Towards integrated environmental models of everywhere: uncertainty, data and modelling as a learning process

Developing integrated environmental models of everywhere such as are demanded by the requirements of, for example, implementing the Water Framework Directive in Europe, is constrained by the limitations of current understanding and data availability. The possibility of such models raises questions about system design requirements to allow modelling as a learning and data assimilation process in the representation of places, which might well be treated as active objects in such a system. Uncertainty in model predictions not only poses issues about the value of different types of data in characterising places and constraining predictive uncertainty but also about how best to present the pedigree of such uncertain predictions to users and decision-makers.