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Kingdom of Morocco   Natural Disaster Risk  Management in Morocco          For an integrated approachMohamed Tabyaoui Tech...
Morocco
Decision making needs figures Earthquakes cost Morocco an average of  85 M$ per year The North region are the most expos...
Decision making needs figures Annual losses caused by floods are 5 times  more important than those caused by  earthquake...
Source   All these figures are calculated and    scenarios generated by Moroccan national    hazard Probabilistic Risk As...
The story behind
Risk management analysis find-out Post crisis oriented Ex post financing Coordination needed among sectoral  strategies...
New strategy:Triggers Recent events 2004 earthquake in the  North of Morocco Recurrent floods and drought Recurrent pri...
The needs   Develop Global and integrated strategy   Coordinate all sectoral risk policies   Cause change in paradigm: ...
The 3 pillars of our strategy 1-price volatility 2-Natural hazards 3-Risks in Agriculture
Natural Hazards strategy Assessment and risk modeling in Morocco What if scenarios Sectorial Strategies elaboration Na...
Assessment: perimeter   5 major risks       Floods       Earthquakes       Tsunamis       Land slides       Drought
Risk Modeling                5. Estimate                Losses                4. Compute Damage                3. Define a...
Assessment: Method Probabilistic model Economic model after a choc situation Assessment of risk perception into  commun...
Deployment/make it durable    Official Institution for coordination    Information system    Financial instruments
Task force World Bank: coordination +International  Experts hiring +project TOR + project  supervising Swiss cooperation...
Assessment: Project phases Hazard Modeling Vulnerability/ potential impacts What if scenarios cost/benefit analysis
Assessment objectives   calculate with enough precision the level    of exposure of infrastructure, population       Cal...
Data types3 data types :- Scientific data Sesmic data, Meteorology   Hydrology MOU-   infrastructure data   Industria...
Major partners   Urbanism   Education   Agriculture   Finance   Equipment       Rail roads       Airports       Da...
Data collection: The success factors Participative approach scientific quality of the work Respond to specific needs I...
Assessment outputs Risk maps Risk modeling and simulations Impacts/potential losses Economic modeling assuming a chock...
What’s next Sectoral strategies: National strategy: aggregation of Sectoral  Strategies National institutions for coord...
Financial instrument Annual Budgets National Fund for Natural Catastrophes Insurances       Insurance to cover Natural...
value added Readness and resilience for Morocco  (infrastructure and population) Better cooperation at regional and  int...
In reel !
Risk Modling
Earthquake Catalogue              Compiled Catalogue Only large historical events prior  to 1901 are considered from Pelá...
Stochastic EventsEarthquake event never apoint sourceConsidered a line sourceArea sources aresubdivided into Area-linesour...
Sebou Basin: Hydraulic Model                               #30
Stochastically simulated flows                                 #31
Data used in Numerical ModelGeneral Bathymetry Chart of Oceans (GEBCO): resolution (1 min)          GRID A                ...
1st November 1755 Lisbon Tsunami – Contd.,Extreme water surface elevations after 3hrs of simulation Gorringe Bank         ...
LEC/AAC
1    Definitions: LEC and AAL                                      Kingdom of Morocco                                 GDP ...
Average Annual Loss (AAL)  Loss (MAD)                    AAL = ‘pure premium’                               Insurance prem...
MnhPRA: Moroccan National Hazards Probabilistic RiskAssessment Models were incorporated in SIG software Extensible adap...
MnhPRA – Hazard data aggregation – Contd   .,                                                # 38
MnhPRA – Hazard data aggregation                                   # 39
Earthquake losses                              Country Level Losses Million                              MAD        Return...
Flood losses
Flood losses                    Country Level Losses Million MAD                                              Return Perio...
Tsunami lossesCountry Level Losses Million MAD                                   #43
Tsunami losses                                           Return Period                  Average AnnualOccupancy           ...
Inondations: pertes potentielles parcategories d’infrastructure                                                           ...
Tremblement de terre: pertespotentielles par categoriesd’infrastructure Exposure       Estimated Estimated Exposure       ...
