Please note that this session was withdrawn and is no longer available in the respective programme. This withdrawal might have been the result of a merge with another session.
HS6.7 | Synthesising Remotely Sensed and In-Situ Data to Understand Hydrological Processes at Regional and Local Scales
EDI
Synthesising Remotely Sensed and In-Situ Data to Understand Hydrological Processes at Regional and Local Scales
Convener: Christina Anna Orieschnig | Co-convener: John W. Jones
With the proliferation and wide accessibility of remotely sensed information, data from missions such as Landsat, Sentinel, MODIS, VIIRS, and SWOT are being increasingly used to develop a better understanding of hydrological processes on the earth’s surface. Acquiring this understanding is a crucial prerequisite to improve resource management, optimise the development of infrastructure, and adjust land use practices to changing climate conditions and hazards such as floods and droughts. However, many analyses incorporate remote sensing data by default and without a thorough critical examination of their applicability and limitations. In-situ data, though often less readily available and more eclectic, provide a valuable layer of information to act as a benchmark for remotely sensed data.

This session aims to highlight innovative approaches to synthesizing remotely sensed and in-situ data to better understand processes related to hydrology at regional and local scales in a variety of environments. We welcome contributions that focus on combining remote sensing and in-situ information and critically engage this intersection in relation to:
- Processes such as evapotranspiration, infiltration, inundation, and water use
- Hydrological extremes such as floods and droughts
- Coping with a sparsity of in-situ data in poorly gauged and ungauged basins
- Developing novel methods of gathering in-situ data to benchmark remote sensing approaches
- Reviewing recent advances regarding the synthesis of remote sensed and in situ data for hydrology in natural and anthropised ecosystems