributaries are rather insignificant (Mukherjee et al., 2007a). At locations downstream of the confluence of the Rupnarayan River and the Hooghly River but upstream of the tidal reach,  18O

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values of the Hooghly water during the post- monsoon period of 2012 are higher by up to 0.6‰ compared to the locations upstream of the confluence. In contrast, during the monsoon period of

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the year 2013,  18O values at a location downstream of the confluence is decreased by up to 0.8‰ compared to the upstream values. These observations suggest that the water contributions

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from the rivers Rupnarayan and Damodar, and their  18 O values may not be imparting a

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consistent change in  18 O values of the Hooghly River freshwaters. It is noteworthy that consistent and noticeable modifications of the Hooghly water  18 O values via the addition of

and the Hooghly River.

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water from the tributaries require a significant contrast between the  18O values of the tributaries

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The observation of lower  18 O values of the freshwater during the post- monsoon than during the monsoon period that accounts for ~80% of the annual rainfall in the catchment area,

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albeit counterintuitive, is not unexpected. The rainfall data reported for locations in the upper and middle reaches (Devaprayag, Rishikesh, Roorkee, Lucknow) and lower reaches (Patna, Kolkata) depict similar seasonal trend in  18 O: the lowest values in post-monsoon (–14.7 to –7.5‰) and the highest values in the pre- monsoon (–4.5 to –2.1‰, Table 3). Massive and continuous rainout throughout the monsoon period is expected to cause a depletion of

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thus resulting in the lowest  18 O values in the post-monsoon rainfall (Yang et al., 2011). The observed similarity in the seasonal variation of  18O between the rainwater and the river water indicates that rainfall exerts a major influence on the variation of  18 O of river water. Using an

ACCEPTED MANUSCRIPT average value of –7.7‰ for the rainfall during the monsoon period (Table 3) and the rainwater fractions of 13–20% in the river water discharge during the monsoon periods of the years 2012– 2013, it is calculated that the rainfall imparts a change of 1.0 to 1.5‰ to the  18 O value of the Hooghly River freshwater. The influence of rainfall on the  18 O value of the freshwater during the pre- monsoon periods, however, are relatively minor and fall in the range of 0.1 to 0.3‰. It is,

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however, noteworthy that the estimated freshwater  18O (Table 2) is lower than the  18 O of

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rainfall in the pre-monsoon period. The implication of this observation is discussed in section

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5.3. 5.3. The meltwater contribution

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The rivers Alaknanda and Bhagirathi, which join together to form the river Ganga, draw water from the glacial melt in their source region. Some other rivers such as the Gandak and the

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Kosi that integrate water from snow and glacial melt in the Himalaya join the Ganga River at various locations along its course. The importance of meltwater in the Ganga River would vary

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both spatially and temporally. While the meltwater fractions are likely to be significant in the upper reaches and proximity to the glaciers, the cumulative contributions of water from other

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sources may overwhelm the meltwater supply in the lower reaches. In the summer months, particularly during the pre- monsoon and monsoon periods, the meltwater contributions to the

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total flow are likely to be higher owing to a higher temperature. The studies on the estimates of the meltwater in the Ganga River in the upper reaches are

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limited. Furthermore, the existing studies do not agree on the results of meltwater estimates. Based on the  18O and EC of waters, Maurya et al. (2011) reported an average meltwater fraction

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of 32% in the Ganga River at Rishikesh. The study of Khan et al. (2017), however, showed t hat such high estimates of meltwater fractions are inconsistent with the observed degree of glacial thinning. They provided meltwater estimates of 10-15% in the Ganga River at Rishikesh based on the mass balance of  18O and EC of waters. Although the results of both of these studies are based on the mass balance of  18 O and EC of water, the inconsistency between the estimates of meltwater was ascribed to the difference in the end member composition that arise s due to the seasonal variation of  18 O of water sources (Khan et al., 2017).

ACCEPTED MANUSCRIPT As discussed earlier, the  18O values of the rainfall in the catchment area of the Hooghly River show clear seasonal variation, with the highest  18 O of rainfall in the pre- monsoon and the lowest in the post- monsoon periods (Table 3). The  18 O-intercepts determined from the regression of salinity- 18O data of seasonally collected samples (Table 2) are generally bracketed by the  18 O values of rainfall and the groundwater that were reported for the monsoon and post-

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monsoon periods in the upper and lower reaches of the Ganga River (Tables 3 and 4). In

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contrast, the  18O-intercepts for the pre- monsoon periods (–6.6 to –6.2‰, Table 2) are significantly lower than the  18 O values reported (–5.1 to –3.5‰, Tables 3 and 4) for rainfall and

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groundwater during the pre- monsoon period. Together, these observations are in line with the expectation that the meltwater contributions are likely to be more significant in the pre- monsoon

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periods. In this study, the estimates of the meltwater contributions to the freshwater of the Hooghly River in the pre- monsoon and monsoon periods were made based on a simple mass

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balance of  18 O of the meltwater and non-meltwater (groundwater and rainwater): (2)

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 18 O MWfMW +  18 O NMW fNMW =  18O Hooghly

where subscripts MW and NMW represent the meltwater and non- meltwater (groundwater and

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rainwater), respectively. The fractions of meltwater and non- meltwater are represented by fMW and fNMW such that fMW + fNMW = 1. The freshwater  18O values of the Hooghly River

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( 18O Hooghly ) are based on the  18O-intercept values obtained from the regression of data (Table 2). The  18O value of the non- meltwater was obtained based on the average of the reported  18O

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values of the groundwater and rainwater, and the  18O value of the meltwater was based on the

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data reported for glaciers in the Himalaya (Table 4; see the footnotes for the data sources). The results of isotopic mass balance calculations show that the meltwater accounts for 20±12% of the freshwater of the Hooghly River in pre- monsoon period of 2012 and 24±13% in the premonsoon period of 2013. The meltwater fraction in the monsoon periods varies from 13±12% in the year 2012 to 23±16% in the year 2013. The  18O value of the meltwater is likely to increase downstream if evaporation is significant during its transport from the upper reaches to the lower reaches. While it is not straightforward to quantitatively assess the degree of evaporation of the meltwater during its transport, we recognize that our estimates of meltwater fractions are upper limits if the  18 O values of the meltwater are subject to significant modification via evaporation.

