A Bayesian network approach to modelling rip current drownings and shore-break wave injuries

Abstract. A Bayesian network (BN) approach is used to model and predict shore-break related injuries and rip-current drowning incidents based on detailed environmental conditions (wave, tide, weather, beach morphology) on the high-energy Gironde coast, southwest France. Six years (2011–2017) of boreal summer (15 June–15 September) surf zone injuries (SZIs) were analysed, comprising 442 (fatal and non-fatal) drownings caused by rip currents and 715 injuries caused by shore-break waves. Environmental conditions at the time of the SZIs were used to train two separate Bayesian networks (BNs), one for rip current drownings and the other one for shore-break wave injuries, each one with a hidden hazard and exposure variables. Both BNs were tested for varying complexity using K-fold cross-validation based on multiple performance metrics. Validation (prediction) results slightly improve predictions of SZIs with a poor to fair skill based on a combination of different metrics. Shore-break related injuries appear more predictable than rip current drowning incidents as the shore-break BN systematically performed better than the rip current BN. Sensitivity and scenario analyses were performed to address the influence of environmental data variables and their interactions on exposure, hazard and resulting life risk. Most of our findings are in line with earlier SZI and physical hazard-based work, that is, that more SZIs are observed for warm sunny days with light winds, long-period waves, with specifically more shore-break related injuries at high tide and for steep beach profiles, and more rip current drownings near low tide with near shore-normal wave incidence and strongly alongshore non-uniform surf zone morphology. The BNs also provided fresh insight, showing that rip current drowning risk is approximately equally distributed between exposure (variance reduction Vr = 14.4 %) and hazard (Vr = 17.4 %), while exposure of water user to shore-break waves is much more important (Vr = 23.5 %) than the hazard (Vr = 10.9 %). Large surf is found to decrease beachgoer exposure to shore-break hazard, while this is not observed for rip currents. Rapid change in tide elevation during days with large tidal range was also found to result in more drowning incidents, presumably because it favors the rapid onset of rip current activity and can therefore surprise unsuspecting bathers. We advocate that such BNs, providing a better understanding of hazard, exposure and life risk, can be developed to improve public safety awareness campaigns, in parallel with the development of more skillful risk predictors to anticipate high life-risk days.