This paper proposes a model to represent and simulate human activities in farming systems. Our definition of the activity concept (otherwise said 'action') stems from the 'situated action' theory (Suchman, 1987). Action may be summarized simply as 'what people are actually doing'. Therefore, we characterize action according to four dimensions: actors (persons or machines engaged in activity), time (start date, end date and duration), space (locations where action occurs) and the interaction with the actor's environment. To take into account all these dimensions, our model is based on: (i) an 'agent' approach, (ii) a mathematical formalism to represent action over time (Guerrin, 2009) and (iii) a discrete representation of space inspired from cellular automata. Our aim is to apply this model to representing the human component of agricultural systems, i.e. the farming practices. Space is modelled as a regular grid, each cell being controlled by a specific autonomous abstract 'agent', in the sense of multiagents systems (MAS), called 'cell-agent'. Since activity depends, according to the situated action paradigm, on its context of occurrence and continuously involves interactions with the environment, we focused on the concepts of stigmergy and affordance to carry the information necessary to realize actions and on the reactive agent approach. The radical notion of reactive agent postulates that agents' actions are reactions to stimuli. But if several stimuli motivate an agent to execute various actions at the same time, how should this agent act? In addition, various constraints to be dealt with are imposed by our application domain (farming systems), namely temporal constraints cell-agents must consider for acting. Consequently, our model, although based on a stimulus-response mechanism, involves also a process, kept as simple as possible, allowing an agent to select the most appropriate action when several actions are concurrently possible. Cell-agent actions are r