Introduction Plan The model Validation Integration The challenge Bodrum/Kos Final Comments. Tsunami-HySEA

Transcription

1 Tsunami-HySEA A Computer Code for Fast Tsunami Calculations Jorge Macías EDANYA Research Group (Differential Equations, Numerical Analysis and Applications) Universidad de Málaga International Conference on the Recent Tsunami Events in the Aegean Sea, December, 2017

2 Introduction Two major earthquakes in the Aegean Sea last summer 12th June - Mw th July - Mw. 6.6 that have generated Tsunami along the coasts of Greece and Turkey Although of limited magnitude... the two events raised several questions on the preparedness of Mediterranean countries it is important to analyze the behavior and the effectiveness of up-to-date developments

3 Plan Plan The model Features Good properties Equations Numerics Validation and verification process Integration in Tsunami Systems The Mediterranean challenge Bodrum/Kos event Concluding remarks

4 Tsunami-HySEA. Model features Seabed deformation model: Okada Model Okada model for seabed deformation Hypothesis: Intantaneous transmition to the water free surface Then a shallow water model propagates the initial tsunami wave Okada Model (1985) To define the initial seabed deformation is necesary to provide: Longitude, Latitude, and source depth Fault plane length and width Dislocation Strike angle, slip angle and dip angle Tsunami-HySEA model

5 Tsunami-HySEA. Model features Seabed deformation model: Multi-Okada Model Multiple Okada segments can be defined Rupture can be synchronous or asynchronous Seabed deformation model Other rupture models can be implemented Filtering (as Kajiura) - Nosov-Kolesov Support for rectangular or triangular faults Massively parallel CUDA and MPI GPU and multi-gpu Others capabilities Nested meshes (two-way) 2D domain decomposition and load balancing Direct output of time series NetCDF input/output files Resuming a stored simulation (new grids and new points for the time series) Overlapping writing and computing

6 Tsunami-HySEA. Model equations Shallow Water Models frequently used in ocean and coastal simulations seldom used to explicitely reproduce coastal inundation or run-up height. Non Linear Shallow Water = 0, >< x density; g @x q 2 x h + g 2 qxq y qxq y H(x) bathymetry; h(x, t), water layer thickness; (u x(x, t), u y(x, t)) flow velocity; q x(x, t) =u x(x, t)h(x, t), S f =(S x, S y) bottom friction effects. h q 2 y h + g 2 h2 q y(x, t) =u y(x, t)h(x, t) fluxes; S x, S y. Tsunami-HySEA

7 2. Tsunami-HySEA. Numerics Numerics: A family of Finite Volume numerical schemes Scenarios: WAF method (LW+HLL) 1 and higher order TEWS: hybrid 2s+WAF 2 Laboratory experiments: higher order methods Wet/Dry front treatment 3,4,5 Nested meshes and/or AMR (GPU) 1 de la Asunción et al. (2012). Efficient GPU implementation of a two waves TVD-WAF method for the two-dimensional one layer shallow water system on structured meshes, Computers & Fluids. 2 Article in progress 3 Castro, González-Vida, Parés (2005). Numerical treatment of wet/dry fronts in shallow water flows with a modified Roe scheme. Math. Mod. and Meth. in Applied Sci. 4 Gallardo, Parés, Castro (2007). On a well-balanced high-order finite volume scheme for shallow water equations with topography and dry areas. J. Comput. Phys. 5 Castro, Fernández, Ferreiro, García, Parés (2009). High order extensions of Roe schemes for two dimensional nonconservative hyperbolic systems. J. Sci. Comput. Tsunami-HySEA model

8 2. Tsunami-HySEA. Numerics Numerics: A family of Finite Volume numerical schemes Scenarios: WAF method (LW+HLL) 1 and higher order TEWS: hybrid 2s+WAF 2 Laboratory experiments: higher order methods Wet/Dry front treatment 3,4,5 Nested meshes and/or AMR (GPU) Nice properties Well-balanced (avoid spurious oscillations) Transitions from sub to super critical situations (arrival to coast) Positivity (no negative layer thickness) Inundation area and runup heights are model outputs Discontinuities in data or solutions (no need to smooth bathymetry) Implementation CUDA/MPI - GPU/Multi-GPU (very short computing times) Tsunami-HySEA model

9 Tsunami-HySEA. Validation A long and exhaustive benchmarking process - NTHMP standards 1. Propagation and Inundation 2. Tsunami currents 3. Landslide generated tsunamis

