HS2.3.1Innovative sensing techniques and data analysis approaches to increase hydrological process understanding
|Convener: Heye Bogena | Co-Conveners: Theresa Blume , Miriam Coenders-Gerrits , Serena Ceola|
Data availability is one of the major constraints in hydrological and ecohydrological research, limiting our ability to analyze hydrological processes, their interactions, relations with the ecosystem, and to test different model hypotheses. This is in particular true at the catchment scale, where it is frequently difficult to obtain adequate representations of climate and landscape spatial heterogeneity to inform bottom-up modeling approaches, or to design and perform integrated measurements to meaningfully constrain top-down modeling approaches. Notwithstanding this, there are several data sources that even if available are rarely used or poorly exploited in (eco)hydrological applications. These include new types of data (e.g. wireless distributed sensors and new remote sensing products), whose potential contribution to processes understanding is still under research, as well as new proxies for (eco)hydrological processes, and traditional types of data (e.g. results of fieldwork investigations, maps of various characteristics of the landscape), which for reasons such as commensurability problems or inadequate models, are seldom exploited to a full degree in (eco)hydrological studies.
Recent advances in observation techniques, including both field measurements and remote sensing, together with innovative approaches to take advantage of the information content of available data are therefore of interest.
This session will thus focus on how data obtained from new observation techniques and from innovative ways of using and extracting information can be used to inform model design and process knowledge at the catchment scale and to assess such latest developments for our understanding of various aspects of the ecohydrological system.
We thus solicit contributions related but not limited to:
(i) Innovative sensing techniques to advance (eco)hydrological understanding (e.g. wireless network, fiber optic, cosmic-ray etc.) and applications
(ii) Methods for the evaluation, visualization and interpretation of distributed data sets (e.g. soil moisture, micrometeorology, groundwater)
(iii) Analysis of (eco)hydrological patterns at different scales in experimental river basins and ecosystems
(iv) Unusual and unexpected (eco)hydrological phenomena identified by measurements that could not be explained by existing theoretical considerations
(v) Gaps in knowledge on integrated basin responses and ecosystems to present and future anthropogenic and/or climate impacts
(vi) Innovative ways of information gain and efficient information extraction for models from existing data
(vii) Innovative use and novel combinations of different data sources from existing data to maximize the information gain from catchment scale models