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| Titel |
Evaluation of the satellite-based Global Flood Detection System for measuring river discharge: influence of local factors |
| VerfasserIn |
B. Revilla-Romero, J. Thielen, P. Salamon, T. De Groeve, G. R. Brakenridge |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1027-5606
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| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 18, no. 11 ; Nr. 18, no. 11 (2014-11-07), S.4467-4484 |
| Datensatznummer |
250120523
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| Publikation (Nr.) |
 copernicus.org/hess-18-4467-2014.pdf |
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| Zusammenfassung |
One of the main challenges for global hydrological modelling is the limited
availability of observational data for calibration and model verification.
This is particularly the case for real-time applications. This problem could
potentially be overcome if discharge measurements based on satellite data
were sufficiently accurate to substitute for ground-based measurements. The
aim of this study is to test the potentials and constraints of the remote
sensing signal of the Global Flood Detection System for converting the flood
detection signal into river discharge values.
The study uses data for 322 river measurement locations in Africa, Asia,
Europe, North America and South America. Satellite discharge measurements
were calibrated for these sites and a validation analysis with in situ
discharge was performed. The locations with very good performance will be
used in a future project where satellite discharge measurements are obtained
on a daily basis to fill the gaps where real-time ground observations are
not available. These include several international river locations in
Africa: the Niger, Volta and Zambezi rivers.
Analysis of the potential factors affecting the satellite signal was based
on a classification decision tree (random forest) and showed that mean
discharge, climatic region, land cover and upstream catchment area are the
dominant variables which determine good or poor performance of the
measure\-ment sites. In general terms, higher skill scores were obtained for
locations with one or more of the following characteristics: a river width
higher than 1km; a large floodplain area and in flooded forest, a
potential flooded area greater than 40%; sparse vegetation, croplands or
grasslands and closed to open and open forest; leaf area index > 2;
tropical climatic area; and without hydraulic infrastructures. Also,
locations where river ice cover is seasonally present obtained higher skill
scores. This work provides guidance on the best locations and limitations for
estimating discharge values from these daily satellite signals. |
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