Low-Cost Space-Borne Data for Inundation Modelling: Topography, Flood Extent and Water Level - Yan, Kun
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This thesis explores the potential and limitations of low-cost, space-borne data in flood inundation modelling under unavoidable, intrinsic uncertainty. In particular, the potential in supporting hydraulic modelling of floods of: NASA's SRTM topographic data, SAR satellite imagery of flood extents and radar altimetry of water levels are analyzed in view of inflow and parametric uncertainty. Three river reaches with various scales (from medium to large) and topographic characteristics (e.g. valley-filling, two-level embankments, large and flat floodplain) are used as test sites. In conclusion, the usefulness of this data is discussed.…mehr

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Produktbeschreibung
This thesis explores the potential and limitations of low-cost, space-borne data in flood inundation modelling under unavoidable, intrinsic uncertainty. In particular, the potential in supporting hydraulic modelling of floods of: NASA's SRTM topographic data, SAR satellite imagery of flood extents and radar altimetry of water levels are analyzed in view of inflow and parametric uncertainty. Three river reaches with various scales (from medium to large) and topographic characteristics (e.g. valley-filling, two-level embankments, large and flat floodplain) are used as test sites. In conclusion, the usefulness of this data is discussed.
Autorenporträt
Kun Yan was born on 31st December 1985, in Bengbu, Anhui Province, China. Kun received his Bachelor degree from the College of Hydrology and Water Resourses, Hohai University in May 2008. He then enrolled in the Master program of Ecohydrology at Hohai University. A year later, he moved to the Netherlands and joined the Master program of Hydroinformatics of UNESCO-IHE. He started his PhD at UNESCO-IHE in July 2011, and after two months obtained his MSc degree. His PhD topic is the integration of low-cost space-borne data into hydraulic modelling of floods. Kun was also involved in the EC FP7 KULTURisk project, which aims at developing a culture of risk prevention for natural disasters including floods. Kun`s research interests including remote sensing, flood inundation modelling and uncertainty. He is now an advisor/researcher at Deltares.