Catchments are considered to be an ideal place for studying water and solute transport. Numerous studies suggest a complex interplay between hydrological and biogeochemical processes that cannot easily be transformed into adequate models. More specifically, field measurements are often inadequate to parameterise complex models and to rigorously test the large number of processes interacting in these models. Furthermore, it is often difficult to â€˜translateâ€™ model results from one site-specific application to another. Consequently, modelling in catchment hydrology is based more on the intuition of the expert rather than on a systematic approach.
In contrast to these problems, technological and methodological advances, by facilitating extensive data collection and development of integrated hydrological models, have brought hydrological research to a new level, including establishment of the field of Hydroinformatics. They have also given rise to a host of ideas, such as the dominant process concept, thresholds, nonlinear determinism, scaling and catchment classification, which could help to more systematically model water and solute transport in catchments. However, it is not clear how these advances and ideas can be used to solve practical problems in catchment hydrology, e.g. to reliably assess the impact of land use change on stream water quality. The following questions are obvious towards clarifying this point: What can models learn from data? How can dominant processes be identified from given data sets and used for setting up a parsimonious model structure? How can data be used to discriminate and evaluate competing modelling concepts? What data to be monitored/type of model to be used to estimate the effect of a specific catchment process?
This session is intended to bring a collective perspective on these issues. We invite abstracts on relevant topics. Abstracts that address the supplementary and complementary role of each of these topics with respect to the others and their integration towards generalisation in hydrological modelling are especially encouraged.
1. Peter C. Young (Lancaster University, Lancaster, UK)
2. Luis Samaniego (Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany)
3. Jasper A. Vrugt (Los Alamos National Laboratory, Los Alamos, USA)