ACCEPTED MANUSCRIPT One of the striking results that emerge from the above calculations is that the uncertainties associated with the estimates of the meltwater fractions are rather large. These errors are the collective outcome of the uncertainties of the end- member source composition (Table 4) as well as the contrast between the  18 O values of the sources. Considering that the amount of rainfall and groundwater (non- melt water) and their  18O depict large temporal and

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spatial variation, the meltwater fractions are very likely to show the corresponding variation both

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in time and space. This reasoning allows us to contend that the uncertainties of the meltwater estimates of our study are a fair reflection of the actual variation in time and space. It is

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noteworthy that our estimates of the meltwater fractions, within the errors of estimates, agree well with the estimates of 12-38% of snowmelt in the river runoff at Farakka during the pre-

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monsoon period that was obtained independently based on high-resolution dynamical regional climate models (Siderius et al., 2013).

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5.4. Intra-estuarine sources of water

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It is observed for all the sampling periods that at any given salinity,  18O values of the waters are higher in the year 2012 than in the year 2013 (Fig. 2). The  18O differences between the two

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years are more pronounced specifically in the monsoon period. Such annual differences in the 18O are most likely a result of variable amounts of rainfall and groundwater contributions

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between two years. In the catchment area of the Hooghly estuary, the annual rainfall in the year 2013 (2300 mm) was 75% higher than that in the year 2012 (1310 mm; IMD, 2013). The

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catchment areas in the upper reaches of the Hooghly River also experienced 25-60% higher rainfall in 2013 compared to 2012. It is observed that the  18 O values of the Hooghly estuary for

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the year 2012 plot generally above the line defined by conservative mixing of seawater and freshwater (Fig. 2). Such an observation also exists for the year 2013 although the deviation of the data points from the mixing trend is less pronounced. Together, these observations suggest that there is internal source(s) of water within the estuary which is likely more significant in the year 2012 than in 2013. The most likely internal source of water is the groundwater discharge into the estuary. Taken together, the following observations: – the annual differences between the years 2012 and 2013 in the degree of deviation of the estuarine  18 O values from the conservative mixing line, higher rainfall amount and lower  18O values of the freshwater in the monsoon period of the year 2013 (Table 2), lower rainfall amount and higher  18O values for the

ACCEPTED MANUSCRIPT monsoon freshwater in the year 2012– all suggest that the variation in the relative proportions of the rainfall and groundwater in the Hooghly estuary regulate the salinity- 18O distribution for a given period of a year. As indicated earlier, groundwater is the most likely candidate for the additional source of water in the Hooghly River estuary. The salinity of deep groundwater is 0.76, indicating that the deep groundwater does not have a component of seawater. In contrast, the salinity of the shallow groundwater is as high as 4.2‰, and is suggestive of contribution of

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submarine groundwater discharge (SGD) to the estuary. The SGD consists of two major components: the fresh water and the saline water. The freshwater water of the SGD is the

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percolated meteoric water in the aquifer that is sourced from precipitation and/or surface water and is driven to the coastal ocean by the hydraulic gradient mainly during the low tide period.

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The saline component of the SGD results from the recirculation of seawater in the coastal aquifer. Due to the encroachment of seawater into the coastal aquifer during the high tide time,

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the mixing occurs between the fresh meteoric water and saline water (Moore et al., 1999; Burnett et al., 2003; Abarca et al., 2013). The chemical interaction of encroached seawater with the

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aquifer solids results in the release of elements and their isotopes from the aquifer to the dissolved phase (Moore et al., 1999; Abarca et al., 2013). It is interesting to note that salinity and

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18O values of shallow groundwater do not define a significant linear trend. Such an observation suggests that (i) the groundwater composition is not a result of simple mixing of freshwater and

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seawater and (ii) there has been chemical interaction between the seawater and the aquifer solids, a process that results in additional modification of the salinity of the groundwater beyond what is

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predicted from mixing of freshwater and seawater. In contrast, the  18 O values are unlikely to be subject to such modifications. Consequently, the degree of variation of 18O values of shallow

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groundwater is less whereas the salinity depicts a variation by up to nine folds. 5.5. Source apportionment using an inverse model The contributions of water from various sources (river water, seawater, and groundwater) to the estuary can be estimated using both the forward modelling as well as the inverse modelling (Negrel et. al., 1993; Moon et. al., 2007; Tripathy and Singh, 2010; Rahaman and Singh, 2012; Tripathy and Das, 2014). Here we estimate the relative contributions of river water, seawater, and groundwater in the Hooghly estuary using an inversion model. The application of the inversion model, using multi- mixing equations, was first developed by Negrel et al. (1993) for

ACCEPTED MANUSCRIPT apportionment of sources of dissolved elements in rivers. Such a model was later applied to estimate weathering contributions to the elemental mass budgets of the major rivers of the world (Gaillardet et al., 1999; Moon et al., 2007; Tripathy and Singh, 2010). The model is developed based on different mass budget equations that define the mixing of the tributaries and rivers. Based on the salinity, Sr and

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Sr/86 Sr of the estuary water, the inversion model was also used to

estimate the proportion of freshwater, seawater and SGD in the estuary (Rahaman and Singh,

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2012).

Previous studies have quantified the fractions of seawater, river water and groundwater in

2012). While

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estuaries using salinity, 87 Sr/86 Sr and Sr concentrations (Huang et al., 2011; Rahaman and Singh, Sr/86 Sr and Sr concentrations are useful tracers of mixing, it should be cautioned

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that their use could be complicated in estuaries where dissolution of particulate carbonate phases and/or the ion exchange process driven by solute-particle interaction could be significant. On the

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other hand, salinity and  18 O values are ideal conservative tracers implying that their estuarine variation can be brought about mostly by mixing of waters of variable composition. Given that in

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the Hooghly River estuary, the dissolution of particulate carbonate phases is inferred (Samanta et al., 2015) and the solute-particle interaction is significant in the distribution of the dissolved

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concentrations of Ba (Samanta and Dalai, 2016) and other metals (Samanta and Dalai 2018), the data on salinity and  18O values are better suited to estimate relative water contributions from

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various sources.

