Assimilation of radar altimetry to a routing model of the Brahmaputra River

Claire Irene B. Michailovsky, Christian Milzow, Peter Bauer-Gottwein

    Research output: Contribution to journalJournal articleResearchpeer-review

    Abstract

    While satellite-based remote sensing has provided hydrologists with valuable new data sets, integration of such data sets in operational modeling systems is usually not straightforward due to spatial or temporal resolution issues or because remote sensing does not directly measure the hydrological quantities of interest. This is the case for satellite-based radar altimetry. River-level variations can be tracked using radar altimetry at a temporal resolution between 10 and 35 days, depending on the satellite, but hydrologists are typically interested in river flows rather than levels and require predictions at daily or even subdaily temporal resolutions. One way to exploit satellite radar altimetry is therefore to combine the data with hydrological models in a data assimilation framework. In this study, radar altimetry data from six ENVISAT virtual stations were assimilated to a routing model of the main reach of the Brahmaputra River driven by the outputs of a calibrated rainfall runoff model. The extended Kalman filter was used to update the routed water volumes for the years 2008-2010. Model performance was improved with the Nash-Sutcliffe model efficiency for daily discharge increasing from 0.78 to 0.84. The method uses very little in situ data and is easily implemented as an add-on to hydrological models, and it therefore has the potential for large-scale application to improve hydrological predictions in many river basins. ©2013. American Geophysical Union. All Rights Reserved.
    Original languageEnglish
    JournalWater Resources Research
    Volume49
    Issue number8
    Pages (from-to)4807-4816
    ISSN0043-1397
    DOIs
    Publication statusPublished - 2013

    Keywords

    • Data processing
    • Forecasting
    • Hydrology
    • Radar
    • Radar stations
    • Remote sensing
    • Rivers
    • Geodetic satellites

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