Assessing the Uncertainty Associated with Flood Features due to Variability of Rainfall and Hydrological Parameters

Author:

Sharafati Ahmad123ORCID,Khazaei Mohammad Reza4ORCID,Nashwan Mohamed Salem56ORCID,Al-Ansari Nadhir7ORCID,Yaseen Zaher Mundher8ORCID,Shahid Shamsuddin5ORCID

Affiliation:

1. Institute of Research and Development, Duy Tan University, Da Nang 550000, Vietnam

2. Faculty of Civil Engineering, Duy Tan University, Da Nang 550000, Vietnam

3. Department of Civil Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran

4. Department of Civil Engineering, Payame Noor University, Tehran, Iran

5. Faculty of Engineering, Universiti Teknologi Malaysia (UTM), Skudai, Johor 81310, Malaysia

6. Faculty of Engineering and Technology, Arab Academy for Science, Technology and Maritime Transport (AASTMT), Cairo, Egypt

7. Civil, Environmental and Natural Resources Engineering, Lulea University of Technology, Lulea 97187, Sweden

8. Sustainable Developments in Civil Engineering Research Group, Faculty of Civil Engineering, Ton Duc Thang University, Ho Chi Minh City, Vietnam

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.

Publisher

Hindawi Limited

Subject

Civil and Structural Engineering

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