Sea level rise, a consequence of climate change, is one of the biggest challenges that countries and regions with coastal lowlands will face in the medium term. This study proposes a methodology for assessing the vulnerability to sea-level rise on the Atlantic coast of mainland Portugal. Some scenarios of extreme sea levels for different return periods and extreme flooding events were estimated for 2050 and 2100, as proposed by the European Directive 2007/60/EC. A set of physical parameters are considered for the multi-attribute analysis based on the Analytic Hierarchy Process, in order to define a Physical Vulnerability Index fundamental to assess coastal vulnerability. For each sea-level rise scenario, coastal vulnerability maps, with a spatial resolution of 20 m, are produced at a national scale to identify areas more vulnerable to sea-level rise, which are key elements for triggering adaptation plans for such vulnerable regions. For 2050 and 2100, it is estimated that there will be 903 and 1146 km² of vulnerable areas, respectively; the Lisbon district being identified as the most vulnerable in both scenarios. Results are available as a Web Map Service for the Portuguese public entities, and through a web map viewer for the public and communities in general.

In recent months, omicron (B.1.1.529) became the dominant variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), displaying some degree of immune evasion.¹ The initial omicron subvariants, BA.1 and BA.2, are being progressively displaced by BA.5 in many countries, possibly owing to greater transmissibility and partial evasion of BA.1- and BA.2-induced immunity.^2,3 The protection afforded by BA.1 against infection by the BA.5 subvariant is critical because adapted vaccines under clinical trials are based on BA.1.

In this study, we present 10 m resolution tsunami flooding maps for Lisbon downtown and the Tagus estuary. To compute these maps we use the present bathymetry and topographic maps and a reasonable estimate for the maximum credible tsunami scenario. Tsunami modeling was made with a non-linear shallow water model using four levels of nested grids. The tsunami flood is discussed in terms of flow depth, run-up height and maximum inundation area. The results show that, even today, in spite of the significant morphologic changes in the city river front after the 1755 earthquake, a similar event would cause tsunami flow depths larger than one meter in a large area along the Tagus estuary and Lisbon downtown. Other areas along the estuary with a high population density would also be strongly affected. The impact of the tide on the extent of tsunami inundation is discussed, due to the large amplitude range of the tide in Lisbon, and compared with the historical descriptions of the 1755 event. The results presented here can be used to identify the potential tsunami inundation areas in Lisbon; this identification comprises a key element of the Portuguese tsunami emergency management system.

Portugal’s mainland has hundreds of thousands of people living in the Atlantic coastal zone, with numerous high economic value activities and a high number of infrastructures that must be adapted and protected from natural coastal hazards, namely, extreme storms and sea level rise (SLR). In the context of climate change adaptation strategies, a reliable and accurate assessment of the physical vulnerability to SLR is crucial. This study is a contribution to the implementation of flooding standards imposed by the European Directive 2007/60/EC, which requires each member state to assess the risk associated to SLR and floods caused by extreme events. Therefore, coastal hazard on the Atlantic Coast of Portugal’s mainland was evaluated for 2025, 2050, and 2100 over the whole extension due to SLR, with different sea level scenarios for different extreme event return periods. A coastal probabilistic flooding map was produced based on the developed probabilistic cartography methodology using geographic information system (GIS) technology. The Extreme Flood Hazard Index (EFHI) was determined on probabilistic flood bases using five probability intervals of 20% amplitude. For a given SLR scenario, the EFHI is expressed, on the probabilistic flooding maps for an extreme tidal maximum level, by five hazard classes ranging from 1 (Very Low) to 5 (Extreme).