INFLUENCE OF DIFFERENT TEMPORAL SAMPLING STRATEGIES ON ESTIMATING TOTAL PHOSPHORUS AND SUSPENDED SEDIMENT CONCENTRATION AND TRANSPORT IN SMALL STREAMS

Author(s):  
Dale M. Robertson
Author(s):  
Leandro Dalbianco ◽  
Rafael Ramon ◽  
Claudia A. P. de Barros ◽  
Jean P. G. Minella ◽  
Gustavo H. Merten ◽  
...  

ABSTRACT The influx of sediments carried by rivers can be measured continuously using a turbidimeter through the indirect relationship between turbidity and suspended sediment concentration (SSC). However, this process is dependent on obtaining water samples with suspended sediments to calibrate the turbidimeter. Sampling can be carried out through different methods, resulting in errors and uncertainties in estimating the SSC. Four different possibilities for the composition of the calibration curve were tested in order to evaluate the effectiveness of the turbidimeter calibration for different sampling strategies. The study was conducted in 2012 and 2013 in two catchments in southern Brazil that had a strong sediment yield impact. The results indicate that sampling during rainfall events generate a significant and representative SSC for the turbidimeter calibration. The use of an integrating sampler for synthetic samples provides an effective calibration, but overestimates SSC compared to calibration from rainfall event sampling. The samples collected at fixed intervals - weekly and daily - generated an insufficient amount of data and are not representative of real sediment concentrations of the catchments.


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.


2021 ◽  
Vol 180 ◽  
pp. 108107
Author(s):  
Guillaume Fromant ◽  
Nicolas Le Dantec ◽  
Yannick Perrot ◽  
France Floc'h ◽  
Anne Lebourges-Dhaussy ◽  
...  

Earth ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 32-50
Author(s):  
Rocky Talchabhadel ◽  
Jeeban Panthi ◽  
Sanjib Sharma ◽  
Ganesh R. Ghimire ◽  
Rupesh Baniya ◽  
...  

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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