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Saqib Ehsan, M. Sc. Universität Stuttgart Institut für Wasserbau Lehrstuhl für Wasserbau und Wassermengenwirtschaft Prof. Dr.-Ing. Silke Wieprecht Risk.

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Presentation on theme: "Saqib Ehsan, M. Sc. Universität Stuttgart Institut für Wasserbau Lehrstuhl für Wasserbau und Wassermengenwirtschaft Prof. Dr.-Ing. Silke Wieprecht Risk."— Presentation transcript:

1 Saqib Ehsan, M. Sc. Universität Stuttgart Institut für Wasserbau Lehrstuhl für Wasserbau und Wassermengenwirtschaft Prof. Dr.-Ing. Silke Wieprecht Risk and Planet Earth Conference 2009, Leipzig Estimation of possible damages due to catastrophic flooding for long-term disaster mitigation planning

2 Risk and Planet Earth Conference, Panel 2 for Junior Scientists, 4 th March 2009, Leipzig 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

3 Risk and Planet Earth Conference, Panel 2 for Junior Scientists, 4 th March 2009, Leipzig 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

4 Risk and Planet Earth Conference, Panel 2 for Junior Scientists, 4 th March 2009, Leipzig Introduction cont‘d

5 Risk and Planet Earth Conference, Panel 2 for Junior Scientists, 4 th March 2009, Leipzig 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)

6 Risk and Planet Earth Conference, Panel 2 for Junior Scientists, 4 th March 2009, Leipzig Introduction cont‘d Gross storage (original)7.25 E+9 m 3 Net storage (original)6.59 E+9 m 3 Catchment area of reservoir (original)33,360 km 2 Water surface area of reservoir (original) (at maximum conservation level) 253 km 2 Power generation1,000 MW Crest length of main dam2,561 m Design capacity of main spillway28,583 m 3 /s Design capacity of emergency spillway6,452 m 3 /s

7 Risk and Planet Earth Conference, Panel 2 for Junior Scientists, 4 th March 2009, Leipzig 1D-Hydrodynamic modeling with MIKE 11 Chenab River Upstream Trimmu Barrrage Jhelum Bridges Rasul Barrage Malikwal Bridge Khushab Bridge Confluence Point Suketar Nallah Bandar Kas Jabba Kas Kahan River Mangla dam Bunha River -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

8 Risk and Planet Earth Conference, Panel 2 for Junior Scientists, 4 th March 2009, Leipzig 1D-Hydrodynamic modeling with MIKE 11 cont‘d

9 Risk and Planet Earth Conference, Panel 2 for Junior Scientists, 4 th March 2009, Leipzig 1D-Hydrodynamic modeling with MIKE 11 cont‘d Rasul Barrage

10 Risk and Planet Earth Conference, Panel 2 for Junior Scientists, 4 th March 2009, Leipzig 1D-Hydrodynamic Modeling with MIKE 11 cont’d

11 Risk and Planet Earth Conference, Panel 2 for Junior Scientists, 4 th March 2009, Leipzig Rasul Barrage 1D-Hydrodynamic Modeling with MIKE 11 cont’d

12 Risk and Planet Earth Conference, Panel 2 for Junior Scientists, 4 th March 2009, Leipzig Development an improved LOL estimation method LOL i = PAR i x FAT BASE x F sv x F age x F mt x F st x F h x F war x F ev LOL i = loss of life at a particular location ´´i`` downstream of the dam PAR i = Population at risk at a particular location ´´i`` downstream of the dam FAT BASE = 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.

13 Risk and Planet Earth Conference, Panel 2 for Junior Scientists, 4 th March 2009, Leipzig F sv = Flood Severity factor High Severity very likely 1.0 Medium Severity unlikely 0.3 Low Severity very unlikely 0.1 F age = Age risk factor A ( =65yrs)),B (10-15)yrs and C (15-64)yrs F age = 1.25 *A% +1.1* B%+ 0.8* C% (general form) F mt = Material risk factor F mt = 1 * X % * Y % (general form) Where, X= % of other type of houses, Y= % very low strength houses Development an improved LOL estimation method

14 Risk and Planet Earth Conference, Panel 2 for Junior Scientists, 4 th March 2009, Leipzig F st = Storey risk factor F st = 1 (for high severity and all house types) F st = 1- S % (for medium and low severity) Where, S= % of more storey houses F h = Health risk factor; 3% disabled people F h = 1 *H % *D % (general form) Where, H= % of PAR with avg. health, D= % of disabled PAR Development an improved LOL estimation method

15 Risk and Planet Earth Conference, Panel 2 for Junior Scientists, 4 th March 2009, Leipzig F war = Warning factor (Graham,1999) Warning Flood Severity understanding F war No No 1 Some (15-60min) Vague/unclear 0.7 Adequate (>60min) Precise/clear 0.3 F ev = Ease of evacuation factor Warning Ease of evacuation F ev No No 1 Some (15-60min) Some 0.7 Adequate(>60min) Good 0.3 Development an improved LOL estimation method

16 Risk and Planet Earth Conference, Panel 2 for Junior Scientists, 4 th March 2009, Leipzig Loss of Life estimation Estimated PAR is related to the highest flood event in the past

17 Risk and Planet Earth Conference, Panel 2 for Junior Scientists, 4 th March 2009, Leipzig Loss of Life estimation

18 Risk and Planet Earth Conference, Panel 2 for Junior Scientists, 4 th March 2009, Leipzig Loss of Life estimation

19 Risk and Planet Earth Conference, Panel 2 for Junior Scientists, 4 th March 2009, Leipzig Loss of Life estimation

20 Risk and Planet Earth Conference, Panel 2 for Junior Scientists, 4 th March 2009, Leipzig 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

21 Risk and Planet Earth Conference, Panel 2 for Junior Scientists, 4 th March 2009, Leipzig 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

22 Risk and Planet Earth Conference, Panel 2 for Junior Scientists, 4 th March 2009, Leipzig THANKS FOR YOUR ATTENTION QUESTIONS?? Lehrstuhl für Wasserbau und Wassermengenwirtschaft Institut für Wasserbau, Universität Stuttgart


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