10 Validation. 1 Propagation and Inundation NTHMP benchmarks Analytical solutions BP1. Simple wave on a simple beach - analytical Laboratory benchmarking BP2. Simple wave on a simple beach - laboratory BP3. Solitary wave in a conical island - laboratory BP4. Complex 3D Monai Valley beach - laboratory Field benchmarking BP5. Okushiri Island tsunami - field NTHMP (2012). Proceedings and Results of the 2011 NTHMP Model Benchmarking Workshop Repport was submitted to the NTHMP in 2015 Macías et al (2017). Performance benchmarking of T-HySEA model for NTHMP s inundation mapping activities. PAAG, [doi: /s ] NTHMP certification - August 2017

11 Validation. 1 Propagation and Inundation NTHMP certification - August 2017!National!Tsunami!Hazard!Mitigation!Program!Benchmarked!Tsunami!Models! Reference:! Updated:!17!August!2017 Model Name Model affiliation & contact States or Territories that use Digital Elevation Model Model specifics NTHMP Benchmarks Download website (if available) Developer Resolution Physics Uses (sources) Inundation Currents Landslide Documentation or peer-review Pros Cons Comments Alaska Geophysical Institute Seismic; Alaska GI'-T Dmitry Nicolsky Alaska: Inundation NCEI? SW Y Pending Pending User interface Landslide djnicolsky@alaska.edu National Tsunami Warning Center ATFM Paul Huang US TWCs: Forecasting NCEI? SW Seismic Y Pending paul.huang@noaa.gov University of Delaware FUNWAVE-TVD, v.1.0 Jim Kirby East Coast: Inundation NCEI,?? B Seismic Y Pending kirby@udel.edu! GeoClaw MOST NEOWAVE SELFE THETIS TSUNAMI3D BOSZ University of Washington Adaptive mesh Randy LeVeque Washington: Inundation NCEI? B Seismic Y Pending refinement NOAA PMEL Can US TWCs: Forecasting 1/3-3 Computationally Diego Arcas NCEI, PMEL SW Seismic Y Pending become Washington: Inundation arcsec Fast diego.arcas@noaa.gov unstable University of Hawaii Hawaii, Am. Samoa, Puerto Rico, 1/3-3 Two-way nested Kwok Fai Cheung Hawaii NH Seismic Y Y? - Gulf of Mexico, BC arcsec grids cheung@hawaii.edu Oregon Health & Science University Resolves current Joseph Zhang Oregon: Inundation Oregon, NCEI?? CFD Sceismic Y Pending vortices Univ. of Rhode Island Seismic; Resolves current Stephan Grilli N/A NCEI,?? CFD Y Pending Pending Landslide vortices Texas A&M University at Galveston Seismic; Resolves current Juan Horrillo Gulf of Mexico: Inundation NCEI? CFD Y Pending Pending Landslide vortices horrillj@tamug.edu Tohoku Univ. & Univ of Hawaii Resolves current 1/9-3 no grid Voelker Roeber Hawaii: Inundation Hawaii, NCEI? B Seismic Y Pending vortices, works also arcsec nesting roeber@irides.tohoku.ac.jp for swell waves User interface: ComMIT Cliffs HySEA E.Tolkova, PAAG, 171(9), NW Research Associates NCEI Any SW Seismic Y Pending (2014); User Computationally Elena Tolkova, e.tolkova@gmail.com Manual at: Fast; easy set-up https//:github.com/delta-function/cliffs-src Alaska (testing):tsunami Modeling University de Malaga Jorge Macías (jmacias@uma.es) PMEL (testing)- US TWCs: 1/3-3 Seismic; Computationally NOAA/PMEL Diego NCEI SW/B Y Pending Pending ysea/index.php/referenc forecasting arcsec Landslide Fast; Robust; Stable Arcas (diego.arcas@noaa.gov) es - NetCDF I/O Nested meshes; run on - GPUs and mulit-gpu architectures NHWAVE University of Delaware East Coast: landslide tsunami generation NCEI? Seismic Y Pending Pending Definitions Physics based Model types

