A data assimilation approach to discharge estimation from space

JC Neal, GJ-P Schumann, PD Bates, W Buytaert, P Matgen, Florian Pappenberger

Research output: Contribution to journalArticle (Academic Journal)peer-review

99 Citations (Scopus)

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.
Translated title of the contributionA data assimilation approach to discharge estimation from space
Original languageEnglish
Pages (from-to)3641 - 3649
Number of pages8
JournalHydrological Processes
Volume23 (25)
DOIs
Publication statusPublished - Dec 2009

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