Changes in woody debris and bed material texture in a gravel-bed channel

Geomorphology ◽  
2004 ◽  
Vol 60 (3-4) ◽  
pp. 241-267 ◽  
Author(s):  
Judith K. Haschenburger ◽  
Stephen P. Rice
Keyword(s):  
Woody Debris ◽  
Gravel Bed ◽  
Material Texture ◽  
Bed Material

scholarly journals The Prediction of Fine Sediment Distribution in Gravel-Bed Rivers Using a Combination of DEM and FNN

Water ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 1515
Author(s):  
Van Hieu Bui ◽  
Minh Duc Bui ◽  
Peter Rutschmann
Keyword(s):  
Feedforward Neural Networks ◽  
Fine Sediment ◽  
Sediment Distribution ◽  
Gravel Bed ◽  
Fine Sediments ◽  
Porosity Variation ◽  
Sediment Sorting ◽  
Gravel Bed Rivers ◽  
Bed Material ◽  
The Relationship

Large amounts of fine sediment infiltration into void spaces of coarse bed material have the ability to alter the morphodynamics of rivers and their aquatic ecosystems. Modelling the mechanisms of fine sediment infiltration in gravel-bed is therefore of high significance. We proposed a framework for calculating the sediment exchange in two layers. On the basis of the conventional approaches, we derived a two-layer fine sediment sorting, which considers the transportation of fine sediment in the form of infiltration into the void spaces of the gravel-bed. The relationship between the fine sediment exchange and the affected factors was obtained by using the discrete element method (DEM) in combination with feedforward neural networks (FNN). The DEM model was validated and applied for gravel-bed flumes with different sizes of fine sediments. Further, we developed algorithms for extracting information in terms of gravel-bed packing, grain size distribution, and porosity variation. On the basis of the DEM results with this extracted information, we developed an FNN model for fine sediment sorting. Analyzing the calculated results and comparing them with the available measurements showed that our framework can successfully simulate the exchange of fine sediment in gravel-bed rivers.

Effects of woody debris on the growth and behaviour of brown trout in experimental stream channels

1998 ◽  
Vol 76 (1) ◽  
pp. 56-61 ◽  
Author(s):  
Karl Sundbaum ◽  
Ingemar Näslund
Keyword(s):  
Brown Trout ◽  
Salmo Trutta ◽  
Woody Debris ◽  
Feeding Activity ◽  
Control Channel ◽  
Invertebrate Drift ◽  
Stream Channels ◽  
Gravel Bed ◽  
Brown Trout Salmo Trutta ◽  
Experimental Stream

We examined the effects of woody debris on the growth and behaviour of brown trout (Salmo trutta) in experimental stream channels. Two types of habitat were used in the study: a complex habitat created by placing woody debris on a gravel bed and a uniform habitat consisting of a gravel bed only. The experiment was run both outdoors with wild fish that fed on natural invertebrate drift and indoors with hatchery fish that were fed artificial food. In both treatments most of the fish lost mass. In all trials, however, the fish in the woody debris channel lost less mass than the fish in the control channel. Study of the fishes' behaviour revealed less swimming activity, less aggression, and less feeding activity in the woody debris channel than in the control channel. The results of this study indicate that the presence of woody debris decreases intraspecific competition through visual isolation, allowing fish to reduce aggressive interactions and energy expenditure.

scholarly journals A decision classifier to classify rivers for river management based on their structure in China: an example from the Yongding river

2016 ◽  
Vol 74 (7) ◽  
pp. 1539-1552 ◽  
Author(s):  
Yinjun Zhao ◽  
Aizhong Ding
Keyword(s):  
River Management ◽  
Classification Systems ◽  
Geographical Information ◽  
River Classification ◽  
Material Texture ◽  
Function Management ◽  
Bed Material ◽  
Geomorphic Units ◽  
The Yongding River ◽  
Yongding River

River classification is a very useful tool for river management yet still a difficult task. This paper proposed a new decision classifier (DCF) to classify rivers for Chinese river management based on existing classification systems. Aimed at river function management, the DCF with the five-layers frame was developed on reach level in a spatially nested pattern that from top to bottom are natural province, basin, valley, reach, habitat and microhabitat. Five indexes (artificial degree, closeness, sinuosity, bed material texture, geomorphic units (GUs)) were selected and organized into the DCF according to the importance of the influence on river structure from macro to micro, large to small and top to bottom, because they represent main aspects of river structures and are easy to obtain. In addition, the closeness index is another good connector between valley level and reach level, and the GUs index links reach level to habitat level. The overall procedure to use DCF includes primary indoor classification and field validation. Remote sensing, geographical information system and global positioning system technologies were adopted in the process to dramatically reduce workload, especially fieldwork. Finally, the approach was applied to the Yongding river as a good example, and 17 river styles were identified.

scholarly journals The dominance of dispersion in the evolution of bed material waves in gravel-bed rivers

2001 ◽  
Vol 26 (13) ◽  
pp. 1409-1420 ◽  
Author(s):  
Thomas E. Lisle ◽  
Yantao Cui ◽  
Gary Parker ◽  
James E. Pizzuto ◽  
Annjanette M. Dodd
Keyword(s):  
Gravel Bed ◽  
Gravel Bed Rivers ◽  
Bed Material

Accuracy of Surface Samples from Gravel Bed Material

1983 ◽  
Vol 109 (6) ◽  
pp. 842-851 ◽  
Author(s):  
Richard D. Hey ◽  
Colin R. Thorne
Keyword(s):  
Gravel Bed ◽  
Surface Samples ◽  
Bed Material
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