Tsunami: pertes potentielles parcategories d’infrastructure                                AAL    Exposure      Estimated ...
Mitigation Planning Strategies   Options that reduce hazard                                                              ...
CostDecision-making               (MAD)            CT = Total Cost            = CD + CI                         CI = Inves...
losses         #50
#51
Tsunami Warning and Evacuation                                 #52
What-if ’s : 47 cases examined (so far)                                     #53
What-if ’s what   where   protected   rebuild   optimum    Cost     2013   2014 ~   201?                                  ...
MnhPRA – Morocco natural hazard Probabilistic Risk Assessment Software   FOSS (Free Open Source Software) Delivered to M...
MnhPRA – Morocco natural hazard Probabilistic Risk Assessment Software   Built using Open Source platforms        Quantu...
editing capabilities Available Damage functions       Structure – 29 type       Site specific – 15 type       Occupancy – ...
National Disaster Risk Management and Financing StrategyMitigation Alternatives – “what if” scenarios•“what if” I put in a...
Thank you
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Risk Management of Natural Disasters in Morocco: a project of Global and Integrated Strategy

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Tabyaoui MOHAMED

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Risk Management of Natural Disasters in Morocco: a project of Global and Integrated Strategy

  1. 1. Kingdom of Morocco Natural Disaster Risk Management in Morocco For an integrated approachMohamed Tabyaoui Technical Adviserto The Chief of Government Davos 28 -08- 2012
  2. 2. Morocco
  3. 3. Decision making needs figures Earthquakes cost Morocco an average of 85 M$ per year The North region are the most exposed The probability for an earthquake to cause a loss of 1.5 b $ is 25% on the coming 30 years
  4. 4. Decision making needs figures Annual losses caused by floods are 5 times more important than those caused by earthquakes. Annual losses caused by flood are around 0.44 b $ per year A tsunami similar to the one occurred in the 1755 will produce a wave high as 8 m and will sink the whole Casablanca port
  5. 5. Source All these figures are calculated and scenarios generated by Moroccan national hazard Probabilistic Risk Assessment (MnhPRA) a GIS software elaborated recently within the process of settling our new approach to tackle natural hazards risk management in Morocco
  6. 6. The story behind
  7. 7. Risk management analysis find-out Post crisis oriented Ex post financing Coordination needed among sectoral strategies Program overlapping Many actors but at different speed law text need updating ….etc
  8. 8. New strategy:Triggers Recent events 2004 earthquake in the North of Morocco Recurrent floods and drought Recurrent price volatility International organisations (sensitizing; technical support (WB, GFDR/UNISDR) awareness increasing among top management
  9. 9. The needs Develop Global and integrated strategy Coordinate all sectoral risk policies Cause change in paradigm: prevention and resilience first
  10. 10. The 3 pillars of our strategy 1-price volatility 2-Natural hazards 3-Risks in Agriculture
  11. 11. Natural Hazards strategy Assessment and risk modeling in Morocco What if scenarios Sectorial Strategies elaboration National strategy
  12. 12. Assessment: perimeter 5 major risks  Floods  Earthquakes  Tsunamis  Land slides  Drought
  13. 13. Risk Modeling 5. Estimate Losses 4. Compute Damage 3. Define and Overlay Inventory 2. Characterize Hazard 1. Identify Study Region #13
