Author

Sanaz Borhani

Date of Award

Summer 2019

Document Type

Open Access Dissertation

Department

Civil and Environmental Engineering

First Advisor

Enrica Viparelli

Abstract

Tracer particles are used to study bedload transport in gravel bed rivers. One of the advantages associated with their use is that they allow for direct measurements of particle entrainment rates in bedload transport and particle displacement. The main issue in field studies with tracer particles is the difference between tracer short term and long term behavior. This difference is due to the fact that particles undergo vertical mixing or move to less active locations such as bars or even floodplains. For these reasons the mean tracer velocity decreases over time. This phenomenon has been called tracer slowdown and it can have a significant impact in estimating the bedload transport or in modeling the dispersal of contaminated sand and gravels. The vast majority of the morphodynamic models that account for the non-uniformity of the bed material (tracer and not tracer, in this case) are based on a discrete description of the alluvial deposit. The deposit is divided in two different regions; the active layer and the substrate. The active layer is a thin layer in the topmost part of the deposit in which particles can interact with the bed material transport. The substrate is the part of the deposit below the active layer. Due to the discrete representation of the alluvial deposit, active layer models are not able to reproduce tracer slowdown. To overcome some of the limitations of layer-based models, Parker and co-authors introduced probabilistic, not layer-based morphodynamic framework. This framework is based on a probabilistic description of the temporal variation of bed surface elevation associated with sediment transport processes, and it is used herein to model the dispersal of tracer particles. Particle entrainment rates are computed as a function of the flow and sediment characteristics, and particle deposition is modeled with a step length formulation. Here we present one of the first implementation of the probabilistic framework at laboratory scale, validate it against laboratory data, and then we use the validated model to investigate some of the characteristics of tracer dispersal at laboratory and field scales.

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