High-Resolution Flood Simulation in Urban Areas Through the Application of Remote Sensing and Crowdsourcing Technologies

Frontiers in Earth Science

Earth Science

Jen-Yu Han¹  Yuan-Fong Su²  Jiun-Huei Jang³  Yan-Ting Lin⁴ 

[1] Department of Civil Engineering, National Taiwan University, Taipei, Taiwan;Department of Harbor and River Engineering, National Taiwan Ocean University, Keelung, Taiwan;Department of Hydraulic and Ocean Engineering, National Cheng Kung University, Tainan, Taiwan;National Center for Research on Earthquake Engineering, National Applied Research Laboratories, Taipei, Taiwan;

关键词: urban flooding;    unmanned aerial vehicle;    volunteered geographic information;    computational flood simulation;    social media;   

DOI  :  10.3389/feart.2021.756198

 received in 2021-08-10, accepted in 2021-12-28,  发布年份 2022

来源: Frontiers

【 摘 要 】

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.

【 授权许可】

Unknown   
Copyright © 2022 Su, Lin, Jang and Han.