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HS6.5

High to coarse resolution remote sensing for operational hydrological applications
Convener: N.E.C. Verhoest  | Co-Conveners: A. Bartsch , R. Ludwig , G. Mascaro 
Poster Programme
 / Attendance Wed, 25 Apr, 17:30–19:00 / Hall A
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The session is intended to discuss the merits of remote sensing as a useful tool in water resources management and thus welcomes all hydrologists, hydrologic modellers and water resources managers and researchers to gather related information about up-to-date developments in remote sensing. The application of remote sensing is termed operational if at least one of two conditions is met: (a) the application produces an output on a regular basis, or (b) the remote sensing data are used on a continuous basis as part of a procedure to problem solving or decision making.

The manifold impacts of a rapidly changing environment require advanced monitoring approaches to develop sound water management practices. It is generally acknowledged that remote sensing observations can contribute to the knowledge of the spatial and temporal variations of hydrological quantities. Although major advances have been made on an experimental level, the use of remote sensing information in operational hydrology and water resources management has long been relatively limited due to a lack of observation frequency or missing opportunities for suitable sensor synergies. In the recent past new platforms, sensors and application techniques have been and are being developed, providing data at different scales. Applying these data give hydrologists and water resources managers tools for better understanding of hydrological processes in the landscape, and for better predicting hydrological states or fluxes at field, catchment or regional scale.

The session solicits contributions that either (i) demonstrate ongoing operational remote sensing applications or (ii) clearly show a strong potential for making a remote sensing application operational in hydrology and water resources management. The session focuses as well on the application of high resolution as coarse resolution remote sensing imagery.