Bathymetry Inversion for Nearshore Applications Using Standoff Measurements

Abstract:

The bathymetry from the surfzone to the shoreline incurs active movement due to wave energy interacting with the seafloor. Measurement of the bathymetry is difficult without direct deployment of single-beam or multi-beam sonar mounted on a boat or jet ski. While these direct measurements are optimal, they are usually limited in space and time. Only a small section of a coastline can be measured during a collection, and it often can be years before another survey is conducted.

In this work, we consider a framework for estimating bathymetry in the nearshore that combines model-based inversion with standoff measurement. Standoff measurements allow flexible deployment over large spatial ranges with longer look times than are available from satellite-based platforms, but often do not provide direct measurements of the seabed, necessitating an inverse model. The coupling of nearshore wave measurements with numerical models can provide continuously evolving bathymetry estimates with larger spatial coverage than is available with standard techniques. The considered framework incorporates a variety of sensors including X-band radar, LiDAR, and video imagery to provide measurements of wave height, wave speed, or energy dissipation in order to drive the inversion model. Here, we evaluate a test case at the U.S. Army Corps of Engineers Field Research Facility where we are able to constrain the inversion problem using a number of different data measurement methods. A methodology for handling both data sparse and data rich environments is examined to determine the impact on the resulting bathymetry. Additionally, reduced order modeling and sampling based frameworks are evaluated for potential performance improvements.