A national‐scale study of spatial variability in the relationship between turbidity and suspended sediment concentration and sediment properties

2020 ◽  
Vol 36 (8) ◽  
pp. 1449-1459
Author(s):  
Christina E. Bright ◽  
Sarah M. Mager
2018 ◽  
Vol 40 ◽  
pp. 05016
Author(s):  
Rui Aleixo ◽  
Massimo Guerrero ◽  
Nils Ruther ◽  
Siri Stokseth

Monitoring stations in rivers and water courses are an important mean to obtain critical data about the different variables that play a role in the hydrodynamics and ecological processes. Measuring suspended sediment concentration often requires the displacement of equipment and manpower to the field. This is often expensive and not practical, in particular during severe weather and flow conditions. A method to determine the suspended sediment concentration as a result of ADCP remote measurements is here presented. This method relies on the relationship between the attenuation to backscatter ratio and the normalized attenuation coefficient. To test this method, data from a field monitoring station in Kokel, on the banks of the Devoll river in Albania, is used.


Water ◽  
2019 ◽  
Vol 11 (12) ◽  
pp. 2497 ◽  
Author(s):  
Irma Ayes Rivera ◽  
Ana Claudia Callau Poduje ◽  
Jorge Molina-Carpio ◽  
José Max Ayala ◽  
Elisa Armijos Cardenas ◽  
...  

Fluvial sediment dynamics plays a key role in the Amazonian environment, with most of the sediments originating in the Andes. The Madeira River, the second largest tributary of the Amazon River, contributes up to 50% of its sediment discharge to the Atlantic Ocean, most of it provided by the Andean part of the Madeira basin, in particular the Beni River. In this study, we assessed the rainfall (R)-surface suspended sediment concentration (SSSC) and discharge (Q)-SSSC relationship at the Rurrenabaque station (200 m a.s.l.) in the Beni Andean piedmont (Bolivia). We started by showing how the R and Q relationship varies throughout the hydrological year (September to August), describing a counter-clockwise hysteresis, and went on to evaluate the R–SSSC and Q–SSSC relationships. Although no marked hysteresis is observed in the first case, a clockwise hysteresis is described in the second. In spite of this, the rating curve normally used ( SSSC = aQ b ) shows a satisfactory R2 = 0.73 (p < 0.05). With regard to water discharge components, a linear function relates the direct surface flow Qs–SSSC, and a hysteresis is observed in the relationship between the base flow Qb and SSSC. A higher base flow index (Qb/Q) is related to lower SSSC and vice versa. This article highlights the role of base flow on sediment dynamics and provides a method to analyze it through a seasonal empirical model combining the influence of both Qb and Qs, which could be employed in other watersheds. A probabilistic method to examine the SSSC relationship with R and Q is also proposed.


Author(s):  
Agnieszka Hejduk ◽  
Kazimierz Banasik

Suspended sediment concentration and yield in snowmelt flood events in a small lowland river Results of investigation on suspended sediment delivery from small lowland, agriculturally used catchment of Zagożdżonka River, located in central Poland, during snowmelt periods of 2001-2007 are presented. The study catchment's area, upstream of the well equipped gauging station at Czarna, is 23.4 km2. Suspended sediment concentration and sediment yield has been calculated and analysed for 15 snowmelt flood events. The relationship between suspended sediment concentration and the discharge has been analyzed. It has been found that the relation, in majority of the cases, has the form of clockwise hysteresis, however the existance of other types of hysteresis i.e. anticlockwise and "8" shape, have been also confirmed. Significant relation between suspended sediment yield and runoff volume of snowmelt flood events has been also found.


2013 ◽  
Vol 11 (4) ◽  
pp. 457-466

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.


Sign in / Sign up

Export Citation Format

Share Document