HYDRO 2013_Pradyumna

© Lahmeyer International (India) Pvt. Ltd. © Lahmeyer International (India) Pvt. Ltd.

One-dimensional sediment modelling for Chuzachen and Devsari hydroelectric power projects to check the feasibility of reservoirs’ usage as pseudo-desanders Author and Presenter : Pradyumna Machhkhand Senior Manager (Hydropower & Water Resources)| Lahmeyer International (India) Pvt. Ltd. | Gurgaon-122002

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© Lahmeyer International (India) Pvt. Ltd.

Outline of the presentation

2

Introduction

Background Information

Reservoir Sedimentation

Sediment Modelling

Theory

Case Studies

Modelling Scheme

Model Set Up

Data Organization

Results

Comparison

Conclusion

Model Description


• Reservoir sedimentation in hydroelectric projects (HEP): a major problem that interrupts the smooth functioning of hydropower plants.

A schematic and classical illustration of reservoir sedimentation

Introduction

3


• In general, the problem is seen as a big hindrance and therefore, as a remedial measure – “n” number of desanders, based on studies, are usually proposed to manage the sediment removal operation.

• The presented case studies foray into the primary investigation of reservoir sedimentation prior to making decisions on sediment management.

• The investigation of sediments lies on two basic searches:

Where & How Much

Introduction

4

To examine the location and capacity of the reservoir in discrete form

To understand the relation between sediment concentration and discharge in the reservoir


• Two different hydroelectric projects have been studied: a. Devsari HEP (Devsari Reservoir) b. Chuzachen HEP (Rangpo Reservoir & Rongli Reservoir) • Project features:

contd...

Background information

5

Project features Devsari HEP Chuzachen HEP

(Rangpo)

Location Uttarakhand, India Sikkim, India


Background information

6

Project features Devsari HEP Chuzachen HEP

(Rangpo)

Type of structure Dam Dam

Height of structure 35m 48m

Extent of reservoir 4.8Kms from dam axis 508m from dam axis

Storage 9.026 Mm3 0.360 Mm

3

…contd


• Empirical methods

a. Advantage : explicit methods (such as, Hazen, Vetter, and Camp), computational ease while computing the sediment trap efficiency.

b. Limitations : i. cover only the settling phase of reservoir operation, ii. and other factors which are NOT included in the empirical methods are:

the sediment transporting capacity of flow in a settling reach, the change in conditions as reservoir fills with sediment, the effect of variation in flow depth down a basin or reservoir, and the additional turbulence caused by inlet condition to a basin or

reservoir. contd...

Reservoir sedimentation

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• 1-dimensional numerical model

a. Advantages :

models the effect of turbulence in sediment movement and mass deposition,

not only simulates deposition, but also sluicing,

does not require grids to approximate cross-sections,

and requires less field data to set up.


8

…contd


• 1-dimensional numerical model

b. Limitations:

does not offer a detailed view of hydrodynamics of reservoir

system like 2-D or 3-D models.

Although 2-D or 3-D models have certain advantages, but at the cost of a

longer computational time and substantial amount of field data to

capture the complexities of 2-D or 3-D flow.

contd...


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• SHARC , a software developed by HR Wallingford, UK, is a suite of integrated

programs designed to assist in the identification and solution of sediment problems at intakes in rivers and canal systems.

• DOSSBAS stands for Design of Sluiced Settling Basins.

• DOSSBAS is tool built within SHARC to model sediment depositions in basins/reservoirs and can model both regular and irregular basins.

• Two suites of DOSSBAS: 1) Deposition Model. 2) Sluicing Model.

Model description : DOSSBAS tool of SHARC

10

contd…


• Deposition model

Assumptions: o the flow is steady,

o the velocities and concentrations are constant across the width of the

channel,

o and the concentrations in one size fraction do not affect other size fraction.


11

…contd


• Deposition model [Basic equation of turbulence (Dobbins ,1994)]

…Equation (1)

= sediment diffusion coefficient in y-direction (m2/sec) , = sediment diffusion coefficient in x-direction (m2/sec), = and settling velocity (formula by Gibbs et al, 1971) of sediment for the sediment size fraction (j) (m/sec).


