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You are here : eLibrary : IAHR World Congress Proceedings : 36th Congress - The Hague (2015) ALL CONTENT : Water resources and hydroinformatics : Computations of trapping coefficient for fine sediment infiltration
Computations of trapping coefficient for fine sediment infiltration
re among the most important environmental issues at stake in recent years. Indeed, they have a strong
impact on biodiversity. The numerous structures that are built in rivers such as dams, hydroelectric plants, dikes, etc. have
dramatically changed the sediment dynamics in some rivers. This fact sometimes causes the clogging of the river bed, i.e.
infiltration of very fine sediments within the coarser matrix forming the bed. It is essential to understand the dynamic of fine
sediments within the bed to quantify how clogging develops. A trapping coefficient is usually used to describe clogging. It
quantifies the amount (or the proportion) of fine sediment that is blocked by a layer of gravels when travelling down into
the bed. Most previous models are based on fitting steady-state profiles of fine sediment contents using results of
laboratory experiments to compute empirical trapping coefficient.
In this article, we explore the Lauk stochastic model (Lauck 1991) that is based on a geometrical analysis. The cumulative
pore size distribution of the bed is computed and compared to the grain size distribution of the fine sediment. The
convolution between these two distributions gives the percentage of fine sediment that is trapped by the bed. To compute
the pore size distribution, a biased coarse sediment frequency distribution is used to take into account the different
probabilities for coarse grains to contribute to a pore depending on their size. This computation can be updated as fine
sediment infiltrates and modifies the grain size distribution of a certain layer. In this article, we present the computation of
the trapping coefficient and analyze how the variation of the trapping coefficient with respect to fine content is affected by
the bias applied in coarse sediment frequency distribution. It appears that whereas the bias has little effect on the trapping
coefficient for a matrix of gravel void of fine sediments, it has a strong impact on how this coefficient varies with a small
amount of sediment trapped within the bed.Form Required :
File Size : 618,516 bytes
File Type : Adobe Acrobat Document
Chapter : IAHR World Congress Proceedings
Category : 36th Congress - The Hague (2015) ALL CONTENT
Article : Water resources and hydroinformatics
Date Published : 20/08/2015
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