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Daily water level Estimation From Interpolation of Satellite Altimetry and In-Situ Measurements
Burrillon, E.1; Roux, E.2; Crétaux, J-F3; Calmant, S.4; Mazzega, P.5; Santos Da Silva, J.6
1CNES; 2IRD/LMTG; 3CNES/LEGOS; 4IRD/LEGOS; 5CNRS/LMTG; 6UFRJ/IRD

Altimetry is a current technique to monitor precisely the river level changes. However it is still limited by the temporal resolution of 10 to 35 days depending on the satellite used. We propose two methodologies of altimetry data interpolation to provide daily river level time series. This is a highly underdetermined problem which require a priori hypothesis to be solved. The first methodology is an optimization method based on multi-objective criterion exploiting data at limited number of ground gauges instruments on the river stage. The second method uses the discrete inverse theory using the least square criterion and is not depending on existence of in-situ data. We evaluate the model and parameter estimation in different situations: for the Amazon River, where several in-situ stations are available, an allow applying both methods for comparison, and with the Congo Basin, where only one station is currently operating. These two methodologies sound to be promising mathematical tools to provide valuable information on river level at high temporal resolution

 

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