Probabilistic Tsunami Hazard Analysis. Hong Kie Thio AECOM, Los Angeles

Transcription

1 Probabilistic Tsunami Hazard Analysis Hong Kie Thio AECOM, Los Angeles May 18, 2015

2 Overview Introduction Types of hazard analysis Similarities and differences to seismic hazard Methodology Elements o Source models o Propagation model o Inundation and runup o Epistemic uncertainties and Aleatory variability Applications Insurance industry Regulatory agencies Disaster mitigation Designing for Tsunamis - Oregon May 17, 2015 Page 2

3 Introduction Tsunami hazard analysis Deterministic o Worst case scenarios o Sometimes semi-probabilistic if source return times are used o Evacuation planning Probabilistic o Comprehensive source models o Includes alternative models of natural processes (epistemic uncertainty) o Includes natural variability of processes and limitations to our ability to model these processes perfectly (aleatory variability) o Consistent with other hazard practices (e.g. seismic) and Performance Based Engineering o Mean, median hazard and fractile hazard Designing for Tsunamis - Oregon May 17, 2015 Page 3

4 PTHA vs PSHA Source Magnitude, location recurrence Source Magnitude, location (large R) recurrence, slip GMPE site, M, R Long wave model bathymetry, numerical solution FD, FV, offshore Integration to site hazard (linear) Integration to offshore hazard Non-linear soil analysis SHAKE, FLAC, etc Inundation nonlinear numerical analysis, analytical/empirical relations

5 Methodology

6 Two step process Probabilistic offshore exceedance amplitude Efficient algorithm using pre-computed sub-fault Green s functions Integration over thousands of earthquakes from sources around the Pacific Rim Comprehensive aleatory and epistemic models Inundation and runup Use offshore probabilistic exceedance amplitudes to anchor the inundation and runup modeling using: o Exact matching off offshore amplitudes for certain probabilities, or o Sampling of the offshore hazard curves Source disaggregation to find significant sources Additional aleatory variability, but more difficult to implement due to non-linearity Designing for Tsunamis - Oregon May 17, 2015 Page 6

7 Source regions for California

8 Subfault Green s function summation +

9 Probabilistic offshore waveheight hazard

10 Tsunami Hazard Curves Santa Monica Golden Gate

11 Source disaggregation

12 Epistemic uncertainties and aleatory variability

13 What are the largest uncertainties in PTHA? Source models Recurrence M max Slip Distribution Digital Elevation Models Near-shore Bathymetry Onshore Elevations (SRTM: errors of >10 m) Numerical Models Near-shore Propagation/Inundation

14 Epistemic uncertainties Uncertainties due to limited knowledge of physics characteristics of the problem Use logic tree approach Branches for: o Scaling models o Rupture extent (top and bottom) o Recurrence rate o Overall slip partitioning We would like to follow seismic models as close as possible, where applicable o Cascadia: yes o Alaska: no Designing for Tsunamis - Oregon May 17, 2015 Page 14

15 Source model Cascadia McCrorey model o Curved fault plane (1x1 km sampling) Used in USGS National Seismic Map 3 different depth terminations Tapers with depth Tapers to the surface Designing for Tsunamis - Oregon May 17, 2015 Page 15

16 Cascadia USGS Logic Tree

17 Uncertainty and variability at the source Aleatory Magnitude distribution Slip distribution Epistemic Mmax Segmentation Recurrence Scaling relation Shallow/deep slip

18 Epistemic: Scaling Relations Average slip Area

19 Aleatory variability Inherent variability in physical processes Magnitude Slip distribution Tides Modeling uncertainty (algorithmic, bathymetric errors and additional source variability) Designing for Tsunamis - Oregon May 17, 2015 Page 19

20 Variability at the shoreline and inland Shoreline In-land

21 Results

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23 Example results Designing for Tsunamis - Oregon May 17, 2015 Page 23

24 Offshore probabilistic exceedance amplitudes (ASCE-7)

25 ASCE 7-16

26 Tsunami Hazard Assessment for Indonesia

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28 Rapid Tsunami Loss Estimation for SOPAC region (Worldbank, through AIR) Event request: Event result:

29 Thank you