Chemical weathering and carbon dioxide consumption in a small tropical river catchment, southwestern India

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Chemical weathering and carbon dioxide consumption in a small tropical river catchment, southwestern India

Baby Krishnan Nisha¹ · Keshava Balakrishna¹ · Harikripa Narayana Udayashankar¹ · Busnur Rachotappa Manjunatha²

Received: 5 December 2020 / Accepted: 13 April 2021 / Published online: 28 April 2021

Abstract

Studies done on small tropical west-flowing river catchments located in the Western Ghats in southwestern India have suggested very intense chemical weathering rates and associated CO₂ consumption. Very less studies are reported from these catchments notwithstanding their importance as potential sinks of atmospheric CO₂ at the global scale. A total of 156 samples were collected from a small river catchment in the southwestern India, the Payas- wini–Chandragiri river Basin, during pre-monsoon, monsoon and post-monsoon seasons in 2016 and 2017, respectively. This river system comprises two small rivers originating at an elevation of 1350 m in the Western Ghats in peninsular India. The catchment area is domi- nated by biotite sillimanite gneiss. Sodium is the dominant cation, contributing ~ 50% of the total cations, whereas HCO3− contributes ~ 75% of total anions. The average anion concentration in the samples varied in the range HCO₃⁻ > Cl⁻ > SO₄²⁻ > NO₃⁻ > F⁻, whereas major cation concentration varied in the range Na⁺ > Ca²⁺ > Mg²⁺ > K⁺. The average silicate weathering rate (SWR) was 42 t km⁻² y⁻¹ in the year 2016 and 36 t km⁻² y⁻¹ in 2017.

The average annual carbon dioxide consumption rate (CCR) due to silicate rock weathering was 9.6 × 10⁵ mol km⁻²y⁻¹ and 8.3 × 10⁵ mol km⁻² y⁻¹ for 2016 and 2017, respectively.

The CCR in the study area is higher than other large tropical river catchments like Ama- zon, Congo-Zaire, Orinoco, Parana and Indus because of its unique topography, hot and humid climate and intense rainfall.

Keywords Tropical river system · Water geochemistry · Silicate weathering rate · Atmospheric CO₂ consumption · Southwest coast of India

* Keshava Balakrishna k.balakrishna@manipal.edu

1 Department of Civil Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal 576104, India

2 Department of Marine Geology, Mangalore University, Mangalagangothri 574199, India

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The chemical composition of rivers is derived from diverse sources like weathering of catchment rocks and soils, atmospheric deposition and anthropogenic discharges. In unpolluted river waters, lithological characteristics (source rock abundance) dominantly affect the concentration of major ions and trace elements (Gaillardet et al. 1999). In a hot and humid tropical setup, chemical weathering predominates over physical weathering, which has a bearing on the long-term global climate change.

Chemical weathering of a terrain plays a key role in the atmospheric CO₂ consumption.

The chemical weathering of a silicate rock converts the atmospheric CO₂ into dissolved inorganic carbon and deposits in the form of carbonic sediments in the ocean (Berner 1991) as noted in

There are several factors affecting the rate of chemical weathering, such as the geology of the terrain (rock type), topography (relief), soil cover, discharge, temperature and precipitation (Gaillardet et al. 1999; Huh 2003; Millot et al. 2002, 2003; Oliva et al. 2003; Guo and Wang 2005; Andersson et al. 2006; Moon et al. 2007). Studies were carried out across the world to estimate the chemical weathering rate and CCR of the major world rivers in the past decades, notably Amazon (Stallard and Edmond 1983), Ganges–Brahmaputra (Sarin et al. 1989), Yel- low (Zhang et al. 1995), Nile (Dekov et al. 1997), Indus (Ahmad et al. 1998), Mississippi (Sharif et al. 2008), Mekong (Huang et al. 2009), Tigris (Varol et al. 2013), Yangtze (Huang et al. 2009; Jiang et al. 2015), Netravathi (Gurumurthy et al. 2012), Kavery (Pattanaik et al.

2013) and Brahmaputra (Das et al. 2016).

