scholarly journals On the Relationship between Suspended Sediment Concentration, Rainfall Variability and Groundwater: An Empirical and Probabilistic Analysis for the Andean Beni River, Bolivia (2003–2016)

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.

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.


2020 ◽  
Vol 13 (21) ◽  
Author(s):  
Caiwen Shu ◽  
Guangming Tan ◽  
Yiwei Lv ◽  
Quanxi Xu

AbstractUsing experimental data of near-bed suspended sediment concentrations at five typical hydrometric stations of the Three Gorges Reservoir at the early reserving stage, the differences were investigated between the common method and improved method during flood seasons and non-flood seasons. The impact of taking measurements below 0.2 times the water depth on the results was discussed. The results show that the average discharges and velocities at each station calculated by the common method were slightly larger than those calculated by the improved method. Regarding the suspended sediment concentration at each station, the errors in the reservoir and downstream channels in dynamic equilibrium state were small, and the largest errors occurred where the river bed was strongly scoured in the downstream reach below the large dam. There was no significant relationship between water discharge and flow velocity, and the missed measurement phenomenon also occurred. The sediment discharge error was affected by the suspended sediment concentration, implying that errors usually occurred in channels with serious erosion during flood seasons. The correction coefficients (R2) of sediment discharge at each station were given during the experiment, which showed that the sediment discharges at the hydrometric stations where a large amount of sediment transport occurred near the river bottom, needed to be modified. Furthermore, the test methods proposed in this study were applied to calculate the sediment discharges of three rivers, and the results indicate that this method can narrow the gap between bathymetric comparisons and sediment load measurements.


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.


2018 ◽  
Author(s):  
Anna Costa ◽  
Daniela Anghileri ◽  
Peter Molnar

Abstract. We analyse the control of hydroclimatic factors on suspended sediment concentration (SSC) in Alpine catchments by differentiating among the potential contributions of erosion and suspended sediment transport driven by erosive rainfall, defined as liquid precipitation over snow free surfaces, icemelt from glacierized areas, and snowmelt on hillslopes. We account for the potential impact of hydropower by intercepting sediment fluxes originated in areas diverted to hydropower reservoirs, and by considering the contribution of hydropower releases to SSC. We obtain the hydroclimatic variables from daily gridded datasets of precipitation and temperature, implementing a degree–day model to simulate spatially distributed snow accumulation and snow–ice melt. We estimate hydropower releases by a conceptual approach with a unique virtual reservoir regulated on the basis of a target–volume function, representing normal reservoir operating conditions throughout a hydrological year. An Iterative Input Selection algorithm is used to identify the variables with the highest predictive power for SSC, their explained variance, and characteristic time lags. On this basis, we develop a hydroclimatic multivariate rating curve (HMRC) which accounts for the contributions of the most relevant hydroclimatic input variables mentioned above. We calibrate the HMRC with a gradient–based nonlinear optimization method and we compare its performance with a traditional discharge–based rating curve. We apply the approach in the upper Rhone Basin, a large Swiss Alpine catchment, heavily regulated by hydropower. Our results show that the three hydroclimatic processes – erosive rainfall, icemelt, and snowmelt – are significant predictors of mean daily SSC, while hydropower release does not have a significant explanatory power for SSC. The characteristic time lags of the hydroclimatic variables correspond to the typical flow concentration times of the basin. Despite not including discharge, the HMRC performs better than the traditional rating curve in reproducing SSC seasonality, especially during validation at the daily scale. While erosive rainfall determines the daily variability of SSC and extremes, icemelt generates the highest SSC per unit of runoff, and represents the largest contribution to total suspended sediment yield. Finally, we show that the HMRC is capable of simulating climate–driven changes in fine sediment dynamics in Alpine catchments. In fact, HMRC can reproduce the changes in SSC in the past 40 years in the Rhone Basin connected to air temperature rise, even though the simulated changes are more gradual than those observed. The approach presented is this paper, based on the analysis of the hydroclimatic control on suspended sediment concentration, allows the exploration of climate–driven changes in fine sediment dynamics in Alpine catchments. The approach can be applied to any Alpine catchment with a pluvio–glacio–nival hydrological regime and adequate hydroclimatic datasets.


2012 ◽  
Vol 9 (7) ◽  
pp. 9011-9041 ◽  
Author(s):  
C. D. Guzman ◽  
S. A. Tilahun ◽  
A. D. Zegeye ◽  
T. S. Steenhuis

Abstract. Loss of top soil and subsequent filling up of reservoirs in much of the lands with variable relief in developing countries degrades environmental resources necessary for subsistence. In the Ethiopia highlands, sediment mobilization from rain-fed agricultural fields is one of the leading factors causing land degradation. Sediment rating curves, produced from long-term sediment concentration and discharge data, attempt to predict suspended sediment concentration variations that exhibit a distinct shift with the progression of the rainy season. In this paper, we calculate sediment rating curves and examine this shift in concentration for three watersheds in which rain-fed agriculture is practiced to differing extents. High sediment concentrations with low flows are found in the beginning of the rainy season of the semi-monsoonal climate, while high flows and low sediment concentrations occur at the end of the rainy season. Results show that a reasonable unique set of rating curves were obtained by separating biweekly data into early, mid, and late rainfall periods and by making adjustments for the ratio of plowed cropland. The shift from high to low concentrations suggests that diminishing sediment supply and dilution from greater base flow during the end of the rainfall period play important roles in characterizing changing sediment concentrations during the rainy season.


2016 ◽  
Vol 18 (1) ◽  
pp. 47-58
Author(s):  
Sanja MANOJLOVIĆ ◽  
Predrag MANOJLOVIĆ ◽  
Mrdjan DJOKIĆ

The study is concerned with determination of the trend of water discharge, suspended sediment concentration and sediment load in the most downstream profile of the Velika Morava River in the period 1967-2007. The gradual trend test (Mann–Kendall test – MK test) and abrupt change test (Pettitt test) have been employed on annual, seasonal and monthly water discharge, suspended sediment concentration and suspended sediment load for the given time series. Both the Mann–Kendall and Pettitt tests indicate that water discharge showed no significant annual trend or abrupt shift. However, annual suspended sediment concentration and sediment load showed significant decreasing trends (α=0.001). The average decrease of suspended sediment load transport amounted to 3.15 t/km2/yr. The Pettitt test results showed that the change-point year was detected in 1982. The average specific sediment load amounted to 134.6 t/km2/yr before the transition year, and 36.5 t/km2/yr after the transition year, i.e., it was reduced by 73 %. In the intra-annual distribution, the MK test results indicate that the most pronounced decreasing trend (α=0.001) of the sediment load is during summer and winter. Strong seasonal and monthly variability in sediment load was found. Sediment was strongly transported during spring months, in the period of frequent flood events. Almost 50% of the annual sediment is transported during March, April and May. Analysis of the discharge and suspended sediment concentration relationship revealed the existence of hysteresis loop in the shape of figure eight. The results of this study confirm the complex and heterogeneous nature of sediment response in the Velika Morava River.


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