Improving hydrological process understanding and model prediction using soil moisture data
Convener:
Anke Hildebrandt
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Co-conveners:
Markus Hrachowitz,
Daniele Penna,
Josie Geris,
Katya Dimitrova PetrovaECSECS
Although spatial and temporal patterns of soil moisture are the result of processes that hydrological models typically capture, the application of the currently available soil moisture information for improving models is progressing only slowly. This is partly due to a gap between the information content provided by the available data and the information required to improve models. Furthermore, some essential parts of soil water storage at the larger scale, like that of the root zone, is typically assessed using combination of models and data, resulting in a lack of independent information for validation.
This session invites contributions dealing with closing these gaps. This could, for example, be achieved by progress in the descriptions of the processes causing the spatial and temporal variations in soil moisture or by more efficiently using information from available data to improve model predictions across scales. The session is explicitly open for research across all relevant hydrological scales: local, hillslope, catchment up to the continental scale, and deal with both the vertical and lateral flow processes.
Examples for suitable contributions are (but are not limited to):
- The role of soil moisture in the functioning of hydrological systems
- Methods and case studies on improving the predictive power of models using soil moisture data
- Deriving process knowledge from soil moisture data that can be used to improve hydrological models
- Evaluating the suitability of given soil moisture data types for representing hydrologic processes