Water managers have to deal with complex problems due to the intertwined characteristics of processes, in particular those that occur in wastewater systems. Existing modelling approaches are usually centred in the physical, chemical and biological aspects of the individual processes, excluding the social and organisational context that will generate the global behaviour. These also include the responsibilities and decision making of different actors in the system. This paper proposes an agent-based model with the novelty to integrate the social and organisational structure of the wastewater system from which emerges the global behaviour of the system. The modelling process allows considering the legal regulations and the technical limits that would drive the decision making. The instantiation of the model, implementing a small system, evidenced the usefulness of this approach to manage the complexity of wastewater systems and its possible contribution to prevent environmental problems.

This paper addresses the critical issue of trust in Artificial Intelligence systems, especially when users might find it challenging to comprehend the internal decision-making processes of such systems. A relevant topic of research in this respect is Theory of Mind, which involves attempting to understand these systems as if they possessed beliefs, desires, and intentions. We focus on the latter: intentions, and we examine how producing explanations based on them can improve \emph{understandability} while allowing for a better interpretation of how they align with human values. We also review some existing methods for identifying intentions in AI systems and we conclude with a discussion on possible future directions in this line of research.