2.FLOOD RISK ANALYSIS _PRADYUMNA MACHHKHAND - Copy

Confidential Restricted Public Internal A company of

10 December 2016

Flood Risk Analysis by Hydrologic Routing and Hydraulic Modelling: A Comparative Study

Confidential Restricted Public Internal A company of

10/12/2016 FLOOD RISK ANALYSIS BY HYDROLOGIC ROUTING AND HYDRAULIC MODELLING: A COMPARATIVE STUDY

10 December 2016

Flood Risk Analysis by Hydrologic Routing and Hydraulic Modelling: A Comparative Study

Author and Presenter : Pradyumna Machhkhand Deputy General Manager (Hydropower & Water Resources)| Lahmeyer International (India) Pvt. Ltd. (A company of

Tractebel Engie) | Gurgaon-122002| Tel. +91 124 4712260 Extn. 574| Mob: +919999326876 | Fax: +91 124 6697601|

Email: [email protected]

mailto:[email protected]

Chapter 1

Chapter 2

Chapter 3

Chapter 4

OUTLINES OF THE PRESENTATION

10/12/2016 FLOOD RISK ANALYSIS BY HYDROLOGIC ROUTING AND HYDRAULIC MODELLING: A COMPARATIVE STUDY 3

Introduction- Project location

- Overview of probable maximum flood (PMF)

- Scope of study

Determination of PMF hydrographs- At Dulhasti HEP

- At Drangdhuran HEP

Hydrologic routing- Muskingum’s method

- Routing parameters

- Routing co-efficients

Hydraulic modelling- Model setup

• River geometry, calibration, initial condition and boundary conditions

Chapter 5Results- Muskingum’s method

- Hydraulic modelling

- Comparative study

Chapter 6Conclusions

OUTLINES OF THE PRESENTATION


Introduction

10/12/2016 DAM BREAK MODELLING OF PHOUPHONG DAM, LAO PDR AND FLOOD INUNDATION MAPPING OF POST DAM BREAK SCENARIO 5

PROJECT LOCATION


PROJECT LOCATION


Particulars Name/Coordinates

Country India

Stream/River Chenab River

Latitude 33° 10' 43”N

Longitude 75° 48' 26”E

CATCHMENT AREA


Ratle catchment area =14209 Sq Km

Hydro-meteorological approach

PMP (Source: Indian Meteorological Department (IMD)

— Estimated PMF at Ratle > PMF of Baglihar, which is located on the downstream; Unrealistic.

PMP of Baglihar

— Estimated PMF at Ratle = 11100 m3/s; Unconcluded.

— To be validated; How??!

PMFs of upstream HEPs to be routed between upstream HEPs and Ratle.

For accuracy, both hydrologic routing and hydraulic modelling are to be compared.

OVERVIEW OF PROBABLE MAXIMUM PRECIPITATION (PMP) AND PROBABLE MAXIMUM FLOOD (PMF) VALUES AT RATLE


PMF hydrographs determination of upstream projects, Dulhasti HEP and Drangdhuran HEP;

hydrologic flood routing by Muskingum method;

hydraulic modelling of river reaches initiating at the locations of Dulhasti HEP and Drangdhuran

HEPs through Ratle on the downstream with an objective to find out the outflow at Ratle Dam site;

and

comparative study.

SCOPE OF STUDY


Determination of PMF hydrographs


Catchment delineations

Dulhasti Catchment:

Hydro-meteorological,

Snyder’s unit hydrograph

Drangdhuran Catchment:

Hydro-meteorological,

Snyder’s unit hydrograph

Approaches for PMF estimation

Unit hydrograph: Dulhasti HEP

Unit hydrograph: Drangdhuran HEP

APPROACHES


0

50

100

150

200

250

300

350

0 10 20 30 40 50 60D

isch

arg

e (m

3/s

/cm

)

Time (Hrs)

Unit Hydrograph by Snyder's Method: Dulhasti HEP

Actual Ordinates

Adjusted Ordinates

0

50

100

150

200

250

300

0 5 10 15 20 25 30 35

Dis

ch

arg

e (m

3/s

/cm

)

Time (Hrs)

Unit Hydrograph by Snyder's Method:Drangdhuran HEP

Actual OrdinatesAdjusted Ordinates

DERIVED PMF HYDROGRAPHS


0

1000

2000

3000

4000

5000

6000

7000

8000

9000

0 10 20 30 40 50 60 70 80 90 100

Dis

ch

arg

e [m

3/s

]

Time [hour]

PMF Hydrpgraph : Dulhasti HEP

Flood (m3/s)

0

1000

2000

3000

4000

5000

0 10 20 30 40 50 60 70 80

Dis

ch

arg

e [m

3/s

]

Time [hour]

PMF Hydrograph : Drangdhuran HEP

Flood (m3/s)

PMF hydrograph: Dulhasti HEP PMF hydrograph: Drangdhuran HEP

Hydrologic routing


Routing

Parameters

Value Unit Remarks

x 0.2 -- weighing factor;

0<x<0.5

K 1.0 hour travel time of flood

wave between

channel reach

Δt 1.0 hour duration

MUSKINGUM ROUTING PARAMETERS


Routing

Co-efficients

Equation Value of

Co-

efficients

Remarks

C0 C0={(Δt/K)-2x}/{2(1-x)+(Δt/K)} 0.231

C0+C1+C2 =1; OkayC1 C1={(Δt/K)+2x}/{2(1-x)+(Δt/K)} 0.538

C2 C2={2(1-x)-(Δt/K)}/{2(1-x)+(Δt/K)} 0.231

MUSKINGUM ROUTING CO-EFFICIENTS


Arrange the flood ordinates of both the stations,

Dulhasti and Drangdhuran in the order of time;

Start time = 0 hr;

For a corresponding duration, sum up the flood

ordinates of both Dulhasti and Drangdhuran to

from a combined hydrograph as inflow; and

Apply Muskingum method to route the combined

hydrograph as inflow to obtain outflow

hydrograph at Ratle on the downstream.

