• Aagaard, T., and D. Holm, 1989: Digitization of wave runup using video records. J. Coastal Res., 5, 547551.

  • Abessolo Ondoa, G., and Coauthors, 2016: Potential of video cameras in assessing event and seasonal coastline behaviour: Grand Popo, Benin (Gulf of Guinea). J. Coastal Res., 75, 442446, https://doi.org/10.2112/SI75-089.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Abessolo Ondoa, G., and Coauthors, 2017: Development of a West and Central Africa regional video camera network to monitor coastal response to multiscale ocean forcing. Proc. Coastal Dynamics, Elsinore, Denmark, University of Copenhagen, 1540–1550.

  • Almar, R., N. Senechal, P. Bonneton, and J. A. Roelvink, 2008: Wave celerity from video imaging: A new method. Proc. 31st Int. Conf. Coastal Engineering, Hamburg, Germany, American Society of Civil Engineers, 661–673.

  • Almar, R., R. Cienfuegos, P. A. Catalan, H. Michallet, B. Castelle, P. Bonneton, and V. Marieu, 2012a: A new breaking wave height direct estimation from video. Coastal Eng., 61, 4248, https://doi.org/10.1016/j.coastaleng.2011.12.004.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Almar, R., R. Ranasinghe, N. Sénéchal, P. Bonneton, D. Roelvink, K. R. Bryan, V. Marieu, and J. P. Parisot, 2012b: Video-based detection of shorelines at complex meso–macro tidal beaches. J. Coastal Res., 28, 10401048, https://doi.org/10.2112/JCOASTRES-D-10-00149.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Almar, R., and Coauthors, 2014: The Grand Popo beach 2013 experiment, Benin, West Africa: From short timescale processes to their integrated impact over long-term coastal evolution. J. Coastal Res., 70, 651656, https://doi.org/10.2112/SI70-110.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Almar, R., and Coauthors, 2015: Response of the Bight of Benin (Gulf of Guinea, West Africa) coastline to anthropogenic and natural forcing. Part 1: Wave climate variability and impacts on the longshore sediment transport. Cont. Shelf Res., 110, 4859, https://doi.org/10.1016/j.csr.2015.09.020.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Almar, R., S. Larnier, B. Castelle, T. Scott, and F. Floc’h, 2016: On the use of the Radon transform to estimate longshore currents from video imagery. Coastal Eng., 114, 301308, https://doi.org/10.1016/j.coastaleng.2016.04.016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Amarouche, L., P. Thibaut, O. Zanife, J.-P. Dumont, P. Vincent, and N. Steunou, 2004: Improving the Jason-1 ground retracking to better account for attitude effects. Mar. Geod., 27, 171197, https://doi.org/10.1080/01490410490465210.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Anderson, T. R., C. H. Fletcher, M. M. Barbee, B. M. Romine, S. Lemmo, and J. M. S. Delevaux, 2018: Modelling multiple sea level rise stresses reveals up to twice the land at risk compared to strictly passive flooding methods. Sci. Rep., 8, 14484, https://doi.org/10.1038/s41598-018-32658-x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Andriolo, U., 2018: Nearshore hydrodynamics and morphology derived from video imagery. Ph.D. dissertation, Faculty of Sciences, University of Lisbon, 227 pp.

  • Angnuureng, D. B., R. Almar, K. Appeaning Addo, N. Senechal, B. Castelle, S. W. Laryea, and G. Wiafe, 2016: Video observation of waves and shoreline change on the microtidal James town Beach in Ghana. J. Coastal Res., 75, 10221026, https://doi.org/10.2112/SI75-205.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Arbic, B. K., R. B. Scott, D. B. Chelton, J. G. Richman, and J. F. Shriver, 2012: Effects on stencil width on surface ocean geostrophic velocity and vorticity estimation from gridded satellite altimeter data. J. Geophys. Res., 117, C03029, https://doi.org/10.1029/2011JC007367.

