A MULTI RISK ASSESSMENT OF DISASTERS A MULTI RISK ASSESSMENT OF DISASTERS RELATED TO CLIMATE CHANGESRELATED TO CLIMATE CHANGES

Paolo Gasparini1 Warner Marzocchi2

Amra Scarl, Napoli

1 Dipt. Di Scienze Fisiche, Università di Napoli Federico II2 Istituto Nazionale di Geofisica e Vulcanologia, Roma

ERUPTIONS (tephra fall, pyroclastic flows, …)

SEA LEVEL RISE

EARTHQUAKES (ground shaking)

ANTHROPOGENIC SOURCES

What is the most dangerous hazard for my city??

…mmm…I don’t really know…

How to focus risk mitigation policies?

RAPID MASS MOVEMENTS

FLASH FLOODS

WHY THE MULTI-RISK?WHY THE MULTI-RISK?

What is the most dangerous hazard for my city??

…mmm…I don’t really know…

How to focus risk mitigation policies? WHAT IS NEEDED TO?1. quantitative risk assessment (probability)

needed for decision makers

1. ranking of risks2. interaction among risks

WHAT DO WE HAVE NOW?

risks are considered independently, through inhomogeneous procedures…

…they are not comparable!!!

INTRODUCING MULTI-RISK…

Different approaches to Hazard:

- Geological hazard can be considered constant with time

- Hazard affected by climate change are not constant with time.

Different Time scales

Different Criteria of damage assessment

Specific vs. systemic vulnerability

Different Spatial definition

RISKS ARE NOT COMPARABLE!!!

RISKS ARE TREATED SEPARATELY

starting from the ADVERSE EVENTfrom CLASSICAL RISK APPROACH…

URBAN VULNERABILITY

CLIMATIC CHANGETEMPERATURE

WINDPRECIPITATION

HAZARDPROBABILITYSCENARIOS

RURAL VULNERABILITYILLNESSHUNGER

REFUGEES MULTI RISK ASSESSMENT

PEOPLE PLACES THINGS

COPING CAPACITY•INDIVIDUAL LEVEL •COMMUNITY LEVEL•GOVERNMENT LEVEL

RESILIENCE

CLIMATIC CHANGE

RAINFALLS

URBANCATCHMENTS

DISCHARGES SEWER NETWORK

URBAN FLASH FLOODS

STRUCTURAL AND SOCIAL DAMAGES

STRUCTURAL AND NON STRUCTURAL

MITIGATION OPTIONS

HYDR

OLO

GICA

L RO

UTI

NE

HYDR

AULI

C RO

UTI

NE

VULNERABILITY OF URBAN AREAS

STORAGE FACILITIES

REAL TIME CONTROL

INNOVATIVE LAND USE

MULTI-RISK: assessment of the potential damages caused by all the events threatening an object (industry, city, environment, etc.).

Usually, multi-risk assessment is provided as the “sum” of independent single riskassessment, but:

1) Single risk assessments are not always liable to be summed (i.e., different spatial and temporal resolution, different approaches to vulnerability);

2) Risks are NOT independent: the hazard and vulnerability of one specific event may change significantly if another event occurred. (INTERACTION AND CASCADE EVENTS).

THIS MAY LEAD TO SEVERE UNDERESTIMATION OF THE REAL RISK.

Better consistency using DAMAGE-from-SOURCE.

starting from the TARGET AREA

Comparable Time scales

Same Type of damage

Comparable Spatial definitions

Comparable Approaches to evaluate hazard

Interaction and cascade effects easier to be accounted for

RISKS ARE COMPARABLE!!!

RISKS TREATED COHERENTLY

……to MULTI-RISK APPROACHto MULTI-RISK APPROACH

The sources of Risk are aleatoric events;

The imperfect knowledge of the processes/parameters

introduces epistemic uncertainties;

Bayesian approach allows us to take into account both aleatory

and epistemic uncertainties;

Bayesian approach allows us to merge different types of

information, such as theories, model output, data, and so on.

Why Bayesian Methods?

