5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland
1. FORMULATION OF A NATURAL RISK
MANAGEMENT PLAN TO SAN
ANTONIO DEL TEQUENDAMA,
CUNDINAMARCA - COLOMBIA
Authors: Wilmer Fabiรกn Montiรฉn Tique
Source: http://sanantoniodeltequendama- 1
cundinamarca.gov.co/foros.shtml?apc=I----
Carlos Andrรฉs Peรฑa Guzman
&x=2719684&s=C&m=v
2. INTRODUCTION
Floods
Landslides
Colombiaยดs
development
process
Water
Scarcity
Poor
populations
Climate
change
Source: http://www.semana.com/nacion/articulo/colombia-recibira-ayuda-venezuela-brasil-caf-para-afectados-
lluvias/125190-3
3. PROBLEM DEFINITION
San Antonio del Tequendama, Cundinamarca Colombia
Landslides Floods
Earthquakes
Source: http://sanantoniodeltequendama- 3
cundinamarca.gov.co/noticias.shtml?apc=Cnxx-1-
&x=2720026
4. Municipal Plan for Disaster Risk
Management (MPDRM)
National Unit for Disaster
Risk Management
(UNGRD) from Colombia.
Instrument
Prioritize
Program
Formule
Risk knowledge
Risk reduction
Disaster management
Municipal guide for risk
management
Technical assistance project in
municipal and goverment risk
management.
Control
Document structure
Risk scenarios general
characterization
Programmatic component
Diagnostic
Identification risk scenarios
Risk scenarios
characterization
Programs and actions
formulation.
Source: Author, 2013.
10. DIAGNOSTIC
Cundinamarca Department
Height 850 m - 2700 m
Rural Zone : 23 Communities
Urban Zone : 4 Center population
Bituima and Corraleja Zaragoza Faults
Predominant soils: IV and VI
Physiography: Peaks and ridges
10 % of the territory is flat, 25% hilly
and 65% rugged
Average rainfall: 1500 mm
Average temperature: 20ยฐC
Bimodal annual rainfall
70% Agriculture
30% Poultry and pork sector
Geography
Geology and
edaphology
Topography
Climatology
Hydric resources
Economic activities
Source: Author, 2013.
11. IDENTIFICATION RISK SCENARIOS
Secondary
information
Identification risk
scenarios
Guide for the preparation of
land use plan methodology
(IGAC)
gvSIG software
Risk
Maps
MPDRM
Methodology
CAR
IDEAM
IGAC
SGC
UNGRD
Different
timescales
Natural hazard studies
Identification
of high risk
areas in the
scenarios
11
16. 80% of the municipality population is vulnerable
to the three risk scenarios identificated,
represented by San Josรฉ, Chicaque, La Rรกpida,
Vancouver, Zaragoza, Quebradagrande, Caicedo,
Cusio, Arracachal, Santafe, Patio de Bolas, El
Cajรณn, Las Angustias, La Rambla and Vancouver
communities as well as the municipal center and
inspecciรณn de Santandercito urban center.
16
18. Risk scenarios
evaluation.
RISK SCENARIOS EVALUATION
Risk control analysis
CAPRA
Software
Probabilistic analysis
Probabilistic risk
analysis
Frequency
Severity
BOEHM
RISKIT
Historical
data
Methodology
review SEI- SRE (Software Engineering
Institute -Software Risk Evaluation)
SERUM
(Software Engineering Risk
Understanding and Management)
SERIM
(Software Engineering Risk Index
Management)
SEI- SRE
Methodology
Risk scenarios
priorization
Qualitative analysis (brainstorming
and diagrams)
Risk management analysis
prioritizing risk scenarios.
Cost - benefit analysis
Risk analysis using stadistics.
@Risk
Software
Exposed
elements
definition
Vulnerability definition
@Risk
Software
Result Risk level
Source: Author, 2013.
19. Chi squared test results, using @ RISK
Software
Probability frequency estimation,
using Poisson Distribution with a
stadistic media of 1.
Probability frequency estimation,
using Poisson Distribution with a
stadistic media of 2.
19
20. Frequency criteria according SEI- SRE methodology
Table 1. Frequency criteria description according SEI โ SRE Methodology
SourRce:e Rosbuertls,t 2s011.
LANDSLIDES SCENARIO: โFREQUENTโ
FLOODS SCENARIO: โPROBABLEโ
EARTHQUAKES SCENARIO: โOCCASIONALโ
20
21. SEVERITY
โข Elements exposed definition.
โข Physical and human vulnerability definition.
โข Probabilistic risk analysis.
21
22. Physical and human vulnerability definition
Graphics 1 and 2. Vulnerability functions by floods.M1 y M2.
FSuoeunrctee:: AAuutthoor,r 2, 2001133. .
22
23. MODEL RESULTS USING @RISK
SOFTWARE
Source: Author, 2013.
23
Source: Author, 2013.
24. FRECUENCY AND SEVERITY PARAMETERS RESULTS OBTAINED
RISK LEVEL ESTIMATED FOR EACH RISK SCENARIO EVALUATED TEQUENDAMA.
Fuente: Autor, 2013.
24
Source: Author, 2013.
Risk scenarios priorization
32. MODEL RESULTS
Fuente: Autor, 2013.
STRUCTURING OF VALUE TREES
CONSTRUCTION OF CRITERIA
DESCRIPTORS
SCORING OF OPTIONS AND
RESULTS.
32
Source Author, 2013.
33. ADDED VALUE FOR THE POST 2015
FRAMEWORK FOR DISASTER RISK REDUCTION
Source Author, 2013.
34. CONCLUTIONS
โข 80% of the current population is vulnerable to the 3 risk
scenarios analyzed.
โข The landslide risk scenario was the most critical, followed by
floods and finally earthquakes.
โข The main causes in the risk scenarios by landslides and floods
were by anthropic activities like deforestation for agriculture
and livestock.
โข Itโs more feasible invest in preventive actions to continue
investing in projects to mitigate the risk once the emergency
occur.
โข Specify the way to prioritize risk scenarios (MPDRM
Methodology limitation) structure analysis in the Risk scenario
characterization (MPDRM Methodology benefit)
34
35. โWE CANNOT STOP NATURAL DISASTERS BUT WE CAN
ARM OURSELVES WITH KNOWLEDGE: SO MANY LIVES
WOULDNยดT HAVE TO BE LOST IF THERE WAS ENOUGH
DISASTER PREPAREDNESSโ
PETRA NEMCOVA.
35