Topography driven conceptual modelling (Invited)

Heterogeneity and complexity of hydrological processes offer substantial challenges to the hydrological modeller. Some hydrologists try to tackle this problem by introducing more and more detail in their models, or by setting-up more and more complex models starting from basic principles at the smallest possible level. As we know, this reductionist approach leads to ever higher levels of equifinality and predictive uncertainty. On the other hand, simple, lumped and parsimonious models may be too simple to be realistic or representative of the dominant hydrological processes. In this paper, a new model approach is proposed that tries to find the middle way between complex distributed and simple lumped modelling approaches. It addresses an aspect often overlooked in model uncertainty assessment: the structural errors made by conceptual misrepresentation. It uses a flexible model architecture based on a classification system that is topography driven. Catchments are divided into different conceptual model classes, which are subsequently modelled with parsimonious conceptual models. The approach is process based, but not physically based in the traditional sense. Instead, it is based on a conceptual representation of the dominant physical processes in certain key elements of the landscape.