48th imia meeting tuesday 29th september 2015, mérida, méxico · emergency response vulnerability...
TRANSCRIPT
48th IMIA Meeting Tuesday 29th September 2015, Mérida, México
Emergency Response
Vulnerability Reduction
Land use planning
Financial protection
$ Human
Applications
Expected physical damage
Exposure
Intensity
% D
amag
e
Vulnerability
Hazard
% D
amag
e
Losses
Cat Risk Large occasional, events History does no reveal the true risk: short observa7on period Exposed elements and their vulnerability change rapidly over 1me Secondary effects are becoming very important Not feasible to build model: sta7s7cs empirical rely on probability
¿Are they new? Large, important buildings and infrastructure (dams, bridges, nuclear power plants, tall buildings, …) Torre La7noamericana (1950) Laguna Verde (1985) Building Codes Earthquake 1942, 1957, 1985 …
Classic Mats + Engineering + Computers + Data Bases
Extensive evaluation of data sources including work of many institutions:
Seismic Source Model for Latin America.
Ordaz et al, (2013). Global Assessment Report on Disaster Risk Reduction – GAR 2013
PGA, Tr = 150 years
Jaimes, M.A, Reinoso, E. y Esteva, L. (2014). Risk analysis for structures exposed to several multi-hazard sources Journal of Earthquake Engineering
Rock
Soft layers
México • Distrito Federal • Acapulco • Oaxaca • Puebla • Guadalajara • Ensenada • Tijuana • Mexicali
Costa Rica • San José Venezuela • Caracas Ecuador • Quito
Colombia • Bogotá • Medellín • Cali • Armenia • Pereira • Maizales • Popayán • Tuluá • Palmira • Buga • Ibagué • Bucaramanga
Perú • Lima Chile • Santiago
Jaimes, M.A., Niño, M. y Reinoso, E. (2014) Regional map of earthquake-induced liquefaction hazard using the lateral spreading displacement index DLL Natural Hazards
CDD
Tienda
Edificio Ad.
Large portfolios in many countries
Model Seismic Response Nivel de desempeño
Frec
uenc
ia de
ocu
rrenc
ia I = 100 gals
Nivel de desempeño
Frecue
ncia de ocurrencia
I = 400 gals
I = 50 gals
I = 1000 gals
Statistics
Nivel de desempeño
Perio
do de retorno (año
s)
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
0 0.1 0.2 0.3 0.4 0.5 0.6Pérdida
Perio
do de retorno (año
s)
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
0 0.1 0.2 0.3 0.4 0.5 0.6
30 VULNERABILITY FUNCTIONS- 4 DIFFERENT BUILDING USES AND 8 STRUCTURES TYPES
for COSTA RICA
Sa (cm/s2)
Dam
age
SEP: Public Schools
SCT: Roads, highways, bridges…
SEDATO: Poor housing SSA: Health sector
CONAGUA: Dams, Irrigation, …
More than10 millon dwellings 13,500 units
135,000 km of roads, more than 7000 bridges
More than 210,000 schools
Water supply main pipelines
Managua, 1972 earthquake, today
San Salvador
Niño, M., Jaimes, M.A. y Reinoso E. (2014) Seismic-event-based methodology to obtain earthquake induced translational landslide regional hazard maps Natural Hazards
Quijano, J., Jaimes, M.A., Torres, M., Reinoso, E., Castellanos, L., Escamilla, J. y Ordaz, M. (2014) Event-based approach for probabilistic agricultural drought risk assessment under rainfed conditions Natural Hazards
• Geocoded type crop
• Geocoded type crop
Jaimes, M.A, Reinoso, E. y Esteva, L. (2013) Seismic vulnerability of building contents for a given occupancy due to multiple failure modes Journal of Earthquake Engineering
Ts = 1.2 sec
NS
012345678910111213
0.0 0.2 0.4 0.6 0.8 1.0Amax (m/s2)
Stor
y
10-Dec14-Sep22-May9-Oct
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
0 200 4000.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
0 200 4000.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
0 200 4000.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
0 200 4000.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
0 200 4000.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
0 200 400
x=z/H EM 30 SF 42 SF 47 SF 48 LA 52 LA 54
Acceleration (cm/s2)
Sierra Madre Big Bear Landers
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
0 200 4000.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
0 200 4000.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
0 200 400
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
0.0 1.0 2.0 3.0 4.0
PFA / PGA
x = z / H
NEHRP 1997-2003
NEHRP 94, UBC 97
For the last 30 years Engineering Cat Models (very) good idea of what may happen more Vulnerability Func7ons detailed Data Bases Expected losses for: Insurance sector Governments Infrastructure Risk managers Earthquake, but almost all perils