29 3.1 Introduction Chemical and isotopic study of the river water provides valuable information on the elemental fluxes to the ocean. Using this information it is possible to model chemical weathering rates and amount of CO2 consumed during silicate weathering in a given drainage basin. Dissolution of CO 2 in the rainwater and pore-water of soil results in lowering of pH and faster weathering of minerals. Silicate weathering is responsible for CO 2 consumption and therefore is an important parameter while modeling global CO 2 cycle (Mortatti and Probst 2003). This chapter presents and discusses major ion composition of the Kaveri, Palar, Ponnaiyar and Vellar in the South India. 3.2 Results 3.2.1 pH, EC and TSL The measured pH, electrical conductivity (EC) values and Total Suspended Load (TSL) only from the monsoon water samples from Kaveri, Palar, Ponnaiyar and Vellar rivers and open/bore well samples are listed in the Appendix I. The range of pH values measured on samples collected during the NE monsoon correspondents to alkaline nature of water. The Palar River is neutral to mildly alkaline (pH 6.95 7.99), Ponnaiyar river is mildly alkaline (pH 7.19 7.69) and the Kaveri river is mildly alkaline to moderately alkaline (pH 7.62 8.76). The pH range in Pre-monsoon sample of Kaveri main course is 7.4 to 8.33, in the tributaries 6.3 to 8.12 and in open/bore wells 6.76 to 8.36. Among these samples highest pH value (8.76) was observed from the monsoon water sample of Kaveri at Mettur, whereas, the lowest pH value (6.3) was observed from the Arkavati river and 62% of total samples had pH ranging between 7.5 and 8.0. The EC value of monsoon samples varies between 170 and 1110 μS cm -1 in the Palar, 430 to 660 μS cm -1 in the Ponnaiyar and 310 to 590 μS cm -1 in the Kaveri river. The EC value of the sample 1PL (Palar) was 1110 μS cm -1 , which was collected very close to the sea at Palar river mouth and has chemical properties indicative of mixing of the seawater with the river water. Therefore, this sample is not considered for further discussion. During pre-monsoon sampling of the Kaveri main course it was observed that EC varies from 355 to 1250 μS cm -1 . Among tributaries of Kaveri, lowest EC value (41.8 μS cm -1 ) observed from river Bhavani at Mettupalayam (45KNT20) and highest value (8650 μS cm -1 ) measured from the Noyil (19KNT7) river. Another sample was collected from the same location of 19KNT7 after digging 30 cm deep pit in the river bed (20KNDW2) having EC values of 4820 μS cm -1 , which indicates that the surface water at this point
Transcript
29
3.1 Introduction
Chemical and isotopic study of the river water provides valuable information on
the elemental fluxes to the ocean. Using this information it is possible to model chemical
weathering rates and amount of CO2 consumed during silicate weathering in a given
drainage basin. Dissolution of CO2 in the rainwater and pore-water of soil results in
lowering of pH and faster weathering of minerals. Silicate weathering is responsible for
CO2 consumption and therefore is an important parameter while modeling global CO2
cycle (Mortatti and Probst 2003). This chapter presents and discusses major ion
composition of the Kaveri, Palar, Ponnaiyar and Vellar in the South India.
3.2 Results
3.2.1 pH, EC and TSL
The measured pH, electrical conductivity (EC) values and Total Suspended Load
(TSL) only from the monsoon water samples from Kaveri, Palar, Ponnaiyar and Vellar
rivers and open/bore well samples are listed in the Appendix
I. The range of pH values
measured on samples collected during the NE monsoon correspondents to alkaline nature
of water. The Palar River is neutral to mildly alkaline (pH 6.95
7.99), Ponnaiyar river is
mildly alkaline (pH 7.19
7.69) and the Kaveri river is mildly alkaline to moderately
alkaline (pH 7.62
8.76). The pH range in Pre-monsoon sample of Kaveri main course is
7.4 to 8.33, in the tributaries 6.3 to 8.12 and in open/bore wells 6.76 to 8.36. Among these
samples highest pH value (8.76) was observed from the monsoon water sample of Kaveri
at Mettur, whereas, the lowest pH value (6.3) was observed from the Arkavati river and
62% of total samples had pH ranging between 7.5 and 8.0.
The EC value of monsoon samples varies between 170 and 1110 µS cm-1 in the
Palar, 430 to 660 µS cm-1 in the Ponnaiyar and 310 to 590 µS cm-1 in the Kaveri river.
The EC value of the sample 1PL (Palar) was 1110 µS cm-1, which was collected very
close to the sea at Palar river mouth and has chemical properties indicative of mixing of
the seawater with the river water. Therefore, this sample is not considered for further
discussion.
During pre-monsoon sampling of the Kaveri main course it was observed that EC
varies from 355 to 1250 µS cm-1. Among tributaries of Kaveri, lowest EC value (41.8 µS
cm-1) observed from river Bhavani at Mettupalayam (45KNT20) and highest value (8650
µS cm-1) measured from the Noyil (19KNT7) river. Another sample was collected from
the same location of 19KNT7 after digging 30 cm deep pit in the river bed (20KNDW2)
having EC values of 4820 µS cm-1, which indicates that the surface water at this point
30
might have been contaminated by the anthropogenic sources. Hence, these two samples
are also excluded from further discussion. EC values for open/bore well samples varies
between 113 and 4820 µS cm-1. Frequency diagrams of EC and pH value for 72 samples
of all rivers and bore/open wells are plotted in the figure 3.1 (A) and (B) respectively. The
temperature of the water samples for both the seasons ranged between 24 and 32.3 ºC,
and the lower temperatures were typically from the samples collected from the Nilgiri
Range.
The difference in EC values checked at the time of sampling and again prior to
analysis in the laboratory determines the freshness of the sample. The conductivity due
to divalent cations is more than that of monovalent cations, but same is not true for the
anions. The conductivity of a water sample can be approximated using the equation EC =
(Ci × fi) in which, EC in µS/cm, Ci = concentration of ionic species i in solution (mg /
L), fi = conductivity factor for ionic species (Hamilton, 1978). The calculated EC value
(ECc) and measured EC values (ECm) for 69 water samples are related by equation ECc =
(1.01 × ECm) + 21.5 with r2 = 0.98.
The total suspended load (TSL) measured on samples collected during the NE
monsoon from Kaveri, Palar and Ponnaiyar rivers are plotted in the figure 3.2. Expectedly
the suspended load decreases drastically in samples collected immediately downstream of
a dam or check dam. In the Palar river TSL varies between 15.06 to 492.42 mg/l, in
Ponnaiyar it is between 52.76 and 85 mg/l in the main stream and in its tributary
(Pamber) 29.74 mg/l is observed.
EC Range
100
200
300
400
500
600
700
800
900
1000
1200
1300
2000
3000
> 30
00
Fre
qu
ency
0
2
4
6
8
10
12
14n = 72A
pH Range6.5 7 7.5 8 8.5 9
Fre
qu
ency
0
10
20
30
40
50n = 72B
Fig 3. 1 A) Number of samples falling in different EC range for 72 samples is plotted here. Nearly 30% of samples are falling between 300 and 600 µS cm-1, B) Frequency of different pH range among 72 sample shows that 62% are falling between 7.5 and 8 pH.
31
Table 3.1 Major ions, Ba, Sr, Rb abundance and 87Sr/86Sr ratios with errors (1 ) determined on water sample of Kaveri, Palar, Ponnaiyar and Vellar rivers are listed below. Major ions are given in µmol/l and Total Dissolved Solids (TDS) are in mg/l. Sampling period and replicates for 87Sr/86Sr ratios measurements are also given for the respective samples. (Note - * Sampling period, M
Monsoon, PM
Pre-monsoon, ** Error and b. d.
below diction limit).
Name S*
Ca Mg Sr Ba Na K Rb Si HCO3
Cl SO4
PO4
TDS
87Sr/86Sr E**
Replicates
E**
Kaveri Main Course
2K M 810 468 2.7 0.65 828 45 0.30
271 2414
560 193 0.5
255
0.714978
± 9 3K M 882 534 2.9 0.71 1057 55 0.02
266 2594
908 270 1.1
295
0.715520
± 5
0.715518
± 4 4K M 1004
635 3.7 0.80 1471 69 0.09
250 2954
1393
344 1.1
357
0.714967
± 6 5K M 881 532 3.0 0.62 1009 51 0.37
334 2624
761 238 0.9
289
0.715763
± 8
0.715747
± 5 7K M 756 460 2.4 0.55 681 34 0.26
254 1573
387 186 0.3
191
0.716171
± 6 9K M 722 430 2.1 0.42 636 30 0.08
230 2293
328 174 0.2
227
0.717165
± 7
0.717176
± 5 10K M 798 502 2.3 0.34 759 30 0.11
292 1918
366 177 0.3
216
0.717931
± 4 1KN1 PM
839 1048
6.0 1.22 4303 174
10.63
343 1804
3960
566 0.9
472
0.713181
± 7 0.713174
± 4 2KN2 PM
887 1109
5.6 1.23 3833 164
11.04
375 1936
3292
580 0.9
451
0.713852
± 6 6KN3 PM
960 1036
5.4 1.23 3409 131
7.62
365 1870
2882
418 0.8
409
0.714039
± 6 9KN4 PM
830 1013
4.8 1.08 3686 132
7.79
373 1837
3178
445 0.8
420
0.713992
± 6 0.713998
± 3 18KN5 PM
867 1057
4.7 0.81 5204 145
7.65
416 2067
4369
458 1.4
516
0.713537
± 6 21KN6 PM
813 880 3.6 0.64 2227 85 7.52
442 1870
1227
240 0.9
299
0.714166
± 6 0.714161
± 4 23KN7 PM
757 906 3.5 0.56 1899 76 8.99
442 1837
898 216 1.2
274
0.715435
± 7 28KN8 PM
787 796 3.8 0.49 1900 81 3.55
373 1870
852 240 1.2
273
0.718107
± 5
0.718119
±3 29KN9 PM
797 785 3.7 0.47 1893 83 13.76
367 1870
854 257 1.1
275
0.718162
± 6 30KN10 PM
794 822 3.8 0.46 1861 77 3.19
370 1936
828 212 1.1
273
0.718068
± 6 34KN11 PM
905 819 3.9 0.47 1389 47 3.76
399 1903
711 119 1.6
253
0.716592
± 5 0.716577
± 4 35KN12 PM
678 593 2.7 0.37 1001 54 11.28
379 1903
457 52 1.4
215
0.713439
± 6 36KN13 PM
985 707 3.5 0.34 971 42 8.53
348 1804
536 91 1.3
228
0.719887
± 5 38KN14 PM
397 717 3.1 0.24 1059 49 9.13
381 1804
529 95 1.5
208
0.702018
± 5 39KN15 PM
537 644 2.8 0.22 968 48 9.08
351 1541
373 33 1.5
182
0.720296
± 4 0.720317
± 5 47KN16 PM
660 740 3.1 0.51 1693 62 11.03
403 1837
704 143 1.5
247
0.716198
± 5 48KN17 PM
1746
2099
5.8 1.08 4263 156
2.62
783 1903
4149
2167
2.6
685
0.710329
± 5 0.710341
± 4 Cont
32
Name S* Ca Mg Sr Ba Na K Rb Si HCO3
Cl SO4
PO4
TDS
87Sr/86Sr E**
Replicates
E**
Kaveri Tributaries
6K M 956 639 5.1 1.06 1292 51 0.02
260 2323
934 276 0.4
290
0.712770
± 7
8K M 1554
1002
5.8 1.16 1604 119
0.37
445 4154
1166
682 2.9
491
0.710002
± 9
4KNT1 PM
2570
1701
38.3
1.04 14377
160
7.52
421 1837
6673
3955
1.2
1162
0.708921
± 5
7KNT2 PM
927 1054
5.2 1.10 3422 128
12.51
369 1870
2717
449 1.0
405
0.713955
± 5
8KNT3 PM
1352
2117
8.7 2.17 5489 113
10.98
660 2692
5334
1129
1.6
701
0.707886
± 5
0.707907
± 3 10KNT4 PM
2953
3845
24.2
8.40 17933
485
13.85
405 572 16536
1152
1.3
1372
0.715433
± 5 12KNT5 PM
776 3802
4.9 0.97 17918
1222
7.28
463 2199
15498
1069
22.3
1368
0.716415
± 4 15KNT6 PM
791 1961
12.4
1.86 8136 398
7.01
660 2051
5503
1569
2.0
748
0.711678
± 6 19KNT7 PM
2746
4403
24.1
1.89 85146
1364
10.79
684 5551
72885
3955
49.3
5494
0.711899
± 6 22KNT8 PM
1244
776 4.4 1.30 1531 89 10.46
468 1755
1195
307 1.0
296
0.709339
± 6 0.709347
± 3 24KNT9 PM
1182
1506
10.2
1.78 12191
183
7.72
747 4006
4943
1462
3.6
931
0.708256
± 6 25KNT10 PM
489 859 3.1 0.31 1930 77 10.91
399 1673
867 171 1.1
247
0.714599
± 5 26KNT11 PM
878 2023
8.0 0.86 6559 118
3.37
1112
3973
2214
1021
2.9
675
0.705285
± 5 27KNT12 PM
762 1424
5.2 0.65 5694 55 8.86
891 3250
2145
645 2.8
551
0.708529
± 4 32KNT13 PM
1626
1309
5.4 0.66 5758 211
6.03
680 3382
4198
328 23.4
641
0.728212
± 5 0.728235
± 4 33KNT14 PM
815 747 3.9 0.49 2180 87 9.52
314 1870
857 324 1.6
285
0.719798
± 4 0.719807
± 4 37KNT15 PM
640 569 2.8 0.40 1005 57 7.85
374 1410
470 84 1.6
186
0.713381
± 6 40KNT16 PM
408 395 1.9 0.25 572 42 3.85
297 917 296 56 1.6