12 Validation. 1 Propagation and Inundation NTHMP certification - August 2017!National!Tsunami!Hazard!Mitigation!Program!Benchmarked!Tsunami!Models! Reference:! Updated:!17!August!2017 Model Name Model affiliation & contact States or Territories that use Digital Elevation Model Model specifics NTHMP Benchmarks Download website (if available) Developer Resolution Physics Uses (sources) Inundation Currents Landslide Documentation or peer-review Pros Cons Comments Alaska Geophysical Institute Seismic; Alaska GI'-T Dmitry Nicolsky Alaska: Inundation NCEI? SW Y Pending Pending User interface Landslide djnicolsky@alaska.edu National Tsunami Warning Center ATFM Paul Huang US TWCs: Forecasting NCEI? SW Seismic Y Pending paul.huang@noaa.gov University of Delaware FUNWAVE-TVD, v.1.0 Jim Kirby East Coast: Inundation NCEI,?? B Seismic Y Pending kirby@udel.edu! GeoClaw MOST NEOWAVE SELFE THETIS TSUNAMI3D BOSZ University of Washington Adaptive mesh Randy LeVeque Washington: Inundation NCEI? B Seismic Y Pending refinement NOAA PMEL Can US TWCs: Forecasting 1/3-3 Computationally Diego Arcas NCEI, PMEL SW Seismic Y Pending become Washington: Inundation arcsec Fast diego.arcas@noaa.gov unstable University of Hawaii Hawaii, Am. Samoa, Puerto Rico, 1/3-3 Two-way nested Kwok Fai Cheung Hawaii NH Seismic Y Y? - Gulf of Mexico, BC arcsec grids cheung@hawaii.edu Oregon Health & Science University Resolves current Joseph Zhang Oregon: Inundation Oregon, NCEI?? CFD Sceismic Y Pending vortices Univ. of Rhode Island Seismic; Resolves current Stephan Grilli N/A NCEI,?? CFD Y Pending Pending Landslide vortices Texas A&M University at Galveston Seismic; Resolves current Juan Horrillo Gulf of Mexico: Inundation NCEI? CFD Y Pending Pending Landslide vortices horrillj@tamug.edu Tohoku Univ. & Univ of Hawaii Resolves current 1/9-3 no grid Voelker Roeber Hawaii: Inundation Hawaii, NCEI? B Seismic Y Pending vortices, works also arcsec nesting roeber@irides.tohoku.ac.jp for swell waves User interface: ComMIT Cliffs HySEA E.Tolkova, PAAG, 171(9), NW Research Associates NCEI Any SW Seismic Y Pending (2014); User Computationally Elena Tolkova, e.tolkova@gmail.com Manual at: Fast; easy set-up https//:github.com/delta-function/cliffs-src Alaska (testing):tsunami Modeling University de Malaga Jorge Macías (jmacias@uma.es) PMEL (testing)- US TWCs: 1/3-3 Seismic; Computationally NOAA/PMEL Diego NCEI SW/B Y Pending Pending ysea/index.php/referenc forecasting arcsec Landslide Fast; Robust; Stable Arcas (diego.arcas@noaa.gov) es - NetCDF I/O Nested meshes; run on - GPUs and mulit-gpu architectures NHWAVE University of Delaware East Coast: landslide tsunami generation NCEI? Seismic Y Pending Pending Definitions Physics based Model types

13 Validation. 2 Tsunami currents Tsunami model validation Tsunami models well validated against wave height and runup Comparisons with speed data less common But still destructives in the farfield Nearfield: large waves, high flow depth and large flooding areas Farfield: strong currents (harbors and bays) Therefore, for risk assessment and hazard mitigation purposes reproducing tsunami flow velocities is of importance besides for sediment transport is fundamental Scarcity of data, but from Tohoku 2011 Field data for tsunami currents were recorded at several locations

14 Validation. 2 Tsunami currents The NTHMP Strategic Plan To help produce accurate and consistent maritime hazard products Need to evaluate the numerical tsunami modeling of currents Expected results better awareness of hability to capture the physics of tsunami currents better understanding of how to used these tools for hazard assessment and mitigation efforts

15 Validation. 2 Tsunami currents NTHMP Mapping & Modeling Benchmarking Workshop: Tsunami Currents 1 Benchmark 1 - SB4 02 Lloyd & Stansby (1995) 2 Benchmark 2 - Hilo Harbour (field data) 3 Benchmark 3 - Tauranga Harbour (field data) 4 Benchmark 4 - Seaside (Oregon) 5 Benchmark 5 - Triangular shaped shelf with an island Tsunami-HySEA passed ALL THE 5 BENCHMARKS producing good results NTHMP Report (2015) Lynett, P.J. et al. (2017). Inter-model analysis of tsunami-induced coastal currents. Ocean Modeling, 114: [doi: /j.ocemod ] Macías et al (2018a). Performance assessment of the Tsunami-HySEA model for NTHMP tsunami currents benchmarking. Part I Laboratory data. Macías et al (2018b). Performance assessment of Tsunami-HySEA model for NTHMP tsunami currents benchmarking. II Field data.

