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| Titel |
Flood extent maps from satellite imagery, hydrometric data and downstream water surface slope to constrain uncertainty in inundation modelling based on SRTM or LiDAR topography |
| VerfasserIn |
Kun Yan, Giuliano Di Baldassarre, Jeffrey Neal, Dimitri P. Solomatine |
| Konferenz |
EGU General Assembly 2013
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 15 (2013) |
| Datensatznummer |
250083586
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| Zusammenfassung |
| Flood inundation modelling is one of the essential steps in flood risk assessment.
However, in many rivers and floodplains the desirable input data are not sufficient or
unavailable. A potential opportunity to fill this gap might be offered nowadays
by the global remote sensing data, which can be freely (or at low cost) obtained
from internet, such as the Shuttle Radar Topography Mission (SRTM). However, it
is not clear to what extent modellers can trust or make use of these topographic
data.
Previous studies have assessed the usefulness of SRTM topography data in supporting
flood inundation modelling of one-dimensional (1D) hydraulic model in a medium-large
scale river (River Po) considering the major source of uncertainty (parameter and inflow)
(e.g. Yan et al., 2012). This study attempts to prove the potential value of SRTM
topography in supporting two-dimensional (2D) inundation modelling. The usual
practice by modellers is to apply a normal depth (calculated from the energy slope) as
the downstream boundary condition. The energy slope is usually unknown and is
estimated as the average bed slope under the assumption of uniform flow near the
downstream boundary. Being a study involving the attenuation of the flood wave,
a steeper energy slope is expected. Thus, the inundation modelling results (e.g.
water levels, inundation extent) are affected by this assumption. The sensitivity and
the interrelationship of energy slope, roughness coefficients for the prediction of
water stage and flood extent are investigated for both high resolution topography
(i.e. LiDAR) and global topography (i.e. SRTM) in a river reach of the Dee, in the
United Kingdom. Through the comparison of the two models, the performance of the
SRTM-based Model in reproducing the food extent and downstream water levels were
demonstrated.
Reference: Yan, K., Di Baldassarre, G., Solomatine, D.P. (2012). Exploring the potential
of SRTM topographic data for flood inundation modelling under uncertainty. Journal of
Hydroinformatics, in press. |
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