Improving process understanding, classification, model development and evaluation in hydrology using comparative assessment techniques
Convener: Fabrizio Fenicia  | Co-Conveners: Jim Freer , Tobias Krueger , Koray Kamil Yilmaz 
Oral Programme
 / Tue, 04 May, 15:30–17:15  / Room 36
Poster Programme
 / Attendance Tue, 04 May, 17:30–19:00  / Hall A
Comparative hydrology is the inclusion of multiple datasets and/or models to understand consistencies and differences in hydrological functioning at various scales of interest. Such research can be conducted over local, national and international datasets to understand how hydrological functioning varies spatially within a region as well as across regions with hydro-climatic differences. From the modelling perspective, the potential advantages of such comparative analyses are to provide information about individual model performance, characterize consistencies and differences in models, and enhance the understanding of hydrological behaviour in a systematic model comparison framework. This session specifically targets hydrologic and model classification frameworks in the broadest sense that identify hydrological similarities/differences and patterns in generalised forms from multiple datasets and/or modelling approaches.

We invite presentations focusing on both model and data comparisons for understanding similarities and differences in hydrological behaviour at different spatial scales. We encourage a move away from the single model and single data evaluation dogma, which we believe limits the utility and learning potential of results for the wider hydrological community. Therefore we particularly welcome applications where the results of modelling studies are placed in a general context of comparison, showing how this can help understanding the structural or behavioural characteristics of individual catchments. We also encourage general methodologies, which allow for characterization of the relative merits of individual models and their performance on multiple catchments.

Solicited people: Dmitri Kavetski, dmitri.kavetski[at]gmail.com; Neil Mcintyre, n.mcintyre[at]imperial.ac.uk.