Understanding the role of initial soil moisture and precipitation magnitude in flood forecast using a hydrometeorological modelling system

Dongxiao Yin, Z. George Xue, Daoyang Bao, Arezoo RafieeiNasab, Yongjie Huang, Mirce Morales, John C. Warner

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

We adapted the WRF-Hydro modelling system to Hurricane Florence (2018) and performed a series of diagnostic experiments to assess the influence of initial soil moisture and precipitation magnitude on flood simulation over the Cape Fear River basin in the United States. Model results suggest that: (1) The modulation effect of initial soil moisture on the flood peak is non-linear and weakens as precipitation magnitude increases. There is a threshold value of the soil saturation, below and above which the sensitivity of flood peak to the soil moisture differentiates substantially; (2) For model spin-up, streamflow needs longer time to reach the ‘practical’ equilibrium (10%) than the soil moisture and latent heat flux. The model uncertainty from spin-up can propagate through the hydrometeorological modelling chain and get amplified into the flood peak; (3) For ensemble flood modelling with a hydrometeorological system, modelling uncertainty is dominated by the precipitation forecast. Spin-up induced uncertainty can be minimized once the model reaches the ‘practical’ equilibrium.

Original languageEnglish
Article numbere14710
JournalHydrological Processes
Volume36
Issue number10
DOIs
StatePublished - Oct 2022

Keywords

  • cape fear river basin
  • flood modelling
  • hurricane florence
  • initial soil moisture
  • precipitation magnitude
  • spin-up
  • WRF/WRF-hydro

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