Integrated flood forecasting and warning system against flash rainfall in the small-scaled urban stream

Jung Hwan Lee, Gi Moon Yuk, Hyeon Tae Moon, Young Il Moon

Research output: Contribution to journalArticlepeer-review

19 Scopus citations

Abstract

The flood forecasting and warning system enable an advanced warning of flash floods and inundation depths for disseminating alarms in urban areas. Therefore, in this study, we developed an integrated flood forecasting and warning system combined inland-river that systematized technology to quantify flood risk and flood forecasting in urban areas. LSTM was used to predict the stream depth in the short-term inundation prediction. Moreover, rainfall prediction by radar data, a rainfall-runoff model combined inland-river by coupled SWMM and HEC-RAS, automatic simplification module of drainage networks, automatic calibration module of SWMM parameter by Dynamically Dimensioned Search (DDS) algorithm, and 2-dimension inundation database were used in very short-term inundation prediction to warn and convey the flood-related data and information to communities. The proposed system presented better forecasting results compared to the Seoul integrated disaster prevention system. It can provide an accurate water level for 30 min to 90 min lead times in the short-term inundation prediction module. And the very short-term inundation prediction module can provide water level across a stream for 10 min to 60 min lead times using forecasting rainfall by radar as well as inundation risk areas. In conclusion, the proposed modules were expected to be useful to support inundation forecasting and warning systems.

Original languageEnglish
Article number971
JournalAtmosphere
Volume11
Issue number9
DOIs
StatePublished - Sep 2020

Keywords

  • Flood risk
  • Inland-river combined flood system
  • LSTM
  • Urban flood forecasting and warning

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