Data-driven system identification of the WEFE nexus: Challenges and prospects

The Water-Energy-Food-Ecosystem (WEFE) nexus presents many challenges with regards to modelling. While attempts at conceptual modelling of this nexus have been made, increasing data availability due to electrification, smart infrastructure, and digitization of these sectors encourages a data-driven approach to system identification and control. Data-driven methods have had wide success in disciplines dealing with similar challenges as the WEFE nexus, such as the multiplicity of scales, nonlinearity and chaos, high dimensionality, fuzzy and stochastic social dynamics, as well as rare- or extreme event exposure. Here we provide a brief summary of data-driven methods of system identification that may address these challenges by looking at cross-disciplinary applications and its relevance for the WEFE nexus.