Tropical rivers are the largest carriers of dissolved and sediment load to the world’s oceans and significantly influence the biogeochemical cycles of elements. Limited studies are done on the tropical systems worldwide, because of their location in the developing and underdevel- oped countries. Meybeck (1987) emphasized the importance of tropical ecosystems and the paucity of data on these systems, though they are responsible for contributing 50% of water, 38% of dissolved ions and 68% of dissolved silica into the global oceans. The objectives of the present study are to partially fill the paucity in data from the tropical systems. Samples were collected from the tropical Payaswini–Chandragiri river basin, southwest coast of India during pre-monsoon, monsoon and post-monsoon in 2016 and 2017. Currently, no studies have been reported on the major ion chemistry of this river system. This river system is the biggest in northern Kerala state among the 13 river systems draining silicate-rich rock terrains. This study investigated the presence, distribution and source of major ions in the southwest-flowing river and estimated the SWR and associated CCR using the forward model (Wu et al. 2008).

These data will add to the database of global silicate weathering rates of world rivers and fill- ing the gaps existing on the silicate weathering and CCR in Indian tropical rivers.

CaSiO₃+ 2CO₂+ H₂O → Ca²⁺+ 2HCO⁻₃ + SiO₂ (1) Ca²⁺+ 2HCO₃→ CaCO₃↓ +H₂O + CO₂↑

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2.1 Study area

The Chandragiri–Payaswini river system (area 1406 km² and length 105 km) is located along the southwest coast of peninsular India originating in the Western Ghats. Geographi- cally the study area lies between 74° 48′ E and 75° 45′ E and 12° 18′ N and 12° 32′ N longitudes and latitudes, respectively. These rivers originate at an altitude of about 1350 m above mean sea level (MSL) and join the Arabian sea near Kasaragod town (Fig. 1).

Geologically, the basement of the study area belongs to the Archean metamorphics (Fig. 1). The main rock types are granite biotite sillimanite gneiss, charnockite, schist and dolerite. Charnockites, hornblende-biotite gneiss and high-grade schistose rocks are exten- sively lateritized in the lower reaches and dominate the drainage basin of Chandragiri river.

There are no reports of the presence of carbonates/evaporates. The study area experiences typical tropical climate with hot (20°–38 °C) and humid conditions (4,000 mm annual rainfall), high surface runoff (2715 mm for entire west-flowing river catchment) with an annual water discharge of 4.40 km³/ year (Reddy et al. 2019) (Fig. S1).

Anthropogenic activities are minimal in the area, though two plywood industries located near Sullia town, on the banks of Payaswini River, and hospital discharge outlet near Aleti are discharging their effluents into the river (Fig. 1). Kasaragod municipal wastewater is discharged directly into the river estuary.

2.2 Sampling and analysis

Twenty-six river water samples were collected in each season, from the mainstream and tributaries (Fig. 1) during pre-monsoon (April), monsoon (August) and post-monsoon (December) seasons for a period of 2 years (2016, 2017). A total of 156 samples were collected in six seasons. Water samples were collected from road bridges such that samples are received from the center of the river and in the well-mixed condition. A polypropylene (PP) bucket tied with Nylon rope was dropped to the river for the sample collection. pH, temperature, electric conductivity (EC) and dissolved oxygen (DO) were measured on-site using HACH-make portable multiparameter, calibrated with the standard solution.

Locations 1. Jodupala 2. Abhikolli 3. Koyanadu 4. Sampaje 5. Peraje 6. Adikehitilu 7. Doddathotta 8. Paichar 9. Adkar 10. Uddanthadka 11. Aletti 12. Parappa 13. Pandi 14. Panjikkal 15. Adoor 16. Erinjipuzha 17. Pandikandam 18. Karike 19. Karike 20. Panathur 21. Balamthod 22. Kolichal 23. Kallar 24. Kottody 25. Moonnamkadav 26. Periya

Fig. 1 Geological map of Payaswini–Chandragiri river basin with sampling locations ( source of the data;

1:20 K geological map of India)

