scholarly journals Nearbed current and suspended sediment concentration recorded by a seabed lander deployed in the deep water at Sackville Spur, Grand Banks, Newfoundland and Labrador

2016 ◽  
Author(s):  
M Z Li ◽  
D J Schillinger ◽  
A Robertson
Keyword(s):  
Suspended Sediment ◽  
Deep Water ◽  
Newfoundland And Labrador ◽  
Suspended Sediment Concentration ◽  
Sediment Concentration ◽  
Grand Banks

Analysis of the Sediment Characteristics of the Caofeidian Sea Area

2011 ◽  
Vol 250-253 ◽  
pp. 3484-3488 ◽  
Author(s):  
Cui Ping Kuang ◽  
Ying Hu ◽  
Jie Gu ◽  
Jing Huang ◽  
Xu Liu
Keyword(s):  
Suspended Sediment ◽  
Deep Water ◽  
Suspended Sediment Concentration ◽  
Water Channel ◽  
Sediment Concentration ◽  
Eastern Coast ◽  
West Part ◽  
Under Construction ◽  
Bed Material ◽  
Sea Area

Caofeidian harbor is a large size deep-water harbor currently under construction in the eastern coast of north China. The construction began in 2003. Based on the measurements and analysis of the sediment samples collected from 2008 to 2010, the characteristics of suspended sediment concentration, suspended sediment and bed material grain diameter of the Caofeidian sea area with the progress of the engineering are presented. The measurements and analysis reveal that i) the suspended sediment concentration is low and decreases with the engineering progress; ii) the suspended sediment is very fine and becomes coarse in the deep-water channel; iii) the bed sediment in the east of Caofeidian foreland is much coarser than that in the west part.

Neural networks approached for modelling river suspended sediment concentration due to tropical storms

2013 ◽  
Vol 11 (4) ◽  
pp. 457-466
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Suspended Sediment ◽  
Suspended Sediment Concentration ◽  
Time Series Data ◽  
Water Discharge ◽  
Sediment Concentration ◽  
Series Data ◽  
Generalized Regression Neural Network ◽  
Event Based

Artificial neural networks are one of the advanced technologies employed in hydrology modelling. This paper investigates the potential of two algorithm networks, the feed forward backpropagation (BP) and generalized regression neural network (GRNN) in comparison with the classical regression for modelling the event-based suspended sediment concentration at Jiasian diversion weir in Southern Taiwan. For this study, the hourly time series data comprised of water discharge, turbidity and suspended sediment concentration during the storm events in the year of 2002 are taken into account in the models. The statistical performances comparison showed that both BP and GRNN are superior to the classical regression in the weir sediment modelling. Additionally, the turbidity was found to be a dominant input variable over the water discharge for suspended sediment concentration estimation. Statistically, both neural network models can be successfully applied for the event-based suspended sediment concentration modelling in the weir studied herein when few data are available.

scholarly journals Suspended sediment concentration field quantified from a calibrated MultiBeam EchoSounder

2021 ◽  
Vol 180 ◽  
pp. 108107
Author(s):  
Guillaume Fromant ◽  
Nicolas Le Dantec ◽  
Yannick Perrot ◽  
France Floc'h ◽  
Anne Lebourges-Dhaussy ◽  
...  
Keyword(s):  
Suspended Sediment ◽  
Suspended Sediment Concentration ◽  
Concentration Field ◽  
Sediment Concentration ◽  
Multibeam Echosounder

scholarly journals Insights on the Impacts of Hydroclimatic Extremes and Anthropogenic Activities on Sediment Yield of a River Basin

Earth ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 32-50
Author(s):  
Rocky Talchabhadel ◽  
Jeeban Panthi ◽  
Sanjib Sharma ◽  
Ganesh R. Ghimire ◽  
Rupesh Baniya ◽  
...  
Keyword(s):  
Suspended Sediment ◽  
River Basin ◽  
Extreme Precipitation ◽  
Suspended Sediment Concentration ◽  
Anthropogenic Activities ◽  
Sediment Concentration ◽  
Sediment Flux ◽  
Mountain River ◽  
Ecological Processes ◽  
Precipitation Indices

Streamflow and sediment flux variations in a mountain river basin directly affect the downstream biodiversity and ecological processes. Precipitation is expected to be one of the main drivers of these variations in the Himalayas. However, such relations have not been explored for the mountain river basin, Nepal. This paper explores the variation in streamflow and sediment flux from 2006 to 2019 in central Nepal’s Kali Gandaki River basin and correlates them to precipitation indices computed from 77 stations across the basin. Nine precipitation indices and four other ratio-based indices are used for comparison. Percentage contributions of maximum 1-day, consecutive 3-day, 5-day and 7-day precipitation to the annual precipitation provide information on the severity of precipitation extremeness. We found that maximum suspended sediment concentration had a significant positive correlation with the maximum consecutive 3-day precipitation. In contrast, average suspended sediment concentration had significant positive correlations with all ratio-based precipitation indices. The existing sediment erosion trend, driven by the amount, intensity, and frequency of extreme precipitation, demands urgency in sediment source management on the Nepal Himalaya’s mountain slopes. The increment in extreme sediment transports partially resulted from anthropogenic interventions, especially landslides triggered by poorly-constructed roads, and the changing nature of extreme precipitation driven by climate variability.

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