Optimizing a coupled hydrologic-hydraulic model using remotely sensed soil moisture and flood extents
(2012) Workshop Belgian Earth Observation Day — Location: Bruges, Belgium
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- Abstract
- An important issue in water management is to adequately respond to extreme events. Floods often cause large disasters, which may include casualties, loss of properties, damage and economic losses. One way to respond to such disasters is to anticipate to its occurrence, such that people can be warned in time, enabling them to secure valuable properties and evacuate in time. Therefore, hydrologic models and/or hydraulic models can be used to predict discharge volumes, flood extents and heights. However, as models are prone to errors, external data may be used to improve the model output and increase the prediction accuracy. One source of external data is remotely sensed information. As soil moisture determines the partitioning of precipitation into infiltration and direct runoff, the retrieval of this variable from remote sensing received major attention within this project. At the micro-catchment scale, this is achieved using a combination of advanced hydro-geophysical techniques, focusing on Ground Penetrating Radar (GPR), which is optimized and integrated for fast and high resolution soil moisture measurements. At the catchment scale soil moisture is derived from radar remote sensing through a new retrieval scheme which omits the use of detailed measurements of surface roughness. Alternatively, possibility theory is explored for the retrieval of soil moisture from Synthetic Aperture Radar (SAR) data in order to assess the uncertainty in the soil moisture retrievals. Further, it was validated whether time series of radar images can be used to obtain soil moisture information. Another important variable for water management is the extent of floods. Remote sensing of floods was generally thought to be unfeasible within urbanized areas and beneath a vegetation cover. Through fusing of SAR data and high accuracy digital elevation models a solution for these problems was found. Furthermore, the uncertainty of the flood maps due to speckle in the radar image was studied. The remote sensing and modelling aspects of the proposal are then integrated in a number of hydrologic modelling and data assimilation studies. Retrieved soil moisture data are incorporated in a hydrologic and hydraulic model through adequate data assimilation algorithms, aiming at improved predictions of soil moisture fields and discharge. Methodologies to assimilate flood extents and inundation depths into hydraulic models have been developed.
- Affiliations
Laboratory of Hydrology and Water Management Ghent University, Belgium Department of Mathematical Modelling, Statistics and Bioinformatics Ghent University, Belgium Laboratory of Hydrology and Water Management Ghent University Centre de recherche public Gabriel Lippmann Belvaux, Luxembourg
Citations
Verhoest, N., Vanclooster, M., De Baets, B., Pauwels, V., Hoffman, L., Lieven, H., Lambot, S., Minet, J., Vernieuwe, H., Plaza, D., Matgen, P., & Giustarini, L. (2012). Optimizing a coupled hydrologic-hydraulic model using remotely sensed soil moisture and flood extents. Proceedings. Workshop Belgian Earth Observation Day, Bruges, Belgium. https://hdl.handle.net/2078.5/159601