This document discusses using remote sensing to estimate water discharge in Himalayan rivers. It begins by explaining the importance of measuring water discharge but limitations of conventional gauge-based methods. It then outlines how remote sensing approaches can establish width-discharge relationships based on a threshold theory of channel formation. Applying this to Landsat images of several Himalayan rivers allows estimating total discharge across multiple channels as well as generating hydrographs without in-situ gauges. In conclusions, the study finds its width-discharge method is valid for both single-thread and multiple-thread rivers and could be applied to estimate average annual discharge in other alluvial rivers globally.

1. Remote sensing to estimate formative water
discharge of the Himalayan Foreland rivers.
Department of Earth & Environmental Sciences
Indian Institute of Science Education and Research, Bhopal
(India-UK Water Centre)
19 June 2017
Kumar Gaurav (IISER, Bhopal) Remote sensing to estimate discharge 0 / 14

2. Introduction
Flow discharge and its measurement:
Q=?
v
Water discharge in river
channels is an important
quantity of hydrologic cycle
Kumar Gaurav (IISER, Bhopal) Remote sensing to estimate discharge 1 / 14

3. Introduction
Flow discharge and its measurement:
Q=?
v
Water discharge in river
channels is an important
quantity of hydrologic cycle
It is needed to understand:
- Terrestrial water budget
- Flood management
- River morphology
- Water security etc.....
Kumar Gaurav (IISER, Bhopal) Remote sensing to estimate discharge 1 / 14

4. Introduction
Flow discharge and its measurement:
Q=?
v
Water discharge in river
channels is an important
quantity of hydrologic cycle
It is needed to understand:
- Terrestrial water budget
- Flood management
- River morphology
- Water security etc.....
Kumar Gaurav (IISER, Bhopal) Remote sensing to estimate discharge 1 / 14

5. Hydraulic geometry relationship
Width(W ) = αW QβW
(1)
Depth(H) = αHQβH
(2)
Slope(S) = αS Q−βS
(3)
[Leopold and Wolman 1957]
Kumar Gaurav (IISER, Bhopal) Remote sensing to estimate discharge 2 / 14

6. Discharge estimation: Conventional approach
Stage-Discharge rating curve:
(x10)
30 60 90
0
20
10
0
Discharge (Q)
Depth(H)
Flow H
[source: Sanders 1998]
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7. Discharge estimation: Conventional approach
Stage-Discharge rating curve:
(x10)
30 60 90
0
20
10
0
Discharge (Q)
Depth(H)
Flow H
[source: Sanders 1998]
Site dependent
Requires a gauging station
Assumes river flows as
single-thread and have a
stable boundary
Kumar Gaurav (IISER, Bhopal) Remote sensing to estimate discharge 3 / 14

8. Discharge estimation: Conventional approach
Stage-Discharge rating curve:
(x10)
30 60 90
0
20
10
0
Discharge (Q)
Depth(H)
Flow H
[source: Sanders 1998]
Site dependent
Requires a gauging station
Assumes river flows as
single-thread and have a
stable boundary
Flo
w
Flow
Flow
?
Kumar Gaurav (IISER, Bhopal) Remote sensing to estimate discharge 3 / 14

9. Discharge estimation: Remote sensing approach
Width-Discharge rating curve:
Discharge
Width
0 1000 2000
400
800
(Q)
(W)
[source: Smith et al., 1996]
At a station rating
curves.
Assumes river is stable.
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10. Alluvial river: channel migration
Channels are mobile in
space and time
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11. Width-discharge relationship: Physical basis
Threshold theory
µ =
Tangential force
Normal force
µ is Coulomb friction coefficient
For a given discharge this
mechanism sets the size of a
channel.
[Glover and Florey 1951, Henderson 1963, and Seizilles et al 2013]
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12. Threshold theory: regime relations
W =
π
µ3/4
3
23/2 K [1/2]
√
Cf
g1/4
1
L1/4
√
Q (Lacey’s law)
L =
θt (ρs − ρf ) ds
µρf
W and Q are width and discharge
θt is threshold parameter
ds is grain size
Cf is Chézy friction coefficient
µ is Coulomb’s friction coefficient
ρf and ρs is fluid and water density
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13. Himalayan foreland rivers and threshold channel: width
10
1
10
2
10
3
10
4
Discharge [ ]
10
1
10
2
10
3
Width[m]
Multiple Single channel
Threshold
theoryBest fit
[Gaurav et al, 2017 (In press)]
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14. Hypothesis
10
1
10
2
10
3
10
4
W
Discharge
Width Regime relation
10
1
10
2
10
3
10
4
[m]
[m3
/s]
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15. Locations
0 650 km
Indus
Brahmaputra
Indo-Gangetic Basin River
0 650 km
Himalayan Frontal Thrust
Indus
Brahm
aputra
Chenab
Ganges
Kosi
Teesta
N
Bhimnager barrage
Panjnad
Kotri barrage
Farakka barrage
Anderson br
Kaunia
Bahadurabad
Paksay
Data
Landsat satellite images (resolution 30 m)
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16. Discharge at a section
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17. Discharge at a section
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18. Discharge at a section
Total discharges;
Qtot = Q1 + Q2 + Q3
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19. Hydrograph
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
10
2
10
3
10
4
Discharge[m3
s−1
]
Kosi Bhimnagar barrage
Image derived
Average
In-situ
Average
Month
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20. Conclusions
Average annual discharge can be estimated using remotely sensed
images.
Width-Discharge regime relation established in this study is equally
valid for multiple and single-thread river system.
This finding could be extend to alluvial rivers located in different
environments worldwide.
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21. Thank you
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