Assessing the uncertainty associated with flood features due to variability of rainfall and hydrological parameters

Ahmad Sharafati, Mohammad Reza Khazaei, Mohamed Salem Nashwan, Nadhir Al-Ansari, Zaher Mundher Yaseen*, Shamsuddin Shahid

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

An assessment of uncertainty in flood hydrograph features, e.g., peak discharge and flood volume due to variability in the rainfall-runoff model (HEC-HMS) parameters and rainfall characteristics, e.g., depth and duration, is conducted. Flood hydrographs are generated using a rain pattern generator (RPG) and HEC-HMS models through Monte Carlo simulation considering uncertainty in stochastic variables. The uncertainties in HEC-HMS parameters (e.g., loss, base flow, and unit hydrograph) are estimated using their probability distribution functions. The flood events are obtained by simulating runoff for rainfall events using the generated model parameters. The uncertainties due to rainfall and model parameters on generated flood hydrographs are evaluated using the relative coefficient of variation (RCV). The results reveal a higher RCV index for flood volume (RCV = 153) than peak discharge (RCV = 116) for a 12-hr rainfall duration. The average relative RCV (ARRCV) index computed for hydrological component (e.g., base flow, loss, or unit hydrograph) indicates the highest impact of rainfall depth on flood volume and peak. The results indicate that rainfall depth is the main source of uncertainty of flood peak and volume.

Original languageEnglish
Article number7948902
JournalAdvances in Civil Engineering
Volume2020
DOIs
StatePublished - 2020
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2020 Ahmad Sharafati et al.

ASJC Scopus subject areas

  • Civil and Structural Engineering

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