12

…contd

2

2

2

2

x

C

y

C

yV

y

C

x

Cu

j

x

jy

sj

j

y

j

where, u = flow velocity at height y above the bed (m/sec), y = height above bed (m), Cj = sediment concentration at height (y) above bed for size fraction( j), x = distance co-ordinate along channel (m),

y

x

sjV


• Deposition model


13

…contd


Deposition model : Turbulent diffussion within a sub-reach

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•

Deposition model : Boundary conditions

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Overall structure of deposition model

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• Sluicing model

Sluicing model simulates only sand movements. It is assumed that any silt in the exposed bed material is sluiced instantly and therefore, only sand transport controls the sluicing rates.

Diffusion is not a dominant process in sluicing. Sluicing is modelled using equation,

Note: The threshold value to differentiate between silt and sand in DOSSBAS is 63 micron (default).


17

…contd


Overall structure of sluicing model

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Modelling scheme of reservoir sediment management plan

Modelling scheme

19

contd…


Modelling scheme

20

…contd

• Set of parameters

X1 is the set of input parameters, viz., reservoir geometry, and sediment data

X2 is the set of parameters that includes the temperature, and the sand concentrations to be applied in both deposition and sluicing model.

The input parameters for deposition model can be expressed as, (X1 ∪ X2).

The set X3 is composed of additional parameters such as, flushing/sluicing discharge, the water level at the time of sluicing, and the duration of sluicing.

Y1 is the set of longitudinal bed profiles, which are results of deposition models.

The input parameters for sluicing model can be expressed as, (Y2 ∪ X2 ∪ X3).

The set Y2 comprises results of sluicing models in terms of elapsed time for flushing out the sediments and change in bed profiles at different time.


• Hydrological year mean flow duration curves

Data organization

21

contd…

0

20

40

60

80

100

120

140

160

180

200

220

240

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Dis

char

ge (m

3/s

ec)

Exceedance probability (%)

Flow duration curve divisions: Devsari HEP

Flow duration curve

Qdesign (Intake) = 120.76 m3/sec

Division3 Qm = 44.8 m3/sec



0

20

40

60

80

100

120

140

160

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Dis

ch

arg

e (cum

ec)

Exceedance Probability (%)

Flow duration curve divisions : Rangpo

Flow duration curve

Qm = 33.2 m3/sec (Division 3)

Qm= 95.8 m3/sec (Division 1)



Qdesign = 21.5 m3/sec


• Pre-processed data: average discharge and mean concentration

Data organization

22

contd…

Divisions

Devsari Rangpo

Qm

Mean conc.

Qm

Mean conc.

m3/s ppm m3/s ppm

1 205.3 511 95.8 707

2 160.1 436 58.1 389

3 44.8 192 33.2 187

4 - - 8.4 47


• Optimization of input parameters

Data organization

23

contd…

y = 16.54x0.6445

R² = 0.6115

0

100

200

300

400

500

600

700

800

900

0 50 100 150 200 250

Me

an

Co

nc

en

tra

tio

n [

pp

m]

Mean Discharge [m3/s]

Mean discharge vs mean concentration

Obs.Mean …Power (Obs.Mean …

Devsari Reservoir

6445.054.161

xCm


• Optimization of input parameters

Data organization

24

…contd

Rangpo Reservoir

o from the table of the pre-processed data, the annual sediment volume of Rangpo is about 70% the capacity of the Reservoir, and therefore, it is quite conservative to adopt the same values.


• Bed gradation curves

Model setup

25

contd…


• Input parameters

Model setup

26

…contd

Divisions

Flow

Sediment concentration

Deposition cycle time

Flushing discharge

Silt Sand

m3/sec ppm ppm Days Hours m3/sec

1 205.3 465 199 37 876 84.5

2 160.1 397 170 44 1051 39.3

3 44.4 174 74 285 6833 NA

Divisions

Flow

Sediment Concentration

Deposition cycle time

Flushing discharge

Silt Sand

m3/sec ppm ppm Days Hours m3/sec

1 95.8 495 212 37 876 74.3

2 58.1 273 117 37 876 36.6

3 33.2 131 56 73 1752 11.7

4 8.4 33 14 219 5256 NA

Devsari Rangpo


• Input parameters

Model setup

27

…contd


• Deposition model: Devsari

Results

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1265

1270

1275

1280

1285

1290

1295

1300

1305

0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000

Distance downstream (m)

Minimum bed lev el (m)

Bed lev els at time 0.00 (hours )







Final w ater lev el

Longitudinal Profile Down Basin

Ele

vati

on

(m

)

