Observations of cohesive sediment behaviors in the muddy area of the northern Taiwan Strait, China

Wang, Ai‐Jun; Xiang, Yu‐Tao; Du, Xiaoqin; Zheng, Binxin

doi:10.1016/j.csr.2014.04.002

Cited by 19 publications

(14 citation statements)

References 49 publications

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“…Meanwhile, resuspension contributed~5 mg L −1 SSC near the Maumee River mouth (Fig. 10b2), resulting from the corresponding high τ cw (8.9 × 10 −5 Pa) generated by the rapid F MA -induced currents (τ c = 7.5 × 10 −5 Pa), which is typical in wavesheltered channel systems (e.g., Wang et al 2014). As a result, HTE concentrated near the river mouths throughout flood11 and originated from rivers in the main (Figs.…”

Section: Relative Contributions Of River Loading Vs Resuspension To mentioning

confidence: 99%

High‐turbidity events in Western Lake Erie during ice‐free cycles: Contributions of river‐loaded vs. resuspended sediments

Niu

Xia

Ludsin

et al. 2018

Limnology & Oceanography

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High‐turbidity events (HTEs) are common phenomena in shallow‐water environments that can alter ecological interactions. The relative contributions of river input (external loading) vs. resuspension (internal loading) to the occurrence, duration, and influenced areas of HTEs are not fully understood in most systems, owing to the lack of long‐term, source‐specified sediment maps. Using a Finite Volume Community Ocean Model‐based wave‐current forced sediment model, we investigated sediment dynamics in the shallow, river‐dominated Western Lake Erie during ice‐free cycles (April–November) of 2002–2012. Results indicated that wind waves predominated sediment dynamics in the offshore areas, with river discharges causing substantial inshore to offshore gradients. Owing to varying wind waves and river discharges, both the mean and extreme sediment dynamics had distinctive seasonal variations. The basin was turbid during spring and fall, with frequent (> 15%), broad (O [102–103 km2]), and more persistent (means of 3.2/4.4 d during spring/fall) HTEs caused mainly by resuspension events. During summer, the basin was clearer with occasional (< 1%), small (O [1–102 km2]), and short (mean of 1.5 d) HTEs near the mouths generated by pulsing river loadings. Although river loading rarely induced basin‐wide HTEs, they were important during floods, enlarging the high‐turbidity areas by 11.3%. Overall, by delineating the drivers of HTEs in Western Lake Erie, this study furthered the understanding of sediment dynamics in shallow ecosystems and provides a basis for investigating the ecological impact of sediments from different sources in river‐ and wave‐energetic systems.

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Section: Relative Contributions Of River Loading Vs Resuspension To mentioning

confidence: 99%

High‐turbidity events in Western Lake Erie during ice‐free cycles: Contributions of river‐loaded vs. resuspended sediments

Niu

Xia

Ludsin

et al. 2018

Limnology & Oceanography

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“…The ADV also recorded the distance from the probe to the surface of the sediment (i.e., the boundary elevation; Salehi and Strom, 2012; measurement accuracy: ±1 mm). The vertical distance from the probe to the surface of the sediment increases when resuspension occurs (net erosion), and decreases when deposition occurs (net accretion) (Salehi and Strom, 2012;Wang et al, 2014). Thus, changes in the bed level attributable to net erosion or accretion can be measured using the ADV.…”

Section: Field Measurementsmentioning

confidence: 99%

“…Thus, changes in the bed level attributable to net erosion or accretion can be measured using the ADV. We thus acquired information on the intratidal bed-level changes during the data collection periods, and related erosion and deposition from the time series (Andersen et al, 2007;Salehi and Strom, 2012;Wang et al, 2014). We used an ADV because it can provide data on intratidal bedlevel changes to an accuracy of 1 mm (Andersen et al, 2007;Salehi and Strom, 2012).…”

Section: Field Measurementsmentioning

confidence: 99%

“…The above evidence suggests that field measurements of intratidal bed-level changes are important in identifying the causes of the variability in SSC (e.g., Dyer, 1989;Andersen et al, 2007;Salehi and Strom, 2012). With the development of high-precision instruments, such as acoustic Doppler velocimeters (ADV; e.g., Andersen et al, 2007;Pratolongo et al, 2010;Salehi and Strom, 2012;Wang et al, 2014;Shi et al, 2015) and acoustic scour monitors (ARXII; e.g., Christie et al, 1999Christie et al, , 2000, which can measure intratidal bed-level changes during submergence and through the transport and deposition phases, it is possible to determine whether an increase in the SSC is caused by resuspension or advection processes over an intertidal wetland. These new technologies also allow the quantitative estimation of the relative contributions of resuspension, deposition, and advection processes to SSCs.…”

Section: Introductionmentioning

confidence: 98%

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Field and theoretical investigation of sediment mass fluxes on an accretional coastal mudflat

Shi

Wang

et al. 2016

Journal of Hydro-environment Research

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“…The Seapoint Turbidity manual reported that the sensor response becomes nonlinear above 750 FTU; however, the useful range can be extended by calibrating the sensor and fitting the response to a second-order polynomial equation. Similarly, Wang et al (2014) reported that values up to 600 FTU had good relations with SSC. It can be concluded that turbidity measurements should be conducted for lower sediment concentrations and that subsamples with dilution should be used for high concentrations (Foster et al, 1992).…”

Section: Regression Analysesmentioning

confidence: 99%

Analyses of Turbidity and Acoustic Backscatter Signal With Artificial Neural Network for Estimation of Suspended Sediment Concentration

Meral¹

2018

Appl. Ecol. Env. Res.

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Abstract. The commonly used sampling method is restrictive for the spatial and temporal measurement of suspended sediment and requires intensive labor. These limitations and technological advances have led to methods based on sound or light scattering in water. In this study, the turbidity and acoustic backscattering signal (ABS) values were used with the aim of improving these methods with different artificial neural network (ANN) models; Multilayer Perceptron (MLP), Radial Basis Neural networks (RBNN) and General Regression Neural Network (GRNN). Measurements were taken in a vertical sediment tower for two different sediment sizes (< 50 µm and 50-100 µm) and concentrations (0.0-6.0 g L -1 ). In the results of the regression analyses, turbidity values had strong relationships with sediment concentration for both sediment size groups (R 2 = 0.937 and 0.967). Although the ABS values had a reasonable R 2 value (0.873) for the 50-100 µm group, the < 50 µm group did not produce a significant R 2 value with regression analyses. The remarkable differences were not observed among MLP, RBNN and GRNN model for this sediment size group, and the reasonable R 2 and RMSE results were not produced with any ANN model that had a single ABS input for the < 50 µm sediment group. On the other hand, for the other sediment group (50-100 µm), ABS values were used as a single input, and the highest R 2 (0.917) value was obtained with MLP model and it was improved with the turbidity input (up to R 2 = 0.999). The results show that the ANN model could be considered as an alternative method because it was applied successfully to estimate suspended sediment concentration using with turbidity and ABS under different particle size conditions.

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Observations of cohesive sediment behaviors in the muddy area of the northern Taiwan Strait, China

Cited by 19 publications

References 49 publications

High‐turbidity events in Western Lake Erie during ice‐free cycles: Contributions of river‐loaded vs. resuspended sediments

High‐turbidity events in Western Lake Erie during ice‐free cycles: Contributions of river‐loaded vs. resuspended sediments

Field and theoretical investigation of sediment mass fluxes on an accretional coastal mudflat

Analyses of Turbidity and Acoustic Backscatter Signal With Artificial Neural Network for Estimation of Suspended Sediment Concentration

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