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MSc Research(Interim) Presentation

INFLUENCE OF GEO-MORPHOLOGICAL

CHANGES IN WATER DEPTH DURING FLOODEVENTS: A CASE STUDY IN A LARGE

ALLUVIAL RIVER

ParticipantMd Shamim Shams

WSE, HI

Supervisors

Prof Dr.. R.K. Price

Emeritus Professor of Hydroinformatics, (UNESCO-IHE)

Dr. I. PopescuSenior Lecturer in Hydroinformatics (UNESCO-IHE)

Dr. B. Bhattacharya

Senior Lecturer in Hydroinformatics (UNESCO-IHE)


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ACKNOWLEDGEMENT

I deeply express my gratitude to the authority of TheNetherlands Fellowship Programmes (NFP) which is fundedby the Dutch Ministry of Foreign Affairs under the budget for

development cooperation for funding my MSc. Program inWater Science and Engineering (Specialization inHydroinformatics) at UNESCO-IHE.


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PROBLEMS STATEMENT

The problems associated with this research topic are the followings-In alluvial river during flood events neglecting changing bed-forms as well as riverbed roughness create improper water level prediction in numerical model.

Due to the first stated problem produced flood risk maps may not fully supportive fora particular area for flood risk assessment.


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Research Questions

How to properly identify the dune evolution during a floodevents?

How much effect on bed roughness due to dune evolution andhow to incorporate this phenomena into built up numericalmodel?


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Research Objective

General Objective

The objective of this research work is to develop/upgradenumerical model which include-

Presence of change of dune geometry and bed roughnesscondition in large alluvial rivers during flood events.

What is the consequence to flood risk assessment due to

the water level changes due change of dunes geometryfrom model output.


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Secondary Objective

Marking the highest flood level for a particular case study area consideringchange of water level. This information can be used for construction offlood protection structures in particular case study area in future.


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Literature Works

The main objective is to include literature review is to find out whatis previous researchers or sedimentologists work on identifying dune

height ( ) and dune length ( ) and associated roughness during flood

events.

For dune height ( ) and dune length ( )

- Julien-Klasseen expression

- Van Rijn expression

For dune evolution

-

Shimizu and Giri expression (2006)

-Andries Paarlberg expression (2008)

For roughness evolution

-Colebrook-White expression (1984)


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Used/Fit for purpose ResearchExpressions

Calculation of dune geometry during flood events

Method described by Pierre, Julien and Klaassen, 1996

Average dune height will be calculated by dividing number of dunes n over the total

length of reach.

Average dune length will be calculated from the reach length over the number ofdunes.

By plotting like above graph with respect to T (transport-stage parameter where,T=R/d50) bed form dunes height and steepness can be predict.


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For dune height ( ) and dune length ( )

- Julien-Klasseen expression (1996)

- Van Rijn expression (1984)

= h(d50/h)0.3

where is dune height coefficient and value are within 0.8 < < 8 ;

the average value = 2.5.

For the dune length

= (h/d50)0.3

where is dune length coefficient and value are within 0.5 < < 8;

the average value 2.5.


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For Dune evolution

-Shimizu and Giri expression (2006)

-Andries Paarlberg expression (2008)

For Roughness evolution

-Colebrook-White expression (1984)

Cm = 18 log(12hm/km)where Cm is the Chezy coefficient

Which is based on Van Rijn (1983, 1984) roughness equations

km = kgrains + kdunes

kdunes = 1.1 [1-exp(-25/ )]


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Flow chart of the research methodology

Discharge, Boundary condition, Bank line data, Bathymetric data, sedimentdata, grain size analysis data will be input as Initial condition and systemproperties of numerical model

1-D numerical model

Dune evolution model to calculate dune height ( ) and

dune length ( )

Dune roughness modelling

Calibration and validation of water level with respect to actual flood event

Geomorphological character will define for flood of a particular river


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General 1D numerical model

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Changes of bed level showing in normal1D numerical model

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Changes of bed level showing in normal1D numerical model

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Dune Evolution model

15Where H (average height of thewater column), h(x) (bottomdisturbance) and (x;t) (surface

elevation


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Dune Evolution model


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Case Study Area

The Nzoia river in Western Kenya. Thecatchment area lies between latitudes1.5 N and 0.5 Sand longitudes 34 and35.75 E. It is one of the major riversflowing to the Lake Victoria.

It is one of the major rivers in Nile basincontributing large amount of sharedwater to the LakeVictoria .

The total length of the longest reachwhere river meets Lake Victoria is 334

km.

The Nzoia river basin is divided in tothree sub-catchments . They are, LowerNzoia (1303.28 km2), Middle Nzoia(3129.36 km2) and Upper Nzoia

(8244.98 km2)


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Expected Output

The result of water level will validate with actual flood event waterlevel and observe

The percentage of change of the height of flood water level due toconsideration of dunes height and altered bed roughness co-efficient.

Differences in the stage-discharge relationships between thedunes heights.


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Thanks


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Questions?

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