Our methodology : Modelling

Modelling can be defined as a process that goes through all the phases of the scientific approach, from observation to the conceptualisation of a phenomena, translating it into a language (a model) and confronting the model with new observations. This can seem trivial, but we must stress that all the phases are influenced by the observer's science and experience.

There are many different types of models which can be used : a mock-up, a text, a drawing, a curve on a chart, a mathematical formalism… Indeed, every scientist does modelling. However, there is a difference between « experimenting » and « modelling », the experimenter focusing on the « observation » and the modeller focusing on « translating it into a language ». When modelling is brought up in science, it mostly refers to mathematical and digital (computer) modelling of « complex » systems, i.e. systems that take into account the non-linearity of processes and interactions in space and time.

Why use these complex models?

Here are some questions that can be solved using this type of model:

What could the dynamics of nitrate concentration be at any point of the catchment in 2050?
Will restoring/building a wetland have a significant impact, and how long will it take?
Does spatially targeting input reduction (nitrogen fertilising) have an impact on this catchment?
Will we be able to reach the set goals in terms of average (or median) nitrate concentration in the stream with the suggested arrangement, and how long will it take?

Incorporating our knowledge on various time and space scales, the use of these « complex » models is unavoidable to answer these questions. The reason for this is simple: all interactions between the processes in time and space are non-linear. When the simplification is too great, the results become at best illogical. The modelling approaches developed allow us to test « operational » scenarios (predictive analysis) and help define new production systems or industrial processes, adapted to change (for instance climate) and above all to environmental demands (societal and regulatory). In this perspective, the expertise offered by our company is at the heart of today's ecological issues.

Le processus de modélisation : une démarche scientifique