Preprints
https://doi.org/10.5194/nhess-2021-387
https://doi.org/10.5194/nhess-2021-387
 
17 Mar 2022
17 Mar 2022
Status: this preprint is currently under review for the journal NHESS.

Modelling tides and storm surge using intertidal bathymetry derived from the waterline method applied to multispectral satellite images

Wagner Luiz Langer Costa1, Karin Roisin Bryan1, and Giovanni Coco2 Wagner Luiz Langer Costa et al.
  • 1School of Science, University of Waikato, 124 Hillcrest road, E-F link, Hamilton, New Zealand
  • 2School of Environment, University of Auckland, Auckland, New Zealand

Abstract. Bathymetric data are essential for accurate predictions of flooding in estuaries, because water depth is a fundamental component in the shallow-water hydrodynamic equations used in numerical models. Where LiDAR or acoustic in-situ surveys are unavailable, recent efforts have centred on the use of satellite images to estimate bathymetry (SDB). This work is aimed at (1) determining the accuracy of SDB, and (2) assessing the suitability of the SDB for surge/tidal modelling of estuaries. The SDB is created by extracting the waterline as it tracks over the bathymetry with changing tides, and is applied to 4 different estuaries in New Zealand: Whitianga, Maketū, Ōhiwa and Tauranga Harbour. Results show that the waterline method provides similar bathymetries to the LiDAR with root-mean squared error equal to 0.2 m, and it is slightly improved when two proposed correction methods are applied to the bathymetry derivations: the removing of statistical bias (by 2 cm) and hydrodynamic modelling correction (by 1 cm). Finally, the use of SDB in numerical simulations of surge levels is assessed for Tauranga Harbour with 4 different scenarios that explore the use of SDB in comparison to bathymetry data collected using non-satellite survey methods. One of these includes the well-known Stumpf-ratio method to extract the SDB of subtidal regions (so that only satellite information is used). The use of the satellite derived bathymetry in hydrodynamic models does not result in significant differences in terms of water levels, when compared with the scenario modelled using surveyed bathymetry.

Wagner Luiz Langer Costa et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on nhess-2021-387', Anonymous Referee #1, 25 Apr 2022
    • AC1: 'Reply on RC1', Wagner Costa, 26 Jul 2022
  • CC1: 'Comment on nhess-2021-387', Matías Dinapoli, 13 May 2022
    • AC4: 'Reply on CC1', Wagner Costa, 26 Jul 2022
  • RC2: 'Comment on nhess-2021-387', Anonymous Referee #2, 19 May 2022
    • AC2: 'Reply on RC2', Wagner Costa, 26 Jul 2022
  • RC3: 'Comment on nhess-2021-387', Anonymous Referee #3, 09 Jun 2022
    • AC3: 'Reply on RC3', Wagner Costa, 26 Jul 2022

Wagner Luiz Langer Costa et al.

Wagner Luiz Langer Costa et al.

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Short summary
For predicting flooding events at the coast, bathymetric data (or depth/elevation information) are essential. However, elevation data can be unavailable. To tackle this issue, recent efforts have centred on the use of satellite images to estimate bathymetry (SDB). This work is aimed at evaluate SDB’s accuracy and its use for water level prediction of estuaries. Results show that the use of SDB in numerical modelling can produces similar predictions when compared to the surveyed bathymetry data.
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