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were filtered through 0.22-µm pore size, 47-mm-diameter Nuclepore polycarbonate filters using a Sartorius-make membrane filtration apparatus in a laminar flow bench and stored at 4 °C for further analysis. The filtered water samples were analyzed for major ions using DIONEX-1100 ion chromatography with autosampler having separate cation–anion sup- pressor and column system. Accuracy of the results was checked with a known concentration of the standard solutions, which were within ± _5%. Precision of the results was checked with duplicate samples, which were within ± 3% (Table S1). Alkalinity of the samples was measured using the standardized HCl titration method using an autotitrator (METROHM TIAMO). Since the pH of all the samples is less than 8.3, the carbonate alkalinity was nonexistent. The end point of bicarbonate alkalinity ranged from 4.8 to 5.5 (Fig.

S2), with ± 2% accuracy and precision. Dissolved silica (SiO₂) in the river water samples was measured through the UV–Vis spectrometer, HACH DR 5000 by silicon molybdate method at 452 nm wavelengths with a precision of ± 2%. Normalized inorganic charge balance (NICB) was calculated between total dissolved cations (TZ⁺) and total dissolved anions (TZ⁻), and the charge balance was within ± 15% (Fig. 2). Above 10% of NICB values of the samples could be due to the presence of organic anions and cations.

3 Result and discussion 3.1 Hydrogeochemistry

The physiochemical composition of the Payaswini–Chandragiri river water is tabulated in Table 1. The pH of the river was slightly alkaline in nature and showed a small variation seasonally (6.1–8.3) and spatially. In monsoon season, the average pH was lower than the rest of the seasons, because of the mixing of rain water, which has typical pH of 5.5.

The electric conductivity of the river samples varied from 31 to 176 µS/cm in pre-monsoon, 49–93 µS/cm in monsoon and 31–83 µS/cm in post-monsoons. Total dissolved solid of the samples was calculated from the concentration of obtained major ions and silica.

The concentration of TDS in the pre-monsoon varied from 29 to 112 mg/l, 36–80 mg/l in monsoon and 29–84 mg/l in post-monsoon, respectively. The average TDS of Payas- wini–Chandragiri river (60 mg/l) is less than the world’s major rivers (Gaillardet et al.

Fig. 2 Correlation between total anion and total cation

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Table 1 Physicochemical composition of the Payaswini–Chandragiri river basin Loca- tionsTpHECDONa+K+Mg2+Ca2+Cl-NO3-SO42-HCO3-SiO2TZ+ TZ-TDSNICB (°C) (μS/cm)(mg/l)(μmol. L−1)(µequ.L-1)(mg/l)(%) 1. Jodupala N 12° 26′ 25.99" E 75° 39′ 36.23" Pre-monsoon 2016

27.17.681.07.2217.978.5127.5158.460.017.611.6835.2433.3868.2936.598.8− 7.6 Monsoon 201623.96.769.47.6132.812.771.9109.875.724.79.7433.1216.7508.9553.654.3− 8.4 Post- mon-

soon 2016

22.07.559.58.2199.720.5114.8146.563.618.010.2590.2150.0742.9692.363.47.1 Pre-mon-

soon 2017

24.07.264.17.4230.217.8142.0187.170.813.412.7780.2466.7906.1890.997.11.7 Monsoon 201723.66.943.67.9127.313.573.588.769.825.28.0410.533.3465.2521.640.6− 11.4 Post- mon-

soon 2017

27.17.761.27.4206.717.9145.3171.967.422.77.6659.3133.3859.0764.668.611.6 2. Abhikolli N 12° 26′ 26.15" E 75° 39′ 02.15" Pre-mon-

soon 2016

Dry Monsoon 201623.16.970.57.8148.035.479.881.661.913.79.7368.4333.3506.0463.356.48.8

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Table 1 (continued) Loca- tionsTpHECDONa+K+Mg2+Ca2+Cl-NO3-SO42-HCO3-SiO2TZ+ TZ-TDSNICB (°C) (μS/cm)(mg/l)(μmol. L−1)(µequ.L-1)(mg/l)(%) Post- monsoon 2016

