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A MULTI RISK ASSESSMENT OF DISASTERS RELATED TO CLIMATE CHANGES Paolo Gasparini 1 Warner Marzocchi 2 Amra Scarl, Napoli 1Dipt. Di Scienze Fisiche, Università di Napoli Federico II 2Istituto Nazionale di Geofisica e Vulcanologia, Roma
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ERUPTIONS (tephra fall, pyroclastic flows, …) SEA LEVEL RISEEARTHQUAKES (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 MOVEMENTSFLASH FLOODS WHY THE MULTI-RISK?
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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 risks 2. interaction among risks WHAT DO WE HAVE NOW? risks are considered independently, through inhomogeneous procedures… …they are not comparable!!! INTRODUCING MULTI-RISK…
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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 EVENT from CLASSICAL RISK APPROACH…
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URBAN VULNERABILITY CLIMATIC CHANGE TEMPERATURE WIND PRECIPITATION HAZARD PROBABILITY SCENARIOS RURAL VULNERABILITY ILLNESS HUNGER REFUGEES MULTI RISK ASSESSMENT PEOPLE PLACESTHINGS COPING CAPACITY INDIVIDUAL LEVEL COMMUNITY LEVEL GOVERNMENT LEVEL RESILIENCE
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CLIMATIC CHANGE RAINFALLS URBAN CATCHMENTS DISCHARGES SEWER NETWORK URBAN FLASH FLOODS STRUCTURAL AND SOCIAL DAMAGES STRUCTURAL AND NON STRUCTURAL MITIGATION OPTIONS HYDROLOGICAL ROUTINE HYDRAULIC ROUTINE VULNERABILITY OF URBAN AREAS STORAGE FACILITIES REAL TIME CONTROL INNOVATIVE LAND USE
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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 risk assessment, 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.
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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 APPROACH
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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?
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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?
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Prior (e.g. given by models) Prior (e.g. given by models) Likelihood (e.g.. DATA) POSTERIOR PDF (no epistemic uncertainty) Bayes theorem +
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Risks are NOT independent: the hazard and vulnerability of one specific event may change significantly if another event occurred. Example: Risk for one event E 1 that depends on a second one E 2 yellowblue The yellow box is the hazard. The blue box is the damage.
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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 E 1 depending on the event E 2 ) - 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 H 1. - If p(E 2 ) varies with time (e.g., global warming), the database provides a biased estimation. In this case, we need to estimate p(E 2 ), p(E 1 | E 2 ) and p(E 1 | NOT E 2 ). - In the short-term hazard assessment, we may be interested in estimating p(E 1 | E 2 ) instead of H 1, because we know that E 2 is already occurred (cascade effects).
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Risks are NOT independent: the hazard and vulnerability of one specific event may change significantly if another event occurred. Let us consider one hazard (E 1 ) due to the occurrence of intensive rainfall (E 2 ; here for simplicity E 2 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 H 1 that is given by p(E1 | NOT E 2 ) (being p(NOT E 2 )=1). Then, p(E 2 ) is the probability to have a rainfall over the given threshold. p(E 1 | E 2 ) is the probability that we can estimate from a scenario: the probability to have E 1 given a rainfall over the given threshold (INTERACTION).
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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
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NAPLES CASE: SCENARIOS OF IN TOWN LANSLIDE TRIGGERED BY INTENSIVE PRECIPITATION Heavy rainfall Slow landslideFast landslideNo landslide No failure of infrastructure Failure of infrastructures Over threshold GPL Fire Toxic release Explosion NW People (residents, workers,..) Loss of containment WSW Air, soil, subsoil, superficial water, groundwater Below threshold … Clone No loss of containment
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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)
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CLUVA EC FP7 CLUVA Climate Change and Urban Vulnerability in Africa Studied Cities: Douala, Cameroun Saint Louis, Senegal Ouagadougou, Burkina Faso Addis Ababa, Ethiopia Dar Es Salaam, Tanzania
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