The Accuracy and Error Sources of Radar-derived Bathymetry by the XMFit Algorithm

The Accuracy and Error Sources of Radar-derived Bathymetry by the XMFit Algorithm

Tenthof van Noorden, C.

Reniers, A.J.H.M. (mentor)
Friedman, J.A. (mentor)
Hoekstra, R. (mentor)
Radermacher, M. (mentor)
Swinkels, C.M. (mentor)

Civil Engineering and Geosciences

Hydraulic Engineering

Environmental Fluid Mechanics

2015-09-29

The coastal bathymetry is one of the most essential inputs for understanding, monitoring and modelling the coastal environment. A remote sensing technique called marine radar may overcome disadvantages of present monitoring techniques and has the advantage to obtain measurements with a high spatial and temporal resolution. A Fast Fourier Transformation on the radar images produces pairs of wavenumbers and wave frequencies that can be linked to water depths and velocities by means of the dispersion relation. The drawback of present radar processing software is it closed and fixed nature and unclear accuracy. Therefore an X-band Matlab Fitting algorithm (XMFit) was developed by Friedman (2014). This development was induced by a radar stationed near the Sand Motor, a large nourishment, near Kijkduin in the Netherlands. However, XMFit requires further validation and a solution for the present bias in the depth estimate. Therefore, the goal of this thesis is to determine the accuracy of XMFit radar-derived bathymetry at the Sand Motor for a storm in October 2014 and determine the cause for the present overestimation of the water depth by XMFit. The accuracy is obtained by validation studies for the Sand Motor and Ameland radar and the error sources follow from analyses of the 3D wavenumber frequency space (kw-space). The Sand Motor validation study shows a mean depth bias of XMFit of 4.21 m. The XMFit accuracy depends on waveheight, wave period, precipitation and water depth. Additionally, fields of XMFit flow velocities sometimes show a growing eddy on the lee side of the Sand Motor. A mean depth bias of 1.04 m is found for a comparable validation study at Ameland. In contradiction with the Sand Motor, the Ameland depth bias depends differently on the metocean conditions, the water depth and the radar range. Nine different error sources were identified in this thesis. The in situ data, the fitting procedure of the XMFit and the bottom slope were found to have a negligible contribution to the depth bias. The metocean conditions, the precipitation, the Rhine's fresh water plume, amplitude dispersion and the water depth itself do have a considerable effect on the depth bias. Precipitation explains many of the large outliers of the XMFit depth estimate. Some other extreme outliers coincide with the passing of the fresh water plume. The increased depth bias for large ranges at the Sand Motor is due to the increased bias at deeper water depths and not due to the incidence angle. A comparison of the in situ depth with the depth that can actually be felt by the existing wave climate showed that the applicability of the dispersion relation is stretched too far at the Sand Motor. A filter has been developed separating valid from invalid results based on the L

XMFit
accuracy
radar
bathymetry
Sand Motor
Ameland
error sources

http://resolver.tudelft.nl/uuid:a93514c2-721a-490f-bcda-626dec1d61c8

Student theses

master thesis

(c) 2015 Tenthof van Noorden, C.