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A data assimilation approach to discharge estimation from space
Authors:Jeffrey Neal  Guy Schumann  Paul Bates  Wouter Buytaert  Patrick Matgen  Florian Pappenberger
Institution:1. School of Geographical Sciences, University of Bristol, Bristol BS8 1SS, UK;2. Public Research Centre—Gabriel Lippmann, Belvaux L‐4422, Luxembourg;3. European Centre for Medium‐Range Weather Forecasts, Reading RG29AX, UK
Abstract:River discharge is currently monitored by a diminishing network of gauges, which provide a spatially incomplete picture of global discharges. This study assimilated water level information derived from a fused satellite Synthetic Aperture Radar (SAR) image and digital terrain model (DTM) with simulations from a coupled hydrological and hydrodynamic model to estimate discharge in an un‐gauged basin scenario. Assimilating water level measurements led to a 79% reduction in ensemble discharge uncertainty over the coupled hydrological hydrodynamic model alone. Measurement bias was evident, but the method still provided a means of improving estimates of discharge for high flows. The study demonstrates the potential of currently available synthetic aperture radar imagery to reduce discharge uncertainty in un‐gauged basins when combined with model simulations in a data assimilation framework, where sufficient topographic data are available. The work is timely because in the near future the launch of satellite radar missions will lead to a significant increase in the volume of data available for space‐borne discharge estimation. Copyright © 2009 John Wiley & Sons, Ltd.
Keywords:data assimilation  discharge estimation  hydraulic model  SAR
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