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In this study, we developed the model based on inputs from three water sources, river water, groundwater and seawater. We chose a set of a priori end member compositions based on

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available data on  18 O and salinity of end- member sources (Table 5). With the a priori parameter values as inputs, the algorithm of the inversion yields a set of a posteriori values along with the optimized errors through successive iterations aimed at achieving the best- fit for the whole set of model equations. Given that the data of all samples for a given sampling period were used, the inversion model was applied to an over-determined system of equations. The a priori values of salinity and  18 O for riverine freshwater, seawater and groundwater were decided based on the data of this study and those reported earlier (Somayajulu et al., 2002; Achyuthan et al., 2013), and are provided in Table 5. The deep groundwater of the

ACCEPTED MANUSCRIPT Bengal Basin is significantly older (>>100 y) and do not contribute water to the GangaBrahmaputra river system and its tributaries (Dowling et al., 2003). Very low concentrations of the heavy metals, at the level of less than the detection limits, in the deep groundwater samples, together with the observation of massive production of these metals in the estuary (Samanta and Dalai, 2018), indicate that the deep groundwater in the Hooghly River estuary basin is not a source of water to the estuary and does not have a component of the recycled seawater. Such an

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interpretation is consistent with the low salinity (≤0.76‰) observed in the deeper samples (Table

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1). Thus, the data of deep groundwater were not considered while deciding the a priori

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composition of the end-member sources.

𝑆𝑎𝑙 𝑚𝑒𝑎𝑠 = ∑𝑛𝑖=1 𝑆𝑎𝑙 𝑖 × 𝑓𝑖

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The relevant equations that were used to develop the model are given below: (3)

(5)

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∑𝑛𝑖=1 𝑓𝑖 = 1

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𝛿 18 𝑂𝑚𝑒𝑎𝑠 = ∑𝑛𝑖=1 𝛿 18 𝑂𝑖 × 𝑓𝑖 (4)

where i (=1‒3) represents any of the three sources considered, i.e., riverine freshwater, seawater

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and groundwater; the subscript meas represents the measured values and f indicates the fractional contribution of water from a given source. The equations (3) to (5) can be combined to yield a

(6)

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d = g(p)

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general equation

where d and p represent the measured value and the value of the model parameter, respectively.

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The best possible set of the model parameters along with their corresponding uncertainties were obtained using the equations that were generated based on a nonlinear weighted fit following the Quasi-Newton method (Tarantola, 2005; Tripathy and Singh, 2010; Rahaman and Singh, 2012; Tripathy and Das, 2014). More details on the sensitivity test of the model are given in the supplementary material. It can be observed from the sensitivity test results that the degree of variation of a posteriori values is insignificant compared to that of the a priori values, indicating that the a posteriori parameter values are not biased by choice of a priori values. However, the errors of the a posteriori values seem to be dependent on the uncertainties associated with the a priori values.

ACCEPTED MANUSCRIPT The a priori values used for the inversion and the a posteriori values obtained through inversion of the end member source compositions are given in Table 5. There are several lines of observations that attest to the general reliability of the model results. First, for any given sampling period, the a posteriori values of  18 O and salinity of seawater end member (Table 5) agree well the measured  18 O and salinity of the Bay of Bengal (Somayajulu et al., 2002; Achyuthan et al., 2013; Singh et al., 2013). Second, the model yielded the lowest salinity and

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18O values for the seawater (Bay of Bengal) during October-November, a period that is characterized by the lowest  18 O values of the rainwater (Sengupta and Sarkar, 2006; Kumar et.

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al., 2010) and the lowest measured salinity at Gangasagar (Table 1). Third, the model produced a posteriori  18 O values for the Bay of Bengal (‒2.1 to ‒1.4‰) that were more depleted for the

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monsoon and post-monsoon periods of the year 2013 compared to the corresponding periods of the year 2012. These results are consistent with a higher freshwater discharge in the Hooghly

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River in the year 2013 given that the annual rainfall in the catchment area was 75% higher in the year 2013 than in the year 2012.

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The fractional water contributions from three sources, obtained from the inverse model,

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are plotted as a function distance downstream from Kolkata (Fig. 4). The river water fractions at Gangasagar increase from 7‒9% during the pre- monsoon to 29‒43% during the post- monsoon.

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The seawater fractions at Gangasagar are ~75% during the pre- monsoon periods, ~60% during the monsoon periods and ~35% during the post- monsoon periods. Although these results are

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consistent with the seasonal variation of salinity and  18O at Gangasagar (highest values in the pre-monsoon period and the lowest in the post-monsoon period), the observation of the lowest

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seawater fractions in the post- monsoon period is intriguing. Considering that the monsoon period is characterized by the highest river water discharge, one would intuitively expect the seawater fraction to be the lowest during this period. Thus, a higher seawater fraction in the post- monsoon period than in the monsoon period requires that the relative fractions of seawater and river water at any given location in the estuary are regulated by the combined influence of both river water discharge as well as the seawater influx. The inspection of the wind stress vectors and the surface circulation in the northern Bay of Bengal (Shankar et al., 2002; Unger et al., 2003) reveals that both the wind stress vectors and the surface currents are directed into the estuary in the summer months (monsoon period) whereas they are directed away from the estuary in the winter months

ACCEPTED MANUSCRIPT (post- monsoon period). These observations are suggestive of higher tidal influx in the summer months, an inference that is supported by the reported studies (Sadhuram et al., 2005; Mukhopadhyay et al., 2006). Thus, the estimates of higher seawater fractions at Gangasagar in the monsoon period compared to the post-monsoon period can be reconciled with the collective influence of both the river water flow and the seawater influx.

