Monitoring swimmer safety

Practical Applications

The muienradar website is in first instance intended for use by lifeguards and other authorities involved with swimmer safety on beaches. The predictions of the nearshore hydrodynamics are yet to be fully validated and more experience with the forecast system needs now to be gained.

  1. Egmond Beach
  2. Other applications

Egmond Beach

In a pilot study, a forecast system for Egmond Beach was set up. The lifeguards of Egmond aan Zee have identified a strong rip current as the biggest risk for swimmers on this beach. This rip current is located in a channel that interrupts the sand bar just north of the lifeguard station. In the summer of 2010, the lifeguards attributed the rescue of 16 people to this single rip current. Therefore, they feel the need to reduce the risk arising from this rip current.

The forecasts for Egmond Beach are produced with the fully automated Coastal Storm Modelling System (CoSMoS) developed by Deltares. CoSMoS is a Matlab-based shell, which schedules jobs to download real-time data from online databases, pre-process model input, start model simulations, post-process the output and send the results to a website. The workflow of CoSMoS consists of the main loop governing the job scheduling and facilitating data downloading and storage, whereas the model loop controls the different, possibly nested, model simulations. The interval of the main loop depends on the availability of forecast data and duration of model simulations and is 24 hours for the Egmond application. The forecast window depends on the available model boundary data (i.e. meteorological input) and is 2 days for this case.

To achieve sufficient model resolution in the nearshore zone, a nested model train is used. The different models incorporate the effect of tides, waves and meteorological forcing. After running the model loop, the results of the detailed computation are presented as map fields, time series and dedicated rip current warnings. To generate the warnings, the offshore directed current velocities are translated into rip current strength and location and presented as time-stack images. The post-processed model results and warnings are automatically published on the website, where they are visualized in a Google Earth viewer. The compressed model results will in future also be stored on the OpenDAP server for public access.

Other applications

Real-time predictions of nearshore hydrodynamics may be of value in coastal applications other than swimmer safety. Parties interested in nearshore predictions can for instance be:

  • Coastal zone managers who wish to monitor coastal erosion, beach maintenance, recreation, flood hazards;
  • Harbour authorities who want to monitor navigation safety;
  • Contractors and dredging companies who work in the coastal zone and need to schedule works and assess environmental impacts.

The requirements for a new application are:

  • Development of a model system, or, if larger-scale ambient models are available, a detailed local model;
  • Development of a dedicated website;
  • (Network of) PC(s) with sufficient computational capacity and internet infrastructure;
  • Preferably in-situ measurements for validation of the model predictions, or even data-assimilation;
  • In case the local bathymetry is dynamic and not routinely surveyed, an (Argus) camera system can possibly be a solution to monitor the morphology.

The average beach visitor has little knowledge about rips and is usually unable to identify these dangerous currents. In future, the website can therefore also serve as a tool to educate and warn the public. To reach a larger community, the warnings can be distributed through mobile apps, local television stations, at hotels and camp sites or on information panels.

Lessons learned

  • Involve the end users from the start of the project in the development of the website in order to meet their requirements;
  • ‘Ease of access’ and ‘simplicity’ are two key requirements to achieve integration of the forecasts in the daily routine of the lifeguards.
  • Pay attention to the IT facilities at the client side; an inferior internet connection, low screen resolution or slow PC can affect the performance and user perception of the website;
  • The end users are not necessarily familiar with understanding model results and valuing model uncertainties. Communication and education on how to interpret the forecasts is crucial to make the project successful.