121
0.712354
± 5 41KNT17 PM
148 107 0.6 0.14 221 61 6.72
231 194 268 68 1.2
50 0.707333
± 5 0.707338
± 4 42KNT18 PM
87 35 0.3 0.12 52 28 2.54
59 30 58 19 0.5
14 0.709338
± 6 43KNT19 PM
549 46 1.3 0.29 147 16 14.13
69 128 890 1 0.6
70 0.710205
± 6 45KNT20 PM
43 41 0.2 0.06 88 18 0.68
147 112 45 13 0.6
19 0.711209
± 6 0.711158
± 5 46KNT21 PM
319 209 1.1 0.23 382 54 8.36
192 490 381 41 0.8
82 0.711092
± 4 Palar & its tributary
1PL M 632 1297
3.7 0.42 11351
493
0.55
261 1363
13885
883 0.8
991
0.710151
± 5 2PL M 369 204 1.7 0.25 548 47 0.12
301 1243
345 110 1.5
140
0.711634
± 3 0.711637
± 5 3PL M 361 180 1.4 0.20 490 28 0.27
399 1258
379 209 0.2
150
0.712927
± 7 4PL M 1019
433 5.1 0.81 2515 103
0.38
306 3314
1693
314 1.2
410
0.713096
± 4 0.713086
± 3 5PL M 806 326 2.9 0.44 1013 61 0.21
298 2263
642 322 2.0
261
0.716779
± 5 0.716788
± 5 6PL M 771 318 2.7 0.31 916 48 0.18
280 2203
535 261 3.3
244
0.717611
± 3
33
Name S* Ca Mg Sr Ba Na K Rb Si HCO3
Cl SO4
PO4
TDS
87Sr/86Sr E**
Replicates
E**
7PL M 1095
552 4.0 0.35 1152 38 0.22
406 3224
473 361 1.5
340
0.718850
± 3
8PL M 764 317 2.5 0.27 1136 51 0.34
308 2083
761 289 2.6
253
0.718754
± 7
9PL M 801 344 2.7 0.33 1191 53 0.19
302 2323
770 348 2.5
276
0.718226
± 7
Ponnaiyar & its tributary
10AMB M 1244
830 6.8 0.71 2861 119
0.20
449 4545
2002
398 3.1
534
0.715666
± 9
1PO M 1074
453 3.7 0.63 1446 105
0.37
313 2894
1037
186 6.3
329
0.718446
± 4 2PO M 903 498 3.6 0.63 1588 100
0.09
284 2834
1178
284 5.6
335
0.716793
± 5 3PO M 956 529 3.6 0.60 1608 101
0.29
296 1933
1285
264 2.9
286
0.716659
± 6 4PO M 986 562 3.8 0.71 1624 101
0.23
318 3059
1333
283 4.8
361
0.716045
± 5 Vellar
1K M 740 423 2.9 0.47 996 41 0.48
356 2984
789 200 1.4
301
0.711703
± 5 Bore well samples along Kaveri and its tributaries
17KNDW1 PM
1811
2603
18.9
3.74 13362
203
0.19
588 1936
13632
1236
1.8
1170
0.712626
± 5 20KNDW2 PM
1227
2337
13.0
1.31 43672
738
b. d
608 3086
38417
2334
3.8
2895
0.712050
± 7 3KNOW1 PM
271 496 6.4 1.49 14779
86 7.61
920 4170
4549
790 2.7
873
0.713684
± 6 5KNBW1 PM
1532
1597
5.9 0.87 3262 389
b. d
1578
2889
2510
698 3.3
557
0.714052
± 5 11KNBW2 PM
1835
2749
22.8
3.27 2306 222
b. d
1481
3201
2846
392 4.3
574
0.713124
± 5 13KNBW3 PM
5009
5676
42.1
0.96 17978
689
2.20
685 2231
16536
4055
2.4
1850
0.714586
± 5 14KNBW4 PM
4139
5142
32.1
0.94 16676
593
13.91
568 2215
16182
3632
1.9
1717
0.715141
± 5 16KNBW5 PM
447 1173
8.5 0.72 4028 117
8.44
893 2856
2439
717 2.7
489
0.710216
± 7 31KNBW6 PM
1302
1793
4.0 0.64 2306 1523
b. d
1653
4236
539 273 11.9
556
0.707241
± 5 44KNBW7 PM
208 207 0.5 0.21 134 20 5.91
367 375 129 9 1.4
56 0.714431
± 6 Table 3.2 Major ions (µmol/l), Sr abundance (pg/g) and 87Sr/86Sr ratios with errors (1 ) determined using TIMS on rain water
samples and moisture sample are listed below. Date of sample collection and the calculated pH for rain water from the cation and anion given in the table except for PRW1 which was measured after collection. Note: n. m.
not measured.
Name
Date of Collection pH Ca Mg Na K HCO3
Cl SO4
PO4
Sr 87Sr/86Sr Error
PRW1
13/09/2006 4.35
13.99
4.50 43.01
1.42
26.79
48.90 9.40
0.22
324.2 0.710474 ± 5 PRW2
25/09/2006 4.61
8.11 1.41 37.72
3.06
26.79
48.90 n.m 0.37
548.4 0.710143 ± 11 PRW3
04/10/2006 4.33
2.73 0.80 36.20
1.65
26.78
41.64 1.90
0.14
313.8 0.710080 ± 7 PMW
October, 06 n.m 13.87
2.39 n.m n.m
15.76
227.56
n.m n.m
1.41 0.710024 ± 6
34
The highest TSL value (194.37 mg/l) in the Kaveri river was observed from the sample
number 2K and the lowest value (17.05 mg/l) measured from the sample collected
immediately after the Mettur dam. Whereas the sample collected before Mettur dam
(Hogainakal) shows the TSL values of 50.96 mg/l. As the Palar river flooded after several
years, during the 2005 NE monsoon period the highest amount of suspended load (in mg/l)
was observed compared to other three river sampled at the same period.
Monsoon sample locations in the main course
1PL
2PL
3PL
4PL
5PL
6PL
9PL
8PL
4PO
3PO
2PO
1PO 2K 3K 4K 5K 7K 9K 10K
TS
L (
mg
/l)
0
100
200
300
400 PalarPonnaiyarKaveri
Check Dam
Sattnur Dam
Mettur Dam
Towards Mouth
Fig 3.2 The TSL values (mg/l) for the all monsoon samples collected from the main course of the Palar, Ponnaiyar and Kaveri rivers plotted against the location. The locations are arranged in the ascending order (up stream direction) towards right (mouth of the river is towards origin of the graph). Presence of a dam along the course of river is indicated by downward pointing arrow.
3.2.2 Major Ion Chemistry of river water:
The results of chemical analysis of monsoon and pre-monsoon water samples from
Kaveri, Palar, Ponnaiyar and Vellar rivers and open/bore well samples are given in the Table
3.1. Total cation and anions of 24 monsoon samples are related by an equation TZ+= 0.9196
TZ- + 0.4466 (r2 = 0.977) with a correlation coefficient of 0.99, where, TZ
+ = total cation and
TZ-
= total anions, expressed in milli-equivalent per liter (meq/l). There are 40 pre-monsoon
water samples of river Kaveri and its tributaries that show higher TZ+ than the TZ- in (meq/l).
35
These samples are related by an equation TZ+ = 1.1829 TZ- + 1.5301 (r2 = 0.98). The
difference in inorganic charge balance between monsoon and pre-monsoon water sample
may be due to the presence of negatively charged organic acids and ligands (Viers et al.
2000) which is more in monsoon water samples than the pre-monsoon water.
The total cation ( TZ+) and total anion ( TZ-) in the pre-monsoon water samples
show a wide range, TZ+ varies from 0.27 to 100.85 (68% samples are <10 meq/l, 22% are
between 10
25 meq/l) and TZ- varies from 0.12 to 85.15 in meq/l (80% samples are <10
meq/l, 15% are between 10
25 meq/l). Expectedly, the TZ+ (2.97
6.84 meq/l) and TZ-
(2.27
6.46 meq/l) of water samples of Kaveri collected during monsoon are lower than the
pre-monsoon samples. The monsoon water samples of Palar and Ponnaiyar river, TZ+ and
TZ- values are ranges from 1.6
7.14 and 1.77 - 7.21 in meq/l respectively. These temporal
variations indicate that during pre-monsoon period water rock interaction time and
evaporation are higher than the monsoon period hence more ions are present in the pre-
monsoon water samples.
Bicarbonate is the most dominant ion (27
79% of anion budget) in all the river
samples collected during monsoon period and it is followed by Ca2+, whereas, in case of pre-
monsoon water samples Na+ is the most dominate ion in meq/l. Average concentration of
ions are listed both in meq/l and mg/l unit separately in descending order in the table 3. 3. In
mg/l unit bicarbonate shows highest concentration (50
60% of the total ion for monsoon
sample, 10
50% for pre-monsoon sample) among ions in all the water samples. Ca
constitutes 40-45% of cations; Mg and Na constitute 20-28% and 25-35 % respectively of the
total cations in meq/l unit in all three-river monsoon period water samples. The pre-monsoon
water samples of Kaveri main course shows 20
44% of Ca, 22
43% of Mg and 22
57%
of Na, among the total cations in meq/l, whereas, in its tributaries there is no proper trend in
cation or anion concentration as each of them drain different geological formations. Other
cations such as K, Sr, Rb, and Ba contribute much less to the total cations. Dissolved silica in
river water comes entirely from weathering of silicate minerals, which varies between 343
442 µmol/l in the pre-monsoon sample of Kaveri main course; in case of its tributaries it
ranges from 58
1112 µmol/l and in monsoon water samples shows variation between 229 -
449 µmol/l. The average Si value of these rivers is close to the global average of 427 µmol/l.
River Name
S In meq/l In mg/l TDS Avg.
TDS Range
36
Table 3.3 Major ions are arranged in descending order according to their average abundance in meq/l and mg/l. River name, sampling period, average TDS and range of TDS values are also listed here.
The total dissolved solid (TDS) in the river water samples vary between 14
5494
mg/l. All the samples of tributaries that are collected in and around Nilgiri range have < 100
mg/l TDS value, as these exclusively drain massive granulite (charnockite) rocks. The TDS
values in Kaveri main course for pre-monsoon and monsoon period vary between 182 and
685 mg/l, but in its tributaries it varies more widely (14
5494 mg/l). Among 64 samples
(excluding 8 bore/open well sample) analyzed nearly 56% of samples have the TDS value
ranging between 200
400 mg/l (Fig 3.3).
TDS (mg/l)
0 -
100
100
- 20
0
200
- 30
0
300
- 40
0
400
- 50
0
500
- 60
0
600
- 70
0
700
- 80
0
1000
-14
00
> 14
00
Fre
qu
ency
0
5
10
15
20
25n = 64
Fig 3. 3
Frequency distribution plot for total dissolved solid (TDS) for 64 samples. Nearly 56% of samples fall between 200 and 400 mg/l.
The TDS (mg/l) and EC (µS/cm) are related by a constant, TDS = EC × C, where C is
in the range of 0.5 to 0.9, whose value depends on the composition of the ions. Typically the
constant C is high for chloride-rich waters and low for sulphate rich waters (Hydrology
project, 1999). The ratio of TDS / EC for the monsoon samples are 0.84 for Palar, 0.77 for
Palar M
HCO3>Ca>Na>Cl>Mg>SO4>K
HCO3>Ca>Na>Cl>SO4>Si>Mg>K
270.0 140 - 991
Ponnaiyar M
HCO3>Ca>Na>Cl>Mg>SO4>K
HCO3>Cl>Ca>Na>SO4>Mg>Si>K
380.1 286 - 534
Vellar M
HCO3>Ca>Na>Mg>Cl>SO4>K
HCO3>Ca>Cl>Na>SO4>Mg>Si>K
312.8 -
Kaveri M
HCO3>Ca>Mg>Na>Cl>SO4>K
HCO3>Ca>Cl>Na>SO4>Mg>Si>K
290.1 191 - 491
Kaveri main
PM
Na>HCO3>Mg>Ca>Cl>SO4>K
HCO3>Na>Cl>Ca>SO4>Mg>Si>K
334.5 182 - 685
Tributaries (Avg.)
PM
Na>Cl>Ca>Mg>HCO3>SO4>K
HCO3>Cl>Na>Ca>SO4>Mg>Si>K
734.0 14 - 5494
37
Ponnaiyar and 0.81 for Kaveri, whereas, in all pre-monsoon samples it is related by the
equation TDS= (EC × 0.61)
60.8 with r2 = 0.98.
The TDS values and concentration of cations and anions in the monsoon samples of
the three rivers do not show much variation along the main course except in tributaries.
Whereas, the TDS value and abundance of Na+, Mg2+, Cl- and SO42- ions in pre-monsoon
samples of the main course of Kaveri increases (Fig 3.4) and PO4 concentration decreases
towards mouth. Ca, HCO3 and Si concentration do not show much variation throughout the
600 km stretch. The concentration of most of the ions are either lowered or increased in the
samples collected at confluence of tributaries compared to their values in the tributaries.
Distance (km)
0 100 200 300 400 500 600 700
Co
nce
ntr
atio
n (
mg
/l)
0
20
40
60
80
100
120
140
160
180Mg Na Cl SO4
KaveriMouth
Fig 3.4 Abundances of Na+, Mg2+, Cl- and SO42- ions in pre-monsoon samples of Kaveri
plotted against the distance. The concentrations of these ions increase towards mouth.
The sample 47KN16 and 48KN17 of Kaveri were collected, one from the power
channel and another from the causeway of the Mettur dam. The sample collected from the
power channel (47KN16) with TDS value 247 mg/l follows the trend obtained from the main
course of the river sample, whereas, the sample 48KN17 shows higher TDS value (685 mg/l)
and does not show any relation to the adjacent samples. This spurious behavior of the
sample, 48KN17, may be because of the anthropogenic input from a tourist spot immediately
after the dam. The amount of water flow through the causeway is very low compared to the
38
power channel, therefore, this anthropogenic input does not affect the river water chemistry
further down stream. Hence the sample 48KN17 was not considered for further discussion.
