Abstract
High-resolution flood simulation considering the influence of high buildings and fundamental facilities is important for flood risk assessment in urban areas. However, it is also a challenging task due to the difficulties in acquiring detailed topography and monitoring data for model construction and validation. In this study, a high-resolution flood simulation with a grid size of 0.5 m is realized through the use of detailed topography obtained by an unmanned aerial vehicle and real-time flood information acquired from social media. To discover the influence of terrain resolution on flood simulations, the high-resolution simulation results are compared with those with coarser grid resolutions (5, 10, and 20 m) for a flash flood event in Taiwan. In the case with higher grid resolution, the simulation results are in better agreement with the photos from social media in terms of flood extent, depth, and occurrence time. The flood simulation with coarse resolution (>5 m) tends to overestimate the flood duration on roads and provide bias information to decision-makers in the assessment of traffic impact and economic loss.
Highlights
Flash floods resulting from extremely heavy rainfall have been recognized as one of the most common and destructive threats in recent years (Panthou et al, 2014; Chan et al, 2016; Bao et al, 2017; Busuioc et al, 2017; Yang et al, 2017; Fu et al, 2019)
With the help of unmanned aerial vehicle (UAV) and volunteered geographic information (VGI), this study introduces the methodologies and demonstrates the advantages of conducting high-resolution computational flood simulation (CFS) for flood risk assessment in urban areas
The digital elevation model (DEM) derived by UAV integrated with structure from motion (UAV-SfM) and the flood photos collected from VGI are used to establish and validate the CFS, respectively
Summary
Flash floods resulting from extremely heavy rainfall have been recognized as one of the most common and destructive threats in recent years (Panthou et al, 2014; Chan et al, 2016; Bao et al, 2017; Busuioc et al, 2017; Yang et al, 2017; Fu et al, 2019). In the last two decades, computational flood simulation (CFS) has been widely used to generate detailed flood scenarios in space and time by simulating water transportation on the surface and in sewer systems (Hunter et al, 2007; Kuiry et al, 2010; Seyoum et al, 2012; Jahanbazi and Egger, 2014; Chang et al, 2015; Jang et al, 2018; Jang et al, 2019) These CFS models require a detailed digital elevation model (DEM) and real-time flood records for model construction and validation, which are often inadequate in timeliness and accuracy for flash flood events occurring rapidly in localized areas (Suarez et al, 2005; Yin et al, 2016; Pregnolato et al, 2017).
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