16 Validation. 2 Tsunami currents. BP4 Seaside (Oregon) Haga click para visualizar la simulación

17 Integration in Tsunami Systems Versatile integrable tool CAT - INGV (Italy) PMEL/NOAA and TWC TAT - JRC (EC, Ispra) Tridec-Cloud - GFZ (Germany) IGN (Spain) - Spanish NTWC TSUSY - IHC (Spain) and in a near future at SIPAT CAT: Centro Allerta Tsunami TAT: Tsunami Analysis Tool - JRC: Joint Research Center GFZ: German Research Center for Geosciences IGN: Instituto Geográfico Nacional TSUSY: Tsunami System - IHC: Instituto de Hidráulica Ambiental de Cantrabria SIPAT: Sistema Integrado de Predicción y Alarma de Tsunamis

18 The example in the Mediterranean. The INGV challenge INGV. A TEWS for all the Mediterranean Computational domain: the whole Mediterranean Spatial resolution: 30 arc-sec. Size of the problem: = cells Simulation time: 8 hours

19 The example in the Mediterranean. The INGV challenge Output Times series at 17,000 predefined locations Maximum height in all the domain

20 En el Sistema de Alerta Temprana de Tsunamis de Italia

21 Times for the Mediterranean case 2014 Computing times and speed-up # GPUs Computing times Speed-up Requirement: computing time < 6 min * Times for nvidia Titan Black GPUs (Kepler, 2012). 1 Gb ethernet network Continuous improvements Static load balancing CFL adjustment Writing while computing Overlapping of processes

22 Times for the Mediterranean case 2017 Computing times and speed-up # GPUs Computing times Speed-up Requirement: computing time < 6 min * Times for nvidia Titan Black GPUs (Kepler, 2012). 1 Gb ethernet network But also new architectures... 2 NVIDIA Tesla P (already obsolete )

23 Times for the Mediterranean case 2017 Computing times and speed-up # GPUs Computing times Speed-up Requirement: computing time < 6 min * Times for nvidia Titan Black GPUs (Kepler, 2012). 1 Gb ethernet network But also new architectures... 2 NVIDIA Tesla P sec obsolete!!!

24 Bodrum/Kos Earthquake and Tsunami

25 First issue: the source

26 Nested meshes (Kos Port)

27 Nested meshes (Kos Port) Level 0 Resolution: arc-sec ( 9.7 m) # of cells: 3,230 2,586 = 8,352,780 Longitude: [ , ] Latitude: [ , ] Level 1 Resolution: arc-sec ( 2.4 m) # of cells: = 680,960 Longitude: [ , ] Latitude: [ , ] Computing time 42 min simulation - Size of the problem 9,003,740 cells - Finer resolution 2.4 m Saving every 60 sec Saving time series every 15 sec 2 GPUs P min 13 sec

28 Maximum Amplitude

29 Maximum Amplitude

30 Inundation at Kos port

31 Inundation at Kos port

32 Bodrum/Kos Tsunami. Numerical simulation

33 Bodrum/Kos Tsunami. Numerical simulation

34 Bodrum/Kos Tsunami. Time series

35 Bodrum/Kos Tsunami. Time series Point 1 - LAT / LON (Kos port) Point 2 - LAT / LON Kos Port

36 Bodrum/Kos Tsunami. Time series Point 3 - LAT / LON Point 4 - LAT / LON Gumbet Bay Point 5 - LAT / LON

37 Bodrum/Kos Tsunami. Time series Point 6 - LAT / LON Point 7 - LAT / LON Bodrup Port Point 10 - LAT / LON (Tide Gauge)

38 Bodrum/Kos Tsunami. Time series Karaada Island Point 8 - LAT / LON Karaada Island Point 9 - LAT / LON Bitez Bay

39 Final Comments Difficulties Smaller events more difficult Local effects hard to capture To have any chance, high-resolution data Then high-resolution modeling Large uncertainty The seismic source is the main source of uncertainty Is not uncertainty in the source It is a seems nearly an unknown of the problem