Tsunami-HySEA model validation for tsunami current predictions

Model ability to compute and predict tsunami flow velocities is of importance in risk assessment and hazard mitigation. Substantial damage can be produced by high velocity flows, particularly in harbors and bays, even when the wave height is small. Besides, an accurate simulation of tsunami flow velocities and accelerations is fundamental for advancing in the study of tsunami sediment transport. These considerations made the National Tsunami Hazard Mitigation Program (NTHMP) proposing a benchmark exercise focussed on modeling and simulating tsunami currents. Until recently, few direct measurements of tsunami velocities were available to compare and to validate model results. After Tohoku 2011 many current meters measurement were made, mainly in harbors and channels. In this work we present a part of the contribution made by the EDANYA group from the University of Malaga to the NTHMP workshop organized at Portland (USA), 9-10 of February 2015. We have selected three out of the five proposed benchmark problems. Two of them consist in real observed data from the Tohoku 2011 event, one at Hilo Habour (Hawaii) and the other at Tauranga Bay (New Zealand). The third one consists in laboratory experimental data for the inundation of Seaside City in Oregon.Acknowledgements: This research has been partially supported by the Junta de Andalucía research project TESELA (P11-RNM7069) and the Spanish Government Research project DAIFLUID (MTM2012-38383-C02-01) and Universidad de Málaga, Campus de Excelencia Andalucía TECH. The GPU and multi-GPU computations were performed at the Unit of Numerical Methods (UNM) of the Research Support Central Services (SCAI) of the University of Malaga

Numerical tool for tsunami risk assessment in the southern coast of Dominican Republic

The southern coast of Dominican Republic is a very populated region, with several important cities including Santo Domingo, its capital. Important activities are rooted in the southern coast including tourism, industry, commercial ports, and, energy facilities, among others. According to historical reports, it has been impacted by big earthquakes accompanied by tsunamis as in Azua in 1751 and recently Pedernales in 2010, but their sources are not clearly identified. The aim of the present work is to develop a numerical tool to simulate the impact in the southern coast of the Dominican Republic of tsunamis generated in the Caribbean Sea. This tool, based on the Tsunami-HySEA model from EDANYA group (University of Malaga, Spain), could be used in the framework of a Tsunami Early Warning Systems due the very short computing times when only propagation is computed or it could be used to assess inundation impact, computing inundation with a initial 5 meter resolution. Numerical results corresponding to three theoretical sources are used to test the numerical tool.This research has been partially supported by the Spanish Government Research project SIMURISK (MTM2015-70490-C2-1-R), the Junta de Andalucía research project TESELA (P11-RNM7069), and Universidad de Málaga, Campus de Excelencia Internacional Andalucía Tech. The GPU and multi-GPU computations were performed at the Unit of Numerical Methods (UNM) of the Research Support Central Services (SCAI) of the University of Malaga

Un modelo 1D NPZ de acoplamiento entre la hidrodinámica y los flujos biogeoquímicos en estrechos bicapa. Aplicación a la dinámica mareal en el Estrecho de Gibraltar

Los modelos NPZ (siglas para Nutrientes-Fitoplancton-Zooplancton en inglés) son comúnmente utilizados en estudios de biología marina. Este tipo de modelos utiliza un conjunto de ecuaciones diferenciales muy sencillo para definir la dinámica del plancton marino. Las variables de estado de las cuales se modeliza su evolución son los nutrientes, el fitoplancton y el zooplankton, esto se hace en términos de su contenido de nitrógeno, ya que este compuesto el que normalmente limita la producción primaria en el océano. En este trabajo se implementa el acoplado de un modelo NPZ para el modelado de los flujos biogeoquímicos con un modelo de aguas poco profundas bicapa para la hidrodinámica. El objetivo es aplicar este modelo a la simulación de flujos biogeoquímicos en el Estrecho de Gibraltar con imposición de la dinámica mareal.1) Proyecto DAIFLUID. Plan Nacional MTM2012-38383-C02-01. 2) Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

Non-linear shallow water models for coastal run-up simulations

Shallow water models are frequently used to simulate ocean or coastal circulation or tsunami wave propagation. But these models are seldom used to explicitely reproduce for example tsunami wave run-up into coast. In this work we porpose an implementation of dry/wet areas for shallow water models that allow to reproduce coastal inundation and water retrainment once the impact wave passes over. The run-up model has been tested for simple test cases and geometries as in complex, real cases, as the Lituya Bay 1958 megatsunami.Proyecto DAIFLUID - Plan Nacional de I+D (MEC/FEDER) Referencia MTM2012 / TESELA - Proyecto de Excelencia de la Junta de Andalucía (convocatoria 2011) Referencia P11 - RNM7069 / Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

