Sensitivity of rip current forecasts to errors in remotely-sensed bathymetry

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Operational nearshore current forecasts based on numerical model simulations are gaining popularity as a measure to increase the safety of swimmers. Applying remotely-sensed bathymetry in these model simulations is often proposed in order to cope with rapidly changing nearshore bathymetry. Errors in the remotely-sensed bathymetry may negatively affect performance of the hydrodynamic model. Hence, this study aims to determine the sensitivity of modelled nearshore currents (with a strong focus on rip currents) to errors in remotely-sensed bathymetries. The errors in the remotely-sensed bathymetries (depth inversion algorithm applied to video stream) were quantified with a length scale-aware validation technique, providing useful insights in the contribution of pattern and amplitude errors to the total error throughout the analysis domain and over a range of bathymetric length scales. Subsequently, simulations with a nearshore hydrodynamic model were performed, using both in-situ and remotely-sensed bathymetries as an input. A comparison of predicted rip currents on either bathymetry yielded performance statistics for operational current forecasts on remotely-sensed bathymetries, taking the model with in-situ bathymetry as a reference. Linking these performance statistics back to the quantified errors in the remotely-sensed bathymetry finally revealed the relation between errors in flow and bathymetry. Of all rip currents generated on an in-situ bathymetry, 55% were reproduced on the remotely-sensed bathymetry, showing that models predicting nearshore currents on remotely-sensed bathymetry have predictive value. Positive rip current predictions were promoted significantly by accurate reproduction of the pattern and amplitude of nearshore bars at length scales between 200 and 400 m. In contrast to the length-scale aware validation technique applied here, commonly used domain-wide bulk error metrics lack important information about spatial variations in the quality of remotely-sensed bathymetry.

Original languageEnglish
Pages (from-to)66-76
Number of pages11
JournalCoastal Engineering
Publication statusPublished - 1 May 2018


  • Depth inversion
  • Numerical modeling
  • Remote sensing
  • Rip currents
  • Sand motor
  • Swimmer safety

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