EGU2020-15493, updated on 12 Jun 2020
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Simulation and analysis for flood early warning system in small catchments caused by rainfall-induced disaster

Ke-Sin Yu1, Jihn-Sung Lai1,2, and Yi-Huan Hsieh1
Ke-Sin Yu et al.
  • 1National Taiwan University, College of Science, International Degree Program in Climate Change and Sustainable Development, Taipei, Taiwan
  • 2Hydrotech Research Institute, National Taiwan University, Taipei, Taiwan

Under the impact of climate change, rainfall-induced flood disasters have become more frequent in some areas. The development of an hourly rainfall forecast with higher time and spatial accuracy under different rainfall patterns and the connection between meteorological forecast and hydrological flood simulation are urgent issues. In this study, eight flood cases in 2019 in Taipei city, a high-risk urban area with high economic and social resource density, caused by different rainfall patterns were chosen to be analyzed. To improve the accuracy of meteorological data, WRF base ensemble prediction system (WEPS), a quantitative precipitation forecast (QPF) produced by Central Weather Bureau (CWB) of Taiwan was selected as the main meteorological data source, and after processed by objective quantitative analysis methods, the data then be input into the drainage–inundation model. As a one-dimensional and two-dimensional flood simulation system, SOBEK was used to verify the depth and location of floods. Results indicated that the WEPS data would have better performance in drainage–inundation model among the cases in 2019. Combining meteorological forecast data and hydrological simulation can somehow improve the accuracy of flood early warning system in a small catchment.

How to cite: Yu, K.-S., Lai, J.-S., and Hsieh, Y.-H.: Simulation and analysis for flood early warning system in small catchments caused by rainfall-induced disaster, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-15493,, 2020

This abstract will not be presented.