    • Search Google Scholar
    • Export Citation
  • Bergsma, E. W. J., and R. Almar, 2018: Video-based depth inversion techniques, a method comparison with synthetic cases. Coastal Eng., 138, 199209, https://doi.org/10.1016/j.coastaleng.2018.04.025.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bergsma, E. W. J., D. C. Conley, M. A. Davidson, and T. J. O’Hare, 2016: Video-based nearshore bathymetry estimation in macro-tidal environments. Mar. Geol., 374, 3141, https://doi.org/10.1016/j.margeo.2016.02.001.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bergsma, E. W. J., D. C. Conley, M. A. Davidson, T. J. O’Hare, and R. Almar, 2019: Storm event to seasonal evolution of nearshore bathymetry derived from shore-based video imagery. Remote Sens., 11, 519, https://doi.org/10.3390/rs11050519.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Birol, F., and Coauthors, 2017: Coastal applications from nadir altimetry: Example of the X-TRACK regional products. Adv. Space Res., 59, 936953, https://doi.org/10.1016/j.asr.2016.11.005.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Boak, E. H., and I. L. Turner, 2005: Shoreline definition and detection: A review. J. Coastal Res., 214, 688703, https://doi.org/10.2112/03-0071.1.

  • Bouvier, C., Y. Balouin, B. Castelle, and R. A. Holman, 2019: Modelling camera viewing angle deviation to improve nearshore video monitoring. Coastal Eng., 147, 99106, https://doi.org/10.1016/j.coastaleng.2019.02.009.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Brodie, K. L., M. L. Palmsten, T. J. Hesser, P. J. Dickhudt, B. Raubenheimer, H. Ladner, and S. Elgar, 2018: Evaluation of video-based linear depth inversion performance and applications using altimeters and hydrographic surveys in a wide range of environmental conditions. Coastal Eng., 136, 147160, https://doi.org/10.1016/j.coastaleng.2018.01.003.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Carrere, L., F. Lyard, M. Cancet, A. Guillot, and N. Picot, 2016: FES 2014, a new tidal model—Validation results and perspectives for improvements. Living Planet Symp., Prague, Czech Republic, ESA.

  • Catalan, P. A., and M. C. Haller, 2008: Remote sensing of breaking wave phase speeds with application to non-linear depth inversions. Coastal Eng., 55, 93111, https://doi.org/10.1016/j.coastaleng.2007.09.010.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cazenave, A., H. Palanisamy, and M. Ablain, 2018: Contemporary sea level changes from satellite altimetry: What have we learned? What are the new challenges? Adv. Space Res., 62, 16391653, https://doi.org/10.1016/j.asr.2018.07.017.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cipollini, P., F. M. Calafat, S. Jevrejeva, A. Melet, and P. Prandi, 2017: Monitoring sea level in the coastal zone with satellite altimetry and tide gauges. Surv. Geophys., 38, 3357, https://doi.org/10.1007/s10712-016-9392-0.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Codiga, D. L., 2011: Unified tidal analysis and prediction using the UTide MATLAB functions. University of Rhode Island Graduate School of Oceanography Tech. Rep. 2011-01, 59 pp., ftp://www.po.gso.uri.edu/pub/downloads/codiga/pubs/2011Codiga-UTide-Report.pdf.

  • Davidson-Arnott, R., 2010: Introduction to Coastal Processes and Geomorphology. Cambridge University Press, 458 pp.

    • Crossref
    • Export Citation
  • Ding, H., N. S. Keenlyside, and M. Latif, 2009: Seasonal cycle in the upper equatorial Atlantic Ocean. J. Geophys. Res., 114, C09016, https://doi.org/10.1029/2008JD010723.

    • Search Google Scholar
    • Export Citation
  • Elko, N., and Coauthors, Eds., 2014: The future of nearshore processes research. Scripps Institute of Oceanography Rep., 34 pp., https://scripps.ucsd.edu/centers/nearshorefuture/wp-content/uploads/sites/37/2014/12/Future_Nearshore_Processes_Research.pdf.

  • Hallermeier, R. J., 1983: Sand transport limits in coastal structure design, Proc. Coastal Structures ’83, New York, NY, American Society of Civil Engineers, 703–716.

