Blending Bathymetry: Combination of image-derived parametric approximations and celerity data sets for nearshore bathymetry estimation

Estimation of nearshore bathymetry is important for accurate prediction of nearshore wave conditions. However, direct data collection is expensive and time-consuming while accurate airborne lidar-based survey is limited by breaking waves and decreased light penetration affected by water turbidity. Instead, tower-based platforms or Unmanned Aircraft System (UAS) can provide indirect video-based observations. The video-based time-series imagery provides wave celerity information and time-averaged (timex) or variance enhanced (var) images identify persistent regions of wave breaking. In this work, we propose a rapid and improved bathymetry estimation method that takes advantage of image-derived wave celerity and a first-order bathymetry estimate from Parameter Beach Tool (PBT), software that fits parameterized sandbar and slope forms to the timex or var images. Two different sources of the data, PBT and wave celerity, are combined or blended optimally based on their assumed accuracy in a statistical framework. The PBT-derived bathymetry serves as "prior" coarse-scale background information and then is updated and corrected with the imagery-derived wave data through the dispersion relationship, which results in a better bathymetry estimate that is consistent with imagery-based wave data. To illustrate the accuracy of our proposed method, imagery data sets collected in 2017 at the US Army EDRC's Field Research Facility in Duck, NC under different weather and wave height conditions are tested. Estimated bathymetry profiles are remarkably close to the direct survey data. The computational time for the estimation from PBT-based bathymetry and imagery-derived wave celerity is only about five minutes on a free Google Cloud node with one CPU core. These promising results indicate the feasibility of reliable real-time bathymetry imaging during a single flight of UAS.Comment: 21 pages, 14 figures, preprint

CoastalImageLib: An open- source Python package for creating common coastal image products

CoastalImageLib is a Python library that produces common coastal image products intended for quantitative analysis of coastal environments. This library contains functions to georectify and merge multiple oblique camera views, produce statistical image products for a given set of images, and create subsampled pixel instruments for use in bathymetric inversion, surface current estimation, run-up calculations, and other quantitative analyses. This package intends to be an open-source broadly generalizable front end to future coastal imaging applications, ultimately expanding user accessibility to optical remote sensing of coastal environments. This package was developed and tested on data collected from the Argus Tower, a 43 m tall observation structure in Duck, North Carolina at the US Army Engineer Research and Development Center’s Field Research Facility that holds six stationary cameras which collect twice-hourly coastal image products. Thus, CoastalImageLib also contains functions designed to interface with the file storage and collection system implemented at the Argus Tower

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

Complex two-dimensional nearshore current patterns are generated by feedbacks between sub-aqueous morphology and momentum imparted on the water column by breaking waves, winds, and tides. These non-stationary features, such as rip currents and circulation cells, respond to changing environmental conditions and underlying morphology. However, using fixed instruments to observe nearshore currents is limiting due to the high costs and logistics necessary to achieve adequate spatial sampling resolution. A new technique for processing surf-zone imagery, WAMFlow, quantifies fluid velocities to reveal complex, multi-scale (10 s–1000 s meters) nearshore surface circulation patterns. We apply the concept of a wave-averaged movie (WAM) to measure surf-zone circulation patterns on spatial scales of kilometers in the alongshore and 100 s of meters in the cross-shore. The approach uses a rolling average of 2 Hz optical imagery, removing the dominant optical clutter of incident waves, to leave the residual foam or water turbidity features carried by the flow. These residual features are tracked as quasi-passive tracers in space and time using optical flow, which solves for u and v as a function of image intensity gradients in x, y, and t. Surf zone drifters were deployed over multiple days with varying nearshore circulations to validate the optically derived flow patterns. Root mean square error are reduced to 0.1 m per second after filtering based on image attributes. The optically derived patterns captured longshore currents, rip currents, and gyres within the surf zone. Quantifying nearshore circulation patterns using low-cost image platforms and open-source computer vision algorithms presents the potential to further our understanding of fundamental surf zone dynamics

