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| Titel |
Use of High Spatial Resolution Remote Sensing for Hydro-Geomorphologic Analysis of Medium-sized Arid Basins |
| VerfasserIn |
Yuval Sadeh, Dan G. Blumberg, Hai Cohen, Efrat Morin, Shimrit Maman |
| Konferenz |
EGU General Assembly 2016
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| Medientyp |
Artikel
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| Sprache |
en
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 18 (2016) |
| Datensatznummer |
250129357
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| Publikation (Nr.) |
 EGU/EGU2016-9456.pdf |
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| Zusammenfassung |
| Arid environments are often remote, expansive, difficult to access and especially vulnerable
to flash flood hazards due to the poor understanding of the phenomenon and the lack of
meteorological, geomorphological, and hydrological data. For many years, catchment
characteristics have been observed using point-based measurements such as rain gauges and
soil sample analysis; on the other hand, use of remote sensing technologies can
provide spatially continuous hydrological parameters and variables. The advances in
remote sensing technologies can provide new geo-spatial data using high spatial and
temporal resolution for basin-scale geomorphological analysis and hydrological
models.
This study used high spatial resolution remote sensing for hydro-geomorphologic analysis of
the arid medium size Rahaf watershed (76 km2), located in the Judean Desert, Israel. During
the research a high resolution geomorphological map of Rahaf basin was created using
WorldView-2 multispectral satellite imageries; surface roughness was estimated using
SIR-C and COSMO-SkyMed Synthetic Aperture Radar (SAR) spaceborne sensors;
and rainstorm characteristics were extracted using ground-based meteorological
radar.
The geomorphological mapping of Rahaf into 17 classes with good accuracy. The surface
roughness extraction using SAR over the basin showed that the correlation between the
COSMO-SkyMed backscatter coefficient and the surface roughness was very strong with an
R2 of 0.97. This study showed that using x-band spaceborne sensors with high spatial
resolution, such as COSMO-SkyMed, are more suitable for surface roughness evaluation in
flat arid environments and should be in favor with longer wavelength operating sensors
such as the SIR-C. The current study presents an innovative method to evaluate
Manning’s hydraulic roughness coefficient (n) in arid environments using radar
backscattering. The weather radar rainfall data was calibrated using rain gauges located in the
watershed. The quantitative precipitation estimations had an error of 38.6–47.9%,
which is considered fairly good in comparison to previous studies. The radar-based
rainstorm extracted characteristics are used to create accumulated and intensity rain
maps.
Finally, all the remotely sensed data were used as inputs for the Kinematic Runoff and
Erosion Model (KINEROS2) through the Automated Geospatial Watershed Assessment
(AGWA) tool. The model-simulated peak flow and volume were then compared to runoff
measurements from the watershed’s pouring point. |
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