HySEA model verification for Tohoku 2011 Tsunami. Application for mitigation tsunami assessment

In many aspects Tohoku-Oki 2011 mega tsunami has changed our perception of tsunami risk. The tsunami-HySEA model is used to numerically simulate this event and observed data will we used to verify the model results. Three nested meshes of enhanced resolution (4 arc-min, 32 arc-sec and 2 arc-sec) will be used by the numerical model. The propagation mesh covers all Pacific Ocean with more of 7 million cells. An intermediate mesh with 5 millions cells contains the Japanese archipelago and, finally, two finer meshes, with nearly 8 and 6 millions cells, cover Iwate and Miyagi Prefectures at Tohoku region, the most devastated areas hit by the tsunami. The presentation will focus on the impact of the tsunami wave in these two areas and comparisons with observed data will be performed. DART buoys time series, inundation area and observed runup is used to assess model performance. The arrival time of the leading flooding wave at the vicinity of the Senday airport, as recorded by video cameras, is also used as verification data for the model. After this tsunami, control forests as well as breakwaters has been discussed as suitable mitigation infrastructures. As particular case, we will analyse the evolution of the tsunami in the area around the Sendai airport (Miyagi Prefecture) and its impact on the airport. A second simulation has been performed, assuming the existence of a coastal barrier protecting the area. The role of this barrier in modifying tsunami wave evolution and mitigating flooding effects on the airport area are discussed. The protection effect of the breakwaters near Kamaishi (Iwate Prefecture) is also assessed. The numerical model shows how these structures, although did not provide a full protection to tsunami waves, they helped to largely mitigate its effects in the area.Acknowledgements. This research has been partially supported by the Junta de Andalucía research project TESELA (P11-RNM7069), the Spanish Government Research project DAIFLUID (MTM2012-38383-C02-01) and Universidad de Málaga, Campus de Excelencia Internacional Andalucía Tech. The multi-GPU computations were performed at the Laboratory of Numerical Methods (University of Malaga)

Use of Neural Networks for Tsunami Maximum Height and Arrival Time Predictions

Operational TEWS play a key role in reducing tsunami impact on populated coastal areas around the world in the event of an earthquake-generated tsunami. Traditionally, these systems in the NEAM region have relied on the implementation of decision matrices. The very short arrival times of the tsunami waves from generation to impact in this region have made it not possible to use real-time on-the-fly simulations to produce more accurate alert levels. In these cases, when time restriction is so demanding, an alternative to the use of decision matrices is the use of datasets of precomputed tsunami scenarios. In this paper we propose the use of neural networks to predict the tsunami maximum height and arrival time in the context of TEWS. Different neural networks were trained to solve these problems. Additionally, ensemble techniques were used to obtain better results.This work was funded by “Innovative ecosystem with artificial intelligence for Andalusia 20205” project of CEI Andalucía Tech and University of Málaga, UMA-CEIATECH-05. The numerical results presented in this work were performed with the computational resources provided by the Spanish Network for Supercomputing (RES) grants AECT-2020-1-0009 and AECT-2020-2-0001. Finally, this research has been partially supported by the Spanish Government research project MEGAFLOW (RTI2018-096064-B-C21), ChEESE project (EU Horizon 2020, grant agreement N. 823844), and eFlows4HPC project (funded by the EuroHPC JU under contract 955558 and the Ministerio de Ciencia e Innovación, Spain). Partial funding for open access charge: Universidad de Málag