  • Heikkila, J., and O. Silven, 1997: A four-step camera calibration procedure with implicit image correction: Computer vision and pattern recognition. Proc. IEEE Computer Society Conf., San Juan, Puerto Rico, IEEE, 1106–1112, https://doi.org/10.1109/CVPR.1997.609468.

    • Crossref
    • Export Citation
  • Holland, K. T., and R. A. Holman, 1993: The statistical distribution of swash maxima on natural beaches. J. Geophys. Res., 98, 10 27110 278, https://doi.org/10.1029/93JC00035.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Holland, K. T., R. A. Holman, T. C. Lippmann, J. Stanley, and N. Plant, 1997: Practical use of video imagery in near-shore oceanographic field studies. IEEE J. Ocean Eng., 22, 8192, https://doi.org/10.1109/48.557542.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Holman, R. A., and J. Stanley, 2007: The history and technical capabilities of Argus. Coastal Eng., 54, 477491, https://doi.org/10.1016/j.coastaleng.2007.01.003.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Holman, R. A., and M. Haller, 2013: Remote sensing of the nearshore. Annu. Rev. Mar. Sci., 5, 95113, https://doi.org/10.1146/annurev-marine-121211-172408.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ibaceta, R., R. Almar, P. A. Catalán, C. E. Blenkinsopp, L. P. Almeida, and R. Cienfuegos, 2018: Assessing the performance of a low-cost method for video-monitoring the water surface and bed level in the swash zone of natural beaches. Remote Sens., 10, 49, https://doi.org/10.3390/rs10010049.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Idzanovic, M., V. Ophaug, and B. Andersen, 2018: Coastal sea level from CryoSat-2 SARIn altimetry in Norway. Adv. Space Res., 62, 13441357, https://doi.org/10.1016/j.asr.2017.07.043.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Komar, P., 1998: Beach Processes and Sedimentation. 2nd ed. Prentice Hall, 544 pp.

  • Kraus, N. C., M. Larson, and R. A. Wise, 1998: Depth of closure in beach-fill design. Coastal Engineering Tech. Note CETN II-40, 14 pp.

  • Lyard, F. H., L. Carrere, M. Cancet, J. P. Boy, P. Gegout, and J. M. Lemoine, 2016: The FES2014 tidal atlas, accuracy assessment for satellite altimetry and other geophysical applications. EGU General Assembly, Vienna, Austria, European Geosciences Union, 17693.

  • Marti, F., A. Cazenave, F. Birol, M. Passaro, F. Leger, F. J. Beneviste, and J. F. Legeais, 2019: Altimetry-based sea level trends along the coasts of western Africa. Adv. Space Res., https://doi.org/10.1016/j.asr.2019.05.033, in press.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Melet, A., R. Almar, and B. Meyssignac, 2016: What dominates sea level at the coast: A case study for the Gulf of Guinea. Ocean Dyn., 66, 623636, https://doi.org/10.1007/s10236-016-0942-2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Melet, A., B. Meyssignac, R. Almar, and G. Le Cozannet, 2018: Under-estimated wave contribution to coastal sea-level rise. Nat. Climate Change, 8, 234239, https://doi.org/10.1038/s41558-018-0088-y.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Osorio, A. F., R. Medina, and M. Gonzalez, 2012: An algorithm for the measurement of shoreline and intertidal beach profiles using video imagery: PSDM. Comput. Geosci., 46, 196207, https://doi.org/10.1016/j.cageo.2011.12.008.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Passaro, M., P. Cipollini, S. Vignudelli, G. D. Quartly, and H.M. Snaith, 2014: ALES: A multi-mission adaptive subwave form retracker for coastal and open ocean altimetry. Remote Sens. Environ., 145, 173189, https://doi.org/10.1016/j.rse.2014.02.008.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Passaro, M., M. K. Rose, O. B. Andersen, E. Boergens, F. M. Calafat, D. Dettmering, and J. Benveniste, 2018a: ALES+: Adapting a homogenous ocean retracker for satellite altimetry to sea ice leads, coastal and inland waters. Remote Sens. Environ., 211, 456471, https://doi.org/10.1016/j.rse.2018.02.074.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Passaro, M., N. Zulfikar Adlan, and G. D. Quartly, 2018b: Improving the precision of sea level data from satellite altimetry with high frequency and regional sea state bias corrections. Remote Sens. Environ., 218, 245254, https://doi.org/10.1016/j.rse.2018.09.007.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pianca, C., R. Holman, and E. Siegle, 2015: Shoreline variability from days to decades: Results of long-term video imaging. J. Geophys. Res. Oceans, 120, 21592178, https://doi.org/10.1002/2014JC010329.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Polo, I., A. Lazar, B. Rodriguez-Fonseca, and S. Arnault, 2008: Oceanic Kelvin waves and tropical Atlantic intraseasonal variability: 1. Kelvin wave characterization. J. Geophys. Res., 113, C07009, https://doi.org/10.1029/2007JC004495.

