On 9 July 2015, Mr. Kun Yan successfully presented and defended his PhD thesis and was awarded with a Doctoral degree. The PhD research focused on Low-cost Space-borne Data for Inundation Modelling: Topography, Flood Extent and Water Level. Professor Dimitri Solomatine, UNESCO-IHE and Professor Giuliano Di Baldassarre, Uppsla University were his promotors.
Flood inundation modelling under uncertainty
In this thesis Mr. Kun Yan aims to explore 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 (Shuttle Radar Topographic Mission) topographic data, SAR (Synthetic Aperture Radar) satellite imagery of flood extents and radar altimetry of water levels are analyzed in view of inflow and parametric uncertainty.
To this end, research work has been carried out by either following a model calibration-evaluation approaches or by explicitly considers major sources of uncertainty within a Monte Carlo framework. To generalize the findings, 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. Lastly, an application of SRTM-based flood modelling of a large river is conducted to highlight the challenges of predictions in ungauged basins.
This research indicates the potential and limitations of low-cost, space-borne data in supporting flood inundation modelling under uncertainty, including findings related to the usefulness of these data according to modelling purpose (e.g. re-insurance, planning, design), characteristics of the river and considerations of uncertainty. The upcoming satellite missions, which could potentially impact the way we model flood inundation patters, are also discussed.