Abstract Nonlinear Differential Algebraic Equations (DAEs) are an important class of models
for dynamic processes. To establish models that describe the process behavior in a …

Choosing between competing models lies at the heart of scientific work, and is a frequent
motivation for experimentation. Optimal experimental design (OD) methods maximize the …

This study expands the Box‐Hill discrimination function to design an optimal observation
network to discriminate conceptual models and, in turn, identify a most favored model. The …

Estimating parameters accurately in groundwater models for aquifers is challenging
because the models are non-explicit solutions of complex partial differential equations …

The lack of hydrogeological data and knowledge often results in different propositions (or
alternatives) to represent uncertain model components and creates many candidate …

We develop an experimental design algorithm to select locations for a network of
observation wells that provide the maximum robust information about unknown hydraulic …

Forest soils are under‐represented throughout the existing soil hydraulic databases.
Classical measurement methods for the hydraulic soil characteristics are very time …

An optimal experimental design algorithm is developed to select locations for a network of
observation wells that provide maximum information about unknown groundwater pumping …

In groundwater modelling, an appropriate soil characterization is strongly recommended to
evaluate both the fate and transport of solutes and the performance of groundwater …

This study introduces firm information gain for model discrimination based on Shannon
entropy and worst-case scenario experimental design. Firm information gain is the minimal …