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The model results on groundwater fractions at locations upstream of Diamond Harbour

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are mostly <10% for all the sampling periods. The groundwater fractions at any given location,

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particularly for the monsoon and post- monsoon periods, are generally higher in the year 2012 than in the year 2013. In the middle to the lower estuary, the groundwater fractions are mostly 20-30% with a maximum of 36%. To evaluate whether there is a component of recirculated

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seawater in the submarine groundwater discharge to the estuary, the contribution from the meteoric recharge was estimated based on the rainfall amount integrated over the whole

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catchment area from Farakka up to the mouth of the estuary. Based on the knowledge that the meteoric recharge accounts for up to 15% of the total precipitation in the Bengal Basin (SWID,

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1998; Mukherjee et al., 2007b), the maximum contribution of the meteoric recharge to the Hooghly River water flux at Gangasagar were estimated. Such calculations indicate that the

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upper limits of the meteoric recharge contributions during the years 2012-2013 can account for 5-10% of the Hooghly River water flux in the pre- monsoon, 13-16% in the monsoon and 7-15%

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in the post- monsoon periods. It is noteworthy that the estimated groundwater fractions at Gangasagar (up to 18% in the pre- monsoon, up to 36% in the monsoon and the post- monsoon)

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are significantly higher compared to the estimated maximum groundwater contributions from the meteoric recharge in the catchment area. Such an observation would require that a part of the

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groundwater contributions in the Hooghly River estuary is supplied by the re-circulated saline groundwater from the shallow aquifers. The observations of higher groundwater fractions in the middle and lower estuary and high salinity of shallow groundwater (up to 4.21‰); together corroborate the existence of a recirculated seawater component of the submarine groundwater discharge to the Hooghly River estuary. Our contention of the presence of SGD in the Hooghly River estuary is in line with the inference of large contributions of SGD from the GangaBrahmaputra River system to the Bay of Bengal (Basu et al., 2001). The inference of this study also draws strong support from the study of Krishan et al. (2015) who observed significant SGD, based on the data on 222 Rn activities, in areas along both the banks of the Hooghly River estuary.

ACCEPTED MANUSCRIPT The data of Sr and

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Sr/86 Sr in the water columns of the northern Bay of Bengal also support the

SGD contribution from the Bengal Basin to the Bay of Bengal (Chakrabarti et al., 2018). On the contrary, the work of Mukherjee et al. (2007b) did not recognize the SGD to be significant in the western Ganga Basin. Such discrepancies between the estimates of SGD from the tracer-based approach (this study, Krishan et al., 2015; Basu et al., 2001) and hydrological and hydraulic modeling, albeit intriguing, are not uncommon (cf. Harvey, 2002; Basu et al., 2002). Systematic

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investigations are necessary to (i) address such discrepancies and (ii) quantify the contribution of

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the recirculated seawater of the SGD by using tracers such as Rn isotopes.

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The slopes of 18 O-salinity regression lines and implications for the reconstruction of

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paleosalinity

The data generated in this study allow making a critical evaluation of the seasonal covariation of

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salinity and  18 O over two years. From the regression statistics given in Table 2, it is observed that the slopes of the  18 O‒salinity regression lines increase from ~0.2 in the pre- monsoon period

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to 0.3 during the post- monsoon period. Such variations in the slopes can result if one or both the end members show temporal variability in their  18 O values. It is unlikely that the  18O value

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of the seawater would change significantly within such a short period. However, as discussed earlier in section 5.2, the  18 O values of the freshwaters depict significant seasonal variation. As

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a consequence, the slopes of the  18 O-salinity regression lines are modified seasonally by the variable  18 O values of the freshwaters. We discussed below how the variation in the slopes of

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the  18 O-salinity regression lines has implications for the reconstruction of paleosalinity using the  18 O values of the carbonate shells such as molluscs and bivalves (Rohling and Bigg, 1998,

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Hendry and Kalin, 1997; Dettman et al., 2004; Sampei et al., 2005). The studies aimed at the reconstruction of paleosalinity use the empirical salinity- 18O relationship that needs to be independently established for specific estuaries and coastal regions under study. In this study, for any given sampling period, the slopes of the  18 O-salinity regression lines are identical within the error between the years 2012 and 2013 with the exception of the post-monsoon period (Table 2). Thus, the results of this study provide a robust 18O-salinity calibration for the Hooghly River estuary. If paleosalinity reconstruction is required at seasonal scale resolution in the estuarine and coastal regions where large seasonal variation in

ACCEPTED MANUSCRIPT the slopes of the  18 O-salinity regression lines is expected, the organisms that are used as archives for reconstruction of paleosalinity must grow fast enough to record the signal ( 18 O) of a particular season. If the rate of growth of these organisms is slower relative to that of seasonal variation of  18O, the signals would be integrated over more than one season and the reconstruction of paleosalinity is expected to yield an average of the signal over the period of growth of the organisms. In other words, the organisms that grow relatively faster and preserve

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the seasonal  18 O in their shells are better suited for reconstruction of paleosalinity at a high temporal resolution in regions such as the Hooghly estuary where there is a significant seasonal

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variation of  18O with salinity. In addition, the precision of paleosalinity reconstruction will be decided by the magnitude of the seasonally variable slope of the  18O-salinity regression line.

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For example, in the pre- monsoon period (slope = 0.2, Table 2), salinity can be reconstructed with a precision of ~0.5‰ using the  18O of the shell (with a typical measurement precision of 0.1‰)

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whereas in the monsoon period (slope = 0.27), salinity can be determined with a precision of ~0.4‰. It is noteworthy that the slopes of the  18 O-salinity regression lines of the post- monsoon

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periods vary between the two years, 2012 and 2013 (Table 2). The most likely explanation for this observation is the  18 O variation between the months of collection; the sampling month was

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October in the year 2012 whereas it was November in the year 2013. The available data (Kumar et al., 2010; Sengupta and Sarkar, 2006) show that rainfall in October records the lowest 18O

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during the whole year and that the  18 O values of rainfall in November are as much as ~9‰ higher than those in October. The results of this study also support such a trend; the freshwaters

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of the October 2012 collections record lower  18 O values than those of the November 2013 (Fig. 2), thus resulting in a higher  18 O-salinity slope in the post- monsoon period of the year 2012.

