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

Abstract

ObjectiveTo predict the coast-wide risk of drowning along the surf beaches of Gironde, southwestern France.MethodsData 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. Logistic regression models were fitted with data from 2011 to 2013 and used to predict 2015–2017 events employing weather and ocean forecasts.ResultsAir temperature, wave parameters, seasonality and holidays were associated with drownings. Prospective validation was performed on 617 days, covering 232 events (rescues and drownings) reported on 104 different days. The area under the curve (AUC) of the daily risk prediction model (combined with 3-day forecasts) was 0.82 (95% CI 0.79 to 0.86). The AUC of the 3-hour step model was 0.85 (95% CI 0.81 to 0.88).ConclusionsDrowning events along the Gironde surf coast can be anticipated up to 3 days in advance. Preventative messages and rescue preparations could be increased as the forecast risk increased, especially during the off-peak season, when the number of available rescuers is low.

Environmental controls on lifeguard-estimated surf-zone hazards, beach crowds, and resulting life risk at a high-energy sandy beach in southwest France

“…This will also allow inclusion of more weekday data. Indeed, with only nearly nine weeks of data, our findings on the influence of weekday on beach attendance (Figure 5d) are unclear while previous work showed that weekday is important to life risk at the beach [61]. Given our understanding in rip current dynamics, previous modelling work and the relative alongshore uniformity of bar/rip morphology, developing an hourly or daily rip current hazard predictor based on wave and tide predictions should be relatively straightforward.…”

Environmental controls on lifeguard-estimated surf-zone hazards, beach crowds, and resulting life risk at a high-energy sandy beach in southwest France

“…This will also allow inclusion of more weekday data. Indeed, with only nearly nine weeks of data, our findings on the influence of weekday on beach attendance (Figure 5d) are unclear while previous work showed that weekday is important to life risk at the beach [60]. Given our understanding in rip current dynamics, previous modelling work and the relative alongshore uniformity of bar/rip morphology, developing an hourly or daily rip current hazard predictor based on wave and tide predictions should be relatively straightforward.…”