  14. 14. Assessment: Method Probabilistic model Economic model after a choc situation Assessment of risk perception into communities
  15. 15. Deployment/make it durable  Official Institution for coordination  Information system  Financial instruments
  16. 16. Task force World Bank: coordination +International Experts hiring +project TOR + project supervising Swiss cooperation +GFDRR : Funds Consulting firm : Modeling and risk assessment MAGG: focal point, Coordination and follow up Departments: data, capacity building, deployment of sectoral strategies
  17. 17. Assessment: Project phases Hazard Modeling Vulnerability/ potential impacts What if scenarios cost/benefit analysis
  18. 18. Assessment objectives calculate with enough precision the level of exposure of infrastructure, population  Calculate cost (average annual loss , Loss Exceedance Curve (LEC))  casualities  Cost benefit ananlysis of mitigation mesures
  19. 19. Data types3 data types :- Scientific data Sesmic data, Meteorology Hydrology MOU- infrastructure data Industrial zones, ports, airports, rail roads, bridges and road network, drinkable water canalisation, electrical network, housing, schools, mosks, sport facilities …etc.- Data about population Age, sexe, Social situation
  20. 20. Major partners Urbanism Education Agriculture Finance Equipment  Rail roads  Airports  Dams  Roads  ports Health Weather Forcast water, Remote sensing, Scientific community and university lnsurance …
  21. 21. Data collection: The success factors Participative approach scientific quality of the work Respond to specific needs Involvement of politics
  22. 22. Assessment outputs Risk maps Risk modeling and simulations Impacts/potential losses Economic modeling assuming a chock What if scenarios Cost benefit analysis
  23. 23. What’s next Sectoral strategies: National strategy: aggregation of Sectoral Strategies National institutions for coordination  National Bureau  National Platform for Risk Management Information system Law texts Finance:
  24. 24. Financial instrument Annual Budgets National Fund for Natural Catastrophes Insurances  Insurance to cover Natural catastrophes  Insurance to cover extrem events in Agriculture
  25. 25. value added Readness and resilience for Morocco (infrastructure and population) Better cooperation at regional and international level Competitive advantage to attract investments in Morocco
  26. 26. In reel !
  27. 27. Risk Modling
  28. 28. Earthquake Catalogue Compiled Catalogue Only large historical events prior to 1901 are considered from Peláez et al (2007). Events from 1901 to 1984 have been compiled from the book “Fichier des seismes du Maroc et des regions limitrophes 1901-1984 by T.E. Cherkaoui 1988. Events from 1984 to 1990 have been compiled from updated additional records from Cherkaoui T.E. (personal communication) From 1990 to March 2010, event data has been received from CNRST March 2010 to March 2011 data has been received from ANSS #28
  29. 29. Stochastic EventsEarthquake event never apoint sourceConsidered a line sourceArea sources aresubdivided into Area-linesourcesNum of Seismic Sources - 22Num of Stochastic Faults -1,735Num of Stochastic Events -14,670 #29
  30. 30. Sebou Basin: Hydraulic Model #30
  31. 31. Stochastically simulated flows #31
  32. 32. Data used in Numerical ModelGeneral Bathymetry Chart of Oceans (GEBCO): resolution (1 min) GRID A GRID B GRID C GRID D High resolution bathymetry from remote sensing departm ent and topography from SRT M #32