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Considering that the  18 O value of the freshwater is the major driver of the slopes of the  18 Osalinity regression lines, the differences in the slopes is indeed expected for samples collected during different months. Such differences also underscore the need for data at a higher temporal resolution for obtaining a robust calibration of salinity- 18O relationship and meaningful reconstruction of paleosalinity. 5.7. Conclusions The data, observations and the model results allow us to draw the following major conclusions.

ACCEPTED MANUSCRIPT i.

Strong  18 O‒salinity covariation trends are suggestive of efficient estuarine mixing between river water and seawater. The rate of tidal influx, however, is insufficient to homogenize the variation of  18 O values of the freshwater.

ii.

The  18 O‒intercepts of the  18 O‒salinity regression lines provide the average values of the freshwaters for a given sampling period. The pre- monsoon periods are characterized

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by the highest  18O values whereas the post- monsoon periods record the lowest  18O

iii.

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values.

Clear annual variation of  18 O values is observed, particularly for the monsoon and post-

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monsoon periods; with the waters of the year 2012 recording higher  18O values compared to those collected in the year 2013. Such distinct annual variation is consistent

iv.

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with the recorded differences between the in rainfall amount over two years. The mass balance of  18 O values of the meltwater and non- melt water indicates that

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during the study period covering two years, the meltwater contributions account for ~10‒25% of the freshwater of the Hooghly River in the pre- monsoon and monsoon

v.

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periods.

The scatter of the data points in the  18O vs. salinity plots requires the presence of

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source(s) of water within the estuary. The results of inverse modeling indicate that groundwater fractions in the middle to the lower estuary are in the range of 20-30%

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particularly in the monsoon and post- monsoon periods. These estimates are higher than

(5-16%).

The above observation along with higher groundwater fractions in the middle and lower estuary and salinity as high as 4.2‰ in the shallow groundwater samples; together

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vi.

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the maximum meteoric recharge contributions to the Hooghly water flux at Gangasagar

corroborates the presence of recirculated saline water as a component of SGD to the Hooghly River estuary.

ACCEPTED MANUSCRIPT Acknowledgments

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SS thanks IISER Kolkata for a research fellowship. This study is funded by a financial grant to TKD by the Ministry of Earth Sciences (MoES), India under the GEOTRACES Program. Vikas Agrawal and Prem Chand Kisku are acknowledged for their help during the sampling campaigns. Generous help from Gyana Ranjan Tripathy in the inverse model calculations is thankfully acknowledged. We thank two anonymous reviewers for their constructive comments.

ACCEPTED MANUSCRIPT Figure Captions Fig. 1 (a) The map of the Ganga-Brahmaputra River system and the Hooghly River estuary. (b) The water sampling locations and the major localities in proximity to the estuarine transect are also shown.

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Fig. 2 The variation of 18O with salinity in the Hooghly River estuary. The linear covariation trends (regression statistics are given in Table 2, but the regression lines are not plotted) are suggestive of efficient mixing of river water and seawater. The solid lines (black: the year 2012, grey: the year 2013) represent the theoretical mixing of river water and seawater. The seawater composition (S = 34.5‰,  18O = 0.27‰) is based on the reported data for Bay of Bengal (Somayajulu et al. 2002). The data for groundwater are also plotted. PrM: Pre- monsoon, M: Monsoon, PoM: Post-monsoon

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Fig. 3 The seasonal variation of  18O values in the Hooghly River estuary as a function of distance downstream from Kolkata. In general, the pre-monsoon waters have the highest and the post-monsoon waters have the lowest  18O values. Note the shift in the rate of variation of  18O values at ~100 km (marked by the dashed vertical line). Empty symbols: Year 2012, filled symbols: Year 2013, circles: pre-monsoon, squares: monsoon, triangles: post-monsoon.

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Fig. 4 The estimated water contributions plotted as a function of distance downstream from Kolkata. The fractional water contributions along with their uncertainties are marked by shaded envelops (river water: light grey, seawater: white and groundwater: dark grey).

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ACCEPTED MANUSCRIPT Table 1. The details of sampling locations, salinity and oxygen isotope composition (  18O) of the Hooghly River estuary waters and groundwater Salinity Sample Code

Date

Location

Latitude (N)

Longitude (E)

18

 O (‰VSMOW)

(‰)

22.05.2012

Princep Ghat

22 ○ 33' 21''

88 ○ 19' 50''

0.16

-6.5

HGH12-12

22.05.2012

Achhipur

22 ○ 27' 36''

88 ○ 07' 21''

0.16

-6.3

HGH12-11

22.05.2012

Burul

22 ○ 21' 46''

88 ○ 06' 17''

0.21

-6.2

HGH12-5

21.05.2012

Falta

22 ○ 17' 27''

88 ○ 06' 13''

0.60

-6.3

HGH12-6

21.05.2012

Raychalk

22 ○ 12' 28''

88 ○ 07' 15''

1.02

-5.7

HGH12-1

12.05.2012

Diamond Harbour H

22 ○ 11' 05''

88 ○ 11' 22''

2.50

-3.7

HGH12-1A

22.05.2012

Diamond Harbour L

22 ○ 11' 06''

88 ○ 11' 22''

1.12

-5.6

HGH12-2

12.05.2012

Kulpi

22 ○ 05' 01''

88 ○ 13' 19''

3.44

-5.4

HGH12-3

12.05.2012

Kakdwip Lot No. 8

21 ○ 52' 51''

88 ○ 09' 53''

15.87

-3.0

HGH12-7

21.05.2012

Kachuberia Ghat

21 ○ 51' 33''

88 ○ 08' 41''

16.52

-2.8

HGH12-8

21.05.2012

Sapkhali

21 ○ 50' 44''

88 ○ 06' 45''

14.84

-3.0

HGH12-9

21.05.2012

Light House

21 ○ 39' 26''