HYDROLOGIC ROUTING STEPS


Dulhasti HEPDR

AN

GD

HU

RA

N

HE

P

Ratle HEP

Marusudar River

Che

na

b R

ive

r

Ray diagram of river network system

Hydraulic modelling


Conservation of mass (continuity):

...(1)

Conservation of momentum equation:

...(2)

MODELLING THEORYPhysical laws governing the flow of water


01

q

x

Q

t

A

0

fS

x

zgA

x

QV

t

Q

where,

The software, HEC-RAS is designed to perform

one-dimensional hydraulic computations

numerically for a full network of natural and

constructed channels.

The HEC-RAS model comprises two major

components; steady flow and unsteady flow.

HEC-RAS software can model inline structures,

such as dams, weirs, spillways, and structures

with sluice gates, radial gates, and overflow

gates.

MODELLIING SOFTWAREHEC-RAS


MODELLING SCHEME


RIVER GEOMETRYCross-sections of Phouphong River and Bangliang Rivers


Chainage of River

Cross-sections (m)

River Remarks

0.00 to 10400.00 Chenab Cross-sections interval 100m. Cross-sections

interval 100m.

10400.00 to 24700.00 Chenab Cross-sections interval 100m. Confluence at Ch

10500.00 m

0.00 to 29000.00 Marusudar Cross-sections interval 100m. Confluence

at Ch 29000.00 m

The available historical inflow data at Dulhasti, Drangdhuran, and Premnagar (Gauge and discharge

station located on the downstream of Ratle) have been utilized to calibrate the model. The

roughness parameter (Manning’s n) has been found to be sensitive in the model and therefore, with

a number of iterations, the optimum value n = 0.04 has been observed to exhibit less errors while

comparing the modeled outflow hydrograph and the observed hydrograph at Premnagar.

Manning’s n =0.04 has been applied globally in the model.

CALIBRATION


Dulhasti and Drangdhuran HEPs being in the proximity, the PMF events at these catchments are

simultaneous.

ASSUMPTIONS


Station ID Station

name

Initial

condition

Upstream

boundary

condition

Downstream

boundary

condition

XS ID – 72 Dulhasti Base flow PMF

hydrograph

-

XS ID – 6.7 Drangdhuran Base flow PMF

hydrograph

-

XS ID – 1 Ratle - - Normal depth

INITIAL AND BOUNDARY CONDITIONS


Results


HYDROLOGIC ROUTING RESULTS


2000

4000

6000

8000

10000

12000

0 2 4 6 8 101214161820222426283032343638404244464850525456586062646668707274767880828486889092949698100

Dis

ch

arg

e (m

3/s

)

Duration (hours)

Muskingum Hydrologic Routing

Combined Inflow from Drangdhuran and

Dulhasti

Outflow at Ratle

HYDROLOGIC ROUTING RESULTS


1200 2400 1200 2400 1200 2400 120019Sep2011 20Sep2011 21Sep2011 22Sep2011

0

2000

4000

6000

8000

10000

12000

Time

FL

OW

(M

3/S

)

Legend

1

72

6.7

Ratle

Dulhasti

Drangdhuran

The outflow peak flood from the method of Muskingum routing is 10562 m3/s, whereas from

hydraulic modelling; the outflow peak flood is 10589 m3/s.

The results indicate that models have least difference in terms of peak flow magnitude validating

the methods to be appropriate and good measures to check if the results are consistent.

The roots of the PMF hydrographs are same for both the tested methods.

For project planning, the study also exhibits the performance of the models developed.

COMPARATIVE STUDY


The intent of the paper is to describe the methods, hydrologic routing and hydraulic modelling, as an

important part of study in order to establish consistency in the project flood estimation.

The comparison of both the methods is as equally important as the estimation of flood itself. The

hydrologic routing exercise only includes the fluvial storage losses and gain processes, whereas the

hydraulic modelling takes all possible losses, such as friction loss, head loss et al into

considerations. Therefore, one method may be graded better than the other. However, both the

methods, in principle, are assumptions based. The important is to evaluate the assumptions based

on comparative judgments so that the qualities of results remain not negotiable. The results from the

applied models validate the same.

In the project planning of the study, due to availability of peak flood data in the vicinity of the project

site it has been possible to apply other methods and to do numerous comparisons additionally.

However, the availability of data is often scarce. Therefore, in such scenarios, the best possible

comparisons may be made from the methods discussed in this paper. The extent of application may

be wide and it blossoms the possibility of future research.

CONCLUSIONS



QUESTIONS


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