Turbulence Structure and Burst Events Observed in a Tidally Induced Bottom Boundary Layer

Abstract

As a three-dimensional vortex motion with high complexity, disorganization and randomness, turbulence is extremely unstable, unpredictable, and dissipative. With the development of fast responding observation techniques, researchers have carried out extensive research on various aspects of turbulence within the near-bottom boundary layer, including turbulent energy balance (Rippeth et al., 2001;Trowbridge et al., 1999) and intermittence characteristics (Wallace et al., 1972;Willmarth & Lu, 1972). The balance of turbulent kinetic energy (TKE) production and dissipation processes within the bottom boundary layer is controlled by horizontal TKE advection, buoyancy flux, vertical divergence, stratification, and other factors. Experimental verification of this balance has been the subject of numerous investigations (

Turbulence Intermittency Effects on the Initiation Threshold of Sediment Motion in Natural Waters

“…Furthermore, phase method, which posits a linear relationship across the waveband between low and high‐frequency spectra, was employed to decompose wave and turbulence terms (Bricker & Monismith, 2007). More details regarding the ADV data quality‐control and processing can be found in (R Li et al., 2022). The nephelometer measured turbidity was converted to suspended sediment concentration using calibration equations derived by correlating the recorded NTU values with sediment suspension concentration values.…”

“…Numerous studies have recently employed SSC inversion with ADV instruments to produce high‐quality <c'w'> time series and use them to examine the sediment transport characteristics affected by turbulence (R Li et al., 2022; Yuan et al., 2009). The high‐frequency <c'w'> time series presents different intermittency under different dynamic conditions (Figures 1e–1g), and as the dynamic strength increases (shear stress increases), high‐energy burst events occur more frequently, corresponding to lower intermittency.…”

“…Using this criterion, the number (N) of occurrences of successive events is counted. The average time elapsed between successive burst events (Figure 1h) during an ADV measuring segment, referred to as waiting time (R Li et al, 2022), is defined by:…”

“…These findings support the speculation that the sediment transport process within the bottom boundary layer is closely related to intermittent turbulent structures (Salim & Pattiaratchi, 2020; Yuan et al., 2009), and sediment is transported in a burst‐like manner. Nevertheless, the extraction of features for high‐resolution time series and thus the quantification of the connection between the two is still not well addressed (R Li et al., 2022; Yang et al., 2016). Some laboratory studies use statistical parametric approaches to extract intermittency information from experimental data and have further yielded some new insights into sediment initiation (Ancey et al., 2008; Carneiro et al., 2015; Liu et al., 2019).…”

Turbulent Flow Structures Over a Gobi Surface and Their Impact on Aeolian Sand Transport

“…Ejections and sweeps make a positive contribution to the turbulent shear stress or Reynolds stress because of downward momentum transport, while the inward and outward interactions, two weaker motions, contribute negatively to the Reynolds stress (Heathershaw & Thorne, 1985; Sterk et al., 1998). Studies on the relationship between turbulent structures and sediment transport dynamics have mainly focused on water flow (e.g., Dwivedi et al., 2010; Heathershaw & Thorne, 1985; Keylock et al., 2014; Li et al., 2022; Nelson et al., 1995; Wu & Shih, 2012; Yuan et al., 2009). Recent developments in ultrasonic anemometers and saltation sensors have enabled synchronous monitoring of turbulent wind and saltating particle counts at higher temporal resolutions (e.g., Martin et al., 2018), whereby the importance of these turbulent structures on sand transport over flat sand surfaces has been recognized in an increasing number of aeolian studies (e.g., Baas, 2006; Bauer et al., 1998; Leenders et al., 2005; Schönfeldt & von Löwis, 2003; Sterk et al., 1998; Wang et al., 2017).…”