Imperial Beach Binned Sand Elevations

Binned sand elevations at Imperial Beach. Raw sand level observations are binned to coordinates aligned with the wave estimates (MOP lines). MOP lines are separated 100m alongshore, and oriented from the 10m depth contour to the backbeach, to approximately follow the curving coastline. Bins centered on MOP lines with 5m cross-shore resolution are filled with median values, suppressing the effect of outliers. The observations are usually smooth over the 50m maximum distance of alongshore projection and 2.5m cross-shore projection. However, raw data should be used to define features with shorter scales (i.e., scarps). Binned alongshore resolution can be adjusted in the repository code (separate download: analysis_code within analysis folder) by using different binning transects, while cross-shore resolution can be adjusted by redefining the "cres" variable. Be cautious with data at depths greater than 8m below MSL, as ocean temperature stratification can contaminate jet ski soundings

Imperial Beach Sand Level Survey Information

Information on sand level surveys conducted at Imperial Beach. Complete lists of all survey filenames, dates, depth zones surveyed, alongshore regions surveyed, south and north-most surveyed MOP line indices with good coverage, regions influenced by nourishment, and vehicles and transects driven are included in this file

Torrey Pines Beach Mapped Sand Elevations

Mapped sand elevations at Torrey Pines Beach. Elevation maps are created on the same grid as the binned observations, but are smoothed and fill in small data gaps. For each survey, bins containing less than 3 data points are considered unsampled and are discarded. Map boundaries are defined as grid points that are regularly sampled during unnourished quarterly full surveys (must be populated at least 25\% of the time as the most frequently full surveyed grid point, during times without nourishment). Grid points with an unnourished average depth greater than 8m are not mapped because speed of sound errors due to stratification may contaminate jet ski sonar measurements. When the estimated interpolation (or extrapolation) error is large (NMSE>0.2), the map bin elevation is considered missing and filled with the value -99999

Imperial Beach Raw Sand Elevations

Raw (quality controlled) sand elevations at Imperial Beach. An ATV with rear shocks removed and constant tire pressure (to maintain a consistent distance from the GNSS antenna to the sand level below), was used to measure the subaerial beach at low tide, while a 3 wheeled push dolly (with GNSS antenna mounted on a fixed-height mast) was used from the low-tide waterline to chest deep wading depths. A personal watercraft (Yamaha Waverunner, but here the more familiar term jet ski will be used) equipped with 192kHz acoustic sonar, sea surface thermistor (for speed of sound calculation) and GNSS antenna, measures the subaqueous profile at high tide. The dolly is used to help ensure data is collected along a continuous profile, through water that is too deep for ATV, and where there is too much turbidity for the jet ski sonar. The receivers on the vehicles transitioned from Sokkia, to Ashtech ZXtreme, and are now equipped with Trimble NetR9 GNSS receivers (enabling access to multiple Global Navigation Satellite Systems). The GNSS sample rates have increased over time, and data are now collected at 5Hz. Base stations broadcast real-time kinematic corrections that allow jet ski and ATV drivers to monitor the data quality, follow designated transect lines, and guide dolly pushers, using custom in-house software. Vehicles are driven at a speed that samples ~1 point per meter of track. Data are routinely post-processed. SBG Ellipse inertial measurement units on the jet ski and ATV account for tilting of the antenna. Prior to the advent of MEMS, a KVH Gyrocompass was used. The ATV driver also manually records subaerial substrate type with a switch that differentiates between rock, cobble and sand. Full survey cross-shore transects are aligned to MOP lines with 100m alongshore spacing. Subaerial ATV-only surveys are driven alongshore with approximately 10m cross-shore spacing. Nominally, full surveys are quarterly and subaerial surveys are monthly. Quality controlled elevation data (NAVD88 GEOID99 epoch 2002) are provided for each survey at both Lat-Lon (NAD83 CORS96, epoch 2002, ellipsoid GRS80) and UTM (Zone 11) coordinates. When available, subaerial substrate type (sand, rock or cobble) is also provided. Errors in survey elevation are variable in space and time, and depend on GNSS-platform, bed smoothness, and wave and ocean temperature stratification conditions. Root-mean-square-errors are usually less than 15cm with the jet ski, and a few cm smaller with the dolly and ATV. Be cautious with data at depths greater than 8m below MSL, as ocean temperature stratification can contaminate jet ski soundings. Gaps in spatial coverage occurred when low and high tide surveys did not overlap, owing to the nonlinear interaction of sand bars, waves, tides, kelp, permits, and mechanical failures. Pre- and post- survey control points were used for accuracy verification on each survey. The Online Positioning User Service (OPUS) was used to determine base locations and survey control locations. Inertial measurement units were calibrated on the vehicles and tested. Realtime ocean surface water temperature was recorded during the jet ski surveys to correct for the sonar travel time measurements. Jet ski, dolly, and ATV data are collected over the same transect line with overlap for redundancy and as a check on data quality. Vertical discrepancies are flagged and outliers are removed. The sonar and IMU are oversampled to improve noise rejection. ATV tire pressure is held at 5 PSI and verified prior to each survey. Various jet ski parameters were set at thresholds that maintained high quality (e.g. 30 degree max pitch/roll, maximum Position of Dilution of Precision of 5.0). Raw (quality controlled) sand level data provide maximum user flexibility. Binned and mapped data are more user-convenient for many applications, but sharp edges are blurred. Raw data should be used to examine vertical scarps at the seaward face of nourishments, and steep shoal bathymetry. Be cautious with data at depths greater than 8m below MSL, as ocean temperature stratification can contaminate jet ski soundings. Complete lists of all survey filenames, dates, depth zones surveyed, alongshore regions surveyed, south and north-most surveyed MOP line indices with good coverage, regions influenced by nourishment, and vehicles and transects driven are included in the imperial_survey_info.nc file (separate download)