22.07.558.58.2160.836.691.0119.766.65.99.3456.7216.7618.8548.456.612.1 Pre-mon-

soon 2017

23.67.864.37.3217.048.764.3182.363.43.210.8482.3450.0630.2571.574.19.8 Monsoon 201723.57.344.67.9148.066.958.464.856.515.67.8411.0250.0461.4498.653.8− 7.8 Post- mon-

soon 2017

29.87.666.47.1157.811.984.177.961.87.210.2456.2233.3493.7545.654.7− 10.0 3. Koyanadu N 12° 28′ 50.55" E75° 34′ 47.70" Pre-mon-

soon 2016

31.27.995.57.5177.622.678.8139.358.01.011.7647.4150.0636.4730.764.2− 13.8 Monsoon 201625.26.981.88.1148.912.994.5119.279.015.812.7526.9300.0589.2647.866.1− 9.5 Post- mon-

soon 2016

23.97.768.68.5202.916.7261.2170.282.06.513.2866.9133.31082982.583.99.7 Pre-mon-

soon 2017

27.27.873.67.6242.719.8163.8218.585.21.814.2890.2250.01027100692.82.0 Monsoon 201724.97.553.78.0147.314.388.599.874.315.715.5471.0150.0538.3592.052.9− 9.5

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32.57.882.58.3166.314.884.9101.778.16.312.4503.4166.7554.3634.156.0− 13.4 4. Sampaje N 12° 29′ 37.67" E 75° 33′ 57.45" Pre-mon-

soon 2016

30.97.165.34.1267.421.1160.6201.666.50.210.7832.1166.71012.921.383.19.5 Monsoon 201627.66.662.27.4165.812.065.591.376.78.110.5443.3100.0491.5549.546.8− 11.2 Post- mon-

soon 2016

25.17.347.58.0169.712.481.9105.581.04.712.7430.2100.0556.8541.747.22.8 Pre-mon-

soon 2017

27.76.749.24.4220.123.187.3138.8103.35.112.5520.2233.3695.3654.664.56.0 Monsoon 201726.36.943.27.5146.012.766.976.077.06.79.3390.2166.7444.5495.646.4− 10.9 Post- mon-

soon 2017

31.87.856.67.8159.318.093.195.683.24.011.8450.2266.7554.6561.858.2− 1.3 5. Peraje N 12° 31′ 06.70" E 75° 26′ 13.68" Pre-mon-

soon 2016

36.17.278.56.4247.117.8143.2166.445.14.815.3796.4116.7884.1877.875.40.7

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Table 1 (continued) Loca- tionsTpHECDONa+K+Mg2+Ca2+Cl-NO3-SO42-HCO3-SiO2TZ+ TZ-TDSNICB (°C) (μS/cm)(mg/l)(μmol. L−1)(µequ.L-1)(mg/l)(%) Monsoon 201626.07.060.67.6171.911.663.673.880.411.99.6377.966.7458.3489.640.5-6.6 Post- monsoon 2016

27.27.648.88.1169.712.481.9105.581.04.712.7430.2100.0556.8541.747.22.8 Pre-mon-

soon 2017

30.67.661.06.8216.921.7128.9169.292.3BLD11.0700.2250.0834.7815.677.82.3 Monsoon 201726.27.240.47.6162.311.771.853.378.511.37.5341.8216.7424.1446.646.1-5.2 Post- mon-

soon 2017

37.97.454.07.7170.813.260.057.677.72.710.0335.966.7419.2436.736.6-4.1 6. Adikehitilu N 12° 34′ 59.77" E 75° 30′ 11.93" Pre-mon-

soon 2016

31.26.953.15.088.90.542.260.738.0BLD14.1262.883.3295.1329.929.3− 11.1 Monsoon 201627.66.849.47.5121.410.545.858.681.77.67.9290.7166.7340.7395.938.5− 15.0 Post- mon-

soon 2016

25.36.533.48.058.75.881.437.234.8BLD3.4280.0116.7301.6321.730.7− 6.4 Pre-mon-

soon 2017

Dry

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Table 1 (continued) Loca- tionsTpHECDONa+K+Mg2+Ca2+Cl-NO3-SO42-HCO3-SiO2TZ+ TZ-TDSNICB (°C) (μS/cm)(mg/l)(μmol. L−1)(µequ.L-1)(mg/l)(%) Monsoon 201725.76.133.67.7136.316.449.259.972.15.86.5299.0166.7370.8389.939.1− 5.0 Post- monsoon 2017