Divisions

Sediment Volume

Outflow Sediment

Trap Efficiency

Reservoir Storage

Silt Sand Silt Sand Silt Sand Before run

After run

Mm3 Mm3 PPM PPM % % Mm3 Mm3

1 0.1 0.1 215 0 53.7 100.0 9.1 8.9

2 0.1 0.1 164 0 58.6 100.0 9.1 8.9

3 0.1 0.1 35 0 79.8 100.0 9.1 9.0

contd…


• Sluicing model: Devsari

1265

1270

1275

1280

1285

1290

1295

1300

0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000










Elev

atio

n (m

)

Results

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contd… …contd

Divisions

Volume removed Elapsed time for

flushing

Silt Sand Total

sediment

Mm3 Mm3 Mm3 Hours

1 0.1 0.1 0.2 14.44

2 0.1 0.1 0.2 28.59

3 NA


• Deposition model: Rangpo

Results

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contd…

880

885

890

895

900

905

910

915

0 100 200 300 400 500 600










Final w ater lev el


Ele

va

tio

n(m

)

Divisions

Sediment Volume

Outflow Sediment

Trap Efficiency

Reservoir Storage

Silt Sand Silt Sand Silt Sand Before

run After run

Mm3 Mm3 PPM PPM % % Mm3 Mm3

1 0.013 0.045 350.0 5.0 12.6 97.5 0.36 0.31

2 0.009 0.015 217.0 1.0 20.4 99.3 0.36 0.34

3 0.007 0.008 89.0 0.0 31.7 100.0 0.36 0.35

4 0.003 0.002 14.0 0.0 58.8 100.0 0.36 0.36


• Sluicing model: Rangpo

Results

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contd… …contd

880

885

890

895

900

905

910

0 100 200 300 400 500 600








Ele

vati

on

(m)

Divisions

Volume removed Elapsed time for

flushing

Silt Sand Total

sediment

Mm3 Mm3 Mm3 Hours

1 0.014 0.043 0.06 0.41

2 0.009 0.015 0.02 0.35

3 0.005 0.008 0.01 0.79

4 NA


• Velocities and required length of reservoirs to settle 0.2mm particle:

Comparison with empirical method

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Devsari Rangpo Units

Full reservoir level (FRL) = 1300 910 MASL

Minimum drawdown level(MDDL) = 1295 893 MASL

Division1 average discharge (Qa) = 205 90 m3/sec

The approximate average area of flow (A) = 4700 1978 m2

The corresponding flow through velocity (V) = Qa/A = 0.044 0.046 m/sec

Mean flow through velocity for 0.2mm particle to settle down, v’ = 0.2 0.2 m/sec

Settling velocity of 0.2mm particle, w = 0.022 0.022 m/sec

Length of reservoir required to settle 0.2mm particle, L*= v’/w x ( FRL-MDDL) = 45.5 154.5 m

Mid-Length from dam axis of reservoir, L = 2500 254 m

…contd


• It can be safely inferred from the model results that the sediment grain size of 0.2mm and greater than 0.2mm shall be settling down in the reservoirs.

• If periodical flushing operations are realized during the whole life of the

reservoir, the entrance sill of the intake will not be affected by the deposited sediments; as it is already being witnessed in the model studies.

• The model studies have potential scopes to enhance the analysis; the sensitivity analysis of the models is one of them.

Conclusion

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contd…


• It would be in the interest of HEPs, if the utility of the desanders decelerates before placing them in the planning stages, thereby encouraging physically-based hydraulic modelling study of the sediments in the interim to assess whether the reservoirs are self-sufficient for managing the sediment processes or not.

• The case studies of this paper offer supporting results to the usage of

reservoirs for sediment management, but since the rapidification of desanders are commonly observed in HEPs; despite the reservoirs being gigantic in size, the term “pseudo-desanders”, used in the title of the paper, for reservoirs appears reasonable.

Conclusion

34

…contd


• This work would have been due without the moral support of my wife, Imane Ibnoussina. The timely information and encouragement offered by Dr. S.K.Mazumder is highly appreciated; my sincere regards to him and his family. The intensity of the work is recognized and is supported for presentation by Dr. A.K.Jha. The encouragement offered by Lahmeyer International (India) Pvt Ltd. is highly appreciated.

• http://r4d.dfid.gov.uk/Output/5145/

Acknowledgements

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http://r4d.dfid.gov.uk/Output/5145/














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HYDRO 2013_Pradyumna