Analysis of incidents on New Zealand beaches

Mick Kearney¹, Juliana Albertoni de Miranda¹, Nelis Drost², Laura Read³, Prof Giovanni Coco³
1 SurfLife Saving New Zealand
2 Center for eResearch
3 School of Environment

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Analysis of incidents on New Zealand beaches

Muriwai,,Nzl,-,Jan,01,2015:new,Zealand,Woman,Lifeguard,On

Introduction

Beaches are a popular destination for recreational activities such as swimming, surfing, and sunbathing, and they are an important source of economic revenue for countries with coastal regions. However, beaches can also pose significant safety risks, with water-related incidents leading to injuries and deaths each year (World Health Organization, 2014). Despite the risks associated with beaches, they remain a popular destination for locals and tourists alike, and it is crucial to ensure that they are safe for everyone. Beach incidents can have a profound impact on individuals and their families, as well as on society as a whole. In addition to the physical and emotional tolls of injuries and deaths, beach incidents can also result in significant economic costs, including healthcare expenses and lost productivity.

Globally, research has focused on several aspects of beach incidents, but the main hazard to humans occurring on open coast beaches is identified with the presence of rip currents, while other hazards related to beach activities tend to play a minor role. Short and Hogan (1994) reported that around 70% of along the coast of New South Wales were dominated by the presence of rips, and that 89% of rescues on those beaches were related to rip currents. A more recent study dealing with the whole Australian coast reported similar findings (Brighton et al., 2013). Similarly, Scott et al. (2007) analysed beach rescue statistics in Southwest England and found that over 70% of recorded accidents were due to rip currents, which were usually present at low tide. Similar findings were reported by other authors, including, for example, Klein et al. (2003) for the coast of Southern Brazil and (Arun Kumar and Prasad, 2014) for the coast of India. Studies have also analysed in detail the demographics of victims showing that male teenagers tend to be the most likely group subject to incidents (Gensini, and Ashley, 2010, Woodward et al., 2013; Segura et al., 2022). Koon et al. (2018) looked at the oceanic conditions leading to rescue and found that the frequency of incidents increased with wave height up to a certain value of wave beyond which (i.e., very large waves) the frequency of rescues actually decreases. Additionally, Koon et al., (2023) showed that fatal drownings are more likely to occur for low water levels.

New Zealand is home to numerous picturesque beaches that attract both locals and tourists. The beach culture in New Zealand is deeply ingrained, with activities such as surfing, swimming, and sunbathing being extremely popular. The tourism industry is also heavily dependent on the country’s beaches, with visitors drawn to New Zealand’s stunning coastline and pristine waters. Surf Life Saving New Zealand (SLSNZ) is a non-profit organization that aims to promote beach safety and reduce the incidence of drowning and injury in New Zealand. SLSNZ provides essential services such as lifeguard patrols, public education campaigns, and emergency response services. In addition to providing essential lifeguard services and emergency response, SLSNZ collects report/data forms on beach incidents, providing valuable insights into the risks and challenges managing New Zealand beaches.

Moran and Webber (2014) used report forms from SLSNZ to analyse the type of injuries occurring on New Zealand beaches and concluded that over 80% of injuries were minor and of recreational nature. Also, as reported in Brigthton et al (2013), data from SLSNZ indicates an average of 800 rip-related rescues per year, corresponding to almost 50% of all rescues.

Analysing incident data reported by SLSNZ can help identify trends and risk factors, informing strategies for prevention and improving beach safety for all. In this paper, we will analyse the incidents reported by SLSNZ, focusing on the types of incidents, their frequency and severity, and the associated environmental factors.

Data and methodology

The study is based on an analysis of 38310 Incident Report Forms (IRFs) collected by SLSNZ over the summer season from the year 2000 until 2020 (the data collection programme is ongoing) for a variety of beaches around New Zealand (Figure 1). IRFS are routinely completed by SLSNZ lifeguards and include a variety of information related to the incident: the date/time when it occurred, the level of severity, the type of activity being performed when the incident occurred (e.g., running or surfing), the reason for the incident (e.g., rip current or equipment failure), the visually estimated wave height and the weather conditions. The incident severity level involved 5 possibilities: (1) No treatment/Unknown, (2) First Aid/Rescue, (3) Sent to doctor, (4) Ambulance/Life threatening, (5) Deceased. Overall, we used 38310 IRFs for analysis. Because of the limitations in the visual estimate of wave height in the IRFs, we used a validated hindcast (Albuquerque et al., 2021; https://coastalhub.science/data) to extract wave characteristics (significant wave height, peak wave period and mean wave angle) for each of the incidents. While the use of the hindcast data allowed for a better characterization of wave conditions, it also reduced the dataset to the period over which the data was available (1993-2020). Tidal stage for each of the incidents was derived from a model developed by the National Institute of Water and Atmosphere (NIWA, https://tides.niwa.co.nz/). Given the large number of IRFs available, algorithms were generated for both the waves and the tides, to extract the time and location of the incident from the database and automatically obtain wave characteristics and tidal conditions. IRFs that did not provide the incident time were discarded.

