High-resolution bathymetry estimates via X-band marine radar: 1. beaches

Abstract In this paired study, we apply a recently developed high-resolution bathymetry estimation algorithm (“cBathy”) to X-band marine radar observations at two nearshore field sites. The algorithm exploits observations of the spatial structure of wave phase to attain wavenumber estimates, inverts the linear water wave dispersion relation for depth, and then applies a Kalman filter to objectively update the bathymetry estimates. Previously, performance has only been tested using optical video observations. In this first of two papers, performance of the algorithm using X-band radar image time series is tested at two disparate barred beach environments: Duck, NC, USA, and Benson Beach, WA, USA. Each of the test beaches is either co-located with (Duck, NC) or geographically close to (Benson Beach, WA) those utilized in the original algorithm verification. Concurrent echosounder surveys are used as ground truth. The bulk performance of the radar-derived bathymetry estimate at Duck, NC, achieves 0.49 m root-mean-square error (RMSE) with 0.26 m bias deep. This compares well with the bulk performance of the concurrent estimate derived using optical video ( 0.44 m RMSE and 0.23 m bias deep). The radar-derived bathymetry estimate performance at Benson Beach, is similar ( 0.35 m RMSE and 0.11 m bias shallow), and is comparable to that of an optical video derived estimate at a similar Pacific Northwest beach ( 0.56 m RMSE and 0.41 m bias shallow). At both beaches, significantly higher performance is achieved at locations deeper than 2 m (offshore of the surfzone) than at locations shallower than 2 m (surfzone), where errors are often a large fraction of the total depth. Lastly, several weeks of observations are utilized to assess the sensitivity of algorithm quality control to environmental conditions. Thresholds based on the shoreward component of wind stress and offshore wave steepness are identified and shown to impact the areal coverage of radar-derived bathymetric estimates. Overall, these results demonstrate the viability of marine radar observations as input to the cBathy algorithm and delineate some environmental constraints on algorithm performance. In the companion paper, the algorithm is extended to areas where tidal currents are important, including an ebb tidal shoal and an estuary mouth.

[1]  Jay Gao,et al.  Bathymetric mapping by means of remote sensing: methods, accuracy and limitations , 2009 .

[2]  Steven M. De Jong,et al.  Accuracy of Nearshore Bathymetry Inverted From ${X}$ -Band Radar and Optical Video Data , 2017, IEEE Transactions on Geoscience and Remote Sensing.

[3]  William J. Plant,et al.  Optical and Microwave Detection of Wave Breaking in the Surf Zone , 2011, IEEE Transactions on Geoscience and Remote Sensing.

[4]  C. C. Piotrowski,et al.  Water depth and surface current retrievals from airborne optical measurements of surface gravity wave dispersion , 2001 .

[5]  W. Plant,et al.  Microwave backscattering from surf zone waves , 2014 .

[6]  D. Honegger,et al.  Oblique Internal Hydraulic Jumps at a Stratified Estuary Mouth , 2017 .

[7]  S. Elgar,et al.  Evaluation of video-based linear depth inversion performance and applications using altimeters and hydrographic surveys in a wide range of environmental conditions , 2018, Coastal Engineering.

[8]  Nathaniel G. Plant,et al.  Ocean Wavenumber Estimation From Wave-Resolving Time Series Imagery , 2008, IEEE Transactions on Geoscience and Remote Sensing.

[9]  Steve Elgar,et al.  Radar Remote Sensing Estimates of Waves and Wave Forcing at a Tidal Inlet , 2015 .

[10]  John P. Dugan,et al.  Accuracy of bathymetry and current retrievals from airborne optical time-series imaging of shoaling waves , 2002, IEEE Trans. Geosci. Remote. Sens..

[11]  J. Dugan,et al.  Jetski-based nearshore bathymetric and current survey system , 2001 .

[12]  Ian L Turner,et al.  A video-based technique for mapping intertidal beach bathymetry , 2003 .

[13]  R. Holman,et al.  Evaluation of Airborne Topographic Lidar* for Quantifying Beach Changes , 2003 .

[14]  William A. Birkemeier,et al.  The Crab: A Unique Nearshore Surveying Vehicle , 1984 .

[15]  Katherine L. Brodie,et al.  Surf Zone Characterization Using a Small Quadcopter: Technical Issues and Procedures , 2017, IEEE Transactions on Geoscience and Remote Sensing.