Marudaiyar river flows mostly through the Trichinapally Formation of the Cretaceous
age, where occurrence of evporites are reported. The water sample of this river shows the
highest SO4 abundance (317 mg/l) and the third highest Ca concentration (103 mg/l) among
all the samples of Kaveri and its tributaries.
As mentioned earlier the two samples (19KNT7 and 20KNDW2) collected from the
Noyil river show the highest TDS (5494 and 2895 mg/l respectively) and Na and Cl
concentrations among the samples collected during pre-monsoon period. Na and Cl
concentrations together account for the ~82% (in mg/l) of the total ion measured from these
two locations. This unusually high concentrations in the Noyil river water is due to addition
of waste from hundreds of small industries located along the Noyil river. These industries are
mainly dying and bleaching units of textiles, hosiery and carpets that discharge effluents
directly into the river. The turgid, multicolored and foul smelling surface water of the Noyil
river gives abundant indication of pollution. At the sample location (Pugalur) in the Kaveri
main course after Noyil confluence shows sudden increase in Na and Cl concentration (Fig
3.4) during the pre-monsoon period. This is due to lean flow in the main course during the
pre-monsoon period the pollution effect of Noyil river is more pronounced.
After Noyil river samples, 10KNT4 and 12KNT5 samples collected from Kadavanur
and Naganji rivers respectively, show higher TDS values. Both the rivers are tributaries of
Amaravati and during sample collection flow was very less. Na, Mg, Cl, Si, and SO4,
concentrations are nearly similar in these two rivers, but Ca, Sr, Ba and Rb are higher in
Kadvanour river sample (10KNT4) and HCO3, PO4 and K are higher in Naganji river sample
(12KNT5).
The sample collected from Bhavani at Mettupalayam (45KNT20) and from the
tributaries of Payakara (42KNT18) shows very low TDS values of 19.18 and 14 mg/l
respectively. Water samples 41KNT17, 42KNT18 and 43KNT19 show higher Cl values than
the Na in meq/l. Among them the highest Cl/Na ratio was observed from the sample
collected after the Payakara dam (43KNT19) with TDS value of 70 mg/l, in which 45%
account for the Cl, 5% for Na and 31% for the Ca. Near to these sample location, Hindustan
39
Photo Film, the manufacturer of photo film is located and the effluent coming out from its
dumps may be causing excess Cl in the surface water.
Three samples were collected from the Bhavani river course, besides its tributaries.
The TDS and concentrations of various ions gradually increase towards the confluence point
(e.g. 19 to 296 mg/l in case of TDS). Similar trend is observed from the two samples
collected from the Kabini river. This trend was reverse in case of two sample of Ayiar river
(7KNT2 and 8KNT3) where the TDS and other ions abundance decreases towards the
confluence point.
One sample is collected each of the tributaries of Kaveri river such as Shimsa,
Arkavati, Chinnar, Nagavari, Toppayar and Sarvanga. One suface sample at Chinna
Rajpuram (15KNT6) and another dug well sample near Karur were collected from the
Amaravati river but the dug well sample (17TNBW1) shows the higher TDS and other ions
concentration than the surface sample.
3.2.3 Seasonal Variation:
During both monsoon and pre-monsoon period seven samples each were collected
from the seven location along the Kaveri main course and two from its tributaries Amaravati
and Bhavani. Fig 3.5.A., shows the comparison between monsoon and pre-monsoon
concentration of different ions and TDS. River Amaravati was dry near Karur during pre-
monsoon sampling and sample 17KNDW1 was collected after digging a 0.5 m deep pit on
the river bed and surface water was collected from Chinna Rajpuram (15KNT6). Here the
15KNT6 sample was compared with monsoon sample collected from the Karur (6K).
The HCO3 concentration is higher during the monsoon period except in a sample
collected at Erode. Ca concentrations in samples of both the periods are nearly equal and
other ions such as Mg, Na, Cl and SO4 are higher in the pre-monsoon samples. The TDS
value is higher in the pre-monsoon samples except for a sample from Bhavani (Fig 3.5 A).
TDS and major ion abundance in the monsoon samples of the Kaveri, Palar, Ponnaiyar and
Vellar river are compared with each other using samples collected near to the mouth (Fig 3.5
B).
40
0
100
200
300
4000
100
200
300
400
Co
nce
ntr
atio
n (
pp
m)
0
100
200
300
4000
50100150200250300
0
50
100
150
200
250
050
100150200250
Co
nce
ntr
atio
n (
pp
m)
0
200
400
600
0100200300400500Thirumannur
Trichhi
Musiri
Erode Mettur
Hogainakal
Amaravati
Bhavani
HCO3 Cl SO4 TDSNa KCa Mg Si HCO3 Cl SO4 TDSNa KCa Mg Si
Major Ions Major Ions
MonsoonPre-Monsoon
Major Ions
Ca Mg Na K Si HCO3 Cl SO4 TDS
0.1
1
10
100Palar (2PL)
Kaveri (2K)
Ponnaiyar (4PO)
Vellar (1K)
Co
nce
ntr
atio
n (
pp
m)
Fig 3.5 A) Comparison of major ion concentrations and TDS values between monsoon and pre-monsoon water sample of the Kaveri main course. Sampling stations are given in the upper left corner of the plot. B) Comparison of TDS and major ion abundances in the monsoon samples collected near to the mouth of the Kaveri, Palar, Ponnaiyar and Vellar rivers.
A)
B)
41
Table 3.4
Correlation of Major ions and TDS of the water sample collected during
monsoon and pre-monsoon periods and also for open/bore well samples are given separately below.
Kaveri Main Course, Monsoon Sample pH EC Ca Mg Sr Ba Na K Rb Si HCO3
The correlation among major ions and TDS for all the water samples collected during
monsoon and pre-monsoon from the different rivers are given in the Table 3.4. Monsoon
water samples of Kaveri show good positive correlation among all the ions except Rb. In
case of pre-monsoon samples of Kaveri main course, the correlation was selective, Ca shows
good correlation with Mg, Si, SO4 and TDS, Sr with Ba, Na, K, Cl and TDS, and Na with Cl
and TDS. Among the samples of Kaveri tributaries good positive correlation was observed
between Ca and Sr, Mg and K, Sr and SO4, Na with TDS, Cl, K and PO4, K with Cl, PO4 and
TDS, and Si with HCO3 (Table 3.4). Monsoon samples of Palar and Ponnaiyar show good
correlation among various ions except Si (only for Palar), Rb and PO4. In Ponnaiyar river Si
is well correlated with Mg, Sr, HCO3 and TDS.
In the ternary diagram of H4SiO4, HCO3 and Cl+SO4 (Fig 3.6) most of the samples
plot close to the base i.e., line joining HCO3 and Cl+SO4 except those from the three
tributaries. Most of the monsoons samples including those from Kaveri plot more close to the
HCO3 apex, whereas, pre-monsoon samples fall along a trend starting from the Cl+SO4 apex.
Samples from the tributaries Moyar, Paykara and Bhavani (at Mettupalayam) show higher
relative abundance of H4SiO4 among the anions plotted in the ternary diagram than all other
river samples.
The equivalent ratio of Cl/SO4 in the monsoon water samples show a narrow range
varying between 1.02 and 3.34 (mean value 1.9) except the sample of 7PL, a tributary of
Palar (0.78). Whereas, pre-monsoon samples show a wide range between 1.01 and 11.06
(mean = 3.9, 75% of samples are between 1 and 5). Tributaries Kadvanour, Naganji, Noyil
and Arkavati show higher ratio than the other rivers.
Silica shows an overall increasing trend with HCO3 both in monsoon and pre-
monsoon water sample. The average molar ratio of HCO3/silica is higher in the monsoon
water samples (3 to 12, mean ~ 8) than pre-monsoon sample (0.5 to 8, mean ~ 4). The rivers
showing these ratios ~2
3 are consistent with the weathering of minerals from mafic rock to
kaolinite/smectite and if the ratios are higher ~5
10 are from carbonate weathering, salt
affected soil or from anthropogenic source (Das et al., 2005).
44
HCO3
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
H4SiO4
0.0
0.1
0.2
0.3
0.4
0.5
Cl + SO4
0.5
0.6
0.7
0.8
0.9
1.0
Palar (Monsoon)Ponnaiyar (Monsoon)Kaveri (Monsoon)Kaveri (Pre-monsoon)Kaveri Tributaries (Pre-monsoon)Open/Bore Well
Fig 3.6
Ternary anion plot of monsoon and pre-monsoon water sample of Kaveri, Palar and Ponnaiyar rivers and tributaries. Sample of Kaveri collected during monsoon and pre-monsoon define two separate trends.
The strong correlation was observed among SO4
Cl, and (Cl +SO4)
Na (Fig. 3.7
A, B), both in monsoon and pre-monsoon water sample of Kaveri river and its tributaries.
This indicates that Na, Cl and SO4 were derived from common sources, such as rain,
evaporites, salt affected soil and anthropogenic input. Many of the Kaveri tributaries have Cl
and SO4 in excess of that supported by rainwater (Tables 3.1 and 3.2). Potential sources to
balance the excess of these ions are evaporites, saline soils, and discharge from spring water
or groundwater and anthropogenic inputs. In addition, for SO4, pyrite oxidation can be a
source. Only along river Noyil and Amaravathi presence of alkali soil has been reported in
the salt affected soil map of India published by Survey of India. There are no reports of halite
or other evaporites exposed in these river basins except the Trichinapally Formation, which is
exposed at the toe of the Kaveri delta. Therefore, evaporites are unlikely source for these ions
in the tributaries and main course of the river.
45
Cl (meq/l)0.01 0.1 1 10 100
SO
4 (m
eq/l)
0.001
0.01
0.1
1
10
MonsoonPre-monsoon
A
Cl + SO4 (meq/l)
0.01 0.1 1 10 100
Na
(meq
/l)
0.01
0.1
1
10
100
MonsoonPre-monsoon
B
Fig. 3.7 A) Scatter plot of SO4 and Cl of water sample collected during monsoon and pre-monsoon shows a good positive correlation. (B) Na and (Cl+SO4) plot also shows a strong correlation between them. It is inferred that Na, Cl, and SO4 may be derived from a common source.
3.2.5 Water
mineral equilibria:
The chemical composition in terms of dissolved ions can be explained on the basis of
weathering of various minerals in the drainage basin. The two major ions HCO3- and SO4
= in
surface water are dominantly derived from the dissolution of CO2 from atmosphere and by
the oxidation of sulfides. These two reactions (Appendix II
sect 2.1 and 2.2) provide bulk
of the protons used to chemically weather carbonates and silicates in drainage basins. To
46
understand this, the ionic strength of water, PCO2, saturation index of calcite, aragonite,
vaterite, dolomite, gypsum, barite, amorphous silica and quartz (Garrels and Christ, 1965;
Garrels and Mackenize, 1971; Russell, 1976; Holland, 1978; Stumn and Morgan, 1981;
Krauskopf and Bird, 1995; Singh, 1997; White, 2003) were calculated and details given in
the Appendix II.
Mineral stability diagrams helps to understand the existing equilibrium between
silicate mineral and natural water. By studying the water chemistry, stable mineral
assemblage can be theoretically predicted (Garrels and Christ, 1965; Stumn and Morgan,
1981; Faure, 1998). From the position of river water samples in different mineral stability
diagram for silicate system indicate that kaolinite, Mg-montmorillonite and Ca-smectite
minerals are dominant in the drainage basin. Similar clay mineral assemblages are reported
by Singh and Rajamani (2001) from Kaveri flood plain sediments. Details of mineral stability
diagram are given in the Appendix
II.
3.2.6 Open/Bore well samples
The open/bore well samples collected along the Kaveri river and its tributaries are
related by equation TZ+ = 1.5 TZ- + 0.4359 (r2 = 0.98). TDS in case of open/bore well water
samples are ranging from 56 to 1850 mg/l. The bore well sample 44KNBW7collected from
Ooty has lowest TDS value (56.4 mg/l) among 8 open/bore well sample and highest value
(1850 mg/l) was observed from the 13KNBW3 sample, collected at Aravkuruchi.
The sample 13KNBW3 and 14KNBW4 was collected from two nearby bore wells (10
meter away from each other) from outskirt of Aravakuruchi town near the Naganji river.
These two samples show higher concentration of all major ions than other samples, except
SO4. Between these two bore wells, 13KNBW3 is less used for domestic purpose by the local
people and our observation from the water chemistry confirms that it has high TDS value and
higher hardness.
Flood plain and banks of the Naganji river are covered with thick pan of calcrete but
the Ca concentration in the surface water of Naganji river did not show higher Ca value (31
mg/l), whereas, these bore well sample have 166 and 201 mg/l of Ca concentration. The
HCO3, Na and Cl concentrations, both in surface water and in bore well sample are nearly
equal, but Mg, Sr and SO4 values are higher in the bore well samples, and K is higher in the
surface samples. The sample 31KNBW6 collected from Billigundla shows highest HCO3, K
47
and Si concentration of 258, 60 and 46 mg/l respectively among bore well samples. The
surface sample of Kaveri at Billigundla shows the lower concentration than the bore well
sample except for Cl. The sample 11KNBW2 was collected from the banks of Kadvanour
river and it shows lower concentration of major ions than the surface water sample and
higher values for Si, HCO3 and PO4, and similar behavior is observed from the sample
16KNBW5 and 15KNT6 of Amaravati river at China Rajpuram.
These well samples can not be directly compared with the surface running water
samples, although they were collected from location close to surface water sampling points.
Rock-water interaction time is very high in case of bore well sample and it generally gives
the higher TDS value than the surface water. The aquifer, recharge area and the geological
formation through which ground water travel are important while studying the bore well
water sample.
3.3 Sources of Major Ions:
Major ions are supplied to rivers mainly through chemical weathering of various
lithologies in the basin, dry and wet atmospheric deposition and anthropogenic sources.
Generally sea salt aerosols and atmospheric dust are the dominant sources of major ions to
rain in the basin. Contribution of major ions from atmospheric deposition can be determined
from regional rainwater composition and subtracted from the abundance of various ions in
the river water to estimate the other contribution.
