A probabilistic framework for floodplain mapping using hydrological modeling and unsteady hydraulic modeling

Ebrahim Ahmadisharaf, Alfred Kalyanapu, Paul Bates

Research output: Contribution to journalArticle (Academic Journal)

6 Citations (Scopus)
141 Downloads (Pure)

Abstract

Prediction of design hydrographs is key in floodplain mapping using hydraulic models, which are either steady state or unsteady. The former, which require only an input peak, substantially overestimate the volume of water entering the floodplain compared to the more realistic dynamic case simulated by the unsteady models that require the full hydrograph. Past efforts to account for the uncertainty of boundary conditions using unsteady hydraulic modeling have been based largely on a joint flood frequency–shape analysis, with only a very limited number of studies using hydrological modeling to produce the design hydrographs. This study therefore presents a generic probabilistic framework that couples a hydrological model with an unsteady hydraulic model to estimate the uncertainty of flood characteristics. The framework is demonstrated on the Swannanoa River watershed in North Carolina, USA. Given its flexibility, the framework can be applied to study other sources of uncertainty in other hydrological models and watersheds.
Original languageEnglish
Number of pages18
JournalHydrological Sciences Journal
Early online date22 Oct 2018
DOIs
Publication statusE-pub ahead of print - 22 Oct 2018

Keywords

  • floodplain mapping
  • hydrologic modeling
  • unsteady hydraulic modeling
  • uncertainty analysis

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