Hydrodynamics, erosion and accretion of intertidal mudflats in extremely shallow waters

Shi, Benwei; Cooper, James R.; Li, Jiasheng; Yang, Yang; Yang, S.L.; Luo, Feng; Yu, Z. X.; Wang, Ya Ping

doi:10.1016/j.jhydrol.2019.03.065

Cited by 22 publications

(19 citation statements)

References 48 publications

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“…These observational shortcomings, combined with increasing demand for high‐frequency measurements, suggest that new autonomous observation approaches should be explored for obtaining better insight into bed‐level dynamics within the intertidal zones. With the advances in acquisition sensors, data‐loggers, and power supply systems, a wide variety of autonomous instruments have been developed and applied for bed‐level observations over the past decades, including the photo‐electronic erosion pin sensor (PEEP; Lawler 2008), resistive rods (Arnaud et al 2011), ALTUS (Ganthy et al 2013), and acoustic doppler velocimetry (ADV; Andersen et al 2006; Shi et al 2017, 2019; Pang et al 2021). Nonetheless, most of these instruments are associated with high unit cost and labor‐intensive deployment with accompanying external power and data‐logging systems.…”

Section: Instrument Methods Accuracy (Mm) Measurement Frequency Worki...mentioning

confidence: 99%

A comparison and coupling of two novel sensors for intertidal bed‐level dynamics observation

Willemsen

et al. 2023

Limnology & Ocean Methods

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Previous studies have revealed the importance of short-term bed-level change on the long-term development of intertidal ecosystems. One of the recent advancements in the short-term bed dynamics observation is the developments of laser-based surface elevation dynamics (LSED) and acoustic surface elevation dynamics (ASED) sensors. These two sensors are developed to automatically monitor tidally induced bed-level changes, and their measuring windows are during emergent and submerged periods, respectively. So far, there is no direct comparison or joint application of these two sensors. Therefore, in the current study, we first compare their observation precision in both laboratory and field conditions. Results show that both sensors' measurements are in good agreement with the manual measurements in the flume (R 2 > 0.99) and field (R 2 ≈ 0.70), indicating the applicability of each sensor in natural environment. Finally, a coupled system (i.e., combining LSED and ASED) is established in a mangrove wetland and both sensors show good agreement with each other (R 2 = 0.69). Results also demonstrate that the coupled observation system can well capture the bed-level change during emergent and submerged conditions, which provides detailed continuous data sets to study the bed-level dynamics within a tidal cycle. Furthermore, large-scale monitoring systems can also be established via mobile network module embedded in the sensor, providing real-time monitoring for bed-level changes, which is valuable to coastal morphological research and vital for detecting deterioration of coastal ecosystems and the services they provide to be able to apply adaptive management.

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Section: Instrument Methods Accuracy (Mm) Measurement Frequency Worki...mentioning

confidence: 99%

A comparison and coupling of two novel sensors for intertidal bed‐level dynamics observation

Willemsen

et al. 2023

Limnology & Ocean Methods

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“…Acoustic sensors (Andersen et al, 2006;Jestin et al, 1998;Shi et al, 2019;Yu et al, 2017;Zhu et al, 2014 Note. The "dry" condition means when the tidal flat is drained, while the "wet" condition means when the tidal flat is inundated.…”

Section: Appendix A: a Review Of Manual And Autonomous Methods For Inmentioning

confidence: 99%

“…The combination of the machine learning approach and the high-frequency bed level observation system is expected to generate new insights of coastal biogeomorphic processes in future studies. (Andersen et al, 2006;Jestin et al, 1998;Shi et al, 2019;Yu et al, 2017;Zhu et al, 2014 Baptist et al, 2019;Hu, Lenting, et al, 2015;Willemsen et al, 2018 Note. The "dry" condition means when the tidal flat is drained, while the "wet" condition means when the tidal flat is inundated.…”

Section: 1029/2020wr027257mentioning

confidence: 99%

A Novel Instrument for Bed Dynamics Observation Supports Machine Learning Applications in Mangrove Biogeomorphic Processes

Zhou

Wang

et al. 2020

Water Resources Research

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Short‐term bed level changes play a critical role in long‐term coastal wetland dynamics. High‐frequency observation techniques are crucial for better understanding of intertidal biogeomorphic evolution. Here, we introduce an innovative instrument for bed level dynamics observation, that is, LSED‐sensor (Laser based Surface Elevation Dynamics sensor). The LSED‐sensors inherit the merits of the previously introduced optical SED sensors as it enables continuous high‐frequency monitoring with relatively low cost of labor and acquisition. As an iteration of the optical SED‐sensors, the LSED‐sensors avoid touching the measuring object (i.e., bed surface), and they do not rely on daylight by adapting laser‐ranging technique. Furthermore, the new LSED‐sensors are equipped with a real‐time data transmission function, enabling automatic observation networks covering multiple (remote) sites. During a 22‐day field survey in a mangrove wetland, good agreement (R2 = 0.7) has been obtained between the automatic LSED‐sensor measurement and an accurate ground‐truth measurement method, that us, Sedimentation Erosion Bars. The obtained LSED‐sensor data were subsequently used to develop machine learning predictors, which revealed the effect of vegetation is a main driver in the accumulative and daily bed level changes. We expect that the LSED‐sensors can further support machine learning applications to extract new knowledge on coastal biogeomorphic processes.

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“…Wind waves govern the nearshore dynamics in combination with tidal and current flows [1,2]. They are really important phenomena in the sediment resuspension mechanism of coastal lagoons, sheltered estuarine basins, and shallow lakes [3][4][5][6][7][8][9][10]. In these contexts, where depth limits both current velocities and the relative bottom shear stresses, locally generated waves trigger the main morphological processes [11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

“…Experimental wave measurements are still essential to investigate hydrodynamic and erosion-accretion processes on shallow depths [8,16,[21][22][23], but they are quite rare. The available data has revealed that the growth of wind waves, locally generated on finite depth, is greatly affected by energy dissipations due to the interaction with bottom [24][25][26].…”

Section: Introductionmentioning

confidence: 99%

Wave Forecasting in Shallow Water: A New Set of Growth Curves Depending on Bed Roughness

Pascolo

Petti

Bosa

2019

Water

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Forecasting relationships have been recognized as an important tool to be applied together, or not, with complete numerical modelling in order to reconstruct the wave field in coastal areas properly when the available wave data is limited. In recent years, the literature has offered several comprehensive sets of field experiments investigating the form of the asymptotic, depth-limited wind waves. This has made it possible to reformulate the original deep water equations, taking into account the effects of water depth, if wind waves are locally generated in shallow and confined basins. The present paper is an initial attempt to further contribute to the shallow water forecasting curves which are currently available, also considering the role on the wave generation of a variable equivalent bottom roughness. This can offer the possibility of applying shallow growth curves to a broad variety of contexts, for which bed composition and forms can be different. Simple numerical tests have been conducted to reproduce the fully developed conditions of wave motion with variable roughness values. To validate the new set of equations, they have been applied to a real shallow lake for which both experimental and numerical wave data is available. The comparison of the obtained results is very encouraging in proceeding with this approach.

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Hydrodynamics, erosion and accretion of intertidal mudflats in extremely shallow waters

Cited by 22 publications

References 48 publications

A comparison and coupling of two novel sensors for intertidal bed‐level dynamics observation

A comparison and coupling of two novel sensors for intertidal bed‐level dynamics observation

A Novel Instrument for Bed Dynamics Observation Supports Machine Learning Applications in Mangrove Biogeomorphic Processes

Wave Forecasting in Shallow Water: A New Set of Growth Curves Depending on Bed Roughness

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