Abstract
One of the biggest challenges in building intricate realistic real world models is to incorporate data and their subsequent analysis. When analysing such a system, researchers typically only use one of two modelling methodologies. The first modelling methodology is “keep it simple stupid” (KISS), which aims to capture the simplified, sometimes extremely abstract behaviours of the real world. By not including all of the intricate features of a system, leads to the problem of having to justify an abstract model to represent the real world and for the results to be verified through theoretical reasoning. However, this method is often easier to construct and yields a clear overview of the system’s behaviour. The second modelling approach is the “keep it descriptive stupid” (KIDS) approach that aims to include more vital features or behaviours of a system. The justification of using these highly descriptive models is easier, as it captures more intricate behaviours, but are often significantly more difficult to build and to analyse. This thesis shows that by using the KISS methodology to analyse the system as a whole, vital information about the build of the KIDS model, i.e. which behaviours need to be simulated, can be obtained. This simplifies the process for building the KIDS model and ensures that the general behaviour of the system is included. The KIDS model is then used to analyse how the intricate behaviours influence the system. I demonstrate this approach on two case studies, where the first investigates how impacts such as a leader’s reputation and family’s party preference influencing an individual voter alters the re-election rate of a leader or party. The second case study analyses how policies impact the UK phosphorus and nitrogen flows.