Issue |
E3S Web Conf.
Volume 347, 2022
2nd International Conference on Civil and Environmental Engineering (ICCEE 2022)
|
|
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Article Number | 04008 | |
Number of page(s) | 10 | |
Section | Water and Environmental Engineering | |
DOI | https://doi.org/10.1051/e3sconf/202234704008 | |
Published online | 14 April 2022 |
Streamflow evaluation using IHACRES model in Kelantan river basin, Malaysia
1 Department of Civil Engineering, Lee Kong Chian Faculty of Engineering and Science, Universiti
Tunku Abdul Rahman, 43000 Kajang, Malaysia
2 Department of Civil Engineering, Faculty of Engineering, University of Malaya, 50603 Kuala
Lumpur, Malaysia.
3 Institute of Environment and Sustainable Development, Banaras Hindu University, India.
* Corresponding author: chinrj@utar.edu.my
Kelantan is a flood-prone area where in the past years flood had occurred quite frequently. Determining a hydrological model that can represent Kelantan River basin by giving plausible simulated runoff according to the observed runoff is essential as this will allow appropriate prediction of future flood by using forecasted rainfall and other data. In this study, the IHACRES model was used to simulate runoff and the calibrated simulated runoff by daily scale and seasonal flood events were compared with observed runoff. In general, the IHACRES model performed better in seasonal scale as compared with annual scale in terms of calibration. However, performance of IHACRES degraded during validation stage, whereby the model tends to underestimate the high peak flows but estimate rather more accurate when no peak flows were present. In terms of annual scale, the best model was obtained by calibrating the streamflow in 2012 – 2013 (2 years), the validation results were not satisfactory with NSE = 0.473 and PBIAS = 27.7%. On the other hand, for seasonal analysis, the best model was obtained by calibrating the data of NEM 6 (November 2017 – March 2018). 3 out of 5 of the validation periods show unsatisfactory results (NSE ≤ 0.50). NEM 1 (November 2012 – March 2013) show the best validation results with NSE = 0.853. Further calibration is required in order to enhance the accuracy of the model.
© The Authors, published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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