Assessing the Uncertainty Associated with Flood Features due to Variability of Rainfall and Hydrological Parameters
Author(s): |
Ahmad Sharafati
Mohammad Reza Khazaei Mohamed Salem Nashwan Nadhir Al-Ansari Zaher Mundher Yaseen Shamsuddin Shahid |
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Medium: | journal article |
Language(s): | English |
Published in: | Advances in Civil Engineering, January 2020, v. 2020 |
Page(s): | 1-9 |
DOI: | 10.1155/2020/7948902 |
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. |
Copyright: | © Ahmad Sharafati et al. |
License: | This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met. |
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10433960 - Published on:
11/09/2020 - Last updated on:
02/06/2021