LiDAR Observations of Multi-Modal Swash Probability Distributions on a Dissipative Beach
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...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-01-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/13/3/462 |
| _version_ | 1797406267808940032 |
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| author | Caio Eadi Stringari Hannah E. Power |
| author_facet | Caio Eadi Stringari Hannah E. Power |
| author_sort | Caio Eadi Stringari |
| collection | DOAJ |
| 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 (<inline-formula><math display="inline"><semantics><mrow><mi>p</mi><mo>(</mo><mi>ζ</mi><mo>)</mo></mrow></semantics></math></inline-formula>) and trough-to-peak swash heights (<inline-formula><math display="inline"><semantics><mrow><mi>p</mi><mo>(</mo><mi>ρ</mi><mo>)</mo></mrow></semantics></math></inline-formula>) 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. |
| first_indexed | 2024-03-09T03:23:57Z |
| format | Article |
| id | doaj.art-df46c43496e04814afc210062f1fb63d |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-09T03:23:57Z |
| publishDate | 2021-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-df46c43496e04814afc210062f1fb63d2023-12-03T15:05:57ZengMDPI AGRemote Sensing2072-42922021-01-0113346210.3390/rs13030462LiDAR Observations of Multi-Modal Swash Probability Distributions on a Dissipative BeachCaio Eadi Stringari0Hannah E. Power1School of Environmental and Life Sciences, University of Newcastle, 2308 Newcastle, AustraliaSchool of Environmental and Life Sciences, University of Newcastle, 2308 Newcastle, AustraliaUnderstanding 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 (<inline-formula><math display="inline"><semantics><mrow><mi>p</mi><mo>(</mo><mi>ζ</mi><mo>)</mo></mrow></semantics></math></inline-formula>) and trough-to-peak swash heights (<inline-formula><math display="inline"><semantics><mrow><mi>p</mi><mo>(</mo><mi>ρ</mi><mo>)</mo></mrow></semantics></math></inline-formula>) 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.https://www.mdpi.com/2072-4292/13/3/462LiDARswash zonenearshore wavesprobability distributionssandy beaches |
| spellingShingle | Caio Eadi Stringari Hannah E. Power LiDAR Observations of Multi-Modal Swash Probability Distributions on a Dissipative Beach Remote Sensing LiDAR swash zone nearshore waves probability distributions sandy beaches |
| title | LiDAR Observations of Multi-Modal Swash Probability Distributions on a Dissipative Beach |
| title_full | LiDAR Observations of Multi-Modal Swash Probability Distributions on a Dissipative Beach |
| title_fullStr | LiDAR Observations of Multi-Modal Swash Probability Distributions on a Dissipative Beach |
| title_full_unstemmed | LiDAR Observations of Multi-Modal Swash Probability Distributions on a Dissipative Beach |
| title_short | LiDAR Observations of Multi-Modal Swash Probability Distributions on a Dissipative Beach |
| title_sort | lidar observations of multi modal swash probability distributions on a dissipative beach |
| topic | LiDAR swash zone nearshore waves probability distributions sandy beaches |
| url | https://www.mdpi.com/2072-4292/13/3/462 |
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