33.26.239.97.9136.415.541.955.569.82.67.0284.3166.7346.8370.737.6− 6.7 7. Doddathotta N 12° 35′ 34.19" E 75° 26′ 15.66" Pre-mon-

soon 2016

28.36.470.52.7496.379.5184.5133.140.04.417.0975.2216.712101054100.113.8 Monsoon 201626.36.956.77.4133.314.849.072.7105.320.811.3216.7216.7391.6365.740.16.8 Post- mon-

soon 2016

24.07.530.88.0136.69.232.045.265.06.36.9230.0100.0300.2315.129.5− 4.8 Pre-mon-

soon 2017

24.27.139.56.8160.125.965.398.796.48.610.7380.2116.7514.0507.145.41.4 Monsoon 201726.17.037.87.4140.212.445.958.899.320.19.3280.0150.0362.0418.038.9− 14.4 Post- mon-

soon 2017

29.37.238.98.0151.339.750.372.891.211.49.1378.4133.3437.2499.645.1− 13.3

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Table 1 (continued) Loca- tionsTpHECDONa+K+Mg2+Ca2+Cl-NO3-SO42-HCO3-SiO2TZ+ TZ-TDSNICB (°C) (μS/cm)(mg/l)(μmol. L−1)(µequ.L-1)(mg/l)(%) 8. Paichar N 12° 34′ 06.96" E 75° 23′ 19.60" Pre-monsoon 2016

30.48.0175.52.3210.127.0107.2184.0235.253.619.5589.8266.7819.5920.281.4− 11.6 Monsoon 201625.97.260.37.6172.314.157.575.395.421.610.3354.116.7452.1492.437.2− 8.5 Post- mon-

soon 2016

25.07.135.17.0141.912.671.573.0108.16.116.0332.0133.3443.4478.442.4− 7.6 Pre-mon-

soon 2017

28.07.361.26.3256.230.5114.5150.4151.97.212.1600.2166.7816.6784.669.54.0 Monsoon 201726.26.837.27.6129.316.764.170.5103.020.310.0250.033.3415.1393.431.15.4 Post- mon-

soon 2017

29.47.344.27.1159.317.277.881.1101.98.217.0398.2100.0494.3542.845.5− 9.4 9. Adkar N 12° 34′ 06.96" E 75° 21′ 06.84" Pre-mon-

soon 2016

32.97.674.67.4341.042.4175.0237.8118.619.816.91046.966.71209104691.1− 0.4 Monsoon 201626.57.661.07.8156.213.359.4100.291.416.410.4436.2183.3488.8565.352.4− 14.5

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28.18.147.67.6161.419.586.5101.8101.113.915.8380.2266.7557.6527.541.85.5 Pre-mon-

soon 2017

28.66.958.25.8228.339.7115.4153.8136.416.611.0580.2183.3806.4739.368.08.7 Monsoon 201726.16.941.47.7157.714.861.488.387.416.29.3375.4150.0421.8497.545.1− 5.3 Post- mon-

soon 2017

34.98.051.27.0150.021.483.894.492.410.012.8430.2183.3527.6558.742.4− 5.7 10. Uddanthadka N 12° 34′ 44.37" E 75° 22′ 04.11" Pre-mon-

soon 2016

Dry Monsoon 201626.56.567.37.992.16.351.3132.576.016.27.8430.7150.0461.7539.348.5-14.6 Post- mon-

soon 2016

25.06.644.38.0183.610.292.3105.684.27.015.6410.2183.3589.4532.652.010.1 Pre-mon-

soon 2017

29.07.069.87.2174.325.7102.1122.565.21.615.5460.5200.0649.2554.056.214.8 Monsoon 201726.67.065.97.487.78.058.5117.575.316.68.4407.0116.7447.5516.444.8-14.3

