  This work is devoted to the Galerkin projection of highly nonlinear random
quantities. The dependency on a random input is described by Haar-type wavelet
systems. The classical Haar sequence has been used by Pettersson, Iaccarino,
Nordstroem (2014) for a hyperbolic stochastic Galerkin formulation of the
one-dimensional Euler equations. This work generalizes their approach to
several multi-dimensional systems with Lipschitz continuous and non-polynomial
flux functions. Theoretical results are illustrated numerically by a genuinely
multidimensional CWENO reconstruction.