Each beach was analysed individually and compared to its “beach cluster”, where a cluster comprises every beach that falls within a 20 km distance. We have also specifically searched and reported on the role of rip currents, which represent the majority of the incidents (9427 rip incidents out of a total of 38310 incidents).

Figure 2. Number of incidents for different severity levels against wave conditions at Raglan beach: significant wave height (a), peak wave period (b), angle of wave approach (c) from the hindcast model. Circle area is proportional to the number of incidents, not consistent between variables (see scale in each subplot). Each subplot shows the incidents that occurred at a specific club (orange), the cluster related to nearby clubs/beaches (green), and data from all clubs/beaches combined (grey). Circles are randomly shifted vertically to facilitate visualization of overlapping circles. Incident severity: (1) No treatment/Unknown, (2) First Aid/Rescue, (3) Sent to doctor, (4) Ambulance/Life threatening, (5) Deceased.

Figure 3. Incident distribution versus significant wave height (a), peak wave period (b), and wave direction (c) at Muriwai beach. In (a) and (b) the left axis indicated the number of incidents and the right axis refers to the relative probability of occurrence. The lines represent kernel-density plots of all incidents (blue), rip incidents (orange), wave conditions in summer (grey) and winter (grey dashed). All lines are normalized so that the total area under the curve is 1.

Figure 4. Relative probability of incident distribution versus significant wave height (left panel), peak wave period (middle panel), and wave direction (right panel) at Opotiki Beach. See caption of Figure 3 for details.

Figure 5. Incident severity (a) and Incident Likelihood (b) as a result of tidal conditions for Hot Water Beach. See caption of Figure 2 for details of subplot (a). The lines in (b) represent all incidents (blue) and rip incidents (orange),

Discussion

This is the first study that uses IRFs collected by SLSNZ to systematically addresses the association between incident levels and oceanic (waves and tides) conditions. The beaches studied encompass the whole of New Zealand although more data is available for the more touristy beaches of the North Island (Figure 1). The use of IRFs has the advantage of standardizing the reports and so making them comparable between different beaches. Nevertheless, despite the attempt to prescribe all possible incident details in the IRF, the present version contains some limitations. For example, the IRF does not specifically request information on the role of rip currents on the incident. At present, such information is only provided in a space left for additional information about the incident. As a result, it is possible that some rip-related incidents have not actually been reported. In any case, the use of IRFs remains a tremendous tool to improve our understanding of incidents and we can anticipate increasing benefits from continued and improved collection of IRFs.

Conclusions

Our analysis of 38310 incidents Incident Report Forms indicates large similarities in the distribution of incident levels between beaches despite being characterized by different wave exposure and tidal conditions. Data shows clear similarities between the distribution of the wave climate and incident levels, with incidents more often associated to average rather than extreme conditions. Also, it appears evident that both all incidents including rip-related ones, the most common type of incident, are more likely to occur around low tide. There is also large variability around these findings as other local factors are likely to be relevant and determine the occurrence of an incident. This study was possible thanks to the availability of a large number of Incident Report Forms, that provide an incredible record of beach hazard occurrences. It is possible to envisage that IRFs could be further analysed to manage each beach and optimize the use of resources (e.g., number of lifeguards patrolling a beach) and increase awareness of beach hazards.

References:

Albuquerque, J., Antolínez, J.A., Gorman, R.M., Méndez, F.J. and Coco, G., 2021. Seas and swells throughout New Zealand: A new partitioned hindcast. Ocean Modelling, 168, p.101897.
Arun Kumar, S.V.V. and Prasad, K.V.S.R., 2014. Rip current-related fatalities in India: a new predictive risk scale for forecasting rip currents. Natural hazards, 70, pp.313-335.
Brighton, B., Sherker, S., Brander, R., Thompson, M. and Bradstreet, A., 2013. Rip current related drowning deaths and rescues in Australia 2004–2011. Natural hazards and earth system sciences, 13(4), pp.1069-1075.
Gensini, V.A. and Ashley, W.S., 2010. An examination of rip current fatalities in the United States. Natural Hazards, 54, pp.159-175.
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