introduction about stream flow and emerging technique related to remote sensing like surface velocity Radar (SVR) and probability concept

1. School of Water Resources
Indian Institute of Technology
Kharagpur
Environmental Hydrology & Hydraulics
TERM PAPER SEMINAR
ON
STREAMFLOW MEASUREMENT
1
P.G. Lakshmi Priya (17WM60R04)
Chandra Vanshi Thakur (17WM60R07)
Presented by:-

2. Contents
Introduction
Stream Flow
techniques
Surface Velocity
Radars (SVR)
Probability concept of
discharge estimation
Conclusion
References
2

3.  Stream flow, or discharge, is the volume of water that moves over
a designated point over a fixed period of time (Subramanya, 2008).
 Stream flow is measured in units of discharge(m3/s).
 The flow of a stream is directly related to the amount of water
moving off the watershed into the stream channel.
 Affected by weather.
Introduction
3

4. Sources of stream flowSources of Stream Flow
4
Source: http://uregina.ca/sauchyn/geo327/outline.html

5.  Estimating long-term trends in water and sediment discharges
 The design and construction of bank and in-channel structures
requires highly accurate information on flow rate.
 Stream flow is a major element of the water cycle.
Importance of Stream Flow Measurement
5

6. Stream flow Controlled by
 Gradient of the channel bed
 Volume of water within the channel
 The shape of a channel
 Channel roughness , including friction
Selection of Method
 Depends on the cost, time of operation, location and degree of
accuracy.
Contd…
6

7. Stream
Flow
Direct
Area
Velocity
methods
Dilution
techniques
Electromagnetic
method
Ultrasonic
method
Indirect
Slope-area
method
Hydraulic
structures
Stream Flow techniques
7

8. 8
a) b)
c)
e) d) f)
Fig: a) area-velocity b) Dilution technique c) Electromagnetic d) Ultrasonic
e) Slope-Area method f) Hydraulic structures

9.  Forecasting stream flow during extreme hydrologic events
such as floods can be problematic.
 when flow is unsteady, and river forecasts rely on models that
require uniform-flow rating curves to route water from one
forecast point to another.
Limitations
9Source: Fulton et al., 2008

10. Non-Contact
Methods
Remote
sensing
method
Particle
Image
Velocimetry
Emerging technologies
10
Source: Dobriyal et al., 2016

11.  Makes use of Doppler’s effect to provide an estimate of water
surface velocity.
 Surface flow velocity is computed by taking into account the
vertical (tilt) and horizontal (yaw) angles of the beam.
 The return signal represents an average over the beam footprint
(illuminated area which depends horizontal beam width and the
distance between the antenna and the target) on the river water
surface.
SURFACE VELOCITY RADAR (SVR)
11
Source: Welber et al., 2016

12. Contd…
12
Fig: Schemes of SVR operation.

13. Ai=BiDi
Qi=AiVi
Contd…
13
Source: Welber et al., 2016
Source: Fulton et al., 2008

14.  The surface velocity is converted to mean velocity by considering
a velocity coefficient (α),
∝=
𝑽𝒊
𝑽s,i
 Default α: Derived from various literature which is taken as 0.85.
 Calibrated α: Obtained by fitting a power or logarithm law to
individual vertical velocity profiles obtained with current meters
or ADCP
Where
α = Velocity Coefficient
Vi = Depth-averaged velocity
Vs,i = Surface velocity
Contd…
14
Source: Welber et al., 2016

15.  Theoretical α: Local flow velocity variation along vertical z is
given by
Where
Zo = Roughness length
U* = Friction velocity
k = Von karman constant (0.41)
Di = Flow depth
 Surface velocity can be determined by putting z = Di in the first
equation
Contd…
15

16. Default/Theoretical α Calibrated α
 In general, error appeared to be more strongly related to relative
roughness than to other parameters.
Contd…
16
Source: Welber et al., 2016

17. Contd…
 Default α and theoretical α provide discharge values within 10%
of contact survey estimates when the relative roughness was
between 0.002 to 0.05.
 Theoretical α and calibrated α values provided satisfactory
results in smooth channels having relative roughness is less
than 0.001 and 0.002, where as Default α lead to
underestimation.
 Calibrated α provided better accuracy for rough channels where
the relative roughness was more than 0.05
17Source: Welber et al., 2016

18.  The vertical axis i.e. y-axis in the stream consisting the maximum
velocity of the stream was selected from the historical records.
 The surface velocity (uD) at y-axis was measured using radars.
 From the historical records, the maximum stream velocity (umax)
and the mean stream velocity (uavg) for a site was collected and
plotted on a graph.
Probability Concept
Source: Chiu et al., 200518
Where
M= Parameter related to average and Maximum Velocity

19. Contd…
Fig: Network of constants at channel sections
Source: Chiu et al., 200519

20.  The ratio of water depth (D) and the depth (h) of maximum
velocity (umax) below the water surface at y-axis was
measured using:
Contd…

21.  SVR surveys require minimal training, equipment and
manpower.
 Its ease of use and limited cost opens new possibilities for large
scale flood monitoring.
 It can be used to extend the range of validity of rating curves by
providing much-needed direct information on water velocity at
high flows.
 The use of SVR depends on weather conditions like wind and
rainfall.
 Probability concept of discharge computation gave accurate
results and required less field time.
Conclusions
21

22.  Barbarossa, V., Huijbregts, M.A.J., Hendriks, A.J., Beusen, A.H.W., Clavreul, J.,
King, H., Schipper, A.M. 2016. Developing and testing a global-scale
regression model to quantify mean annual streamflow, J. Hydrol. 544:479-
487.
 Chiu, C., Hsu, S.H., Tung, N. 2005. Efficient methods of discharge measurements
in rivers and streams based on the probability concept. Hydrological
Processes. 19:3935-3946.
 Costa, J.E., Cheng, R.T., Haeni, F.P., Melcher, N., Spicer, K.R., Hayes, E., Plant,
W., Hayes, K., Teague, C., Barrick, D. 2006. Use of radars to monitor stream
discharge by non-contact methods. Water Resources Research 42, W07422.
doi:10.1029/2005WR004430.
 Dobriyal, P., Badola, R., Tuboi, C., Hussain, S.A., 2016. A review of methods for
monitoring streamflow for sustainable water resource management, Appl.
Water Sci. 7:2617-2628.
References
22

23.  Fulton, J., and Ostrowski, J. 2008. Measuring real-time streamflow using emerging
technologies: Radar, hydroacoustics, and the probability concept. Journal of
Hydrology. 357(1):1–10.
 Subramanya, K. 2008. Engineering Hydrology, Third Edition, Tata McGraw-Hill,
New Delhi, India.
 Welber, M., J. Le Coz, J. B. Laronne, Zolezzi, G., Zamler, D., Dramais, G., Hauet,
A. and Salvaro, M. 2016. Field assessment of noncontact stream gauging
using portable surface velocity radars (SVR). Water Resour. Res. 52:1108–
1126. doi:10.1002/2015WR017906.
Contd…
23

24. 24