EGU24-4950, updated on 08 Mar 2024
https://doi.org/10.5194/egusphere-egu24-4950
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Enhancing Flood Resilience through Integrated Models in a Streamflow-Scarce Watershed

Yong Jung1, Mun Ju Shin2, and Seong Jae Jeon1
Yong Jung et al.
  • 1Wonkwang , Civil and Environmental Eng., Korea, Republic of (yong_jung@wku.ac.kr)
  • 2Jeju Special Self-Governing Province Development Co.

A watershed with insufficient streamflow data faces challenges in mitigating flood damages through infrastructure. Many small/middle-size watersheds adopt data from nearby watersheds with sufficient measurements, based on the similarity of watershed characteristics and weather conditions. However, not many areas have optimal conditions to utilize data from nearby sources. To generate streamflow, we employ a regional weather model (the Weather Research and Forecasting model or WRF) and a rainfall-runoff model known as Génie Rural à 4 paramètres Horaires (GR4H). The WRF model generated rainfall data for past years base on the globally simulated data (Final (FNL) data from NCEP) with possible physical atmospheric conditions. The optimally conditioned GR4H produced streamflow data using rainfall data from WRF. All produced streamflow data is statistically tested for the applicability as basic data for background information to decrease the flood damages.

How to cite: Jung, Y., Shin, M. J., and Jeon, S. J.: Enhancing Flood Resilience through Integrated Models in a Streamflow-Scarce Watershed, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4950, https://doi.org/10.5194/egusphere-egu24-4950, 2024.