Números y Realidad. Utilizando las matemáticas para modelar nuestro entorno

Unos de los secretos que esconde el cálculo de ecuaciones es la capacidad para diseñar planes de prevención antes catástrofes medioambientales. El grupo EDANYA ha elaborado un modelo de previsión para zonas de riesgo como el Estrecho de Gibraltar a partir de su análisis matemático

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

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)

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)

2D GPU-based HySEA model for tsunami simulation. Some practical examples.

A two-waves TVD-WAF type scheme for solving 2D shallow-water equation is considered together with a first and second order HLL scheme. Comparison among the different schemes will be performed to check the performance for the proposed one. A description of the GPU implementation will be presented as well as some applications to tsunami simulation in real topo-bathymetries.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Deslizamientos submarinos y tsunamis en el Mar de Alborán. Un ejemplo de modelización numérica

Texto científico de carácter divulgativo.Texto científico de carácter divulgativo en el que se presenta un trabajo de modelado matemático y simulación numérica de un hipotético tsunami producido en el Mar de Alborán por un deslizamiento masivo de materiales en el flanco sur de la Dorsal de Alborán.Instituto Español de Oceanografía. Universidad de Málaga

The Making of the NEAM Tsunami Hazard Model 2018 (NEAMTHM18)

ABSTRACT: The NEAM Tsunami Hazard Model 2018 (NEAMTHM18) is a probabilistic hazard model for tsunamis generated by earthquakes. It covers the coastlines of the North-eastern Atlantic, the Mediterranean, and connected seas (NEAM). NEAMTHM18 was designed as a three-phase project. The first two phases were dedicated to the model development and hazard calculations, following a formalized decision-making process based on a multiple-expert protocol. The third phase was dedicated to documentation and dissemination. The hazard assessment workflow was structured in Steps and Levels. There are four Steps: Step-1) probabilistic earthquake model; Step-2) tsunami generation and modeling in deep water; Step-3) shoaling and inundation; Step-4) hazard aggregation and uncertainty quantification. Each Step includes a different number of Levels. Level-0 always describes the input data; the other Levels describe the intermediate results needed to proceed from one Step to another. Alternative datasets and models were considered in the implementation. The epistemic hazard uncertainty was quantified through an ensemble modeling technique accounting for alternative models' weights and yielding a distribution of hazard curves represented by the mean and various percentiles. Hazard curves were calculated at 2,343 Points of Interest (POI) distributed at an average spacing of ∼20 km. Precalculated probability maps for five maximum inundation heights (MIH) and hazard intensity maps for five average return periods (ARP) were produced from hazard curves. In the entire NEAM Region, MIHs of several meters are rare but not impossible. Considering a 2% probability of exceedance in 50 years (ARP≈2,475 years), the POIs with MIH >5 m are fewer than 1% and are all in the Mediterranean on Libya, Egypt, Cyprus, and Greece coasts. In the North-East Atlantic, POIs with MIH >3 m are on the coasts of Mauritania and Gulf of Cadiz. Overall, 30% of the POIs have MIH >1 m. NEAMTHM18 results and documentation are available through the TSUMAPS-NEAM project website (http://www.tsumaps-neam.eu/), featuring an interactive web mapper. Although the NEAMTHM18 cannot substitute in-depth analyses at local scales, it represents the first action to start local and more detailed hazard and risk assessments and contributes to designing evacuation maps for tsunami early warning

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London