Using Sentinel-1 Imagery to Assess Predictive Performance of a Hydraulic Model

Ioanna Zotou (), Vasilis Bellos, Angeliki Gkouma, Vassilia Karathanassi and Vassilios A. Tsihrintzis ()
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Ioanna Zotou: National Technical University οf Athens
Vasilis Bellos: National Technical University οf Athens
Angeliki Gkouma: National Technical University οf Athens
Vassilia Karathanassi: National Technical University οf Athens
Vassilios A. Tsihrintzis: National Technical University οf Athens

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2020, vol. 34, issue 14, No 8, 4415-4430

Abstract: Abstract This study seeks to test the predictive performance of a hydraulic model using as reference the flood extent extracted through Sentinel-1 imagery. A precipitation event which took place between the 22nd and 28th of February 2018 in Pineios river basin, Central Greece, was analyzed. A threshold technique was performed to delineate the inundation extent from the satellite image, whereas both HEC-HMS and HEC-RAS software were coupled to simulate the examined storm event. To assess model response, the flooded area derived through the modeling approach was compared against that derived from the satellite image processing, using an area-based measure of fit. Furthermore, an uncertainty analysis on the parameters of the hydrologic model was elaborated to investigate their impact on the results of the hydraulic model. The sensitivity of the latter to the value of the roughness coefficient as well as to changes in the spatial resolution of the utilized topography was also examined. Considering as a perfect response of the model its complete coincidence with the satellite image product, it was found that the hydraulic model performance ranged between 61.04%-65.49%, depending on the selected upstream flow hydrograph, topography and roughness coefficient. The upstream flow conditions proved to play a more critical role, while roughness coefficient and topography were found to cause slighter changes in model response.

Keywords: Flood map; Sentinel-1 imagery; Remote sensing; HEC-HMS; HEC-RAS; Uncertainty (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (4)

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DOI: 10.1007/s11269-020-02592-7

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