Random forest and similar Machine Learning techniques are already used to generate
spatial predictions, but spatial location of points (geography) is often ignored in the modeling …

Multivariate or compound hydrological-extreme events such as successive floods, large-
scale droughts, or consecutive drought-to-flood events challenge water management and …

This paper is of methodological nature, and deals with the foundations of Risk Assessment.
Several international guidelines have recently recommended to select appropriate/relevant …

The series aims to: present current and emerging innovations in GIScience; describe new
and robust GIScience methods for use in transdisciplinary problem solving and decision …

We propose a new class of transGaussian random fields named Tukey g-and-h (TGH)
random fields to model non-Gaussian spatial data. The proposed TGH random fields have …

We propose a new copula model that can be used with replicated spatial data. Unlike the
multivariate normal copula, the proposed copula is based on the assumption that a common …

This paper highlights the usefulness of the minimum information and parametric pair-copula
construction (PCC) to model the joint distribution of flood event properties. Both of these …

Assessing the rarity and magnitude of very extreme flood events occurring less than twice a
century is challenging due to the lack of observations of such rare events. Here we develop …

Copulas have already proven their flexibility in rainfall modelling. Yet, their use is generally
restricted to the description of bivariate dependence. Recently, vine copulas have been …

Multivariate hydrological extreme events such as successive floods, large-scale droughts, or
consecutive drought-to-flood events challenge water management and can be particularly …