A. Costa, J. Selva, W. Marzocchi, and L. Sandri

1. Single versus multiple scenarios to assess volcanic hazard of calderas: the example of Campi Flegrei A. Costa, J. Selva, W. Marzocchi, and L. Sandri PART I BET_VH: Bayesian Event Tree for Volcanic Hazard PART II Long-term VH for tephra fallout at Campi Flegrei PART III Short-term VH for tephra fallout at Campi Flegrei EGU General Assembly, 05/05/2010

2. BET_VH: BET for Volcanic Hazard BET_VH assesses the long-term Volcanic Hazard from a generic phenomenon in selected areas around the volcano…

3. BET_VH: BET for Volcanic Hazard NODE 1-2-3 are merged together… It is assesses directly the probability of eruption in the time window t

4. BET_VH: BET for Volcanic Hazard NODES 4 and 5: identical to BET_EF… The vent position and the size define the Eruptive Setting (ES). The selected ESs may be a single reference event (1 vent location and 1 size), or many possible events simultaneously (MANY vent locations and MANY sizes)

5. BET_VH: BET for Volcanic Hazard NODE 6: producing the studied phenomenon… It assesses the probability that a given size class will produce the studied phenomenon, e.g., tephra fallout, lahars, pyroclastic flow, etc., (given an eruption and an ES)

6. BET_VH: BET for Volcanic Hazard NODE 7: reaching episode… It assesses the probability that the studied phenomenonwill reach a specific area (given an eruption, an ES and the occurrence of the phenomenon)

7. BET_VH: BET for Volcanic Hazard NODE 8: overcoming episode… It assesses the probability that the studied phenomenonwill overcome a given threshold of danger in the area (given an eruption, an ES, the occurrence of the phenomenon and that the area is reached)

8. BET_VH: BET for Volcanic Hazard At all nodes, BET_VH integrates MODEL(S) and PAST DATA …from MODEL(S) to PRIOR at nodes 7 & 8 • We propose a procedure to estimate prior distributions from the models’ output. The procedure allows to: • use many different models • use many runs of each model (initial/boundary condition variations) • give different weights to each models (reliability of models) • All ESs must be evaluated, but… • simple (and fast) models may define the overall distribution • sophisticated (and slower) models may refine probabilities for more the interesting/likely ESs

9. Long-term for Tephra fallout at Campi Flegrei NODE 1-2-3 Not set at the moment Selva, J, Orsi, G., Di Vito, A.M., Marzocchi, W., Sandri, L. submitted NODE 4 Prior: geo-structural info Past data: eruptions of Epoch III+ 14 x 12.5 Km area divided in 700 boxes 500 x 500 m Orsi, G., Di Vito, A.M., Selva, J, Marzocchi, W. , 2009 Prior: GR from VOTW Past data: eruptions of Epoch III+ NODE 5 • Size classes: • Effusive • Small Explosive (Averno 2) • Medium Explosive (Astroni 6) • Large Explosive (Agnano MS)

10. Long-term for Tephra fallout at Campi Flegrei Prior: from Newhall and Hoblitt [2004] Past data: None NODE 6 • Only the phenomenon “tephra” is defined. We set… • Q6(1) = 0 for Effusive • Q6(2) = 1 for Small Explosive • Q6(3) = 1 for Medium Explosive • Q6(4) = 1 for Large Explosive Prior: semi-analytical solution (Macedonio et al. [2005]; Pfeiffer et al. [2005]) Past data: None NODE 7 & 8 • 13149 wind profiles (last 36 years of daily profiles) • we neglect all possible topography effects • reference eruption for each size class • Size II: Averno 2 • Size III: Astroni 6 • Size IV: Agnano Monte Spina • threshold of 300 kg m-2 of loading for node 8

11. Long-term for Tephra fallout at Campi Flegrei NODE 7: probability that an area is reached GIVEN an eruption with this ES • ES: Astroni 6 eruption • vent: #521 • size: Medium Explosive NODE 8: probability that 300 kg m-2 is overcome GIVEN an eruption with this ES pES = 1.19 10-3 probability of the selected ES, given that an eruption occurs

12. Long-term for Tephra fallout at Campi Flegrei NODE 7: probability that an area is reached GIVEN an eruption with this ES • ES: COMBO 1 (standard for central volcano) • vent: #520 (most likely) • size: all possible sizes NODE 8: probability that 300 kg m-2 is overcome GIVEN an eruption with this ES pES = 4.79 10-3 probability of the selected ES, given that an eruption occurs

13. Long-term for Tephra fallout at Campi Flegrei NODE 7: probability that an area is reached GIVEN an eruption • ES: COMBO 2 • vent: all possible vents • size: all possible sizes NODE 8: probability that 300 kg m-2 is overcome GIVEN an eruption pES = 1 probability of the selected ES, given that an eruption occurs

14. Short-term for Tephra fallout at Campi Flegrei Monitoring: from Elicitation V (Selva et al., 2010) NODE 1-2-3 NODE 4 as Long-Term + Monitoring (VT, Deform, etc.) NODE 5 as Long-Term NODE 6 as Long-Term Prior: 3 models (HAZMAP, TEPHRA2, FALL3D) Past data: None NODE 7 & 8 • 3 days wind forecast • we neglect all possible topography effects • threshold of 300 kg m-2 of loading for node 8

15. Short-term for Tephra fallout at Campi Flegrei NODE 8: probability that 300 kg m-2 is overcome • STANDARD SHORT-TERM VH • 3 models in parallel (here, HAZMAP) • 1 scenario: • 1 eruption size (Astroni, medium explosive, SIZE 3) • 1 vent position (Astroni crater, vent loc #520) pES ≈ 1 10-3 NODE 8: probability that 300 kg m-2 is overcome • SHORT-TERM VH with BET_VH • 3 combined models • 2800 combined scenarios (pE = 1): • 700 vent positions • 4 eruption sizes pES = 1

16. Conclusions • Natural variability has a dominant effect on the Volcanic Hazard (expecially in calderas): • BET_VH allows a comprehensive evaluation of the whole natural variability and uncertainties of volcanic hazard: • all possible ESs may be combined(weighted with their prob.) • initial/boundary conditions • combine models with different run-times/reliability ratios • propagates uncertainties at all the steps of the estimation SINGLE SCENARIOS CANNOT ACCOUNT FOR IT AND INTRODUCE BIASES ON SHORT- TO LONG-TERM VH