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34.77.145.78.1159.915.5116.390.069.74.014.0564.6133.3588.0675.257.3-13.8 11. Aletti N 12° 32.851′ E 75° 23.575′ Pre-mon-

soon 2016

35.17.569.59.1253.639.5165.1203.368.9BLD8.3810.2116.71029897.079.213.8 Monsoon 201626.57.262.97.5136.413.063.984.898.214.910.2379.750.0446.8513.240.1− 13.8 Post- mon-

soon 2016

27.77.146.67.6161.416.345.7103.286.87.210.5410.2116.7475.5525.846.1− 10.1 Pre-mon-

soon 2017

30.17.256.27.0209.321.4115.7149.5105.2BLD8.6620.2166.7761.0743.666.82.3 Monsoon 201725.67.040.57.7131.013.260.370.282.413.28.4340.233.3405.0452.635.1− 11.1 Post- mon-

soon 2017

37.27.152.47.6158.121.585.391.383.66.49.6508.583.3532.8618.150.5− 14.8 12. Parappa N 12° 34′ 57.96" E 75° 14′ 47.84" Pre-mon-

soon 2016

Dry

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29.26.437.88.4165.713.362.068.017.31.73.4391.1183.3438.9417.044.45.1 Pre-mon-

soon 2017

26.97.158.07.0151.722.937.4147.566.42.510.8427.7150.0544.4518.649.84.9 Monsoon 201723.86.955.97.9149.214.185.265.584.54.310.9377.9216.7464.7488.949.0− 5.1 Post- mon-

soon 2017

33.97.040.07.7168.714.0101.397.387.33.811.6471.3133.3579.9590.252.0− 1.8 13. Pandi N 12° 32′ 54.51" E 75° 14′ 19.47" Pre-mon-

soon 2016

Dry Monsoon 201627.06.759.07.7145.912.662.568.166.69.86.8376.2166.7419.7466.844.7− 10.6 Post- mon-

soon 2016

27.97.036.87.6169.310.352.468.610.66.112.4387.4166.7421.5429.543.9− 1.9 Pre-mon-

soon 2017

24.86.838.0174.334.143.172.629.43.82.4410.8116.7439.8449.542.9− 2.2

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31.07.045.17.3177.118.360.276.9106.05.012.1400.2166.7469.6535.449.0− 13.1 14. Panjikkal N 12° 34′ 12.71" E 75° 15′ 58.89" Pre-mon-

soon 2016

30.67.058.38.2507.933.4165.0220.667.7BLD9.01260.366.713121348110.0− 2.7 Monsoon 201625.67.061.47.4139.35.350.7182.197.718.811.1491.8116.7610.0631.554.6− 3.5 Post- mon-

soon 2016

29.97.946.38.4184.718.781.399.7100.212.314.8370.2183.3565.3513.050.29.7 Pre-mon-

soon 2017

33.78.156.18.4243.724.7110.5138.3134.95.917.4560.266.7765.9735.759.74.0 Monsoon 201726.87.240.57.6136.015.174.073.787.816.09.0390.266.7446.6511.941.2− 13.6 Post- mon-

soon 2017

34.37.651.57.8132.912.862.7173.493.010.014.3456.2216.7618.0587.858.15.0

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Table 1 (continued) Loca- tionsTpHECDONa+K+Mg2+Ca2+Cl-NO3-SO42-HCO3-SiO2TZ+ TZ-TDSNICB (°C) (μS/cm)(mg/l)(μmol. L−1)(µequ.L-1)(mg/l)(%) 15. Adoor N 12° 33′ 51.79" E 75° 14′ 45.85" Pre-monsoon 2016