  33. 33. 1st November 1755 Lisbon Tsunami – Contd.,Extreme water surface elevations after 3hrs of simulation Gorringe Bank MPTF/GB source source (Baptista et (Johnson , al., 2003) 1996) Cardiz N160 source subduction (Baptista et source al., 1998) (Gutscher et al., 2002; Gutscher , 2004) #33
  34. 34. LEC/AAC
  35. 35. 1 Definitions: LEC and AAL Kingdom of Morocco GDP MAD 1,300 billion (2011 est.) Probability of Loss Budget: Expenditure: MAD 250 billion being Exceeded (per year) Loss Exceedance Curve (LEC)0 Loss (MAD) Average Annual Loss (AAL) (~ center of gravity) #35
  36. 36. Average Annual Loss (AAL) Loss (MAD) AAL = ‘pure premium’ Insurance premium = pure prem. + overhead + profit Average Annual Loss (AAL) time “ stochastic ” ~ random occurrence #36
  37. 37. MnhPRA: Moroccan National Hazards Probabilistic RiskAssessment Models were incorporated in SIG software Extensible adaptable free of charges (open source)
  38. 38. MnhPRA – Hazard data aggregation – Contd ., # 38
  39. 39. MnhPRA – Hazard data aggregation # 39
  40. 40. Earthquake losses Country Level Losses Million MAD Return PeriodOccupancy Average Annual Loss 20 50 100 500 1,000Residential 506.5 2,849 5,516 8,926 17,680 22,677Commercial 144.4 626 1,248 3,467 8,021 10,061Industrial 34.9 193 409 1,066 2,289 2,871E.Facilities 96.9 549 1,862 1,128 1,855 2,524Infrastructures 64.2 385 623 810 4,939 6,350Total All Exposures 846.8 4,602 9,658 15,397 34,784 44,482 #40
  41. 41. Flood losses
  42. 42. Flood losses Country Level Losses Million MAD Return Period Average Annual Occupancy Loss 20 50 100 500 1,000 Residential 1,895 9,399 11,232 12,092 13,065 14,718 Commercial 434 1,965 2,342 2,530 2,708 3,006 Industrial 471 2,072 2,242 2,231 2,477 2,569 Essential F 369 1,913 2,214 2,351 2,497 2,751Infrastructures 1,210 3,152 3,323 3,218 3,427 3,648 All Exposures 4,380 18,501 21,354 22,423 24,174 26,692 #42
  43. 43. Tsunami lossesCountry Level Losses Million MAD #43
  44. 44. Tsunami losses Return Period Average AnnualOccupancy Loss 20 50 100 388 1,000Residential 23 1 57 1,969 17,639Commercial 18 2 183 2,385 9,053 -Industrial 18 143 3,408 8,898Essential 2 0 4 158 1,421Infrastructures 133 1 146 23,439 60,233All Exposures 195 4 533 31,359 97,243
  45. 45. Inondations: pertes potentielles parcategories d’infrastructure Loss Cost Exposure type Estimated Estimated Exposure Flood AAL AAL (per mille) value (million value in Per parts (Million Contributio MAD) capita MAD) n Residential 1,126,875 34,148 47.2% 1.68 1,895 43.3% Commercial 370,877 11,239 15.6% 1.17 434 9.9% Education 139,428 4,225 5.8% 1.74 242 5.5% (Schools) 3.81 471 10.8% Industrial 123,804 3,752 5.2% 0.26 30 0.7% Electrical 116,538 3,531 4.9% 3.69 Road 105,501 3,197 4.4% 389 8.9% 3.88 Railway 73,009 2,212 3.1% 283 6.5% - Fishing craft 63,964 1,938 2.7% - 0.0% 53,956 1,635 2.3% - Ports - 0.0% Health 48,339 1,465 2.0% 0.96 46 1.1% Mosque 40,985 1,242 1.7% 1.92 79 1.8% Motor Vehicle 31464 953 1.3% 12.30 387 8.8% Airport Value 22867 693 1.0% - #45
  46. 46. Tremblement de terre: pertespotentielles par categoriesd’infrastructure Exposure Estimated Estimated Exposure EQ AAL AAL Loss Cost type value value in Per parts (Million Contribut (per (million capita MAD) ion mille) MAD)Residential 1,126,875 34,148 47.2% 506 59.7% 0.45Commercial 370,877 11,239 15.6% 144 17.0% 0.39 Education 139,428 4,225 5.8% 6.6% (Schools) 0.40 56 Industrial 123,804 3,752 5.2% 0.28 Electrical 116,538 4.9% 4.1% 3,531 0.11 Road 105,501 3,197 4.4% 35 Railway 73,009 2,212 3.1% 1.6% -Fishing craft 63,964 1,938 2.7% 13 0.00 Ports 53,956 1,635 2.3% - 0.0% 0.38 Health 48,339 1,465 2.0% 0.19 0.0% 0.40 Mosque 40,985 1,242 1.7% Motor 31464 1.3% 24.3 2.9% 0.41 953 Vehicle 21.5 2.5% 0.50 Airport 22867 693 1.0% 19.8 2.3% Value 0.01 20.6 2.4% #46 0.18