3.3.1 Atmospheric Contribution:
In this study, three individual rainwater samples were collected at Pondicherry
University on the east coast and analyzed for their major ions and Sr isotopic composition
(Table 3.2). Besides this, the rainwater data (Table 3.5) from Tirupati (Mouli et al., 2005),
Banglore (Sequeria et al., 1978) and Nilgiri (Rao et al., 1995) were used to correct the
atmospheric contribution after following the method outlined by Das et al. (2005). Three
rainwater samples from east coast will reflect the oceanic end-member composition but
Tirupati and Bangalore are urban sites situated ~80 km and ~300 km (air distance) inland off
the east coast respectively, will represent the supply of solute derived from dust to the rain
water. The rainwater data of Nilgiri, located ~100 km inland off the west coast are used for
atmospheric correction of water samples from the Kabini, Bhavani and its tributaries.
48
The Cl- concentration in rain water from Pondicherry and Nilgiri is nearly identical (~
45 µmol/l) and it decreases to 33.9 and 20.59 µmol/l in Tirupati and Bangalore, respectively.
The Cl/Na molar ratio varies among all the rainwater between 0.93 and 1.29. Three rain
samples (PRW1, PRW3 and Bangalore) are close to the value of marine end member
(~1.16). Sample PRW2 showing higher Cl/Na molar ratio of 1.29, indicates that the excess
Cl may be due to salt spray, whereas sample from Tirupati and Nilgiri are having 0.93 and
1.02 indicating supply of dust derived Na to rain.
Table 3.5 Abundance of major ions in rainwater (µmol/l) from three different locations of southern India.
Depending on the sample location and its distance to the four rainwater data location,
rainwater values of either one station or average values of two adjacent stations were used for
the correction of atmospheric contributions. For monsoon water sample the dissolved Na was
corrected for contributions from sources other than chemical weathering, by subtracting an
amount equal to dissolved Cl of the river water (Na* = Na riv
Cl riv). For pre-monsoon water
samples an additional correction is needed for Na, because of its input may be from the
sources other than rain. Hence, Na* is given by Na* = Nar
Clr + {1 - (Na Cl) rain} x Cl rain
fet, where Nar and Clr are the concentrations in rivers, and fet - factor for evapo-transpiration
loss (Das et. al 2005). SO4 and other cations such as Ca, Mg and K were corrected (Table
4.6) using the equation X* = X riv
{(X/Cl) rain × (Cl rain / fet)} (Das et.al 2001).
Due to scarcity of run off data in the drainage basin actual factor for evapo-
transpiration loss could not be reliably estimated. Using remote sensing data, Zade et al.
(2005) estimated average annual runoff for different river basins of India. They have
estimated that Kaveri basin s average annual runoff is 5.16 million hector meter (M ha m)
considering 1249.28 mm annual rainfall over the basin area. The average annual runoff depth
over Kaveri basin found to be 635.8 mm. However, monsoon samples were collected during
heavy rainfall season having high runoff, and therefore the evapo-transpiration factor (fet)
could be close to unity. For the pre-monsoon water sample the fet was calculated as 0.51
(evapo-transpiration enrichment of 49%) from the above rainfall and runoff data. Slight
49
deviation in estimating fet, if any, would not change the inferences drawn as elemental ratios
instead of their abundances were used for the interpretations and modeling.
Table 3. 6 Major ions concentration in µmol/l after correcting for atmospheric input.
Sample
Na* Ca* Mg*
K* SO4*
Sample Na* Ca* Mg* K* SO4*
2PL 202 360 202 45 86
29KN9 1005 751 769 77 182
3PL 112 352 178 26 169
30KN10 999 748 806 71 145
4PL 823 977 418 85 227
34KN11 645 859 803 41 67
5PL 371 764 311 44 233
35KN12 482 634 578 47 16
6PL 380
722
300
29
177
36KN13 373
941
692
35
49
7PL 676 1046 534 20 261
38KN14 468 353 702 42 52
8PL 375 714 299 33 201
39KN15 533 493 629 42 - 9PL 421 751 326 34 250
47KN16 955 614 724 56 87
10AMB
859 1195 812 101 291
4KNT1 7629 2554 1696 156 3285
1PO 409 1025 436 87 115
7KNT2 636 845 1025 93 306
2PO 411
861
483
82
202
8KNT3 86
1270
2087
78
873
3PO 323 914 514 83 186
10KNT4 1348 2856 3810 449 881
4PO 291 978 560 99 230
12KNT5 2371 679 3767 1186 812
1K 208 732 421 39 161
15KNT6 2584 694 1926 362 1229
2K 268 802 466 43 155
19KNT7 12200 2702 4389 1357 3268
3K 150 874 532 53 220
22KNT8 275 1200 761 82 228
4K 78
963
620
52
252
24KNT9 7199
1085
1471
147
1140
5K 248 840 517 33 164
25KNT10 1014 392 824 41 64
6K 358 906 621 32 190
26KNT11 4297 781 1988 82 772
7K 295 707 443 16 115
27KNT12 3500 665 1389 18 459
8K 439 1533 995 115 556
32KNT13 1526 1580 1293 205 242
9K 308 699 421 27 129
33KNT14 1290 769 731 81 238
10K 393
775
494
27
132
37KNT15 446
598
556
49
46
1KN1 268 823 1044 170 461
40KNT16 187 366 381 34 24
2KN2 466 871 1105 160 472
41KNT17 - 127 100 57 45
6KN3 457 879 1006 95 281
42KNT18 - 66 28 24 4
9KN4 438 748 983 97 302
43KNT19 - 528 39 12 - 18KN5 786 770 1022 109 303
45KNT20 43 28 34 14 - 21KN6 951
716
845
48
122
46KNT21 2
277
195
46
11
23KN7 952 660 871 40 101
17KNDW1
- 1714 2568 167 952
28KN8 1014 741 779 75 168
20KNDW2
5193 1183 2322 731 1918
Percentage of atmospheric contribution for each ion was calculated separately for
monsoon and pre-monsoon water samples and their mean and ranges are given in the Table
3.7. Few samples of pre-monsoon period show unusually high percentage of contribution
from rain, which is listed in the last row of the table as excess in PM sample. In case of Na
and K, the mean percentage of atmospheric contributions is nearly equal with respect to
monsoon and pre-monsoon water samples (Table 3.7). Whereas, pre-monsoon water samples
of tributaries like Aiyar, Kadvanur and Bhavani show more than 90 % of Na (in Bhavani
50
99.5%), and Chinnar river shows 66.46 % of K contribution from atmosphere. Similarly,
mean percentage of Mg from atmospheric contribution is nearly equal for monsoon and pre-
monsoon water samples, whereas, two samples from Pyakara and one sample from Bhavani
at Mettupalaym show higher percentage of contribution than the other samples (Table 3.7).
In case of Ca and SO4 the atmospheric contribution is lower in the monsoon water samples
compared to the pre-monsoon samples.
Table 3.7
The mean and range (in percentages) of major ion contribution from atmospheric and other sources given separately for monsoon and pre-monsoon water samples. The pre-monsoon samples that show excess values are listed in the last row with sample name and percentage (inside the parenthesis). M
Monsoon, PM
Pre-monsoon, n
Number of samples.
3.3.2 Anthropogenic and Biological Input:
Water from mining, industrial effluent, agricultural wastes and sewage, when not
properly treated and drained into the river, increases the solute load of the river. High
concentration of certain element like Na, Cl, SO4, NO3 and PO4 are the main indicators of the
anthropogenic contribution. The water sample of 19KNT7 and 20KNDW2 that have
unusually high concentrations of these elements and TDS are those severely affected by the
anthropogenic activities.
The monsoon water samples were collected during northeast monsoon of 2005
(~1200 mm) when these rivers were flowing bank to bank due to unusually heavy rainfall.
Anthropogenic contribution to major ion abundances and Sr isotope composition would have
been much small due to the dilution effect. Estimation of individual contributions from salt-
affected soils and anthropogenic sources to Cl, SO4, and Na budgets of rivers remains
elusive. It is possible to derive the total contribution from these two sources by assuming that
all Cl in rivers in excess of that supplied from rains is from them. A few samples which show
unusual higher Cl concentration than Na are not considered for the further discussion. All
other samples were corrected for atmospheric contribution using the Cl concentration.
Atmospheric
contribution
Na Ca Mg K SO4
M PM M PM M PM M PM M PM Mean 68 64 3.7 8.2 2.5 2.3 19.8 15.9 11.5 22.1 n 23 35 24 37 24 35 24 37 24 37 Range 41-95
34-99.5
0.8-6.5
0.6-24.7
0.17-5.6
0.26-6.6
0.4-54
0.9- 47.7
0.7-25.8
0.3- 75.5
Excess in PM Sample
- 45KNT20 (49.7)
42KNT18 (20.1) 43KNT19 (15.2) 45KNT20 (17.2)
27KNT12 (66.46)
42KNT18 (75.5)
51
The effect of storage of ions in the biomass present in the watershed on the mass
balance calculation is not well understood (Velbel, 1985; Paces, 1986; Bluth and Kump,
1994). The potential of biomass storage of silica and other nutrients in the Amazon was
recognized by Stallard and Edmond (1983), but they did not directly account for the
biological reservoirs in their result. In a quantitative experimental evaluation Robart and
Berthelin (1986) concluded that microbial attack enhanced dissolution rate up to 20% in
periods typically within only a few months.
Drever (1997) recognized that the ions especially K, Ca, P and N are the major
nutrients for biomass and they get accumulated in their different parts of the body. However,
decay of organic matter can release these elements to the river and nutrient like N and P are
recycled and reconverted to organic matter by plant uptake. It is assumed that Si can be used
to determine the balance of relative solute weathering as it is often not affected to any great
extent by biological uptake or absorption. However, earlier studies regarding the effects of
plants on rock weathering, especially on those species in tropical areas have shown that silica
is accumulated in their system (Lovering, 1959; Rodin and Bazilevich, 1965). Hardwoods,
grasses, palms and sugarcane may contain SiO2 as much as 3% of their dry weight. Similarly,
potassium concentrated in plant leaves is derived from silicate weathering (Krishnaswamy
and Singh, 2005). Due to lack of information regarding the role of individual species existing
in the present study area, it is difficult to estimate the exact contribution or absorption of ions
by the biomass.
Fig 3.8 Schematic representation of contributions of various elements from atmosphere, anthropogenic, chemical weathering of rocks and their uptake and release by biomass to the river, ground water and pore waters.
Uptake
Biomass
Rock Weathering
Run off
Ion Budget of River water Ground water Pore water
Anthropogenic input Atmospheric
input
Release after Decay
52
The uptake of major ions as nutrient by biomass will be returned back to the system
on their decay. Hence it may be assumed that on a long time scale the biomass storage of
these ions will reach equilibrium, balancing their uptake and release. This is schematically
represented in Fig 3.8.
3.3.3 Chemical weathering:
Major ion data of the river water after correcting for the atmospheric input into the
river ion budget is given in the Table 3.6. Corrected Ca* and Mg* abundances show a
positive correlation (Fig. 3.9) indicating that both the elements might have derived from a
common source. In this plot, monsoon water samples of Kaveri plot below the pre-monsoon
sample. The water samples of tributaries are more scattered than the main course samples. Ca
and Mg values of the main course samples mostly range between 500 and 1000. Ca and Mg
ions in river samples could be due to weathering of dolomite and/or silicate minerals like
clino-pyroxene, amphibole and plagioclase. Charnockite (hypersthene bearing felsic to mafic
granulites) is a common rock type in this area, which is composed of labrodorite,
diopside/augite and hypersthene as essential mineral and hornblend as a common accessory
mineral. The reaction involved during weathering of Ca-Mg bearing minerals such as
pyroxene and amphibole, are as follows
For pyroxene
CaMg (Si2O6) + 4CO2 + 6H2O
Ca2+ + Mg2+ + 4HCO3
+ 2Si (OH)4
For amphibole
Ca2Mg5Si8O22 (OH)2 + 14CO2 + 22H2O
2Ca2+ + 5Mg2++14HCO3 + 8Si (OH)4
The river water samples corrected for atmospheric contribution are plotted in Ca*,
Mg* and (Na* + K*) ternary diagram (Fig. 3.10). Monsoon water samples of the Kaveri have
higher Ca and Mg abundances than the Palar samples. Pre-monsoon water samples of Kaveri
main course plot in the center of the ternary diagram and most of the tributaries samples are
close to the (Na* + K*) and Mg mixing line. Na and K ions are contributed mainly by
weathering of alkali feldspars (such as albite, orthoclase and microcline), which are common
minerals in the granitoid gneisses. Samples of tributaries Aiyar (8KNT3) and Bhavani
(22KNT8 and 46KNT21) plot close to the Ca* and Mg* mixing line (Fig. 3.10).
Comparatively Aiyar sample is close towards Mg* apex and Bhavani samples are close to
Fig. 3.9 Scatter plot between Mg ( mol/l) and Ca ( mol/l) concentration in the water samples of Kaveri, Palar and Ponnaiyar rivers. Positive linear correlations observed for monsoon and pre-monsoon samples indicate that these ions could have been derived from a common source. All the monsoon water samples are falling below the equline whereas most of the pre-monsoon samples plot above.
Fig 3.10
Major ion data for the monsoon and pre-monsoon water samples from Palar, Ponnaiyar, Kaveri and its tributaries are plotted in ternary diagrams of Ca*, Mg* and (Na* + K*). Monsoon samples of Kaveri plot close to Ca*
Mg* mixing line and the Palar samples distinctly higher Na* + K* value than the Kaveri samples.
Absolute concentrations of major ions in the river water are affected by dilution and
evaporation processes. Instead of concentrations, elemental molar ratios and isotopic ratios
are intensive parameters that permit the comparison between rivers draining different
lithologies and climatic regimes (Louvat and Allegre, 1997). Water samples of the rivers
selected for this study are characterized by a number of elemental molar ratios mainly
normalized with Na such as Ca/Na, K/Na, Mg/Na, Si/Na, HCO3/Na, Sr/Na and Ba/Na ratios
after correcting for atmospheric contribution and listed in the Table 3.8. Samples showing
negative value of Na after atmospheric contribution were not included here. The samples that
are showing unusual ratios were listed in separate column.
