Observations of waves and setup on a steep, sandy beach are used to identify and assess potential applications of spatially dense lidar measurements for studying inner-surf and swash-zone hydrodynamics. There is good agreement between lidar-and pressure-based estimates of water levels (r 2 5 0.98, rmse 5 0.05 m), setup (r 2 5 0.92, rmse 5 0.03 m), infragravity wave heights (r 2 5 0.91, rmse 5 0.03 m), swell-sea wave heights (r 2 5 0.87, rmse 5 0.07 m), and energy density spectra. Lidar observations did not degrade with range (up to 65 m offshore of the lidar) when there was sufficient foam present on the water surface to generate returns, suggesting that for narrow-beam 1550-nm light, spatially varying spot size, grazing angle affects, and linear interpolation (to estimate the water surface over areas without returns) are not large sources of error. Consistent with prior studies, the lidar and pressure observations indicate that standing infragravity waves dominate inner-surf and swash energy at low frequencies and progressive swell-sea waves dominate at higher frequencies. The spatially dense lidar measurements enable estimates of reflection coefficients from pairs of locations at a range of spatial lags (thus spanning a wide range of frequencies or wavelengths). Reflection is high at low frequencies, increases with beach slope, and decreases with increasing offshore wave height, consistent with prior studies. Lidar data also indicate that wave asymmetry increases rapidly across the inner surf and swash. The comparisons with pressure measurements and with theory demonstrate that lidar measures inner-surf waves and setup accurately, and can be used for studies of inner-surf and swash-zone hydrodynamics.
This paper details the collection, geo-referencing, and data processing algorithms for a fully-automated, permanently deployed terrestrial lidar system for coastal monitoring. The lidar is fixed on a 4-m structure located on a shore-backing dune in Duck, North Carolina. Each hour, the lidar collects a three-dimensional framescan of the nearshore region along with a 30-min two-dimensional linescan time series oriented directly offshore, with a linescan repetition rate of approximately 7 Hz. The data are geo-referenced each hour using a rigorous co-registration process that fits 11 fixed planes to a baseline scan to account for small platform movements, and the residual errors from the fit are used to assess the accuracy of the rectification. This process decreased the mean error (defined as the magnitude of the offset in three planes) over a two-year period by 24.41 cm relative to using a fixed rectification matrix. The automated data processing algorithm then filters and grids the data to generate a dry-beach digital elevation model (DEM) from the framescan along with hourly wave runup, hydrodynamic, and morphologic statistics from the linescan time series. The lidar has collected data semi-continuously since January 2015 (with gaps occurring while the lidar was malfunctioning or being serviced), resulting in an hourly data set spanning four years as of January 2019. Examples of data products and potential applications spanning a range of spatial and temporal scales relevant to coastal processes are discussed.
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