Torrey Pines Beach Characteristics

Characteristics of Torrey Pines Beach. MOP DEFINITIONS: The beach site locations are defined using MOP lines. Backbeach locations of each line (spaced 100m apart in the alongshore) and the corresponding offshore locations in 10m depth are included, as well as the MOP site names, index number, and the angle of the line relative to true north. REGIONS: The monitoring schemes at each beach evolved over time with consistently surveyed regions spanning between 1.6 and 2.7km alongshore. Region outlines, and MOP site names and index numbers within each region are provided, as well as times with minimal nourishment influence. SECTIONS: Beaches were split into sections spanning 700-900m alongshore. Location outlines, MOP sites and index numbers, and times of minimal nourishment influence are provided for each section. Additionally, features (e.g. reef, lagoon, canyon) are listed. The sections that are labeled as 1D, have a coherent seasonal cross-shore sand exchange signal along the profile, as identified with empirical orthogonal function analysis. During times of minimal nourishment influence, these 1D sections are recommended for testing 1-D cross-shore beach profile evolution models. Note that cobble may be present even in 1D sections, especially at North Torrey Pines when subaerial sand levels are eroded. NOURISHMENT: Sand nourishment placement locations and start and end times are provided. The nourishment placement outline is defined as the bulge in the 2m contour (relative to MSL) location between the pre and post-nourishment surveys. HARD SUBSTRATE: Subaerial substrate is monitored by the ATV driver, however, offshore substrate is difficult to identify. Areas with underlying hard substrate erode to minimum levels significantly less than adjacent sandy areas. Specifically, these areas are defined as areas with mapped minimum surface greater than 30cm relative to the time- and alongshore-averaged mapped profile in the alongshore uniform sections. These locations agree qualitatively with limited available sidescan sonar which helped to identify the hard substrate as rocky reef. VOLUMES: For each survey, maps are used to estimate sand volumes relative to the minimum surface. The minimum value in each mapped grid point over the study period is used to calculate the minimum surface. The total volume is estimated over the survey area, while subaerial volume is calculated over an area which extends from the mean shoreline position (average location of the intersection of the profile with MSL) to the backbeach. Estimates are provided for each beach, region and section. Volume estimates are discarded if more than 10% of the mapped area has NMSE>0.2. BEACH WIDTHS: Beach width is calculated along each MOP line as the positive slope intersection of the MSL contour with the mapped profile where NMSE< 0.2. If more than one intersection is found, the most offshore MSL position is used, as long as no negative slope intersection is seaward of it. Alongshore-averaged beach widths are provided for each beach, region and section when less than 10% of MOP lines were missing estimates

README

Overview README file for the entire repositor