The Si and corrected Na*, Mg*, K* values of pre-monsoon water samples are higher
than the monsoon water samples, whereas Ca* concentration is nearly equal for both of the
period and HCO3 is higher during monsoon period in the main course of Kaveri. In case of
Na-normalized molar ratio, monsoon samples show higher values than the pre-monsoon due
to lower value of Na* in samples collected during monsoon. Samples of Kaveri collected at
Trichinapally and Thirumanur during monsoon period, and at Chidambaram, Kanannur,
Aravakurchi and Sataymangalam during pre-monsoon period are showing unusually high
ratios.
Table 3.8 Na and Sr normalized molar ratios of major ions for monsoon and pre-monsoon water samples of Kaveri, Palar and Ponnaiyar were listed with mean, range and number of sample.
Molar Ratio
Monsoon Pre-monsoon Pre-monsoon - Tributary n Mean
Range Ex. n Mean
Range Ex. n Mean
Range Ex. HCO3/Na*
22
7.7 4.0 - 17.3 37.8 15
3.00 1.84 - 4.83 6.7 17
1.83 0.24 - 6.4 31.3,319.2
Ca/Na* 21
2.4 1.2 - 3.5 5.8,12.3
15
1.18 0.64 - 2.52 3.1 17
0.91 0.15 - 4.4 14.7,180.5
Mg/Na* 22
1.4 0.5 - 3.5 7.9 15
1.33 0.75 - 2.37 3.89 17
1.05 0.2 - 2.8 24.3, 127
Si/Na* 23
1.14 0.4 - 3.5 -- 15
0.62 0.36 - 0.85 1.28 17
0.63 0.05 - 3.4 7.7, 125.1
Sr/Na* 22
0.0097
0.006 - 0.02
0.047 15
0.0064
0.003 - 0.012
0.022
17
0.005
0.0014 - 0.02
0.1, 0.7 K*/Na* 22
0.15 0.02 - 0.35 0.65 15
0.11 0.041 - 0.63 0.63 17
0.153
0.005 - 0.5 0.9, 29.9 Ba/Na* 23
0.0021
0.0005-0.005
-- 15
0.001
0.0004-0.0027
0.004
17
0.001
0.0003-0.006
0.025,0.15
Ca*/Sr 23
261.5
174.7 - 331
-- 16
185.25
113.5 - 266.9
-- 22
154.6
56.16 - 293.3
391.7 Mg*/Sr 23
144 81.2 - 211.1
-- 16
211.61
187.6 - 251.7
-- 20
188.1
103.1 - 267.5
29.1, 44.2, 769.2
Ba/Sr 23
0.17 0.08
0.24
-- 16
0.15 0.076
0.23 -- 23
0.17 0.03
0.34 0.44 Ca*/Mg*
23
1.8 1.45 - 2.45 -- 16
0.88 0.5 - 1.35 -- 21
0.82 0.18 - 1.57 2.35,13.45
Ex.
exceptions.
55
The molar ratios of Ca/Na, Mg/Na, HCO3/Na and Si/Na are particularly well suited to
distinguish between carbonate or silicate dominated weathering (Gillardate et al. 1999),
when they are plotted as X/Na vs. Y/Na (X and Y are the dissolved species). In such a plot,
trend can be interpreted as a mixing line between two end members of characteristics X/Na
and Y/Na ratios.
The Na* normalized molar ratios (Table 3. 8) of the Kaveri water samples were
compared with that of different rock types exposed, flood plain sediments and weathering
profile in the basins (Fig 3. 11). The major rock types exposed in the drainage basins of
Kaveri, Palar and Ponnaiyar can be grouped as i) granite and granitic gneisses (GG), ii)
granulites (Gr), iii) meta volcanic rocks (MV) and iv) carbonates. Different molar ratios for
these four rock types are listed in the Table 3.9 with the mean value, range and number of
sample.
Table 3.9 Na and Sr normalized elemental molar ratio of granite and granitic gneisses, granulites, meta volcanic rock, flood plain sediments and weathering profile found in the Kaveri drainage basin were listed with mean, range and number of sample.
Molar
Ratio
Granite & Granitic Gneisses (n =25)
Granulites (n = 30)
Meta Volcanic Rock
(n = 13) Weathering Profile
(Granulites) (n = 13)
Flood Plain Sediment (n = 51)
Mean
Range Mean
Range Mean
Range Mean
Range Mean
Range Ca/Na
0.3 0.19
0.7 0.63 0.4
1.2 2.36 0.8
9.3 0.76 0.52
1 0.68
0.46
1.38 Mg/Na 0.113
0.013-0.53 0.72 0.18
1.07 1.2 0.15
2.6 0.4 0.16
1.13 0.52
0.18
1.15 Si/Na
9.6 6.5
12.6 10.6 6.4
16.97 10.01 6.9
15.3 10.15
5.87
14.02 17.19
9.69
47.67
Sr/Na
0.0028
0.0007
0.008
0.003
0.001-0.0094
0.002 0.0005-0.004
0.006
0.004
0.008
0.005
0.002
0.009
K/Na
0.68 0.15
1.14 0.23 0.086
0.38
0.141 0.0016-0.338
0.23 0.117
0.395
0.56
0.38
1.05 Ba/Na
0.0032
0.0005
0.008
0.0025
8E-4
0.0052
0.001 0.0001-0.002
0.0038
0.0014
0.006
0.007
0.004
0.015
Rb/Na
0.0017
0.0002
0.006
0.0002
3E-5
0.0005
0.00026
3.6E-6
7E-4
-- -- -- -- Ba/Sr
1.6 0.14
8.5 0.86 0.34
4.38 0.5 0.06
1.6 0.63 0.264
0.925
1.27
0.8
2.24 Ca/Sr
118.4
32.53
329.8
222.8
80.5
662.7
826.5 282.4
1961
133.7
67.5
178.5 120.9
76.9
226.1
Mg/Sr
39.8 3.8
111.6 256.7
60.8
537.4
812.8 241
1846 62 39.2
130.8 92.5
38.2
188.7
Ca/Mg 3.7 1.28
9.07 0.97 0.5
3.5 1.45 0.3
4.85 2.6 0.88
4.25 1.39
0.68
2.5
Refe-
rence
Rao et. al. 1992, Jayananda et. al.
2000, Tylor et. al.1984
Raith et. al. 1999,
Tomson et. al. 2006
Rao et. al. 1992 Sharma and
Rajamani 2001 Singh and
Rajamani 2001
In most of the Na normalized elemental molar ratio plots (Fig 3. 11), field for
sediment samples of flood plain (FP) and weathering profiles (WP) overlaps with the
granulites field. The field for granulites falls in between the fields for granitic gneisses and
meta volcanic rocks.
56
0.01
0.1
1
10
100
0.01 0.1 1 10 100Ca*/Na*
Mg
*/N
a*
GG
Gr, FP & WP
MV
CarbEquiline
A
0.0001
0.001
0.01
0.1
0.1 1 10Ca*/Na*
Sr/
Na*
GG
MVGr
FP & WP
B
0.0001
0.001
0.01
0.1
0.01 0.1 1 10 100Mg*/Na*
Sr/
Na*
GG
FP & WP
Gr
MV
CarbC
Monsoon
Pre-monsoon Main CoursePre-monsoonTributaries
57
0.0001
0.001
0.01
0.1
0.01 0.1 1 10Mg/Na*
Ba/
Na*
MV
GG
Gr
FP & WP
D
0.0001
0.001
0.01
0.1
0.0001 0.001 0.01 0.1Sr/Na*
Ba/
Na*
Silicate Rock
Sediment
E
0.00001
0.0001
0.001
0.01
0.1
0.001 0.01 0.1 1 10K*/Na*
Rb
/Na* GG
GrMV
F
0.0001
0.001
0.01
0.1
0.001 0.01 0.1 1 10K*/Na*
Ba/
Na*
GG
MV
Gr
FP & WP
G
0.01
0.1
1
10
100
0.1 1 10Ca*/Na*
Si/N
a*
GG MV
Gr,FP & WP
H
0.01
0.1
1
10
100
0.01 0.1 1 10Mg*/Na*
Si/N
a*
GG
FP & WP
GrMV
I
Pre-monsoon
Pre-Monsoon Tributaries
Main Course
Monsoon
58
0.0001
0.001
0.01
0.1
0.1 1 10Si/Na*
Sr/
Na*
Monsoon
Pre-monsoon Main CoursePre-Monsoon Tributaries
J
0.001
0.01
0.1
1
0.01 0.1 1 10Si/Na*
K*/
Na*
Monsoon
Pre-monsoon Main CoursePre-Monsoon Tributaries
K
Fig 3.11 Comparison between different Na*-normalized molar ratios (X/Na* vs. Y/Na* plots) of the Kaveri and its tributaries water samples. Fields for different rock types exposed in the catchment area including weathering profiles are given. Here Gr & Gn
Granite and Granitic gneisses, MV
Meta volcanic rocks, FP
Flood plain Sediments, WP
Sediments of weathering profile.
The water samples fall along the equiline in the logarithm plot of Ca*/Na* vs.
Mg*/Na* (Fig 3.11. A) and as also the fields for Gr, MV, FP and WP and upper part of GG
field. The field for carbonate is distinct from others and plots below the equline. Similar plot
between Ca*/Na* and Sr/Na* (Fig 3. 11 B) shows that samples plots in GG and Gr field,
whereas, in the diagram Mg*/Na* vs. Sr/Na* (Fig 3. 11. C) the sample plots in the field of Gr
and MV. Interestingly none of the sample plot in the carbonate field or even close to it in the
molar ratio plots (Fig 3. 11. A, B and C). In the Mg*/Na* vs Ba/Na* diagram (Fig 3. 11. D)
sample plots in the field of MV but in case of Sr/Na* vs Ba/Na* diagram (Fig 3. 11. E) all
sample plot below the silicate and sediment field. From fig 3.11, it is observed that except in
plots involving K* and Rb (K*/Na* vs Rb/Na*, Fig 3.11.F, and K*/Na* vs. Ba/Na*, Fig
3.11. G), the samples show positive correlations.
It is known that, large cations like Rb and K are preferentially retained on clay
minerals by cation exchange and fixations (Wiklander, 1964) during weathering of primary
minerals and cycled between soils and weathering zone. Hence, the plots involving Rb and K
do not show good correlation. The minerals like K-feldspar, biotite and microcline are the
major source of K and Rb in the silicate rocks. In case of Barium, it is neither enriched nor
depleted in the river water because it is not leached or retained in the profile in preference to
K (Nesbitt et al., 1980). The Ba/K ratio of average continental crust (Taylor, 1964) is similar
to the dissolved constituents in average river water (Nesbitt et al., 1980).
59
As the samples (both monsoon and pre-monsoon samples) cluster in and around the
silicate field in most of the molar ratio plots, a dominant role for silicate weathering is
inferred. In Si/Na* vs Ca*/Na*, Mg*/Na* and Sr/Na* (Fig 3. 11. H, I and J), samples define
a positive correlation and plot below the various fields for rocks exposed in the basin. This
may be due to low dissolution rate of Si compared to Na (also Ca, Mg and Sr) during
chemical weathering, which result in low Si/Na* ratios in the river water.
In the catchment area granulites and granitic gneisses are the major rock types
exposed and this region was subjected to tectonic uplift. It has experienced a high degree of
erosion through out the geological time, which has resulted in formation of planation surfaces
at different elevations over both the rock types. Due to structural, compositional and
lithological heterogeneity the gneisses had undergone rapid physical weathering and as a
result it formed low lying areas with thick soil cover, whereas, the massive granulites remain
areas of high relief (Gunnel, 1998c).
In most of the water samples Ca and Mg abundances are higher compared to other
major cations. Presence of granulites, calc gneisses with Ca Mg bearing minerals and thick
calcrete in the river banks and/or flood plains form major sources of Ca and Mg to the Kaveri
river ionic budget. Though there is no report of major carbonate outcrop in the upper and
middle reach of Kaveri river, but thin bands of limestone in the granulites, carbonates in
schist belts of Dhrwar craton also contribute to the Ca
Mg ionic budget of the Kaveri river.
Another observation made by Durand et al. (2006) for explaining the presence of secondary
carbonate in a non-calcareous setting (thick calcrete pan/nodules in the river bank and flood
plain) in this area is related to weathering of host rocks, such as, calc-gneisses, gneisses and
granulites.
In this study, the Mg / (Mg + Ca) ratio of water sample is higher than granite and
granitic gneisses and equal or lesser than the granulites and meta-volcanic rocks. Hence, it is
inferred that the contribution of Mg and Ca from granulites is more than granitic gneisses.
Weathering of ortho- and clino-pyroxenes, amphiboles and other mafic minerals present in
the granulites will result in higher Mg/(Mg + Ca) ratio in the water.
The atmospheric corrected, Na-normalized, molar ratios of different major ions of
Kaveri, Palar and Ponnaiyar rivers (X/Na vs. Y/Na in logarithmic plot) are compared with
other Indian rivers in the Fig 3.12. The fields for oceanic, silicate and carbonates end
60
members were drawn from published data. Evaporites field is not shown in these plots as it is
not exposed in the Kaveri river basin.
The carbonate end member can be assumed to have the ratios: Ca/Na = 55 ± 35,
Fig 3.12 Correlation between different Na*-normalized molar ratios (X/Na* vs. Y/Na* plots) of the Kaveri, Palar, Ponnaiyar water samples. Fields for other Indian rivers and different end members are given. Here, OC
Oceanic, S
Silicate and C
Carbonate end member (reference given in the text). GY
Ganga, Yamuna, Indus (Krishnanswami and Singh, 2005) and Brahmaputra (Singh et. al. 2005), KB
Fig 3. 13 Na*-normalized molar ratios Sr/Na* vs. Ca*/Na* and Mg*/Na* plots of the Kaveri, Palar, Ponnaiyar water samples with fields for different end members are given.