  47. 47. Tsunami: pertes potentielles parcategories d’infrastructure AAL Exposure Estimated Estimated Exposure type value value in Per parts Tsunam Contrib (million capita i AAL ution Loss Cost MAD) (Million (per mille) Residential 1,126,875 34,148 47.2% MAD) Commercial 370,877 11,239 15.6% 12.2% 0.02 Education 139,428 4,225 5.8% 23 0.05 (Schools) 9.7% 18 0.01 Industrial 123,804 3,752 5.2% Electrical 116,538 3,531 4.9% 0.6% 0.15 Road 105,501 3,197 4.4% 1 0.03 Railway 73,009 2,212 3.1% 9.6% 18 0.00 Fishing craft 63,964 1,938 2.7% Ports 53,956 1,635 2.3% 1.7% 0.01 Health 48,339 1,465 2.0% 3 0.41 Mosque 40,985 1,242 1.7% 0.1% 0 1.21 Motor 31464 953 1.3% Vehicle 0.3% 0.01 Airport 22867 693 1.0% 1 0.01 Value 13.7% 26 0.02 Agriculture* 20340 616 0.9% #47 34.5%
  48. 48. Mitigation Planning Strategies Options that reduce hazard Ê  Reduce flood peak by providing storage  Confine the hazard in predetermined area  Divert flood water to another area Options that reduce vulnerability  Seismic retrofitting of buildings Legend Roads  Earthquake proof foundations Proposed Levee Flood Extent 0 0.25 0.5 Settlements Kilometers  Increasing Ground Floor Elevation  Water level planning for reservoirs  Hazard Zoning Ê Loss Exceedance Probablity curve for households 0.6 With Mitigation Without mitigation 0.5 0.4 0.3 P E 0.2 Legend Roads Settlements 0 1 2 0.1 Kilometers 0 #48 15,000 25,000 35,000 45,000 55,000 65,000 Loss (USD) Thousands
  49. 49. CostDecision-making (MAD) CT = Total Cost = CD + CI CI = Investment CostCD= Cost ofDamage Design level (PGA) Min CT = Optimum Design level
  50. 50. losses #50
  51. 51. #51
  52. 52. Tsunami Warning and Evacuation #52
  53. 53. What-if ’s : 47 cases examined (so far) #53
  54. 54. What-if ’s what where protected rebuild optimum Cost 2013 2014 ~ 201? mns MAD 18 #54
  55. 55. MnhPRA – Morocco natural hazard Probabilistic Risk Assessment Software FOSS (Free Open Source Software) Delivered to Morocco Loss Estimation System  Hazard data aggregation  Exposure  Vulnerability  Risk Assessment – LEC, AAL # 55
  56. 56. MnhPRA – Morocco natural hazard Probabilistic Risk Assessment Software Built using Open Source platforms  Quantum GIS  PostgreSQL Secure / password protected Hazard Identification Vulnerability Assessment Risk Assessment Built Environment (Buildings Economic Impact Infrastructure Agriculture) and Reporting Engine Demographics # 56
  57. 57. editing capabilities Available Damage functions Structure – 29 type Site specific – 15 type Occupancy – 7 type and Causality S. No Occupancy Type 1 Villa 2 Apartment in a building 3 a. Traditional Moroccan house b. Modern Moroccan house 4 Informal housing (habitat sommaire) 5 Rural Type 6 Others S.No. Site Specific Exposure 1 Airport 2 Road 3 Railway 4 Motor Vehicle 5 Seaport 6 Electrical System 7 Communication System 8 Portable Water 9 Waste Water 10 Oil & Gas 11 Police Station 12 Fire Station 13 Mosque 14 Coranic school # 57
  58. 58. National Disaster Risk Management and Financing StrategyMitigation Alternatives – “what if” scenarios•“what if” I put in a flood warning system? • What are the benefits (avoided deaths, losses)? • What does it cost? • Is the cost more, or less, than the benefits? Benefits = AAL /i i = interest rate per year “what if” I… • Strengthen high risk schools for earthquake? B? C? • Build flood levees in high flood risk areas? B? C? • Put in a tsunami warning system? • With evacuation routes clearly marked with signs? • Strengthen all houses for earthquake? • Insure all houses for disasters? • …. #58
  59. 59. Thank you

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