32.68.1113.66.6307.228.0128.7128.5104.428.614.8704.6200.0849.5869.678.3− 2.3 Monsoon 201626.57.161.07.5152.813.681.346.289.515.49.2330.250.0421.3453.436.0− 7.3 Post- mon-

soon 2016

28.97.746.27.9160.08.379.852.347.15.47.1361.5233.3432.6428.346.81.0 Pre-mon-

soon 2017

34.47.760.37.9248.926.5113.5153.1134.57.521.5590.233.3808.6775.060.94.2 Monsoon 201727.07.541.27.6139.813.660.471.289.515.49.2330.233.3416.6453.435.2− 8.5 Post- mon-

soon 2017

33.77.551.97.5154.318.283.591.391.74.612.2420.2233.3522.0540.854.3− 3.5 16. Erinjipuzha N 12° 29′ 40.54" E 75° 09′ 24.93" Pre-mon-

soon 2016

29.87.546.08.0165.73.059.570.319.01.73.1472.133.3428.2499.640.1− 15.4

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Table 1 (continued) Loca- tionsTpHECDONa+K+Mg2+Ca2+Cl-NO3-SO42-HCO3-SiO2TZ+ TZ-TDSNICB (°C) (μS/cm)(mg/l)(μmol. L−1)(µequ.L-1)(mg/l)(%) Pre-monsoon 2017

soon 2017

35.47.652.27.7168.712.4101.186.992.84.111.0500.266.7557.0619.149.4− 10.0 17. Pandikandam N 12° 28′ 20.60" E 75° 07′ 02.76" Pre-mon-

soon 2016

36.37.6128.27.6507.933.4165.0220.6296.8BLD23.01082.5116.713121425111.5− 8.2 Monsoon 201626.67.359.87.8180.912.958.376.286.519.811.5394.983.3462.6524.143.6− 12.5 Post- mon-

soon 2016

30.08.045.48.1119.711.468.349.440.410.06.4331.0133.3366.5394.437.7− 7.4 Pre-mon-

soon 2017

32.07.454.66.7207.126.1106.3129.7131.2BLD14.3530.2100.0705.1691.557.91.9 Monsoon 201727.37.640.97.7573.313.661.573.1291.816.010.0573.3250.0856.0901.180.4− 5.1

(17)

35.57.751.57.6165.017.882.292.990.85.312.3497.4133.3519.4618.253.0− 14.8 18. Karike N 12° 26′ 19.85" E 75° 27′ 56.59" Pre-mon-

soon 2016

Dry Monsoon 201627.67.293.27.6128.29.979.977.291.76.712.5398.2233.3452.4522.451.5− 14.3 Post- mon-

soon 2016

23.97.552.98.4135.713.576.377.560.11.28.2440.266.7456.8517.942.4− 12.6 Pre-mon-

soon 2017

Dry Monsoon 201724.57.642.17.5127.99.091.872.881.15.68.2350.2116.7466.1453.340.82.8 Post- mon-

soon 2017

30.57.654.77.9151.910.6115.7103.081.92.59.6551.066.7599.9654.952.4− 8.8 19. Karike N 12° 26′ 47.83" E 75° 25′ 06.56" Pre-mon-

soon 2016

33.28.074.27.4133.313.185.8120.731.532.027.6500.5150.0559.4619.755.8− 10.2

(18)

21.77.848.48.4140.110.2100.8106.170.15.915.9490.266.7563.9605.648.7− 7.1 Pre-mon-

soon 2017

27.47.644.87.6165.210.2107.6109.566.0BLD16.1510.2300.0609.5609.564.20.1 Monsoon 201724.47.843.79.1122.68.580.669.769.47.47.8400.2100.0431.6492.642.0− 13.2 Post- mon-

soon 2017

30.27.754.48.3158.112.9114.692.969.25.514.1500.2100.0586.0603.751.3− 3.0 20. Panathur N 12° 27′ 26.17" E 75° 21′ 36.85" Pre-mon-

soon 2016

35.27.364.76.9202.724.2125.5122.681.1BLDBLD780.2266.7722.9781.377.1− 7.8 Monsoon 201626.17.460.87.6130.324.176.389.975.215.99.6440.7116.7470.3551.147.6− 12.4 Post- mon-

soon 2016

25.37.651.27.7178.116.7114.5109.280.78.012.1470.2216.7642.2583.658.19.6 Pre-mon-

soon 2017

29.97.750.56.3183.114.5118.2116.583.5BLD15.5550.2216.7666.9665.463.30.2