The Bayesian approach is particularly useful in practical problems characterized by few data and scarce theoretical knowledge.

The Bayesian approach implies that the probability is not a single value but it is a probability distribution.

The probability distribution has an average (the best guess of the probability) and a standard deviation.

These two parameters estimates the aleatoric and epistemic uncertainties.

Why Bayesian Methods?

Prior (e.g. given by models)

Likelihood (e.g.. DATA)

POSTERIOR PDF

(no epistemic uncertainty)

Bayes theoremBayes theorem

+

Risks are NOT independent: the hazard and vulnerability of one specific event may change significantly if another event occurred.

Example: Risk for one event E1 that depends on a second one E2

The yellowyellow box is the hazard. The blueblue box is the damage.

R1 p(E1 | E2)p(E2) p(E1 | E 2)p(E 2)

p[Ck1 | (E1,E 2)]p(E 2) p[Ck1 | (E1,E2)]p(E2) k Lk

Risks are NOT independent: the hazard and vulnerability of one specific event may change significantly if another event occurred.

Let us consider only one hazard (due to the event E1 depending on the event E2)

- Usually, long-term H1 is determined by databases. If p(E2) is not changed across the time covered by the database (i.e., the boundary conditions are the same), the database provides directly an unbiased estimation of H1.

- If p(E2) varies with time (e.g., global warming), the database provides a biased estimation. In this case, we need to estimate p(E2), p(E1 | E2) and p(E1| NOT E2).

- In the short-term hazard assessment, we may be interested in estimating p(E1 | E2) instead of H1, because we know that E2 is already occurred (cascade effects).

H1 p(E1 | E2)p(E2) p(E1 | E 2)p(E 2)

Risks are NOT independent: the hazard and vulnerability of one specific event may change significantly if another event occurred.

Let us consider one hazard (E1) due to the occurrence of intensive rainfall (E2; here for simplicity E2 is dichotomic: 0 – no intensive rainfall; 1 – intensive rainfall, e.g. rainfall over a given threshold):

- if no heavy rainfall occurred in the past, from the database we can estimate a biased value of H1 that is given by p(E1 | NOT E2) (being p(NOT E2)=1). Then, p(E2) is the probability to have a rainfall over the given threshold. p(E1 | E2) is the probability that we can estimate from a scenario: the probability to have E1 given a rainfall over the given threshold (INTERACTION).

H1 p(E1 | E2)p(E2) p(E1 | E 2)p(E 2)

Naples case Annual risks for human life:

•R seis = 0.0017

•R vulc = 1.37

•R flood = 4.2 10-5

•R land = 6 10-7

•R ind = 1.83 10-6 < IR < 1.83 10-8

•R env = 0.0125

Multi risk annual probabilities

Industrial accident (Toxic emission): 3.6 x 10-3

NAPLES CASE: SCENARIOS OF IN TOWN LANSLIDE TRIGGERED BY INTENSIVE PRECIPITATION NAPLES CASE: SCENARIOS OF IN TOWN LANSLIDE TRIGGERED BY INTENSIVE PRECIPITATION Heavy rainfall

Slow landslide Fast landslide No landslide

No failure of infrastructure

Failure of infrastructures

Over threshold

GPL

Fire Toxic release Explosion

NW

People (residents, workers,..)

Loss of containment

W SW Air, soil, subsoil, superficial water,

groundwater

Below threshold

…

Clone Clone

No loss of containment

Heavy rainfall

Flash floodsFast landslides

Damage to tanks of water supply network

Failure of sewer network

Damage to building and infrastructures

Over the threshold Below the threshold

Fast landslides

Damage to building and infrastructures

Damage to tanks of water supply network

Damage to building and infrastructures

Rio Yanuncay, Cuenca, Ecuador

Cuenca Project (supporting agencies: BID, ETAPA)

EC FP7 CLUVA CLUVA

Climate Change and Urban Vulnerability in Africa

Studied Cities:Douala, CamerounSaint Louis, SenegalOuagadougou, Burkina FasoAddis Ababa, EthiopiaDar Es Salaam, Tanzania