HySEA: An operational GPU-based model for Tsunami Early Warning Systems

HySEA numerical model for the simulation of earthquake generated tsunamis is presented. The initial sea surface deformation is computed using Okada model. Wave propagation is computed using nonlinear shallow water equations in spherical coordinates, where coastal inundation and run-up are suitable treated in the numerical algorithm. Generation, propagation and inundation phases are all integrated in a single code and computed coupled and synchronously when they occur at the same time. Inundation is modelled by allowing cells to dynamically change from dry to wet and reciprocally when water retreats from wetted areas. Special effort is made in preserving model well-balanced (i.e. capturing small perturbations to the steady state of the ocean at rest). The GPU model implementation allows faster than real time (FTRT) simulation for real large-scale problems. The large speed-ups obtained make HySEA code suitable for its use in Tsunami Early Warning Systems. The Italian TEWS at INGV (Rome) has adopted HySEA GPU code for its National System. The model is verified by hindcasting the wave behaviour in several benchmark problems. Numerical results for an earthquake-generated tsunami in the Mediterranean Sea is presented and computing time analysed. The interest of using higher order methods, analysing numerical schemes from first order up to order five, in the context of TEWS, is also addressed. Tsunami codes do not usually use higher than second order methods. It is demonstrated that this should idea should be revised.This research has been partially supported by the Junta de Andalucía research project TESELA (P11-RNM7069), the Spanish Government Research project HySEA2 (MTM2009-11923) and Universidad de Málaga, Campus de Excelencia Internacional Andalucía Tech. The multi-GPU computations were performed at the Laboratory of Numerical Methods (University of Malaga)

Uncertainty quantification in tsunami modeling using multi-level Monte Carlo finite volume method

Shallow-water type models are commonly used in tsunami simulations. These models contain uncertain parameters like the ratio of densities of layers, friction coefficient, fault deformation, etc. These parameters are modeled statistically and quantifying the resulting solution uncertainty (UQ) is a crucial task in geophysics. We propose a paradigm for UQ that combines the recently developed path-conservative spatial discretizations efficiently implemented on cluster of GPUs, with the recently developed Multi-Level Monte Carlo (MLMC) statistical sampling method and provides a fast, accurate and computationally efficient framework to compute statistical quantities of interest. Numerical experiments, including realistic simulations in real bathymetries, are presented to illustrate the robustness of the proposed UQ algorithm

The Lituya Bay landslide-generated mega-tsunami – numerical simulation and sensitivity analysis

The 1958 Lituya Bay landslide-generated mega- tsunami is simulated using the Landslide-HySEA model, a recently developed finite-volume Savage–Hutter shallow wa- ter coupled numerical model. Two factors are crucial if the main objective of the numerical simulation is to reproduce the maximal run-up with an accurate simulation of the in- undated area and a precise recreation of the known trimline of the 1958 mega-tsunami of Lituya Bay: first, the accu- rate reconstruction of the initial slide and then the choice of a suitable coupled landslide–fluid model able to reproduce how the energy released by the landslide is transmitted to the water and then propagated. Given the numerical model, the choice of parameters appears to be a point of major im- portance, which leads us to perform a sensitivity analysis. Based on public domain topo-bathymetric data, and on in- formation extracted from the work of Miller (1960), an ap- proximation of Gilbert Inlet topo-bathymetry was set up and used for the numerical simulation of the mega-event. Once optimal model parameters were set, comparisons with ob- servational data were performed in order to validate the nu- merical results. In the present work, we demonstrate that a shallow water type of model is able to accurately reproduce such an extreme event as the Lituya Bay mega-tsunami. The resulting numerical simulation is one of the first successful attempts (if not the first) at numerically reproducing, in de- tail, the main features of this event in a realistic 3-D basin geometry, where no smoothing or other stabilizing factors in the bathymetric data are applied

Treatment of Soil Contaminated by Mining Activities to Prevent Contamination by Encapsulation in Ceramic Construction Materials

[EN] Mining is an essential activity for obtaining materials necessary for the well-being and development of society. However, this activity produces important environmental impacts that must be controlled. More specifically, there are different soils near new or abandoned mining productions that have been contaminated with potentially toxic elements, and currently represent an important environmental problem. In this research, a contaminated soil from the mining district of Linares was studied for its use as a raw material for the conforming of ceramic materials, bricks, dedicated to construction. Firstly, the contaminated soil was chemically and physically characterized in order to evaluate its suitability. Subsequently, different families of samples were conformed with different percentages of clay and contaminated soil. Finally, the conformed ceramics were physically and mechanically characterized to examine the variation produced in the ceramic material by the incorporation of the contaminated soil. In addition, in this research, leachate tests were performed according to the TCLP method determining whether encapsulation of potentially toxic elements in the soil occurs. The results showed that all families of ceramic materials have acceptable physical properties, with a soil percentage of less than 80% being acceptable to obtain adequate mechanical properties and a maximum of 70% of contaminated soil to obtain acceptable leachate according to EPA regulations. Therefore, the maximum percentage of contaminated soil that can be incorporated into the ceramic material is 70% in order to comply with all standards. Consequently, this research not only avoids the contamination that contaminated soil can produce, but also valorizes this element as a raw material for new materials, avoiding the extraction of clay and reducing the environmental impact.S