Attitudes, perceived bathing risks and behaviours among recreational users at a high-energy beach in South-West France. A dataset containing human and environmental data, beachgoers and lifeguards assessments.

The dataset provides data on beachgoers' behaviours, attitudes and perceptions of coastal bathing risks at a high energy beach in South-West France [1]. Data were collected from a face-to-face quantitative survey conducted at La Lette Blanche beach, during the lifeguard-patrolled summer period (July-August) 2022 from a sample of 722 visitors. Beachgoers were interviewed across various times of the day (i.

Satellite-derived sandy shoreline trends and interannual variability along the Atlantic coast of Europe.

Monitoring sandy shoreline evolution from years to decades is critical to understand the past and predict the future of our coasts. Optical satellite imagery can now infer such datasets globally, but sometimes with large uncertainties, poor spatial resolution, and thus debatable outcomes. Here we validate and analyse satellite-derived-shoreline positions (1984-2021) along the Atlantic coast of Europe using a moving-averaged approach based on coastline characteristics, indicating conservative uncertainties of long-term trends around 0.

Morphological and ecological responses of a managed coastal sand dune to experimental notches.

In northern Europe, coastal dune remobilization by restoring natural processes is considered by some to maintain the coastal dune in chronically eroding sectors by migrating landward and to restore dune ecology. In wet climatic contexts, this nature-based solution has been shown to induce an increase in both sand bare areas and vegetation diversity. However, it has never been tested in the coastal dunes of southern Europe with a drier climate and, thus, more stressful conditions, where disturbance may inversely decrease vegetation diversity.

Predicting drowning from sea and weather forecasts: development and validation of a model on surf beaches of southwestern France.

Objective: To predict the coast-wide risk of drowning along the surf beaches of Gironde, southwestern France.

Methods: Data on rescues and drownings were collected from the Medical Emergency Center of Gironde (SAMU 33). Seasonality, holidays, weekends, weather and metocean conditions were considered potentially predictive.

16 years of topographic surveys of rip-channelled high-energy meso-macrotidal sandy beach.

Sandy beaches are highly dynamic environments buffering shores from storm waves and providing outstanding recreational services. Long-term beach monitoring programs are critical to test and improve shoreline, beach morphodynamics and storm impact models. However, these programs are relatively rare and mostly restricted to microtidal alongshore-uniform beaches.

Blind testing of shoreline evolution models.

Beaches around the world continuously adjust to daily and seasonal changes in wave and tide conditions, which are themselves changing over longer time-scales. Different approaches to predict multi-year shoreline evolution have been implemented; however, robust and reliable predictions of shoreline evolution are still problematic even in short-term scenarios (shorter than decadal). Here we show results of a modelling competition, where 19 numerical models (a mix of established shoreline models and machine learning techniques) were tested using data collected for Tairua beach, New Zealand with 18 years of daily averaged alongshore shoreline position and beach rotation (orientation) data obtained from a camera system.

Characteristics of drowning victims in a surf environment: a 6-year retrospective study in southwestern France.

Background: Drowning is the third cause of non-intentional injury death worldwide. Beaches of Gironde, in southwestern France, are exposed to strong environmental conditions, leading to rip currents and shore breaks. Bathing season usually lasts from April to October and is supervised from June till mid-September.

Author Correction: Quantifying uncertainties of sandy shoreline change projections as sea level rises.

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Quantifying uncertainties of sandy shoreline change projections as sea level rises.

Sandy shorelines are constantly evolving, threatening frequently human assets such as buildings or transport infrastructure. In these environments, sea-level rise will exacerbate coastal erosion to an amount which remains uncertain. Sandy shoreline change projections inherit the uncertainties of future mean sea-level changes, of vertical ground motions, and of other natural and anthropogenic processes affecting shoreline change variability and trends.