5.7 RESULTS AND DISCUSSION
5.7.3 River-Aquifer Exchange Flux
RIVER-AQUIFER INTERACTION
Table 5.1: Evaluation statistics of Groundwater Model
Station Name
Groundwater Recharge
used Duration R2 NSE RMSE
(m)
Supaul
SWAT Recharge Calibration 0.71 0.33 0.61
Validation 0.67 0.38 0.43
SWB Recharge Calibration 0.83 0.85 0.36
Validation 0.79 0.81 0.25
Jaynagar
SWAT Recharge Calibration 0.71 0.56 0.45
Validation 0.69 0.67 0.51
SWB Recharge Calibration 0.80 0.84 0.38
Validation 0.77 0.80 0.37
Figure 5.8: Spatio-temporal variations of River-Aquifer exchange flux along Kosi river reach (upstream to downstream) obtained using MODFLOW model with Keff-10 value of
Scenario 1 (S1) and recharge estimated by (a) SWAT model (case I) (b) SWB method (case II).
[*Note: (1) Green to Red color indicates river losing state and blue color indicates river gaining state (2) Positive value of river leakage indicates the river is losing water to the aquifer whereas negative value indicates the river is gaining water from aquifer]
Table 5.2: Zonal statistics of river-aquifer exchange flux obtained using SWAT and SWB recharge
Case Zone River-Aquifer Exchange Flux (m3/day)
Minimum Average Maximum Standard Deviation I
Zone I 1 292 794 191
Zone II -149 177 584 119
Zone II -597 -156 283 126
II
Zone I 33 433 979 211
Zone II -196 262 891 139
Zone II -768 -177 439 164
Aug-98 Apr-00 Dec-01 Aug-03 Apr-05 Dec-06 Aug-08
Apr-10 800
600
400
200 0
-200
-400
Month
River Leakage (m3/day)
40 140 200 220
(a)
Aug-98 Apr-00 Dec-01 Aug-03 Apr-05 Dec-06 Aug-08
Apr-10 1000
800 600 400 200 0 -200 -400 -600 20 40 60 80 100 120 140 160 180 200 220
-800 (b)
Month
-600
Distance (km)
40 Zone II140 200 220
Zone I Zone III
RIVER-AQUIFER INTERACTION
The observations from both the cases reveal that the losing rate is found be higher during the non-monsoon season than that in monsoon season throughout the study period.
However, the gaining rate is observed to higher during monsoon season than that of non- monsoon season. Similar observation can be found in the study carried out on wetland-river interactions in Kosi river basin [Chembolu et al., 2019]. Their study also revealed that the flow was coming out of the river (losing) during monsoon period whereas the flow was leaving from the wetland (gaining) during non-monsoon season.
In comparison with case I and case II, the losing rates are noted to be lesser throughout Zone I and II in case I than case II. But, the gaining rates in case I are found to be higher in Zone III (falls in Sub-basin 17 (S-17)) in comparison with case II throughout the zone except the maximum values. It is resulted due to the incorporation of over- predicted recharge (section 3.10) into the groundwater model. However, the highest value of gaining rate (-769 m3/day) is observed to be found in case II in comparison with the case I (-597 m3/day). It has happened due to the highest value of recharge in S-17 (annual recharge of 67 cm per year) corresponding to the wettest year (1999) was obtained using SWB method against SWAT simulated recharge (24 cm per year), Also, the effect of wet and dry years on river-aquifer interaction is not well captured by the model in case I. For example, this behaviour can be clearly seen in zone III during wet and dry periods. The river is found to be significantly gaining water from the aquifer even during and after the dry cycle (2005 onwards) whereas the influence of the dry cycle can be seen in case II (2005 onwards) and the river is observed to lose water in comparison with the behaviour in early periods except in 2007. Also, the wet year influence can be clearly seen in case II than in case I. In comparison with case I (Figure 5.8(a)), the influence of wet year can be strongly seen throughout the stretch in zone III during wettest year (1999) in case II (Figure 5.8(b)).
This inter-comparison between case I and case II clearly indicate that the groundwater modelling with SWB recharge can able to capture wet and dry year impacts on river-aquifer exchange fluxes than that of SWAT recharge-based modelling.
