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Kingdom of Morocco


   Natural Disaster Risk
  Management in Morocco
          For an integrated approach




Mohamed Tabyaoui Technical Adviser
to The Chief of Government           Davos 28 -08- 2012
Morocco
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
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
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
The story behind
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
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
The needs
   Develop Global and integrated strategy

   Coordinate all sectoral risk policies

   Cause change in paradigm: prevention
    and resilience first
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
 National strategy
Assessment: perimeter
   5 major risks
       Floods
       Earthquakes
       Tsunamis
       Land slides
       Drought
Risk Modeling
                5. Estimate
                Losses




                4. Compute Damage




                3. Define and
                Overlay Inventory



                2. Characterize
                Hazard



                1. Identify Study
                Region


                                    #13
Assessment: Method
 Probabilistic model
 Economic model after a choc situation
 Assessment of risk perception into
  communities
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 +GFDRR : Funds
 Consulting firm : Modeling and risk
  assessment
 MAGG: focal point, Coordination and follow
  up
 Departments: data, capacity building,
  deployment of sectoral strategies
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
       Calculate cost (average annual loss , Loss
        Exceedance Curve (LEC))
       casualities
       Cost benefit ananlysis of mitigation mesures
Data types
3 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
Major partners
   Urbanism
   Education
   Agriculture
   Finance
   Equipment
       Rail roads
       Airports
       Dams
       Roads
       ports
   Health
   Weather Forcast
   water,
   Remote sensing,
   Scientific community and university
   lnsurance …
Data collection: The success factors

 Participative approach
 scientific quality of the work
 Respond to specific needs
 Involvement of politics
Assessment outputs
 Risk maps
 Risk modeling and simulations
 Impacts/potential losses
 Economic modeling assuming a chock
 What if scenarios
 Cost benefit analysis
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:
Financial instrument
 Annual Budgets
 National Fund for Natural Catastrophes
 Insurances
       Insurance to cover Natural catastrophes
       Insurance to cover extrem events in
        Agriculture
value added
 Readness and resilience for Morocco
  (infrastructure and population)
 Better cooperation at regional and
  international level
 Competitive advantage to attract
  investments in Morocco
In reel !
Risk Modling
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
Stochastic Events

Earthquake event never a
point source


Considered a line source
Area sources are
subdivided into Area-line
sources




Num of Seismic Sources -     22
Num of Stochastic Faults -
1,735
Num of Stochastic Events -
14,670




                                  #29
Sebou Basin: Hydraulic Model




                               #30
Stochastically simulated flows




                                 #31
Data used in Numerical Model
General 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
1st November 1755 Lisbon Tsunami – Contd.,
Extreme water surface elevations after 3
hrs 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
LEC/AAC
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
Average Annual Loss (AAL)
  Loss (MAD)                    AAL = ‘pure premium’

                               Insurance premium =
                           pure prem. + overhead + profit
        Average Annual Loss (AAL)




                                          time

        “ stochastic ” ~ random occurrence
                                                 #36
MnhPRA: Moroccan National Hazards Probabilistic Risk
Assessment

 Models were incorporated in SIG software
 Extensible
 adaptable
 free of charges (open source)
MnhPRA – Hazard data aggregation – Contd   .,




                                                # 38
MnhPRA – Hazard data aggregation




                                   # 39
Earthquake losses
                              Country Level Losses Million
                              MAD        Return Period
Occupancy             Average Annual Loss      20      50      100      500    1,000

Residential           506.5                  2,849   5,516    8,926   17,680   22,677

Commercial                           144.4    626    1,248    3,467   8,021    10,061
Industrial                            34.9    193      409    1,066   2,289     2,871
E.Facilities                          96.9    549    1,862    1,128   1,855     2,524
Infrastructures                       64.2    385      623      810   4,939     6,350


Total All Exposures                  846.8   4,602   9,658   15,397   34,784   44,482




                                                                        #40
Flood losses
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    2,751

Infrastructures       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
Tsunami losses




Country Level Losses Million MAD




                                   #43
Tsunami losses
                                           Return Period
                  Average Annual
Occupancy              Loss      20   50       100   388      1,000

Residential            23             1        57    1,969    17,639

Commercial             18             2        183   2,385    9,053
                                           -
Industrial             18                      143   3,408    8,898

Essential              2              0        4     158      1,421

Infrastructures       133             1        146   23,439   60,233


All Exposures         195             4        533   31,359   97,243
Inondations: pertes potentielles par
categories 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
Tremblement de terre: pertes
potentielles par categories
d’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%      0.45
Commercial       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
Tsunami: pertes potentielles par
categories 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%
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
Cost
Decision-making               (MAD)

            CT = Total Cost
            = CD + CI                         CI = Investment
                                              Cost

CD
= Cost of
Damage




                                          Design level (PGA)
                 Min CT
                 = Optimum Design level
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?
                                                mns MAD            18




                                                                          #54
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
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
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
National Disaster Risk Management and Financing Strategy

