Challenges to the representation of suspended sediment transfer using a depth‐averaged flux

Abstract

The sediment saturation recovery process (i.e. the adaptation of suspended sediment concentration [SSC] to local forcing) is the main feature of the non‐equilibrium suspended sediment transport (SST) frequently occurring in fluvial, estuarine and coastal waters. In order to quantitatively describe this phenomenon, a series solution is analytically derived, including the evolution of both vertical SSC profile and near‐bed sediment flux (NBSF), and is verified by net erosion and net deposition experiments, respectively. The results suggest that the sediment saturation recovery process involves vertically varying fluxes that are not represented correctly by depth‐averaging. Consequently, a vertical two‐dimensional (2D) combined scheme is established and applied respectively in to a dredged trench and to a sand wave feature to demonstrate this argument. By analyzing the variations of the calculated depth‐averaged SSC and NBSF we reveal that the equilibrium state presented by the sediment carrying capacity (SCC) form of the NBSF, which is usually applied in depth‐integrated SST models, lags behind the actual dynamic bed equilibrium state. Moreover, the key factor α, the so‐called saturation recovery coefficient within this form, is not only a function of local Rouse number but also is influenced by the local SSC profile. Finally, a three‐dimensional (3D) non‐orthogonal curvilinear body‐fitted SST model is developed and validated in the Yangtze estuary, China, combined with the in situ hourly hydrographic data from August 14–15, 2007 during spring tide in the wet season. Model results confirm that the vertically varying sediment saturation recovery process, the discrepancies between the actual and SCC form of NBSF and non‐constant value of α are significant in actual real geomorphic cases. The quantitative morphological change resulting from variations in environmental conditions may not be correctly represented by uncorrected depth‐integrated SST models if they do not treat the effects of vertical motion on the sediment saturation recovery process. Copyright © 2016 John Wiley & Sons, Ltd.

Using Landsat 8 data to estimate suspended particulate matter in the Yellow River estuary

“…A strong relationship was observed between multiyear mean distributions of SPM and the current field (Figures 8a and 14), with high SPM concentrations found in the strong current areas. This is attributable to the fact that strong currents not only keep sediments suspended in water but also stir and resuspend sediments [Cheng et al, 2016]. Therefore, we can conclude that distributions of the multiyear mean SPM are mainly attributable to currents.…”

Seasonal and Interannual Variability of Satellite-Derived Chlorophyll-a (2000–2012) in the Bohai Sea, China

“…This dataset spanned 2000 to 2012 for a rectangular region (36)(37)(38)(39)(40)(41)(42) • N and 117-124 • E) that encompassed our study region. Additionally, the Level 3 monthly SST and PAR data with global coverage during our study period were obtained from the NASA ocean color website.…”

“…For instance, the Tassan-like algorithm [8] and OC4 algorithm [10] have been widely In this study, the Bohai Sea was subdivided into six sub-regions, following geographical regions (Figure 1b), including Liaodong bay (156 pixels), Qinhuangdao coast (144 pixels), Bohai bay (169 pixels), Laizhou bay (128 pixels), central Bohai Sea (256 pixels), and Bohai strait (165 pixels). The areas along the coastline of the Bohai Sea were excluded because of high levels of suspended sediment, which may increase the uncertainties of satellite-derived Chl-a [35,36]. Meanwhile, the northern Yellow Sea (400 pixels) was distinguished separately as a specific region.…”

Study on the Spillover of Sediment during Typical Tidal Processes in the Yangtze Estuary Using a High-Resolution Numerical Model

“…The size ranges of fractions 1-4 are, sequentially, 0-0.031, 0.031-0.125, 0.125-0.5, and >0.5 mm. In real applications, researchers often determined the settling velocity (w s ) of the fine particles according to field data, experiments or their experience [11,12,[17][18][19][20]. In the present model, the w s of fraction 1 is set according to field data in the Yangtze Estuary, while the primitive settling velocity is directly used for other fractions.…”