However, it can be observed that irrespective of case (I or II) considered for modelling, the river always loses water to aquifer (as influent River) at upstream and mostly gains water from aquifer (as effluent river) at downstream during wet and dry years which indicates that significant influence of topography on river-aquifer exchange flux. This influence of topography on river-aquifer exchange flux from Kosi barrage (upstream) to the point of conference with Ganga river (downstream) in different zones can be
represented through a conceptual diagram (Figure 5.9). It shows the spatial variation of the groundwater table along the river reach (from upstream to downstream) during wet and dry years. During wet and dry years, the groundwater levels at upstream (at higher ground elevations) always lie below the river water surface which causes the river to be behave influent in Zone I while the groundwater levels at downstream (at lower ground elevations) lie above the river water level which makes effluent river in Zone III. In Zone II, the groundwater levels rise above the river water levels during wet years which makes the river to behave as influent whereas falls below river water levels during dry years which makes the river to behave as effluent i.e. combination of influent and effluent nature can be seen in Zone II.
Figure 5.9: Conceptual diagram of groundwater table spatial variation along Kosi river reach (upstream to downstream) during wet and dry years
Overall, the groundwater modelling in case II (using SWB recharge) is found to have good agreement with observed groundwater levels and also able to capture the wet and dry year effects on river-aquifer interaction process in Kosi river basin. Like Kosi, Gandak river is also one of the major tributaries of Ganga river and the study on river- aquifer interaction in Gandak river revealed that the exchange rates varied in the range between -500 to 1000 m3/day [Singh et al., 2018]. Similar to Gandak river, the river-aquifer exchange rates are found to vary in the range of -600 to 1000 m3/day in Kosi river basin.
Zone I Zone II Zone III
Kosi Barrage (upstream)
Ganga River (downstream) Dry Year Wet Year Groundwater Table
Elevation
River water Surface
Distance
RIVER-AQUIFER INTERACTION
5 . 7.4Inter-comparison of River-Aquifer Exchange Flux of Scenario 1 and 3 In order to see the influence of riverbed conductance on river-aquifer exchange flux, three different percentiles (Keff-10, Keff-50 and Keff-90) (Section 4.4, Table 4.21) were used in riverbed conductance calculation which were further used in the groundwater flow modelling to assess the spatio-temporal variations of the exchange flux rate in the basin.
Figures 5.10 and 11 show the exchange flux spatio-temporal variations in the three- dimensional plot of case II modelling for Scenario 1 and 3 (S1 and S3) considered in the sandbox experiments. The variations of exchange flux obtained using SWB recharge and riverbed conductance calculated with Keff-10 of S1 are shown in Figure 5.10(a). It can be noted that the river is observed to lose water (as influent) in Zone I with an average of 433 m3/day, gain water (as effluent) in Zone III with an average of -177 m3/day) whereas combination influent and effluent nature of river can be seen in Zone II with an average of 262 m3/day. The losing rates are observed to vary between 33 and 979 m3/day whereas, the gaining rates are found to vary in the range of -196 to -768 m3/day respectively in the study area. It is observed that the river was significantly losing water to the aquifer after the dry cycle (2005 onwards) and this behaviour can be clearly seen in Zone III, whereas, the influence of the wet year can be strongly seen throughout the stretch in zone III during the wettest year (1999). Similar variations in the exchange rate are noted in case II groundwater modelling with riverbed conductance calculated with Keff-50 and Keff-90 values (Figures 5.10(b-c)). It can be found that there is not much significant difference in the exchange rates in the modelling outcomes with the variations of riverbed conductance value. This can be clearly seen with the statistics of river-exchange flux in all the three zones for S1 can be seen in Table 5.3.
