New Perspectives for Nonlinear Depth‐Inversion of the Nearshore Using Boussinesq Theory
Kévin Martins, Philippe Bonneton, O. de Viron, Ian L. Turner, Mitchell D. Harley, Kristen D. Splinter
Abstract
Abstract Accurately mapping the evolving bathymetry under energetic wave breaking is challenging, yet critical for improving our understanding of sandy beach morphodynamics. Though remote sensing is one of the most promising opportunities for reaching this goal, existing depth‐inversion algorithms using linear approaches face major theoretical and/or technical issues in the surf zone, limiting their accuracy over this region. Here, we present a new depth‐inversion approach relying on Boussinesq theory for quantifying nonlinear dispersion effects in nearshore waves. Using high‐resolution datasets collected in the laboratory under diverse wave conditions and beach morphologies, we demonstrate that this approach results in enhanced levels of accuracy in the surf zone (errors typically within 10%) and presents a major improvement over linear methods. The new nonlinear depth‐inversion approach provides significant prospects for future practical applications in the field using existing remote sensing technologies, including continuous lidar scanners and stereo‐imaging systems.