In Ca*/Na* vs. Sr/Na* and Mg*/Na* vs. Sr/Na* plot (Fig 3. 13 A and B) monsoon
and pre-monsoon samples were together showing a single positive trend with r2
0.87 and
0.96 respectively. This positive trend could be attribute to contribution of these ions
predominantly from silicate and carbonate end members. From the Fig 3.13, it is inferred that
the release of Ca and Sr, Mg and Sr are congruent and hence their molar ratios can be used to
estimate the relative contribution from each end members.
3.3.4 Quantification of input sources:
Determining the relative contributions of silicate and non-silicate to the total major
ion budget of river water is one of the objectives of this study. In the absence of evaporites,
Na and K are essentially released by feldspar weathering, whereas, Ca and Mg could be
released by weathering of Ca-pyroxene, Ca-amphibole, as well as, carbonates (Fig 3.11, 3.12
A
B
64
and 3.13). To estimate relative contribution of Ca and Mg from the silicate weathering, here
two mixing models were employed and these are a) Forward model and b) Inverse model.
Both the forward and inverse models consist of mass balance equations using
major cations (Na, Ca, Mg, and K) and a priori assumptions about the compositions of the
sources (Moon et al., 2007). For both models, the uncertainties are dependent on the ability
to correctly identify the relevant source and to assign appropriate end member constraints
(Negrel et al., 1993; Wu et al., 2005; Moon et al., 2007). In these calculations, instead of
concentrations, elemental molar ratios were used.
For estimating silicate and non-silicate contributions the following mass balance
equations was used:
[X]R = [X]S + [X]NS + [X]A + [X]Rain (1)
Here X = major ions, R = river, S = silicate, NS = non-silicate and A = Anthropogenic.
Using ClR as index of sum of atmospheric contribution (with the consideration of
evapo-transpiration), cyclic salt and anthropogenic input, major ions of river water were
corrected (Table 3.6). Then the equation 1 can be rewritten for the corrected value [X]* as
[X]* = [X]S + [X]NS (2)
As the evaporites are not reported from the basin, the non-silicate contribution will be
mainly from the carbonate end member. The contribution of Na in these rivers originating
from carbonate weathering may be neglected (Dalai et al., 2002). Hence, the corrected Na
concentration can be assumed as silicate contribution, [Na]* = [Na]S. The dominant source of
K in the river waters is silicate weathering (Galy and France-Lanord, 1999), hence [K]* =
[K]S.
a) Forward model:
Determination of silicate derived Ca and Mg will carry more uncertainties as these
elements were supplied by multiple sources. Even among the silicate mineral (pyroxene,
amphibole and plagioclase), Ca and Mg contributions can be significantly different
depending on their composition and weatherability. Therefore, to obtain silicate Ca and Mg
contribution it is necessary to know the mineralogical composition of silicate rocks of the
basins (Singh et. al. 2005). In river waters, Ca and Mg derived from silicate weathering [Ca]S
and [Mg]S can be written as (Galy and France-Lanord, 1999, Krishnaswami et al. 1999):
[Ca]S = [Na]S × [Ca/Na]Sol (3)
65
[Mg]S = [Na]S × [Mg/Na]Sol (4)
Where [Ca/Na]Sol and [Mg/Na]Sol are the molar ratios released to river waters from
silicates in the drainage basins during chemical weathering. Few assumptions and results of
laboratory experiments are required for estimating [Ca/Na]Sol and [Mg/Na]Sol, but it caries
considerable uncertainties. For calculating silicate weathering rate different authors have
estimated [Ca/Na]Sol and [Mg/Na]Sol based on the ratio of the whole silicate rock, soil profile
or stream flowing through monolithological terrain and some of them are listed in the table
3. 10. Considerable variability exists in estimation of (Ca/Na)Sol and (Mg/Na)Sol as seen from
the table 3.10.
Table 3.10 [Ca/Na]Sol and [Mg/Na]Sol ratio used by different researcher for the river basins studied by them.
Author River Basin
Based on [Ca/Na]sol
[Mg/Na]sol
Galy and France-Lanord (1999)
Rivers in Nepal Himalaya
Silicate whole rock of Higher Himalaya, Lesser Himalaya and plagioclase of Higher Himalaya Crystalline.
0.18
0.3 0.5 ± 0.2
Krishnaswami et al. (1999), Singh et. al (1998)
Ganga River system
Lower Himalaya granites/gneisses, soil profiles and in rivers draining predominantly silicates
0.7 ± 0.3 0.3 ± 0.2
Dalai et. al. (2002)
Yamuna From Krishnaswami et al. (1999) and silicate whole rock
0.7 ± 0.3 0.35 ± 0.15
0.3 ± 0.2
Jha et. al. (2009)
Godavari For basalt and silicate by Gaillardet et al., 1999
0.42 ± 0.17
0.36 ± 0.16
Qin et al. (2006)
Min Jiang Silicate fraction 0.7 0.3 Moon et. al. (2007)
Hong Using monolithological river with in the study area.
0.44 0.16
In this study X/Na molar ratios of exposed silicate rocks of drainage basin were used.
The silicate rocks exposed in this basin can be considered under three groups (as discussed in
section 3.3.3) such as a) granites and granitioid gneisses (GG), b) granulites (Gr) and c)
meta-volcanic rocks (MV). Based on their exposed area estimated from the geological map
of the drainage basins, area weighted factor (Y)f was calculated. For Kaveri river the area
weighted values were calculated up to Musuri (Sample location 5K during Monsoon period)
as the water discharge data was available up to this location. Similar method was also
followed for selected tributaries of Kaveri, whose lithologies were clearly marked in the map
and individually area weighted values, were calculated for them separately (Table 3.11). To
calculate the contribution (of X/Na) to the river by silicate weathering the following equation
generally have CaCO3 of ~95% resulting in Ca/Mg molar ratio of ~ 11. Finally, considering
above factor Ca/Mg ratio of 10 was used in this calculation. The fs values obtained using
Ca/Mg ratios are similar to those estimated using the Ca/Sr ratios within the uncertainty.
Table 3.13 Fit of the regression line and fs calculated using Ca/Sr, Mg/Sr and Ca/Mg of Kaveri, Palar and Ponnaiyar river basin.
c) Comparison between Forward and Inverse Model:
The [Ca]S and [Mg]S were calculated from equation 3 and 4 after using the results of
equation 5 in case of forward model, whereas, in case of inverse model using fs, [Ca]S and
[Mg]S were calculated. Using these values, the fraction of cation contributions from the
silicates to the rivers, ( Cat)S, can be calculated as
R
S
R
Si
S KNaMgCa
KNaMgCa
Cat
XCat (14)
It has been observed that the calculated fractional contribution of cations by silicate
weathering using inverse mixing model is higher than the forward mixing model (Table
3.14). This may be due to the i) lower [Ca/Na]Sol and [Mg/Na]Sol ratio assumed for the
calculation as the whole rock value was considered here, ii) the area weighted value of
[Ca/Na]Sol and [Mg/Na]Sol ratio may not be applicable to all the sampling locations as the area
of exposure of different rock types used in the equation 5 varies from site to site and iii) the
rainfall and runoff are not uniform and differ widely. The results of forward and inverse
models converge in case of tributaries where the ratio of different rocks exposed is better
known and climate parameters are uniform. The ratio of individual minerals which are more
susceptible to chemical weathering has important role in determining the major ion ratios in
water than the whole rock. Here the results of inverse model using Ca/Sr ratio are only
considered for further calculation as it shows a better fit in the regression line and Sr isotope
ratios are used to estimate the contribution for various sources (chapter 4).
Season Rivers Ca/Sr Mg/Sr Ca/Mg
fs R2
fs R2
fs R2
Monsoon Kaveri 0.7 0.81 0.76 0.64 0.83
0.4 Palar 0.61 0.98 0.98 0.63 0.52
0.75
Ponnaiyar 0.89 0.63 0.59 0.41 0.84
0.74
Pre-monsoon
Kaveri 0.7 0.88 0.47 0.69 0.77
0.51
Tributaries
0.63 0.81 - - 0.63
0.67
71
Table 3.14 The range of the silicate fraction of cation ( Cat)S in percentage, calculated using forward (FWD) and inverse (INV) mixing model.
Season River Percentage range of ( Cat)S
Forward Model
Inverse Model
Monsoon
Kaveri 12
50 72
78
Palar 36
73 69
77
Ponnaiyar 34
48 91
93
Pre-monsoon Kaveri
31
86
76
83
Tributaries 31
87 64
91
3.4 Annual Flow and Sediment Load:
The Kaveri basin is fan shaped in the upstream part (Karnataka) and leaf shaped in
the down stream part (Tamilnadu) and both the parts are connected by a norrow gauge
through the Billigirirangan Hills. The run-off at the catchment does not drain quickly because
of its shape and therefore, no fast raising floods occur in the basin (Int. Hyd. Year Book,
CWC, 2007). Apart from the head reach of the Kaveri river, the flow contribution from the
tributaries Hemavati, Kabini and Bhavani are important.
The upper reaches of Kaveri receive rainfall mainly from the SW Monsoon and
partially from the NE Monsoon. Whereas, the lower reaches, close to the east coast receives
good flows from the NE Monsoon. Due to construction of dams and canals, the natural flow
in the course of river is controlled and the surplus water during monsoon is stored in the dam
and in the lean period it flows to the lower reaches. The data on sediment load and water
flow in the river obtained from the gauge stations are affected by these manmade structures.
However, monthly average flow and sediment load data from the different stations of the
river Kaveri, Palar, Ponnaiyar and Vellar and its tributaries were collected from the Int.
hydrological year book, 2007. In the Kaveri basin 16 hydrological observation stations are
present and among them 13 stations are operational for the sediment observation.
Hydrological stations, four along the Palar 4, one along the Vellar, and three along Ponnaiyar
are situated.
In the Kaveri main course ~57% and ~30%, of annual flow contributed by SW and
NE monsoon respectively. The average percentage of annual sediment load supplied during
SW and NE monsoon in the Kaveri main course is ~42% and ~50%, respectively, for the
period of 1999 2000 and 2002 2003. The percentage of average annual flow and annual
sediment loads contributed by SW (June to September), NE (October to December) and non-
72
monsoon (January to May) at different hydrological observation sites of four river systems
are listed in the table 3.16. Laksmanthirtha, Kabini and Kaveri (before Krishna Raja Sagar
Dam, near Mysore) receive more than 80% of annual flow and sediment load during SW
monsoon.
MonthJu
ne Ju
ly Aug
Sept
OctNov
Dec
Jan
FebMar
April
May
Mo
nth
ly A
vg. F
low
(M
CM
)/S
edim
ent
Lo
ad (
To
nn
es/D
ay)
1
10
100
1000
10000
Sediment load at Musuri (6/1999 to 5/2000)
Sediment load at Kollegal (6/1999 to 5/2000)
Monthly Avg. Flow at Musiri (6/1972 to 5/2000)
Monthly Avg. Flow at Kollegal (6/1972 to 5/2000)
A)
MonthJu
neJu
ly
AugustSep
tOct
NovDec Ja
nFeb
Mar
ch
AprilM
ay
Mo
nth
ly A
vg. F
low
(M
CM
)/S
edim
ent
Lo
ad (
To
nn
es/D
ay)
0
50
100
150
200
250
300
Flow at Chengalpattu (Palar), 1977 to 2000Flow at Gummanur (Ponnaiyar), 1978 to 2000Flow at Vazhavachanur (Ponnaiyar), 1978 to 2000Flow at Kudalaiyathur (Vellar), 1990 to 2000Sediment Load at Gummanur, 2003 - 04 Sediment Load at Vazhavachanur, 2003 - 04
B)
Fig 3.14 Graph shows month wise average flow in million cubic meters (MCM), sediment load in tones per day for two stations in Kaveri (A) and Ponniyar, one station each from the river Palar and Vellar in (B).
In the river Arkavathy and Shimsa nearly 41% and 50% of annual flow observed
during SW and NE monsoon respectively, whereas, nearly 80% sediment load is carried by
these rivers during NE monsoon. Bhavani and Moyar river drainage basins receive good
rainfall throughout the year and during non-monsoon period these basins receive more rain
fall compared to other tributaries of Kaveri. Here data of monthly average flow and sediment
load from Musuri and Kollegal (Kaveri), Chengalpettu (Palar), Gummanur & Vadhavachanur
(Ponnaiyar) and Kudaliyathur (Vellar) are plotted month wise for different period in the
Figure 3.14. Maximum water flow and sediment load were observed during SW monsoon in
the upper reaches (Kollegal), and during NE monsoon in the lower reaches (Musiri).
However, the SW monsoon contributes to maximum water flow and NE monsoon
contributes to maximum sediment load when the entire Kaveri river (at Musiri) is considered.
More than 95 % of annual flow and sediment load in the Palar, Ponniyar and Vellar rivers are
observed during NE monsoon as these rivers flow mostly in Tamilnadu.
3.5 Weathering rates:
73
Using average annual flow, total drainage area of different hydrological observation
sites of the Kaveri, Palar, Ponnaiyar, Vellar and their tributaries, chemical and physical
weathering rate, annual flux of different ion species to the ocean were calculated. Annual
flow and drainage area for different sites were collected from hydrological year book of
Central Water Commissions and the site Musiri, Chengalpattu and Villipuram were taken as
the final site for these calculations for Kaveri, Palar and Ponnaiyar river respectively. In case
of tributaries, these calculations were made only for Kabini, Shimsa, Arkavathy, Bhavani and
Amaravati as the discharge/run off data for other tributaries were not available. Based on the
reported sediment load at different sites the physical weathering rate (Wph) was calculated
and the results of monsoon period were close to the value obtained from the total suspended
load measured from the monsoon water samples. The average annual flow at Musiri is
8685.81 million cubic meters (MCM) and sediment load 6.098 ton/km2/y. The reported
suspended load during monsoon period is 4.5 ton/km2/y (75% of the annual load) and
observed load in this study is 4.7 ton/km2/y. Sediment load data for Palar, Ponnaiyar and
Vellar river were not available in the year book and hence suspended load measured from the
monsoon water samples of these rivers were used here to calculate the Wph.