[16]  David T. Walker,et al.  A Simple Model for Marine Radar Images of the Ocean Surface , 2015, IEEE Geoscience and Remote Sensing Letters.

[17]  J. Dugan,et al.  Surface current measurements using airborne visible image time series , 2003 .

[18]  Robert A. Holman,et al.  Phase Speed and Angle of Breaking Waves Measured with Video Techniques , 1991 .

[19]  Paul S. Bell,et al.  A temporal waterline approach to mapping intertidal areas using X-band marine radar , 2016 .

[20]  J. C. N. Borge,et al.  Use of nautical radar as a wave monitoring instrument , 1999 .

[21]  J. MacMahan Hydrographic Surveying from Personal Watercraft , 2001 .

[22]  Ap van Dongeren,et al.  Beach Wizard: Nearshore bathymetry estimation through assimilation of model computations and remote observations , 2008 .

[23]  Paul S. Bell,et al.  Application of marine radar to monitoring seasonal and event-based changes in intertidal morphology , 2017 .

[24]  R. Holman,et al.  Estimation of wave phase speed and nearshore bathymetry from video imagery , 2000 .

[25]  Rob Holman,et al.  Remote sensing of the nearshore. , 2013, Annual review of marine science.

[26]  Applicability of video-derived bathymetry estimates to nearshore current model predictions , 2014 .

[27]  Paul S. Bell,et al.  Nested Radar Systems for Remote Coastal Observations , 2006 .

[28]  Brian Voigt,et al.  Seasonal to Interannual Morphodynamics along a High-Energy Dissipative Littoral Cell , 2005 .

[29]  R. Holman,et al.  Surf zone bathymetry and circulation predictions via data assimilation of remote sensing observations , 2014 .

[30]  C. C. Piotrowski,et al.  Airborne Optical System for Remote Sensing of Ocean Waves , 2001 .

[31]  Satoshi Takewaka Measurements of Shoreline Positions and Intertidal Foreshore Slopes with X-Band Marine Radar System , 2005 .

[32]  Jianfei Liu,et al.  Array Beamforming Algorithm for Estimating Waves and Currents From Marine X-Band Radar Image Sequences , 2017, IEEE Transactions on Geoscience and Remote Sensing.

[33]  Patricio A. Catalán,et al.  Remote sensing of breaking wave phase speeds with application to non-linear depth inversions , 2008 .

[34]  D. Roelvink,et al.  Nearshore bathymetry from video and the application to rip current predictions for the Dutch Coast , 2014 .

[35]  J. Kirby,et al.  The Future of Nearshore Processes Research , 2014 .

[36]  Paul S. Bell,et al.  Shallow water bathymetry derived from an analysis of X-band marine radar images of waves , 1999 .

[37]  Eric Terrill,et al.  The Development of an Inversion Technique to Extract Vertical Current Profiles from X-Band Radar Observations , 2016 .

[38]  Todd K. Holland,et al.  Application of the linear dispersion relation with respect to depth inversion and remotely sensed imagery , 2001, IEEE Trans. Geosci. Remote. Sens..

[39]  W. Large,et al.  Sensible and Latent Heat Flux Measurements over the Ocean , 1982 .

[40]  P. Catalán,et al.  Rip Current Observations via Marine Radar , 2014 .

[41]  Hans C. Graber,et al.  A new technique for the retrieval of near‐surface vertical current shear from marine X‐band radar images , 2015 .

[42]  P. Komar,et al.  The Wave Climate of the Pacific Northwest (Oregon and Washington): A Comparison of Data Sources , 1997 .

[43]  Nathaniel G. Plant,et al.  cBathy: A robust algorithm for estimating nearshore bathymetry , 2013 .

[44]  R. Holman,et al.  The history and technical capabilities of Argus , 2007 .

[45]  Daniel Conley,et al.  Video-based nearshore bathymetry estimation in macro-tidal environments , 2016 .

[46]  S. Lehner,et al.  Synergy and fusion of optical and synthetic aperture radar satellite data for underwater topography estimation in coastal areas , 2011 .

[47]  William J. Plant,et al.  Normalized radar cross section of the sea for backscatter: 1. Mean levels , 2010 .

[48]  R. Holman,et al.  Data assimilation and bathymetric inversion in a two‐dimensional horizontal surf zone model , 2010 .

[49]  A. Kurapov,et al.  Data Assimilation for Bathymetry Estimation at a Tidal Inlet , 2016 .