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Estimation of possible damages due to catastrophic flooding for long-term disaster mitigation planning. Contents. Introduction - 1D-Hydrodynamic modeling with MIKE 11 Development of an improved method for loss of life ( LOL ) estimation

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Estimation of possible damages due to catastrophic flooding for long-term disaster mitigation planning

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Estimation of possible damages due to catastrophic flooding for long term disaster mitigation planning

Estimation of possible damages due to catastrophic flooding for long-term disaster mitigation planning


Contents

Contents

  • Introduction

    - 1D-Hydrodynamic modeling with MIKE 11

  • Development of an improved method for loss of

    life (LOL) estimation

  • Loss of life (LOL) estimation for different scenarios

  • Conclusions and Suggestions


Introduction

Introduction

  • Role of climate change in disaster management

  • Possible extreme changes in climate as guidelines for the development of new concepts for disaster mitigation

  • Drastic weather change

  • Heavy rainfall

  • Catastrophic flooding downstream of the dam

  • Risk to people and property


Introduction cont d

Introduction cont‘d


Introduction cont d1

Introduction cont‘d

  • Jhelum river valley downstream of Mangla dam in Pakistan

  • One of largest earth and rock-fill dams in world

  • Main dam height ~125 m high above riverbed

(by Google earth)


Introduction cont d2

Introduction cont‘d


Estimation of possible damages due to catastrophic flooding for long term disaster mitigation planning

1D-Hydrodynamic modeling with MIKE 11

Jhelum Bridges

Mangla dam

Kahan River

Suketar Nallah

Bandar Kas

Rasul Barrage

Bunha River

Jabba Kas

Malikwal Bridge

  • Project Reach: about 329km

  • Different Hydraulic

  • structures

  • Five tributaries between

  • Mangla and Rasul Barrage;

  • No gauges are existing there

  • 1D-modeling for unsteady

  • flow conditions

Khushab Bridge

Chenab River

Confluence Point

Upstream Trimmu Barrrage


Estimation of possible damages due to catastrophic flooding for long term disaster mitigation planning

1D-Hydrodynamic modeling with MIKE 11cont‘d


Estimation of possible damages due to catastrophic flooding for long term disaster mitigation planning

1D-Hydrodynamic modeling with MIKE 11cont‘d

Rasul Barrage


Estimation of possible damages due to catastrophic flooding for long term disaster mitigation planning

1D-Hydrodynamic Modeling with MIKE 11cont’d


Estimation of possible damages due to catastrophic flooding for long term disaster mitigation planning

1D-Hydrodynamic Modeling with MIKE 11cont’d

Rasul Barrage


Development an improved lol estimation method

Development an improved LOL estimation method

LOLi = PARi x FATBASE x Fsv x Fage x Fmt x Fst x Fh x Fwar x Fev

LOLi = loss of life at a particular location ´´i`` downstream

of the dam

PARi = Population at risk at a particular location ´´i``

downstream of the dam

FATBASE = Base Fatality rate of 0.15 (worst case of medium severity) (Graham, 1999), assuming an average value of 1.0 for all other factors with average conditions.


Development an improved lol estimation method1

Development an improved LOL estimation method

Fsv= Flood Severity factor

High Severity very likely 1.0

Medium Severity unlikely 0.3

Low Severity very unlikely 0.1

Fage = Age risk factor

A (<10yrs+ (>=65yrs)),B (10-15)yrs and C (15-64)yrs

Fage = 1.25 *A% +1.1* B%+ 0.8* C% (general form)

Fmt = Material risk factor

Fmt = 1 * X % + 1.5 * Y % (general form)

Where, X= % of other type of houses, Y= % very low strength houses


Development an improved lol estimation method2

Development an improved LOL estimation method

Fst = Storey risk factor

Fst = 1 (for high severity and all house types)

Fst = 1- S % (for medium and low severity)

Where, S= % of more storey houses

Fh = Health risk factor; 3% disabled people

Fh = 1 *H % + 1.25*D % (general form)

Where, H= % of PAR with avg. health, D= % of disabled PAR


Development an improved lol estimation method3

Development an improved LOL estimation method

Fwar = Warning factor (Graham,1999)

Warning Flood Severity understanding Fwar

No No 1

Some (15-60min) Vague/unclear 0.7

Adequate (>60min) Precise/clear 0.3

Fev= Ease of evacuation factor

Warning Ease of evacuation Fev

No No 1

Some (15-60min) Some 0.7

Adequate(>60min) Good 0.3


Loss of life estimation

Loss of Life estimation

Estimated PAR is related to the highest flood event in the past


Loss of life estimation1

Loss of Life estimation


Estimation of possible damages due to catastrophic flooding for long term disaster mitigation planning

Loss of Life estimation


Estimation of possible damages due to catastrophic flooding for long term disaster mitigation planning

Loss of Life estimation


Estimation of possible damages due to catastrophic flooding for long term disaster mitigation planning

Conclusions and Suggestions

  • Severe climate change can cause extreme flooding downstream of a

  • dam

  • Estimation of possible damages is an important part of any dam

  • safety study

  • - Loss of life increases with the delay in warning initiation with respect

  • to dam failure

  • For all dam failure cases, maximum LOL (~80%) occurs in first

  • 50 km downstream of Mangla dam

  • % total LOL for the worst case of Mangla dam failure is close to 4%

  • which seems to be very high


Estimation of possible damages due to catastrophic flooding for long term disaster mitigation planning

Conclusions and Suggestions

  • - LOL results clearly show the need of improvement in existing risk

  • Reduction measures in order to reduce possible LOL due to Mangla

  • dam failure

  • More research is required to estimate

  • - ease of evacuation

  • - risks posed by age groups

  • - very low strength houses and more storey houses

  • - Realistic estimation of possible LOL due to natural hazards like

  • floods helps in long-term disaster mitigation planning


Estimation of possible damages due to catastrophic flooding for long term disaster mitigation planning

THANKS FOR YOUR ATTENTION

QUESTIONS??

[email protected]

www.iws.uni-stuttgart.de

Lehrstuhl für Wasserbau und Wassermengenwirtschaft

Institut für Wasserbau, Universität Stuttgart


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