The silicate weathering rate (SWR) can be calculated as the sum of cations arising
from silicate weathering, whether obtained by carbonic acid or sulfuric acid (Roy et al.,
1999), as follows:
SWR = (Nasil + Ksil + Casil + Mgsil + SiO2) × discharge / drainage area / density of silicate
Where Nasil, Ksil, Casil and Mgsil represents cations supplied by silicates (mg/l).
And carbonate weathering rate is calculated as follows (Roy et al., 1999):
Here Cacarb, Mgcarb and HCO3carb are derived from carbonate weathering (mg/l).
Half of the HCO3 produced by dissolution of carbonates comes from the atmosphere
(Roy et al., 1999). It is assumed that all non-silicate Ca and Mg are of carbonate origin as
there is no report of evaporates occurrence up to Musiri, the final site considered for
calculation. Results (Table 3. 17) of weathering rate were indicated as m/Ma or tons/km2/y.
Here, the average densities of 2700 and 2400 kg m 3 for silicates and carbonates respectively,
(Galy and France-Lanord, 1999) were used. The total specific chemical denudation rate was
calculated as:
74
Wcha = SWR + CWR
Wchb = SWR+CWR + flux of SO4*
(Assuming all SO4* derived from rock weathering)
All above calculations for monsoon, non-monsoon and annual periods were done
separately. Monsoon water samples were not collected from Kabini, Shimsa, and Arkavathy,
hence the weathering rate was calculated only for the non-monsoon period. For Billigundla
and Kollegal, monsoon water sample data of the Hogainakal were used. Palar and Ponnaiyar
rivers are having flow only during monsoon period and it is very close to the annual flow,
hence, using monsoon water sample data and annual flow calculation were made. Generally
SO4 is not included to the total chemical weathering; hence Wchb which is higher than the
Wcha (Table 3.17) is not compared to the any other reported value.
In Kaveri river the physical weathering rate (Wph) at Musiri is 6.1 tons/km2/y or 3
m/Ma whereas at Billigundla it is 3 times higher i.e 18.6 tons/km2/y or 9.3 m/Ma. At Musiri
weathering rate is 3 fold higher during monsoon period than the non-monsoon period and at
Billigundla it is 9 times. Because of the dam at Mettur (after Billigundla) the sediment load
of Kaveri river reduces drastically from 680 (×103 Tons/y) to 15 (×103 Tons/y) before and
after the dam, respectively. But at Musuri observed Wph is due to the contribution from other
tributaries like Sarvanga, Bhavani, Noyil and Amaravati, which joins Kaveri after Mettur
dam. Observed Wph of Amaravati at Nallampatti (5.6 tons/km2/y) is nearly two fold higher
than the Bhavani at Savandapur (2.9 tons/km2/y). In these two rivers physical erosion is
nearly same during both monsoon and non-monsoon period. In the upper reaches, Kabini
River shows higher Wph (19.3 tons/km2/y) than the Shimsa (3.2 tons/km2/y). As Kabini
originates from Western Ghats and it receives heavy rain fall and the slope is high, the
physical denudation rate is higher in comparison to Shimsa. During monsoon time Kabini
and Shimsa show 8 and 5 fold Wph than the non-monsoon period. In Palar, Ponnaiyar and
Vellar the observed Wph is 1.03, 2.18 and 2.71 tons/km2/y respectively.
Annual flux (103mol/km2/y or 109mol/y) of major ions (without correcting for
atmospheric contribution) and TDS of Kaveri, Amaravati, Bhavani, Palar, Ponnaiyar and
Vellar rivers at a particular location are given in the Table 3.20. River Palar shows lowest
annual major ion and TDS flux to the Bay of Bengal.
75
At Musuri the silicate weathering rate (SWR) is 7.9 tons/km2/y or 2.9 m/Ma and
carbonate weathering rate (CWR) is 5.1 tons/km2/y or 2.1 m/Ma, out of which monsoon
period stands for 80% and 81% respectively. In Kaveri river, SWR flux at Musiri is 0.52
×106 tons a 1 , which accounts for 0.1 % of the global river drainage silicate weathering flux
(total dissolved solid originated from silicate) of 550×106 tons a 1 (Gaillardet et al., 1999).
The drainage coming under the site Musiri (0.066×106 km2) is 0.044% of global continental
area (150×106 km2), but it will be more meaningful if it is compared to the global silicate
exposed area. The SWR value estimated during this study up to Musiri as the final site is
much lower than the value reported by Gaillardet et al. (1999), 2.4×106 tons a 1, where they
have considered the total basin area 0.088 ×106 km2. But CWR value reported by Gaillardet
et al. (1999) for Kaveri river (0.3 ×106 tons a 1) is close to the estimated value of this study
(0.33×106 tons a 1).
SWR and CWR are higher at Billigundla than Musiri just as the Wph (Table 3.17). In
Palar, Ponnaiyar and Vellar SWR (0.89, 1.97 and 3.7 tons/km2/y respectively) is higher than
the CWR (0.45, 0.4 and 2.05 tons/km2/y respectively). Due to heavy downpour during
monsoon the SWR and CWR are higher during this period in these river basins. The SWR
for Palar, Ponnaiyar and Vellar rivers together (0.07 ×106 tons a 1) accounts for 0.01% of the
global river drainage silicate weathering flux.
The Wcha for Kaveri river at Musiri is 13 tons/km2/y or 5 m/Ma, which is much higher
than the Wph at this site, whereas, at Billigundla located upstream of Mettur Dam, they are
nearly equal (Wcha =21.2 tons/km2/y and Wph = 18.6 tons/km2/y). Thus, the Mettur Dam is
considerably reducing, about 50 % of the suspended sediment load of the Kaveri river.
The final specific chemical denudation rate (Wcha) estimated for Kaveri, Palar and
Ponnayar basins (1.3
13 tons/km2/y) are much lower than the published global mean values
of 24 tons/km2/y (Gaillardet et al., 1999), 26 tons/km2/y (Meybeck, 1979) and 21 tons/km2/y
(Berner and Berner, 1996). However, Wcha values similar to the global mean values are
observed in the Bhavani basin (21.6 tons/km2/y), Kaveri at Kollegal (30.7 tons/km2/y) and
Billigundla (21.2 tons/km2/y). The chemical weathering is more intense in the Bhavani and
upper reaches of the Kaveri basin, where erosion balances (mechanical verses chemical) is in
disequilibrium. It indicates that physical removal of materials from weathering profile is less
and it leads to develop thick soil profile. Generally this thick soil profile is observed in the
76
drainage basin of shield complex like Negro river (Mortatti and Probst, 2003). In the Fig 3.15
Wcha and SWR are plotted against the Wph for four river and they show positive
correlations. Largely Wcha is superior to Wph in Kaveri and Vellar river basin indicates the
soil equilibrium or erosion balance has broken (Mortatti and Probst, 2003), but damming in
the Kaveri river is modifying this relationship at different site. In Palar, Ponnaiyar and
Amaravati a tributary of Kaveri are close to the equilibrium where physical and chemical
removal of material from weathering profile is at similar rate.
Wph (tons/km2/y)
0 1 2 3 4 5 6 7
Wch
a o
r S
WR
(to
ns/
km2 /y
)
0
2
4
6
8
10
12
14
SWRWcha
Kaveri
Palar
Vellar
Ponnaiyar
Fig 3.15 Physical weathering rate verses chemical (Wcha) and silicate weathering rates (SWR) plotted for different river basins. Site locations for different rivers are Musiri
Kaveri, Chengalpattu
Palar, Villipuram
Ponnaiyar and Kudalaayithur
Vellar.
The total dissolved silica (as SiO2) from the Kaveri basin at Musiri is calculated as
1.7 ×105 tons a 1 and flux rate is 2.6 tons/km2/y and the Strontium (Sr) flux at Musiri is
2404.4 tons a 1 at the rate of 0.036 tons/km2/y. Calculation at other sites of Kaveri river
shows that dissolved silica and Sr contribution is higher from the upper reaches than the
middle and lower reaches. Bhavani shows higher silica and Sr flux than the Amaravati (Table
3.17). As Palar, Ponnaiyar and Vellar rivers are small they contribute much lower silica and
Sr annually than the Kaveri (Table 3.17). A significant positive linear correlation (Fig 3.16)
between SiO2 flux (tons/km2/y) and SWR (tons/km2/y) is observed for all the three rivers.
Here, monsoon, pre-monsoon and annual results for these rivers and tributaries were
considered together.
77
SWR = 3.338 (SiO2 flux)
0.0589, with r2 = 0.99.
SiO2 flux (tons/km2/y)
0 1 2 3 4 5 6
SW
R (
ton
s/km
2 /y)
0
5
10
15
20
r2 = 0.99
Fig 3.16 Silicate weathering rate verses SiO2 flux for all the three rivers is plotted here and it shows good positive correlation.
Another method to determine the chemical weathering rate of silicate rock layers
(WRch) uses the flux of dissolved silica in the river (Table 3.17). If the chemical
composition of parent rock (So) and of alteration facies (Ss mean soil profile) are known and
assuming isovolumetric rock weathering, the weathering rate of silicate rocks can be
determined as described by Boeglin and Probst (1998) and Mortatti and Probst (2003).
WRch SiO2 = SiO2 flux / (So
Ss)
The average chemical composition of silica in the parent rock in the Kaveri basin is
calculated as 69.24% based on area weighted value of granitic gneisses, granulite and
metavolcanic rocks and average density was taken as 2.65 ton m 3 (Mortatti and Probst
2003). Here for the alteration facies silica from flood plain sediments (Singh and Rajamani,
2001) were taken as 67.1% and the average bulk density of flood plain sediment taken as 1.8
ton m 3. This gives the value of So and Ss equal to 1834 kg m 3 and 1208 kg m 3
respectively, and yields silicate weathering rate of 4.18 m/Ma for the Kaveri river basin at
Musiri, which is higher than the calculated SWR 2.9 m/Ma for the same site. But it is close to
the calculated Wcha (5.0 m/Ma) at Musiri. The silicate weathering rate using Si could not be
determined for the other river as the So and Ss values were not available.
3.6 Weathering types:
78
The main weathering types occurring in these basins were determined from the
geochemistry of river waters, using weathering index RE and this method adopted from
Mortatti and Probst, (2003), which was initially proposed by Tardy (1971). This method is
based on the molecular ratio between dissolved silica and cations resulting from silicate rock
weathering.
MgCaNaK
SiOMgCaNaKRE
75.05.05.0
25.1233 2
(15)
The coefficients used in this formula were based on the major primary minerals of an
average granitic composition with feldspars and micas (Mortatti and Probst, 2003). RE is
also equivalent to the molar ratio of SiO2/Al2O3 remaining in the weathering profile. When
more silica is evacuated RE value decreases and the chemical weathering stage of the
minerals increases. RE = 4, 2 and 0 correspond, respectively, to smectite, kaolinite and
gibbsite genesis.
Table 3.15 Weathering Index, RE values were calculated for all the samples using equation 15 (Mortatti and Probst, 2003). The mean and range of the RE values for the three rivers studied during monsoon and pre-monsoon periods are given.
RE Monsoon Pre-monsoon Kaveri River Kaveri Palar Ponnaiayr
Main Stream Tributaries n 9 8 4 16 15 Mean 2.24 2.54 2.34 2.7 3.11 Range 1.9
2.45
1.59
3.16
2.2 - 2.44 2.1 - 3.12 1.6 - 4.3
The mean RE value obtained for monsoon water samples of Kaveri, Palar and
Ponnaiyar is 2.28, 2.39 and 2.36 respectively (Table 3.15), and pre monsoon water samples
shows 2.7 for main stream and tributaries are showing higher mean of 3.6. It represents that
in the Kaveri basin formation of smectites processes (bisiallitization process) is more active.
Fewer samples shows the RE value less than 2 represents the monosiallitization weathering
process corresponding to kaolinite formation in the soil profile. These results are in good
agreement with the clay mineralogy of Kaveri river flood plain sediments reported by Singh
and Rajamani (2001) and of weathering profiles in the upper reaches studied by Deepthy and
Balakrishnan (2006).
3.7 CO2 consumption by chemical weathering:
79
Chemical weathering of rocks is considered as a significant sink for the atmospheric
CO2 and an important part of the global CO2 cycle. Dessert et al., (2003) and Krishnaswami
and Singh, (2005) have modeled CO2 consumption during weathering of silicate and
carbonate rock types. Lithology, chemical weathering rates and runoff are the predominant
controlling factors for CO2 consumption by rock weathering and the transport of resulting
bicarbonate through rivers into coastal zones (Bluth and Kump, 1994; Amiotte-Suchet et al.,
2003). Other factors, such as relief, temperature, soil and microbial activity also influence
chemical weathering rates but are not yet incorporated into present models. It is difficult to
isolate their effects because of variety of runoff patterns and different mineralogical
compositions in the rock types present in the study area (Drever and Zobrist, 1992; Drever,
1994; Gislason et al., 1996; Brady et al., 1999; Navarre-Sitchler and Thyne, 2007). Despite
these limitations it is possible to correlate chemical weathering and global carbon cycle using
different models.
The atmospheric CO2 consumption during rock weathering must be considered
differently with respect to the time frame. For durations less than 100,000 years (the time
required by rivers to transport dissolved CO2 into the oceans), weathering of all lithologies is
important for the consumption of CO2 from the atmosphere (Wu et al. 2008). With respect to
a million years and more, CO2 supplied from carbonate weathering is removed from the sea
by calcite precipitation and soon returned to the atmosphere. Hence, for such longer time
periods CO2 consumption due to carbonate weathering should not be considered (Berner et
al., 1983).
During natural weathering the reaction between carbonic acid and minerals produces
dissolved cations and inorganic carbon (mainly HCO3-) as widely reported (Garrels and
Mackenzie, 1971; Amiotte Suchet and Probst, 1995; Mortatti et al., 1997; Ludwig et al.,
1999, Mortatti and Probst, 2003). The typical reactions of silicate mineral during weathering
are given in the equations 16
19 and carbonate dissolution in equation 20 (Mortatti and
Probst, 2003).
