Denise Degen , Florian Wellmann 

Numerical simulations are widely used as tools to understand processes or to make predictions about states and their evolution in time. However, in the process of a simulation setup, a multitude of choices and simplifications have to be made - beginning from the definition of the implemented physical laws, over model discretization and spatial parameterisation, to the definition of initial and boundary conditions. In addition, the defined parameters are often subject to significant uncertainties. It therefore becomes paramount to investigate how much a model output, for example the predicted temperature or pressure state at a location, is influenced by a certain input parameter, such as the thermal conductivtiy of a geological unit. Attempts to resolve this question are, consequently, included in many research papers - and generally referred to as sensitivity analyses. However, only a small portion of studies actually perform a meaningful sensitivity analysis in a mathematical sense. We propose that this omission is due to two reasons: (a) a lack of knowledge about the different types of sensitivity analyses, and how these can be properly described and formulated, and (b) a lack of awareness about the tools that are readily available to perform structured sensitivity analyses. In this contribution, we aim to fill this gap through a review of the mathematical foundations of sensitivity analyses, a presentation of the different types, and a suggestion for the choice of a suitable method, with the aim to provide a guidance for a wider application of suitable sensitivity analyses in subsurface process simulations.