4.2 Article

Rip Current Prediction: Development, Validation, and Evaluation of an Operational Tool

Journal

JOURNAL OF COASTAL RESEARCH
Volume 29, Issue 2, Pages 283-300

Publisher

COASTAL EDUCATION & RESEARCH FOUNDATION
DOI: 10.2112/JCOASTRES-D-12-00093.1

Keywords

Macrotidal; XBeach; surf zone; drifter; modeling; hazard; tide; wave dissipation

Funding

  1. Natural Environment Research Council (NERC)-RNLI [NE/H004262/1: DRIBS]
  2. NERC [NE/H004262/1] Funding Source: UKRI
  3. Natural Environment Research Council [NE/H004262/1] Funding Source: researchfish

Ask authors/readers for more resources

Austin, M.J.; Scott, T.M.; Russell, P.E., and Masselink, G., 2013. Rip current prediction: development, validation, and evaluation of an operational tool. Journal of Coastal Research, 29(2), 283-300. Coconut Creek (Florida), ISSN 0749-0208. This contribution details the development, validation, and evaluation of an operational rip current prediction tool. Field measurements of rip current dynamics from a macrotidal beach in the southwest U.K. collected over 87 tidal cycles indicate that the rip currents are highly dynamic over a range of temporal and spatial scales. The morphology of the lower intertidal beach face provides the primary spatial control of the rip currents, whereas the variation in the pattern of wave dissipation due to the tidal translation of the surf zone at spring-neap and semidiurnal frequencies is the principle temporal control. The Lagrangian drift pattern associated with the rip currents displays three key behaviors: rotation, alongshore, and exit. Rotation and exit are observed under moderate conditions, whereas strong alongshore-directed currents prevail during energetic conditions. An operational regional wave model is used to force a two-dimensional horizontal (2D-H) nonstationary model for coupled wave propagation and flow to predict the rip current speed and behavior. The model is calibrated using measured Eulerian field data, and the resultant circulation patterns are validated against measured Lagrangian data. The model was run for a 2-month hindcast period, and the flow speed and behavioral output were combined to allocate a rip current hazard rating. The model performance was evaluated against beach lifeguard incident statistics; 64% of recorded incidents occurred under predicted high-risk conditions, and 36% occurred during medium-risk conditions. The rip hazard prediction model was subsequently run in forecast mode to provide an example of operational-type output.

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