88 ○ 02' 29''

24.48

-0.9

HGH12-10

21.05.2012

Gangasagar

21 ○ 37' 53''

88 ○ 04' 24''

25.92

-0.8

HGH12-4

12.05.2012

Namkhana

21 ○ 45' 41''

88 ○ 14' 06''

21.16

-1.8

HGH12-26

14.07.2012

Achhipur

22 ○ 27' 36''

88 ○ 07' 21''

0.12

-7.1

14.07.2012

Burul

22 ○ 21' 46''

88 ○ 06' 17''

0.12

-7.2

14.07.2012

Falta

22 ○ 17' 27''

88 ○ 06' 14''

0.12

-7.2

HGH12-23

14.07.2012

Raychalk

22 ○ 12' 28''

88 ○ 07' 15''

0.29

-7.0

HGH12-22

14.07.2012

Diamond Harbour

22 ○ 11' 06''

88 ○ 11' 22''

0.65

-6.7

HGH12-21

14.07.2012

Kulpi

22 ○ 05' 02''

88 ○ 13' 19''

0.81

-5.7

HGH12-19

13.07.2012

Kakdwip Lot No. 8

21 ○ 52' 51''

88 ○ 09' 53''

11.00

-3.6

HGH12-14

13.07.2012

Kachuberia Ghat

21 ○ 51' 33''

88 ○ 08' 41''

11.28

-3.5

HGH12-24

M

ED

PT

CE

AC

HGH12-25

US

HGH12-13

CR



AN

IP

T

Hooghly water

ACCEPTED MANUSCRIPT 13.07.2012

Sapkhali

21 ○ 51' 02''

88 ○ 06' 52''

9.15

-3.9

HGH12-18

13.07.2012

Mandirtala

21 ○ 46' 53''

88 ○ 04' 36''

15.27

-2.4

HGH12-16

13.07.2012

Light House

21 ○ 39' 26''

88 ○ 02' 29''

17.55

-2.3

HGH12-17

13.07.2012

Gangasagar

21 ○ 37' 53''

88 ○ 04' 24''

18.84

-2.0

HGH12-20

13.07.2012

Namkhana

21 ○ 45' 41''

88 ○ 14' 06''

18.54

-1.9

HGH12-40

05.10.2012

Burul

22 ○ 21' 46''

88 ○ 06' 17''

0.12

-9.1

HGH12-39

05.10.2012

Nurpur

22 ○ 12' 42''

88 ○ 04' 17''

HGH12-35

05.10.2012

Diamond Harbour L

22 ○ 11' 06''

HGH12-38

05.10.2012

Diamond Harbour H

22 ○ 11' 06''

HGH12-36

05.10.2012

Kulpi

22 ○ 05' 02''

HGH12-37

05.10.2012

Nischindipur

21 ○ 59' 47''

HGH12-31

03.10.2012

Kachuberia Ghat

HGH12-30

03.10.2012

Sapkhali

HGH12-29

03.10.2012

Mandirtala

HGH12-28

03.10.2012

Light House

HGH12-27

03.10.2012

Gangasagar

HGH12-32

04.10.2012

HGH12-33

04.10.2012

HGH12-34

04.10.2012

HGH13-12

25.04.2013

HGH13-11

25.04.2013

HGH13-10

25.04.2013

-8.4

88 ○ 11' 22''

0.23

-8.1

88 ○ 11' 22''

0.20

-8.3

88 ○ 13' 19''

0.30

-8.5

88 ○ 11' 25''

0.43

-7.9

21 ○ 51' 33''

88 ○ 08' 41''

2.56

-7.4

21 ○ 49' 16''

88 ○ 05' 52''

4.23

-6.5

21 ○ 46' 53''

88 ○ 04' 36''

5.08

-6.1

21 ○ 39' 26''

88 ○ 02' 29''

10.83

-4.6

21 ○ 37' 53''

88 ○ 04' 24''

10.50

-4.4

Namkhana

21 ○ 45' 41''

88 ○ 14' 06''

7.95

-5.2

Freserganj

21 ○ 34' 34''

88 ○ 14' 54''

13.20

-3.8

Bakkhali

21 ○ 33' 51''

88 ○ 14' 52''

13.50

-3.9

Acchipur

22 ○ 27' 36''

88 ○ 07' 21''

0.19

-6.6

Burul

22 ○ 21' 46''

88 ○ 06' 17''

0.65

-6.4

Raychalk

22 ○ 12' 28''

88 ○ 07' 15''

1.32

-6.3

23.04.2013

Diamond Harbour

22 ○ 11' 06''

88 ○ 11' 22''

2.04

-5.9

23.04.2013

Kulpi

22 ○ 05' 02''

88 ○ 13' 19''

2.71

-6.1

HGH13-3

23.04.2013

Nischindipur

21 ○ 59' 47''

88 ○ 11' 25''

6.82

-5.3

HGH13-4

23.04.2013

Kakdwip Lot No. 8

21 ○ 52' 51''

88 ○ 09' 53''

13.38

-3.7

HGH13-9

24.04.2013

Kachuberia ghat

21 ○ 51' 33''

88 ○ 08' 40''

12.30

-4.1

HGH13-8

24.04.2013

Sapkhali

21 ○ 49' 16''

88 ○ 05' 52''

17.37

-3.0

HGH13-7

24.04.2013

Light House

21 ○ 39' 26''

88 ○ 02' 29''

25.20

-1.8

HGH13-2

US

AN M

ED

PT

CE

AC

HGH13-1

IP

0.16

CR

T

HGH12-15

ACCEPTED MANUSCRIPT 24.04.2013

Gangasagar

21 0 37' 53''

88 ○ 04' 24''

25.88

-1.5

HGH13-5

23.04.2013

Namkhana

21 ○ 45' 41''

88 ○ 14' 06''

17.76

-3.1

HGH13-14

10.08.2013

Falta

22 ○ 17' 27''

88 ○ 06' 14''

