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

Abstract

Sensitivity of rip current forecasts to errors in remotely-sensed bathymetry Radermacher, M.; de Schipper, M. A.; Reniers, A. J.H.M. A B S T R A C TOperational 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 remotelysensed 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.

Modelling camera viewing angle deviation to improve nearshore video monitoring

“…If not corrected, significant errors are introduced when analyzing remotelysensed hydrodynamic data such as longshore currents, run-up or wave celerity. At the Sand Motor, a mega-scale beach nourishment in the Netherlands, Radermacher et al (2018) observed important errors in the remotely-sensed bathymetry depending on camera graze angles.…”

“…Such movements are likely to occur for a certain number of outdoor installations (Holman and Stanley, 2007;Pearre and Puleo, 2009;Radermacher et al, 2018;Vousdoukas et al, 2011). Thereby, each image requires a specific geometry solution (tilt, roll and azimuth value) calculated after acquisition assuming camera location and intrinsic parameters remain the same.…”

Quantifying Optically Derived Two-Dimensional Wave-Averaged Currents in the Surf Zone

“…Wave-averaged currents are a fundamental driver of numerous nearshore processes, including rip currents that claim lives [1], alongshore currents impacting ecosystem health and pollutant transport [2], and flow gradients altering nearshore morphology [3]. Flows can be forced by breaking wave momentum [4], pressure gradients, and low-frequency motions [5].…”

“…Although present techniques can filter, average, and smooth velocities to retain realistic alongshore flows [13,17,20], the data file sizes and associated computing power necessary for processing prohibits continuous monitoring, timely assimilation to now-cast hydrodynamic models, and real-time early warning systems of persistent and transient rip currents. The objectives of this work are (1) to define an alternate approach, referred to henceforth as WAMFlow, to remotely derive flow features at spatial and temporal scales larger than turbulent structures associated with individual waves (Section 2), (2) to validate the method with drifter deployments that contextualize the spatial variability in flow (Section 3), and (3) to highlight the potential for the technique to contribute new insights to surf zone hydrodynamics (Section 4).…”

Updates to and Performance of the cBathy Algorithm for Estimating Nearshore Bathymetry from Remote Sensing Imagery

“…In terms of drivers or boundary conditions, hydrodynamics such as wave conditions or tides are often measured frequently or can be approximated relatively accurately through wave or tidal models. Bathymetry, on the other hand, is often unknown or outdated, such that numerical models, that are all sensitive to bathymetry accuracy, will perform poorly and cannot be trusted [4,5]. This is a particular problem, as the focus shifts to coastal response of the world's coastlines to climate change [6,7].…”