Abstract
Monitoring the morphological evolution of a river-mouth bar is of both practical and scientific importance. A large amount of sediment is transported from a river to surrounding littoral cells via a deltaic bar after an extreme weather event. However, it is often not feasible to capture drastic morphological changes in the short term with conventional bathymetric surveys. This paper presents a depth-inversion method based on unmanned aerial vehicle technology to estimate two-dimensional bathymetry from video-sensed swell propagation. The estimation algorithm is tested over four cases with varying wave and bathymetric conditions and is validated with transect survey data. The test results suggest that the method can estimate deltaic-bar topography in front of a river mouth with a root-mean-square error of <0.5 m. The applicable range is limited by wave breaking in the inner bar and up to a depth of ~8 m, where swell intensity signals become ambiguous. A comparison of the different cases shows that the method works better under calm weather conditions with dominant swells propagating from non-local sources. Significant morphological changes of a river-mouth bar due to a powerful typhoon are successfully detected by observations right before and after the event.
Highlights
The depth inversion was performed on a regular grid with 2-m grid spacing, and the wave parameters were computed at each grid point with eight reference points (N = 8) along a circumference with r = 20 m; we will later discuss the estimation sensitivity to the two parameters
The exception occurs in the land area, surf zones, and areas where the wave signal is weaker than noise signals, or where two wave components of similar magnitudes superpose in the signal
We developed a simple method to estimate two-dimensional coastal bathymetry from
Summary
From practical and scientific viewpoints, it is crucial to monitor dynamic bathymetry around a river mouth as a relay point of fluvial sediment supply to coastal zones. Without understanding the morphodynamics of a river mouth during an extreme event, we cannot estimate the sediment budget in a coastal zone and conduct proper erosion management in the long term. Water depth estimation from video-sensed waves has gained popularity as a lowcost alternative to obtain two-dimensional coastal bathymetry. There are two main approaches to extract wave parameters from the video imagery: spectral and temporal methods. Both methods assume that the pixel intensity time series is closely related to water surface variation [6].
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