    • Search Google Scholar
    • Export Citation
  • Pujol, M.-I., Y. Faugère, G. Taburet, S. Dupuy, C. Pelloquin, M. Ablain, and N. Picot, 2016: DUACS DT2014: The new multi-mission altimeter data set reprocessed over 20 years. Ocean Sci., 12, 10671090, https://doi.org/10.5194/os-12-1067-2016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Radermacher, M., M. E. Wengrove, J. S. M. Van Thiel de Vries, and R. A. Holman, 2014: Applicability of video-derived bathymetry estimates to nearshore current model predictions. J. Coastal Res., 70, 290295, https://doi.org/10.2112/SI70-049.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ranji, Z., K. Hejazi, M. Soltanpour, and M. Allahyar, 2016: Inter-comparison of recent tide models for the Persian Gulf and Oman Sea. Proc. 35th Conf. on Coastal Engineering, Antalya, Turkey, Coastal Engineering Research Council, 443–454, https://doi.org/10.9753/icce.v35.currents.9.

    • Crossref
    • Export Citation
  • Segura, L. E., J. E. Hansen, and R. J. Lowe, 2018: Seasonal shoreline variability induced by subtidal water level fluctuations at reef-fringed beaches. J. Geophys. Res. Earth Surf., 123, 433447, https://doi.org/10.1002/2017JF004385.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sembiring, L., M. Van Ormondt, A. R. Van Dongeren, and J. A. Roelvink, 2017: Operational prediction of rip currents using numerical model and nearshore bathymetry from video images. AIP Conf. Proc., 1857, 080004, https://doi.org/10.1063/1.4987098.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Slangen, A. B., and Coauthors, 2017: Evaluating model simulations of twentieth-century sea level rise. Part I: Global mean sea level change. J. Climate, 30, 85398563, https://doi.org/10.1175/JCLI-D-17-0110.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Thuan, D. H., R. Almar, P. Marchesiello, and N. T. Viet, 2019: Video sensing of nearshore bathymetry evolution with error estimate. J. Mar. Sci. Eng., 7, 233, https://doi.org/10.3390/jmse7070233.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tissier, M., P. Bonneton, H. Michallet, and G. Ruessink, 2015: Infragravity-wave modulation of short-wave celerity in the surf zone. J. Geophys. Res. Oceans, 120, 67996814, https://doi.org/10.1002/2015JC010708.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tran, N., S. Labroue, S. Philipps, E. Bronner, and N. Picot, 2010: Overview and update of the sea state bias corrections for the Jason-2, Jason-1 and TOPEX missions. Mar. Geod., 33, 348362, https://doi.org/10.1080/01490419.2010.487788.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Uunk, L., K. M. Wijnberg, and R. Morelissen, 2010: Automated mapping of the intertidal beach bathymetry from video images. Coastal Eng., 57, 461469, https://doi.org/10.1016/j.coastaleng.2009.12.002.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Valladeau, G., P. Thibaut, B. Picard, J. C. Poisson, N. Tran, N. Picot, and A. Guillot, 2015: Using SARAL/AltiKa to improve Ka-band altimeter measurements for coastal zones, hydrology and ice: The PEACHI prototype. Mar. Geod., 38, 124142, https://doi.org/10.1080/01490419.2015.1020176.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vousdoukas, M. I., L. Mentaschi, E. Voukouvalas, M. Verlaan, S. Jevrejeva, L. P. Jackson, and L. Feyen, 2018: Global probabilistic projections of extreme sea levels show intensification of coastal flood hazard. Nat. Commun., 9, 2360, https://doi.org/10.1038/s41467-018-04692-w.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wright, L. D., and A. D. Short, 1984: Morphodynamic variability of surf zones and beaches: A synthesis. Mar. Geol., 56, 93118, https://doi.org/10.1016/0025-3227(84)90008-2.

