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Global warming is expected to be most significant in the boreal regions and could greatly affect the discharge regime of arctic rivers. Yet, a modification in the arctic hydrological cycle could then have a feedback on the whole earth climate through increased input of fresh water into the Arctic Oc...

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Bibliographic Details
Main Author: Avenue Edouard Belin
Other Authors: The Pennsylvania State University CiteSeerX Archives
Format: Text
Language:English
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Online Access:http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.558.4808
http://earth.esa.int/workshops/hydrospace07/participants/05_01/05_01_Biancamaria.pdf
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Summary:Global warming is expected to be most significant in the boreal regions and could greatly affect the discharge regime of arctic rivers. Yet, a modification in the arctic hydrological cycle could then have a feedback on the whole earth climate through increased input of fresh water into the Arctic Ocean. Thus, being able to model major arctic rivers, and therefore predict how they may respond to global warming, is a crucial issue. The aim of this work is to model such an arctic river: the Ob River, in Western Siberia. This has been achieved by coupling the land surface scheme ISBA (Interactions between Soil-Biosphere-Atmosphere) developed by the CNRM (Centre National de Recherche Meteorologique, France) with the flood inundation model LISFLOOD-FP developed by the University of Bristol, UK. Using this coupled macroscale hydrology-hydraulic model with different Digital Elevation Models (DEM) and river depths, the Ob discharge has been simulated and compared to in-situ gauge and satellite data. As expected, the choice of the DEM greatly impacts the simulated inundation extent and therefore the discharge. River depth is also a key parameter to simulate an accurate discharge. It appears that use of a constant river depth between 15 and 20m allows a good simulation of the discharge near the Ob river mouth and this is consistent with the limited available data on Ob river depths. Yet, the flood plain flow is underestimated compared to satellite observation.