Parameter identification is an essential step in constructing a groundwater model. The
process of recognizing model parameter values by conditioning on observed data of the …

Since the development of the entropy theory by Shannon in the late 1940s and of the
principle of maximum entropy (POME) by Jaynes in the late 1950s there has been a …

We discuss the arbitrary polynomial chaos (aPC), which has been subject of research in a
few recent theoretical papers. Like all polynomial chaos expansion techniques, aPC …

Stochastic Subsurface Hydrogeology is the study of subsurface, geological heterogeneity,
and its effects on flow and transport process, using probabilistic and geostatistical concepts …

In many applications, it is important to make the distinction between spreading and dilution
of a plume in groundwater. Spreading is associated with the stretching and deformation of a …

In this paper we show that given prior information in terms of a lower and upper bound, a
prior bias, and constraints in terms of measured data, minimum relative entropy (MRE) yields …

Uncertainties in hydrologic parameters could have significant impacts on the simulated
water and energy fluxes and land surface states, which will in turn affect atmospheric …

Model-based uncertainty analysis can help to judge the potentials and hazard in many
engineering applications better. This requires to specify the probability distributions of all …

In situ observations of soil water state variables under natural boundary conditions are often
used to estimate the soil hydraulic properties. However, many contributions to the soil …

We investigate the sensitivity of precipitation characteristics (mean, extreme, and diurnal
cycle) to a set of uncertain parameters that influence the qualitative and quantitative …