Abstract
Energy and agriculture are two big greenhouse gas emitters. Emissions of greenhouse gases lead to rising temperatures and originate long-term shifts in weather patterns, i.e. climate change, causing intense droughts, severe fires, rising sea levels and flooding, together with destructive storms. To reduce emissions, an energy transition from fossil fuels to renewable and low-carbon energy sources is essential, and this cannot be led without considering the deep interlinkages that exist between energy, water and food. Renewable production units can enter into competition with agriculture through land use, and both energy and agriculture are water dependent. Digital tools appear as an efficient and agile way to manage water-energy-food systems. Developing a generic digital tool that contributes to the acceleration of a sustainable energy transition is the aim of this research work. The current work is focused on extending Maelia, a spatially explicit multi-agent simulation platform for integrated assessment and modelling of socio-agro-ecological systems, that enables the simulation of fine-grained spatial and temporal land management scenarios. The platform includes agriculture and hydrology models, considers biomass production and recycling ones, and through this research work, will also integrate solar and windmill models. To make Maelia an innovative digital decision tool that deals with water-energy-food systems, data must be collected, assembled and treated with R, Python and QGIS.