0.20

-7.1

HGH13-15

10.08.2013

Diamond Harbour

22 ○ 11' 06''

88 ○ 11' 22''

0.17

-7.9

HGH13-16

10.08.2013

Kulpi

22 ○ 05' 02''

88 ○ 13' 19''

0.29

-7.9

HGH13-17

10.08.2013

Nischindipur

21 ○ 59' 47''

88 ○ 11' 25''

1.00

-7.7

HGH13-18

10.08.2013

Kakdwip Lot No. 8. L

21 ○ 52' 51''

88 ○ 09' 53''

HGH13-20

11.08.2013

Kakdwip Lot No. 8. M

21 ○ 52' 51''

HGH13-21

11.08.2013

Kakdwip Lot No. 8. H

21 ○ 52' 51''

HGH13-22

11.08.2013

Freserganj

21 ○ 34' 34''

HGH13-23

11.08.2013

Freserjanj Mohana

21 ○ 34' 50''

HGH13-24

11.08.2013

Near Jammu Dwip

HGH13-19

10.08.2013

Namkhana

HGH13-25

15.11.2013

Diamond Harbour

HGH13-26

15.11.2013

Kulpi

HGH13-27

15.11.2013

Nischindipur

HGH13-28

15.11.2013

HGH13-35

16.11.2013

HGH13-34

16.11.2013

HGH13-31

16.11.2013

HGH13-33

16.11.2013

HGH13-32

16.11.2013

-6.1

88 ○ 09' 53''

3.58

-7.0

88 ○ 09' 53''

5.11

-6.6

88 ○ 14' 54''

14.31

-4.0

88 ○ 14' 01''

12.75

-4.4

21 ○ 32' 06''

88 ○ 13' 07''

15.06

-3.9

21 ○ 45' 41''

88 ○ 14' 06''

9.32

-4.7

22 ○ 11' 06''

88 ○ 11' 22''

0.15

-8.0

22 ○ 05' 02''

88 ○ 13' 19''

0.18

-8.0

21 ○ 59' 48''

88 ○ 11' 25''

0.29

-8.1

Kakdwip Lot No. 8L

21 ○ 52' 51''

88 ○ 09' 53''

2.32

-7.6

Kakdwip Lot No. 8L

21 ○ 52' 54''

88 ○ 09' 53''

2.23

-7.6

Kachuberia ghat

21 ○ 51' 34''

88 ○ 08' 41''

1.16

-7.9

Muriganga

21 ○ 49' 12''

88 ○ 09' 42''

6.15

-6.4

Light House

21 ○ 39' 26''

88 ○ 02' 29''

8.80

-5.7

Gangasagar

21 ○ 37' 53''

88 ○ 04' 24''

11.74

-4.9

15.11.2013

Namkhana

21 ○ 45' 41''

88 ○ 14' 06''

5.30

-3.9

HGH12/GW-1

03.10.2012

Gangasagar (300 m)

21 ○ 37' 41''

88 ○ 04' 12''

0.42

-3.3

HGH12/GW-2

03.10.2012

Rudranagar (300 m)

21 ○ 42' 59''

88 ○ 06' 26''

0.47

-3.4

HGH12/GW-3

03.10.2012

Bokulpur (300 m)

21 ○ 51' 01''

88 ○ 08' 08''

0.39

-3.4

Groundwater

US

AN

M

ED

PT

CE

AC

HGH13-29

IP

6.31

CR

T

HGH13-6

&

ACCEPTED MANUSCRIPT 04.10.2012

Maity ghat (300 m)

21 ○ 44' 50''

88 ○ 14' 19''

0.47

-3.5

HGH12/GW-5

04.10.2012

Akshaynagar (300 m)

21 ○ 51' 20''

88 ○ 11' 50''

0.46

-3.6

HGH12/GW-6

04.10.2012

Kakdwip (300 m)

21 ○ 52' 55''

88 ○ 09' 57''

0.39

-3.4

HGH12/GW-7

05.10.2012

Belpukur (300 m)

22 ○ 00' 38''

88 ○ 13' 51''

0.76

-3.5

HGH13/SGW-1

23.04.2013

Kakdwip (61 m)

21 ○ 52' 44''

88 ○ 10' 03''

0.53

-4.0

HGH13/SGW-2

24.04.2013

Sapkhali (67 m)

21 ○ 50' 39''

88 ○ 06' 42''

0.46

-3.9

HGH13/SGW-3

25.04.2013

Raychalk (46 m)

22 ○ 12' 37''

88 ○ 07' 30''

HGH13/SGW-4

25.04.2013

Raychalk (34 m)

22 ○ 13' 14''

HGH13/SGW-5

10.08.2013

Kakdwip (37 m)

21 ○ 51' 11''

HGH13/SGW-6

11.08.2013

Kakdwip (15 m)

21 ○ 51' 04''

HGH13/SGW-7

15.11.2013

Chemaguri (76 m)

21 ○ 40' 05''

HGH13/SGW-8

16.11.2013

Light house (61 m)

21 ○ 39' 23''

M

88 ○ 08' 36''

3.90

-4.3

88 ○ 11' 30''

CR

2.24

-3.7

88 ○ 19' 25''

2.00

-6.5

88 ○ 07' 29''

0.72

NM

88 ○ 02' 30''

0.52

NM

IP

-3.6

US

H

4.21

Low tide period, Hogh tide period, Between low and high tide periods, NM- Not measured

AN

L

T

HGH12/GW-4

&

AC

CE

PT

ED

M

The depth of the groundwater collection are given within the brackets for each location.

