Arvind Singh PhD Defense, Thursday, Aug. 18, 10 a.m.

TITLE: Statistical Mechanics of Sediment Transport

ABSTRACT:

Accurate prediction of the evolution of rivers and landforms under varying

climatic and human-induced conditions requires quantification of the total sediment

transported by a river. Based on a series of controlled laboratory experiments conducted

at the St. Anthony Falls laboratory, University of Minnesota, we demonstrated

that (a) bedload sediment transport at very small time scales can be an order

of magnitude larger or smaller than the long-time average; (b) bed morphodynamics

can be inferred from the spectral properties of turbulent velocity fluctuations above

the bed; and (c) the nature of scaling and the degree of complexity and non-linearity

in bed elevation fluctuations and sediment transport rates depend on the bed shear

stress. These results are discussed in the context of understanding and exploring the

dependence of sediment transport scaling on near-bed turbulence, bed topography,

and particle-size distribution, and deriving stochastic transport models which give

rise to the observed scaling. They also form the foundation of relating microscale

dynamics of particle movement to the macroscale statistics of sediment transport via

minimum complexity stochastic models.

ADVISOR: Efi Foufoula-Georgiou