Figure 5.10: River-Aquifer exchange flux along Kosi river reach (upstream- downstream) obtained from case II groundwater modelling using SWB recharge and riverbed conductance calculated with (a) Keff-10 (b) Keff-50 (c) Keff-90 values of Scenario 1 (S1)
Aug-98 Apr-00 Dec-01 Aug-03 Apr-05 Dec-06 Aug-08
Apr-10 1000
800 600 400 200 0 -200 -400 -600 -800
(a)
Month
River Leakage (m3/day)
Aug-98 Apr-00 Dec-01 Aug-03 Apr-05 Dec-06 Aug-08
Apr-10 1000
800 600 400 200 0 -200 -400 -600 -800
(b)
Month
Zone I Zone II Zone III
Aug-98 Apr-00 Dec-01 Aug-03 Apr-05 Dec-06 Aug-08
Apr-10 1000
800 600 400 200 0 -200 -400 -600
20 40 60 80 100 120 140 160 180 200 220
-800
(c)
Month
Distance (km)
Zone I Zone II Zone III
RIVER-AQUIFER INTERACTION
Figure 5.11: River-Aquifer exchange flux along Kosi river reach (upstream- downstream) obtained from case II groundwater modelling using SWB recharge and riverbed conductance calculated with (a) Keff-10 (b) Keff-50 (c) Keff-90 values of Scenario 3 (S3)
Figure 5.11(a-c) shows the spatio-temporal variations of exchange flux obtained using case II modelling with riverbed conductance calculated using Keff values of Scenario 3. Similar to the modelling with Keff values of S1, the river is observed to be influent (losing river) in Zone I (with an average of 332 m3/day), effluent in Zone III (with an average of -
Aug-98 Apr-00 Dec-01 Aug-03 Apr-05 Dec-06 Aug-08
Apr-10 800
600 400
200 0
-200
-400
(a)
Month
River Leakage (m3/day)
(b)
Month
Aug-98 Apr-00 Dec-01 Aug-03 Apr-05 Dec-06 Aug-08 Apr-10
600 800
200 0 -200 -400 -600 400
Zone I Zone II Zone III
20 40 60 80 100 120 140 160 180 200 220
(c)
Month
Distance (km)
Aug-98 Apr-00 Dec-01 Aug-03 Apr-05 Dec-06 Aug-08 Apr-10
600
400 200 0 -200 -400 -600 800
Zone I Zone II Zone III
137 m3/day) and both influent and effluent in Zone II (with an average of 201 m3/day) respectively. In the study area, the losing rates are found to vary with minimum and maximum of 26 and 756 m3/day whereas, the gaining rates are observed to vary with a minimum and maximum of -149 and -573 m3/day respectively. In comparison with the results obtained with S1, these exchange rates are noted be significantly decreased. Also, the wet and dry year behaviours are found to follow the similar trend observed (Figure 5.11) and there is not much significant difference in the exchange rates in the modelling results by varying riverbed conductance value. This can be clearly seen with the statistics of river-exchange flux in all the three zones for S3 (Table 5.3). From this study, it can be noted that variations in the riverbed conductance of a particular soil stratification combination does not have much significant effect on river-aquifer exchange flux.
However, river -aquifer interaction is highly sensitive to different soil stratification.
Table 5.3: Zonal statistics of rive-aquifer exchange flux obtained using SWB recharge for Scenario 1 and 3
Scenario Keff
Percentile Zone River-Aquifer Exchange Flux (m3/day)
Minimum Average Maximum Standard Deviation
S1
Keff-10
Zone I 33 433 979 211
Zone II -196 262 891 139
Zone II -768 -177 439 164
Keff-50
Zone I 34 444 986 216
Zone II -201 268 902 142
Zone II -787 -182 446 168
Keff-90
Zone I 35 455 994 222
Zone II -206 275 908 146
Zone II -806 -186 455 172
S3
Keff-10
Zone I 26 332 756 161
Zone II -149 201 683 106
Zone II -573 -137 338 127
Keff-50
Zone I 27 350 768 171
Zone II -158 212 721 112
Zone II -581 -145 357 134
Keff-90
Zone I 28 369 794 180
Zone II -166 223 760 118
Zone II -594 -152 376 141
*Note: River-aquifer exchange flux was calculated using SWB recharge (case II) and riverbed conductance calculated with Keff-10,Keff-50 andKeff-90 values of Scenario 1 (S1) and Scenario 3 (S3).
RIVER-AQUIFER INTERACTION