- Title
- Lidar observations of multi-modal swash probability distributions on a dissipative beach
- Creator
- Stringari, Caio Eadi; Power, Hannah E.
- Relation
- Remote Sensing Vol. 13, Issue 3, no. 462
- Publisher Link
- http://dx.doi.org/10.3390/rs13030462
- Publisher
- MDPI AG
- Resource Type
- journal article
- Date
- 2021
- Description
- Understanding swash zone dynamics is of crucial importance for coastal management as the swash motion, consisting of the uprush of the wave on the beach face and the subsequent downrush, is responsible for driving changes in the beach morphology through sediment exchanges between the sub-aerial and sub-aqueous beach. Improved understanding of the probabilistic characteristics of these motions has the potential to allow coastal engineers to develop improved sediment transport models which, in turn, can be further developed into coastal management tools. In this paper, novel descriptors of swash motions are obtained by combining field data and statistical modelling. Our results indicate that the probability distribution function (PDF) of shoreline height timeseries (p(ζ)) and trough-to-peak swash heights (p(ρ)) measured at a high energy, sandy beach were both inherently multimodal. Based on the observed multimodality of these PDFs, Gaussian mixtures are shown to be the best method to statistically model them. Further, our results show that both offshore and surf zone dynamics are responsible for driving swash zone dynamics, which indicates unsaturated swash. The novel methods and results developed in this paper, both data collection and analysis, could aid coastal managers to develop improved swash zone models in the future.
- Subject
- LiDAR; swash zone; nearshore waves; probability distributions; sandy beaches; SDG 14; Sustainable Development Goals
- Identifier
- http://hdl.handle.net/1959.13/1457894
- Identifier
- uon:45388
- Identifier
- ISSN:2072-4292
- Rights
- © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
- Language
- eng
- Full Text
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