ACCEPTED MANUSCRIPT Table 2. Statistics of  18 O-salnity regression analysis

a

PrM-2012 PrM-2013 M-2012b M-2013 PoM-2012 PoM-2013c

Slope

SEslope

0.21 0.20 0.28 0.27 0.36 0.28

0.005 0.003 0.012 0.018 0.002 0.008

CVslope (%) 2.38 1.50 4.29 6.67 0.56 2.86

Intercept

SEintercept

-6.21 -6.58 -7.01 -7.77 -8.36 -8.14

0.07 0.04 0.13 0.15 0.13 0.04

CVintercept (%) 1.13 0.61 1.85 1.93 1.56 0.49

T

Period

a

R2

N

0.993 0.998 0.984 0.961 0.969 0.994

13 13 12 11 14 09

excludes one sample with salinity 2.5. excludes one sample with salinity 0.81. c excludes one sample with salinity 5.3. The data of outlier samples are excluded from regression analysis as noted above a,b,c. The data of these samples are presumably influenced by sources other than river water and seawater. CV: Coefficient of variation. SE: standard error. N: number of samples for which regression analysis was carried out

AC

CE

PT

ED

M

AN

US

CR

IP

b

ACCEPTED MANUSCRIPT Table 3: Seasonal variation of  18 O of rainwater at locations from the upper to the lower reaches of the Ganga River.

CE

PT

ED

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Rainfall amount-weighted average 18 O values are given, nr: Not reported

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Reference

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Kumar et al., 2010 Kumar et al., 2010 Kumar et al., 2010 Kumar et al., 2010 Kumar et al., 2010 Sengupta and Sarkar, 2006 Kumar et al., 2010

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Devaprayag Rishikesh Roorkee Lucknow Patna Kolkata Kolkata Mean

 18 O-rain (‰VSMOW)# Pre-monsoon Monsoon Post-monsoon -4.5 -8.9 -14.7 nr -9.7 -13.0 -2.1 -6.2 -7.5 nr -6.9 -8.0 nr -8.5 -13.7 -3.2 -6.4 -11.8 nr -7.3 -9.7 -3.31.2 -7.71.3 -11.22.8

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ACCEPTED MANUSCRIPT Table 4. The  18 O values used to estimate the meltwater fraction in the Hooghly River

Meltwater Non-melt water Non-melt water Melt water Non-melt water Non-melt water

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Monsoon

Glacier Rainwater Groundwater Glacier Rainwater Groundwater

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Sampling Periods

 18 O (‰VSMOW) ‒14.2±4.6a ‒3.3±1.2b ‒5.1±0.5c ‒14.2±4.6a ‒7.7±1.3b ‒4.1±0.8d

 O values of the Himalayan glaciers (Nijampurkar and Rao, 1993; Pande et al., 2000; Rai et al., 2009; Racoviteanu et al., 2013). b Details on data and sources in Table 3 c 18  O values of the pre-monsoon period groundwater samples from the lower reaches of the Ganga River (Mukherjee et al., 2007a). d 18  O values of the monsoon period groundwater samples (Mukherjee et al., 2007a). # The average of the 18 O values of the rainwater and groundwater as listed above were used as the 18 O value of the non-melt water in the Equation 2 (see text).

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ACCEPTED MANUSCRIPT Table 5. The a priori values used in the inversion model and the model-results of a posteriori values for the end members (sources)

 O (‰)

a posteriori value End member Salinity (‰)

–6.21±0.07 River water

0.10±0.01 33.83±1.10 1.05±0.72

–6.39±0.00

0.1±0.01 29.8±0.7 2.22±1.60

–7.01±0.13 River water –0.21±0.16 Seawater –4.33±1.08 Groundwater

0.09±0.01 29.86±0.69 0.84±0.56

–7.16±0.07 –0.18±0.32 –3.39±0.70

0.1±0.01 29.8±0.9 2.22±1.60

–8.36±0.13 River water –0.57±0.53 Seawater –4.33±1.08 Groundwater

0.10±0.01 29.70±0.97 0.45±0.29

–8.82±0.06 –0.66±0.48 –4.47±0.74

0.1±0.01 33.0±1.0 2.22±1.60

–6.58±0.04 River water

0.10±0.01 34.25±1.12 2.67±1.80

–6.61±0.00 –0.26±0.22 –4.63±0.69

0.1±0.01 29.8±0.7 2.22±1.60

–7.77±0.15 River water –0.21±0.16 Seawater –4.33±1.08 Groundwater

0.10±0.01 30.50±0.70 0.31±0.12

–8.07±0.10 –1.36±0.22 –5.83±0.58

–8.14±0.04 River water –0.57±0.53 Seawater –4.33±1.08 Groundwater

0.10±0.01 30.00±0.97 0.93±0.60

–8.23±0.07 –2.07±0.66 –3.24±0.68

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0.30±1.0 Seawater

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–4.33±1.08 Groundwater

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0.1±0.01 29.8±0.9 2.22±1.60

0.30±1.0 Seawater –4.33±1.08 Groundwater

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0.1±0.01 33.0±1.0 2.22±1.60

 18 O (‰)

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End member PrM, 2012 River watera Seawaterb Groundwaterd M, 2012 River watera Seawaterc Groundwaterd PoM, 2012 River watera Seawaterc Groundwaterd PrM, 2013 River watera Seawaterb Groundwaterd M, 2013 River watera Seawaterc Groundwaterd PoM, 2013 River watera Seawaterc Groundwaterd

a priori value Salinity (‰)

0.13±0.33 –2.93±0.76

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PrM: pre-monsoon, M: monsoon, PoM: post-monsoon a River water salinity was considered as 0.1±0.01‰, 18 O values are based on 18 O-axis intercept in the salinity18 O relationship (Table 2). b Salinity and 18 O values of the northern Bay of Bengal in the pre-monsoon period (Somayajulu et al. 2002). c Salinity and 18 O values of the northern Bay of Bengal in the monsoon and post -monsoon periods )Achyuthan et al. 2013). d Based on average salinity and 18 O values of the shallow groundwater samples collected from the Hooghly estuary (Table 1).

ACCEPTED MANUSCRIPT Highlights

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Strong  18 O-salinity correlations indicate efficient mixing in the estuary. Freshwater compositions regulate the seasonal salinity-18O relationships. Regression of salinity–18O data provide the seasonal freshwater  18 O values. Meltwater contributions account for 10-25% of the freshwater in the Hooghly River. Submarine saline groundwater discharge is inferred the estuary.

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Figure 1

Figure 2

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Figure 4