Albite into kaolinite:
2NaAlSi3O8 + 2CO2 + 11H2O
Al2Si2O5 (OH)4 + 2HCO3- + 2Na
+ + 4H4SiO4 (16)
K-feldspar into montmorillonite:
80
2KAlSi3O8 + 2CO2 + 6H2O
Al2Si4O10 (OH)2 + 2HCO3
- + 2K
+ + 2H4SiO4 (17)
Ca-plagioclase into kaolinite:
CaAl2Si2O8 + 2CO2 + 3H2O
Al2Si2O5 (OH)4 + 2HCO3
- + Ca2+ (18)
Olivine weathering:
Mg2SiO4 + 4CO2 + 4H2O
2Mg2+ + 4HCO3- + H4SiO4 (19)
Calcite dissolution:
CaCO3 + CO2 + H2O
Ca2+ + 2HCO3-
(20)
The flux of CO2 consumed by weathering processes is mainly produced by soil
organic matter oxidation (Mortatti and Probst, 2003) which releases carbonic acid:
CH2O + O2
CO2+ H2O
2HCO3-
(21)
Based on the stochiometric coefficients of cations released versus CO2 consumed in
the above reactions, CO2 consumption rates (FCO2: mol km 2 y 1) were calculated from
silicate and carbonate weathering as follows:
FCO2 sil = FNa sil + FK sil + 2FMg sil + 2FCa sil
FCO2 carb = FMg carb + FCa carb
FCO2 = FCO2
sil + FCO2 carb
Here, it is assumed that only carbonic acid enhanced the weathering processes and
estimated CO2 consumption rate will be the upper limit. If sulphuric acid is also involved in
the weathering processes then cation and sulphate will be release to the solution. The
contribution of H2SO4 can be estimated by calculating equivalent ratios of sulphate R
(equation 22, Vuai and Tokuyama, 2007) and results for all the rivers are given in the table
3.18.
3*4
*4
HCOSO
SOR
(22)
The sulphate can be derived from the evaporites or oxidation of sulfide mineral like
pyrite. As there is no report of evaporites from this catchment area, it is considered that the
SO4* (atmospheric corrected) is derived by oxidation of sulfide mineral or from
anthropogenic sources. Estimating exact amount derived from anthropogenic source is
difficult. SO4*/Sr ratios of the river waters are plotted against the Ca*/Na (Fig. 3.17), where
different fields for silicate, carbonate, evaporates and anthropogenic sources (Millot et al.,
81
2003) indicated. As the samples plot close to the silicate field the anthropogenic contribution
to the total SO4* is considered negligible.
Ca*/Na*0 20 60 80 100
SO
4* /S
r
0
200
400
600
800
Carbonate
Evaporites
Weathering of Black Shale / Anthropogenic
Silicate
Fig 3.17 Ca*/Na* vs. SO4*/Sr plot for understanding the anthropogenic input to river water chemical budget. Different fields are for the various sources to the river water. The water samples of Kaveri, Palar and Ponnaiyar for monsoon and pre-monsoon periods are falling in the silicate field.
Assuming that H2SO4 is mainly derived by oxidation of sulfides total CO2
consumption was calculated using the equation:
Total FCO2 corrected for H2SO4 =
[{FCO2 sil
(R × FCO2 sil)}+{FCO2
carb
(R × FCO2 carb)}] (23)
While calculation of FCO2 it is assumed that the sulphuric acid dissolves carbonate
and silicate minerals with no selectivity. Hence, R was used for both silicate and carbonate
and the lower limit of the total FCO2 calculated. Both the results of FCO2
are listed in the Table
3. 19. The data of major ions of these water samples collected during monsoon and non-
monsoon period and information of discharge at the corresponding period are used to
calculate CO2 consumption. As this area is fully dependant on the monsoon, there is a clear
variation between calculated values for both the period, the values of monsoon period is
factor of ~ 2.5
7 times of non-monsoon period value (table 3.19). At Musiri the calculated
82
result of FCO2sil (upper limit) is 2.95 × 105 mol km 2 a 1 and 0.53 × 105 mol km 2 a 1 for
FCO2carb. The FCO2
carb is ~15% (~ 12
17 % calculated in the Kaveri mainstream at
different site) of the total FCO2sil of Kaveri basin. At the same site, CO2 consumption rate
corrected for H2SO4, is FCO2 total = 3.01 × 105 mol km 2 a 1, FCO2
sil is 2.55 × 105 mol km 2
a 1 and FCO2carb 0.46 × 105 mol km 2 a 1, which is the lower limit. The estimated CO2
consumption rate at different sites of the Kaveri river shows that it increases towards upper
reaches and varies between (3.49
8.48 × 105 mol km 2 a 1) in the main stream of Kaveri
(table 3. 19). Among tributaries Bhavani shows the higher CO2 consumption rate of 5.85 ×
105 mol km 2 a 1. The total CO2 drawdown in this basin (up to Musiri) is between 20.0 and
23.13 × 109 mol a-1 (3.01
3.49 × 105 mol km 2 a 1), which is much lower than the value
reported (58.4 × 109 mol a-1 or 6.65 × 105 mol km 2 a 1) by Gaillardet et al. (1999). Palar,
Ponnaiyar and Vellar river basins together accounts for 2.62 × 109 mol a-1 total CO2 (silicate
and carbonate) drawdown.
The relationship between the atmospheric/soil CO2 consumed during the silicate
weathering (FCO2 sil, here upper limit has used) and the specific silicate weathering for the
Kaveri basin is illustrated in the fig 3.18. The figure 3. 18. (A), gives a comparison between
low and high flow periods i.e. pre-monsoon and monsoon periods. A significant linear
correlation between FCO2 sil (105 mol km-2y-1) and SWR (tons km-2y-1) is observed for Kaveri
samples (annual) including Amaravati and Bhavani. The relation is as follows:
FCO2 sil = 0.3795 SWR + 0.06 with r2 = 0.99.
Palar, Ponnaiyar and Amaravati sample plot at the lower end of the figure 3.18 (B),
with lower SWR and FCO2 sil. The tributaries of Kaveri draining upper reaches fall on the
higher side of the correlation indicating high SWR and FCO2 sil. This is consistent with the
fact that these rivers draining 600
1000 m elevation where both physical and chemical
weathering rates are higher than the catchment area of palar and Ponnaiyar river.
A compilation of CO2 consumption rate, silicate and carbonate weathering rates of
other major Indian and world rivers with Kaveri, Palar, Ponnaiyar and Vellar rivers are given
in the table 3. 21.
83
FCO2 Sil ( x 105 mol/km2/y)
0 1 2 3 4 5 6 7
SW
R (
ton
s/km
2 /y)
0
2
4
6
8
10
12
14
16
18
MonsoonPre-monsoon
FCO2 Sil ( x 105 mol/km2/y)
0 2 4 6 8
SW
R (
ton
s/km
2 /y)
0
5
10
15
207
6
12
34
5
Fig 3.18 A) CO2 consumption rate during silicate weathering (FCO2 sil) is plotted against the silicate weathering rate (SWR) for Kaveri river basin for low and high flow periods i.e. pre-monsoon and monsoon periods separately at different sites. Except sample from Amaravati other monsoon samples fall in the higher side of the positive trend. B) Similar plot of annual silicate weathering rate against CO2 consumption rate for four rivers. Numbers indicate the river or tributary name, 1
Palar, 2
Ponnaiyar, 3
Amaravati, 4
Vellar, 5
Kaveri at Musiri, 6
Kaveri at Billigundla and 7
Kaveri at Kollegal.
84
3.8 Comparison of CO2 consumption rate with other river
The upper limit of CO2 consumption rate of Kaveri basin is close to the the area-
weighted CO2 consumption rate for the Deccan Traps 0.36×106 moles km-2 y-1 (Das et al.,
2005). The other peninsular river of India draining fully or partially Decan Trap shows
higher CO2 consumption rate than Kaveri e.g. reported average value for Narmada-Tapti
river 1.26 × 106 mole km-2 y-1 (Dessert et al., 2001), 0.74 × 106 mole km-2 y-1 for the Deccan
Traps (Dessert et al., 2003), 0.58 ×106 mole km-2 y-1 for silicate weathering in Godavari basin
(Jha et al., 2009).
Himalayan river basin like the Ganges, the Brahmaputra and the Indus which are
larger in terms of size and discharge than Kaveri, the total CO2 drawdown for silicate
mole y-1, Gaillardet et al., 1999) was also found to be higher than the Kaveri river. But total
CO2 consumption for rock weathering in the Indus basin basin (1.46 × 105 mole km-2 y-1) is
lower than the Kaveri whereas, in the Ganga (6.92 × 105 mole km-2 y-1) and the Brahmaputra
(4.93 × 105 mole km-2 y-1) consumption rate (Gaillardet et al., 1999) is higher. The Kaveri
Basin area (0.066 × 106 km2 up to Musiri) is about 0.044% of global continental area (150
×106 km2). Comparison with the percentage of CO2 drawdown (20.00 to 23.13 × 109 mole
y-1) during silicate weathering accounts for 0.22
0.26% of global CO2 consumption for
silicate weathering (8700 × 109 mole y-1, Gaillardet et al., 1999) indicates more intense CO2
consumption in this basin than the other areas of the world.
85
Table 3.16 The average annual flow in million cubic meters (MCM), the annual sediment loads in Metric Tonnes (MT) and the percentage of total contribution by South West Monsoon (SW), North East Monsoon (NE) and non-monsoon (NM) at different hydrological observation sites of four river system for the specified periods are listed.
Hydrological Station Name River
Drainage Basin
Area (km2)
Average Annual Flow Sediment Load (1999-2000) Sediment Load (2002-2003)
Villupuram Ponnaiyar 12900 1973 to 2000 331.5 0.9 95.1
4.0 - - - - - - - - Vazhavachanur
Ponnaiyar 10780 1978 to 2000 336.2 3.8 80.4
15.9
- - - - 2.3 11.1
86.5
1 Gummanur Ponnaiyar 4620 1978 to 2000 204.0 34.9
61.1
4.0 1.8 98.1
0.1 45 2.6 94.6
2.7 2
Kudalaiyathur Vellar 7890 1990 to 2000 520.0 0.1 97.1
2.8 - - - - - - - -
86
Table 3. 17. Physical (Wph) and specific chemical (Wch) weathering rate, silicate (SWR) and carbonate (CWR) weathering rate, total flux of dissolved silica and strontium in the Kaveri and its tributary, Palar and Ponnaiyar river for monsoon, non-monsoon and annual period. Wph were calculated from average sediment load for the period of 1989
Physical weathering rate (Wph) calculated assuming the density of soil 2 g/cm3, for silicate weathering rate density of silicate 2.7 g/cm3 and for carbonate it has been taken as 2.4 g/cm3.
Table 3.18 The mean and range of the R value calculated using equation 22 for monsoon and pre-monsoon water samples of Kaveri, Palar and Ponnaiyar river. R Monsoon Pre-monsoon Kaveri River Kaveri Palar Ponnaiyar Main stream Tributaries
n 9 8 5 16 21 Mean 0.14 0.16 0.12 0.16 0.33 Range 0.1
Table 3. 19 CO2 consumption rate during chemical weathering, its flux during monsoon, non-monsoon and for annual, percentage of CO2 consumed by silicate and carbonate weathering for Kaveri, Palar and Ponnaiyar river basin. Upper limit of consumed CO2
considering the reaction only by carbonic acid and lower limit after subtracting the contribution of H2SO4 for chemical weathering.
Value calculated using the equation 22 for different location and sampling period.
Table 3.20 Annual fluxes of major ions and TDS from Kaveri, Amaravati, Bhavani, Palar, Ponnaiyar and Vellar rivers. a = 103mol/km2/y, b = 109mol/y, c = tons/km2/y and d = 106 tons/y.
River Location Ca Mg Sr Na K HCO3
TDS a b a b a b a b a b a b c d
Kaveri Musiri 112.38
7.44
76.96
5.10
0.41
0.027
177.58
11.76
8.05 0.53
323.17
21.41
39.54
2.62
Amravathi Nallamaranpatti 36.80 0.33
29.07
0.26
0.22
0.002
71.75
0.65 3.06 0.03
89.88 0.82 12.77
0.12
Bhavani Savandapur 191.18
1.10
122.35
0.71
0.70
0.004
206.43
1.19 14.43
0.08
453.59
2.62 56.86
0.33
Palar Chengalpattu 8.27 0.13
4.13 0.07
0.03
0.001
11.24
0.18 0.63 0.01
28.83 0.47 3.43
0.06
Ponnaiyar Villupuram 25.34 0.33
14.44
0.19
0.10
0.001
41.73
0.54 2.59 0.03
78.62 1.01 9.27
0.12
Vellar Kudalaiyathur 48.78 0.38
27.86
0.22
0.19
0.002
65.67
0.52 2.68 0.02
196.65
1.55 19.84
0.16
River Name
Site Name /
Location Drainage
Area km2/
Season
When only carbonic acid considered
R
After subtracting contribution from H2SO4
FCO2
mol/km2/y (×105)
FCO2
mol/y (×109)
FCO2
% FCO2
mol/km2/y (×105)
FCO2
mol/y(×109)
Sil Carb
Total
Sil Carb
Total
Sil Carb
Sil Carb
Total Sil Carb
Total
Arkavaty
Kanakpura 3425
32KNT13 Non-Mon
0.25 0.05 0.29 0.08
0.02
0.10
83.5
16.5
0.13
0.21 0.04 0.26 0.07 0.01 0.09
Shimsha
T.K Halli 7890
33KNT14 Non-Mon
0.32 0.05 0.38 0.26
0.04
0.30
85.5
14.5
0.20
0.26 0.04 0.30 0.20 0.03 0.24 Kabini T. Narsipur 7000
Table 3.21 Comparison of silicate (SWR) and carbonate (CWR) weathering rate, CO2 consumption rates of Kaveri, Palar, Ponnaiyar and Velar river, with major Indian river and selected river basins of the world. Here a = tons km-2 y-1, b = m/Ma, c =105
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