    • Crossref
    • Search Google Scholar
    • Export Citation
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Sea Level at the Coast from Video-Sensed Waves: Comparison to Tidal Gauges and Satellite Altimetry

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  • 1 LEGOS, OMP, UMR 5566, CNES, CNRS, IRD, University of Toulouse, Toulouse, France
  • | 2 Ecosystems and Fishery Resources Laboratory, University of Douala, Douala, Cameroon
  • | 3 EPOC, OASU, UMR 5805, CNRS, University of Bordeaux, Pessac, France
  • | 4 LIENSs, Université de La Rochelle, CNRS, La Rochelle, France
  • | 5 Laboratoire d’Hydrologie Marine et Côtière, Institut de Recherche Halieutique et Océanologique du Benin, Cotonou, Benin
  • | 6 Université Nationale des Sciences, Technologie, Ingénierie et Mathématiques, Abomey, Benin
  • | 7 Water Resources Engineering, Lund University, Lund, Sweden
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Abstract

Nearshore complex and energetic hydrodynamic conditions make observing evolving processes during extreme and short-term events difficult. In particular, total sea levels at the coast are hard to measure with current techniques. Sea level is commonly measured with tidal gauges and spaceborne altimetry, which lack essential details of spatial and wave-related sea level variability along the coast. Hence, novel techniques, adapted to nearshore areas, are required. This paper presents the first-time use of video cameras to derive the total sea level at the coast. This novel approach consists of estimating time-varying total water levels by applying a celerity-based depth inversion method, which is conventionally used to estimate bathymetry from video. The video-derived total sea levels are compared to sea levels derived from an in situ acoustic Doppler current profiler (ADCP), the nearest tide gauge, and altimetry. A tidal harmonic analysis is performed on the video-derived water levels, yielding an accurate determination of the dominant tidal harmonics. However, it remains difficult to separate bathymetric changes due to the waves on beaches when rapid morphological changes occur under energetic conditions. Nonetheless, video-derived water-level anomalies are in good agreement with state-of-the-art altimetry products. Although there is still work to be done, the results show the potential to measure total sea level at the coast using video camera systems.

© 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Gregoire Abessolo Ondoa, gregsolo55@yahoo.fr

Abstract

Nearshore complex and energetic hydrodynamic conditions make observing evolving processes during extreme and short-term events difficult. In particular, total sea levels at the coast are hard to measure with current techniques. Sea level is commonly measured with tidal gauges and spaceborne altimetry, which lack essential details of spatial and wave-related sea level variability along the coast. Hence, novel techniques, adapted to nearshore areas, are required. This paper presents the first-time use of video cameras to derive the total sea level at the coast. This novel approach consists of estimating time-varying total water levels by applying a celerity-based depth inversion method, which is conventionally used to estimate bathymetry from video. The video-derived total sea levels are compared to sea levels derived from an in situ acoustic Doppler current profiler (ADCP), the nearest tide gauge, and altimetry. A tidal harmonic analysis is performed on the video-derived water levels, yielding an accurate determination of the dominant tidal harmonics. However, it remains difficult to separate bathymetric changes due to the waves on beaches when rapid morphological changes occur under energetic conditions. Nonetheless, video-derived water-level anomalies are in good agreement with state-of-the-art altimetry products. Although there is still work to be done, the results show the potential to measure total sea level at the coast using video camera systems.

© 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Gregoire Abessolo Ondoa, gregsolo55@yahoo.fr
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