Evaluation of Parameter Regionalization Methods for Flood Simulations in Kelantan River Basin
M.F. Chow1, M.M. Jamil2, F. Che Ros3, M.A.M. Yuzir4, M.S. Hossain5
1DM.F. Chow, Department of Institute of Energy Infrastructure, Universiti Tenaga Nasional, Jalan, Kajang, Selangor, Malaysia.
2M.M. Jamil, Department of Institute of Energy Infrastructure, Universiti Tenaga Nasional, Jalan, Kajang, Selangor, Malaysia.
3F. Che Ros, Department of Institute of Energy Infrastructure, Universiti Tenaga Nasional, Jalan, Kajang, Selangor, Malaysia.
4M.A.M. Yuzir, Department of Institute of Energy Infrastructure, Universiti Tenaga Nasional, Jalan, Kajang, Selangor, Malaysia.
5M.S. Hossain, Department of Institute of Energy Infrastructure, Universiti Tenaga Nasional, Jalan, Kajang, Selangor, Malaysia.
Manuscript received on 04 May 2019 | Revised Manuscript received on 09 May 2019 | Manuscript Published on 13 May 2019 | PP: 313-318 | Volume-8 Issue-7S May 2019 | Retrieval Number: G10560587S1919©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Parameter regionalization techniques are widely used to estimate the parameters for calibrating the hydrological models in ungauged catchments. This study is aimed to compare global average and regression regionalization method for estimating input parameters for Integrated Flood Analysis System (IFAS) model in Kelantan River basin. The calibrated IFAS parameters were obtained from a number of gauged catchments. The model performances obtained using both methods were evaluated using Nash-Sutcliffe coefficient for peak flow, runoff volume and wave shape for flood event during period Dec 2006 – Jan 2007. The regression-based technique performed better than global averaged technique, with the Nash-Sutcliffe model efficiency coefficient values obtained were greater than 0.7 (indicating good model performance) compared to 0.4 for global averaged technique. The results suggest that it is possible to estimate the IFAS parameters using regression-based techniques for flood simulation.
Keywords: Flood Simulation, Hydrological Modeling, Parameter Regionalization, Ungauged Catchment.
Scope of the Article: Internet Technologies, Infrastructure, Services & Applications