Mitigation 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
Thank you

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

  • 1. Kingdom of Morocco Natural Disaster Risk Management in Morocco For an integrated approach Mohamed Tabyaoui Technical Adviser to The Chief of Government Davos 28 -08- 2012
  • 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. 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. 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
  • 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. 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. The needs  Develop Global and integrated strategy  Coordinate all sectoral risk policies  Cause change in paradigm: prevention and resilience first
  • 10. The 3 pillars of our strategy  1-price volatility  2-Natural hazards  3-Risks in Agriculture
  • 11. Natural Hazards strategy  Assessment and risk modeling in Morocco  What if scenarios  Sectorial Strategies elaboration  National strategy
  • 12. Assessment: perimeter  5 major risks  Floods  Earthquakes  Tsunamis  Land slides  Drought
  • 13. Risk Modeling 5. Estimate Losses 4. Compute Damage 3. Define and Overlay Inventory 2. Characterize Hazard 1. Identify Study Region #13
  • 14. Assessment: Method  Probabilistic model  Economic model after a choc situation  Assessment of risk perception into communities
  • 15. Deployment/make it durable  Official Institution for coordination  Information system  Financial instruments
  • 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. Assessment: Project phases  Hazard Modeling  Vulnerability/ potential impacts  What if scenarios  cost/benefit analysis
  • 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. Data types 3 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. 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. Data collection: The success factors  Participative approach  scientific quality of the work  Respond to specific needs  Involvement of politics
  • 22. Assessment outputs  Risk maps  Risk modeling and simulations  Impacts/potential losses  Economic modeling assuming a chock  What if scenarios  Cost benefit analysis
  • 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. Financial instrument  Annual Budgets  National Fund for Natural Catastrophes  Insurances  Insurance to cover Natural catastrophes  Insurance to cover extrem events in Agriculture
  • 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
  • 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. Stochastic Events Earthquake event never a point source Considered a line source Area sources are subdivided into Area-line sources Num of Seismic Sources - 22 Num of Stochastic Faults - 1,735 Num of Stochastic Events - 14,670 #29
  • 32. Data used in Numerical Model General 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. 1st November 1755 Lisbon Tsunami – Contd., Extreme water surface elevations after 3 hrs 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
  • 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. 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. MnhPRA: Moroccan National Hazards Probabilistic Risk Assessment  Models were incorporated in SIG software  Extensible  adaptable  free of charges (open source)
  • 38. MnhPRA – Hazard data aggregation – Contd ., # 38
  • 39. MnhPRA – Hazard data aggregation # 39
  • 40. Earthquake losses Country Level Losses Million MAD Return Period Occupancy Average Annual Loss 20 50 100 500 1,000 Residential 506.5 2,849 5,516 8,926 17,680 22,677 Commercial 144.4 626 1,248 3,467 8,021 10,061 Industrial 34.9 193 409 1,066 2,289 2,871 E.Facilities 96.9 549 1,862 1,128 1,855 2,524 Infrastructures 64.2 385 623 810 4,939 6,350 Total All Exposures 846.8 4,602 9,658 15,397 34,784 44,482 #40
  • 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 2,751 Infrastructures 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. Tsunami losses Country Level Losses Million MAD #43
  • 44. Tsunami losses Return Period Average Annual Occupancy Loss 20 50 100 388 1,000 Residential 23 1 57 1,969 17,639 Commercial 18 2 183 2,385 9,053 - Industrial 18 143 3,408 8,898 Essential 2 0 4 158 1,421 Infrastructures 133 1 146 23,439 60,233 All Exposures 195 4 533 31,359 97,243
  • 45. Inondations: pertes potentielles par categories 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. Tremblement de terre: pertes potentielles par categories d’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% 0.45 Commercial 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. Tsunami: pertes potentielles par categories 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. 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. Cost Decision-making (MAD) CT = Total Cost = CD + CI CI = Investment Cost CD = Cost of Damage Design level (PGA) Min CT = Optimum Design level
  • 50. losses #50
  • 51. #51
  • 52. Tsunami Warning and Evacuation #52
  • 53. What-if ’s : 47 cases examined (so far) #53
  • 54. What-if ’s what where protected rebuild optimum Cost 2013 2014 ~ 201? mns MAD 18 #54
  • 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. 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. 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. National Disaster Risk Management and Financing Strategy Mitigation 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

Editor's Notes

  1. - La dimension « confidentialité et sensibilité des données stratégiques » les dispositions suivantes ont été prises : ne seront communiquées que des données affichées publiques. Les départements décideront des données qu’ils pourront communiquer La Banque Mondiale s’est engagée officiellement pour que les données collectées et communiquées au bureau d’études ne soient utilisées que dans le cadre de ce projet. - La dimension « confidentialité et sensibilité des données stratégiques » les dispositions suivantes ont été prises : ne seront communiquées que des données affichées publiques. Les départements décideront des données qu’ils pourront communiquer La Banque Mondiale s’est engagée officiellement pour que les données collectées et communiquées au bureau d’études ne soient utilisées que dans le cadre de ce projet. - La dimension « confidentialité et sensibilité des données stratégiques » les dispositions suivantes ont été prises : ne seront communiquées que des données affichées publiques. Les départements décideront des données qu’ils pourront communiquer La Banque Mondiale s’est engagée officiellement pour que les données collectées et communiquées au bureau d’études ne soient utilisées que dans le cadre de ce projet.