  We introduce a dynamical description based on a probability density
$\phi(\sigma,x,y,t)$ of the vorticity $\sigma$ in two-dimensional viscous flows
such that the average vorticity evolves according to the Navier-Stokes
equations. A time-dependent mixing index is defined and the class of
probability densities that maximizes this index is studied. The time dependence
of the Lagrange multipliers can be chosen in such a way that the masses
$m(\sigma,t):=\intdxdy \phi(\sigma,x,y,t)$ associated with each vorticity value
$\sigma$ are conserved. When the masses $m(\sigma,t)$ are conserved then 1) the
mixing index satisfies an H-theorem and 2) the mixing index is the
time-dependent analogue of the entropy employed in the statistical mechanical
theory of inviscid 2D flows [Miller, Weichman & Cross, Phys. Rev. A \textbf{45}
(1992); Robert & Sommeria, Phys. Rev. Lett. \textbf{69}, 2776 (1992)]. Within
this framework we also show how to reconstruct the probability density of the
quasi-stationary coherent structures from the experimentally determined
vorticity-stream function relations and we provide a connection between this
probability density and an appropriate initial distribution.
