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Assessment of Weather Research and Forecasting (WRF) Physical Schemes Parameterization to Predict Moderate to Extreme Rainfall in Poorly Gauged Basin

Author

Listed:
  • Syeda Maria Zaidi

    (Faculty of Civil Engineering Technology, Universiti Malaysia Pahang, Lebuh Persiaran Tun Khalil Yaakob, Kuantan 26300, Pahang, Malaysia
    Civil Engineering Department, Balochistan University of Engineering and Technology, Khuzdar 89100, Balochistan, Pakistan)

  • Jacqueline Isabella Anak Gisen

    (Faculty of Civil Engineering Technology, Universiti Malaysia Pahang, Lebuh Persiaran Tun Khalil Yaakob, Kuantan 26300, Pahang, Malaysia
    State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China)

  • Mohamed Eltahan

    (Institute of Geosciences, Division of Meteorology, University of Bonn, 53121 Bonn, Germany
    Institute of Bio- and Geosciences (Agrosphere, IBG-3), Research Centre Jülich, 52428 Jülich, Germany)

  • Qian Yu

    (State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China
    Research Center on Flood and Drought Disaster Reduction of the Ministry of Water Resources, Beijing 100038, China)

  • Syarifuddin Misbari

    (Faculty of Civil Engineering Technology, Universiti Malaysia Pahang, Lebuh Persiaran Tun Khalil Yaakob, Kuantan 26300, Pahang, Malaysia)

  • Su Kong Ngien

    (Faculty of Civil Engineering Technology, Universiti Malaysia Pahang, Lebuh Persiaran Tun Khalil Yaakob, Kuantan 26300, Pahang, Malaysia)

Abstract

Incomplete hydro-meteorological data and insufficient rainfall gauges have caused difficulties in establishing a reliable flood forecasting system. This study attempted to adopt the remotely sensed hydro-meteorological data as an alternative to the incomplete observed rainfall data in the poorly gauged Kuantan River Basin (KRB), the main city at the east coast of Peninsula Malaysia. Performance of Weather Research and Forecasting (WRF) schemes’ combinations, including eight microphysics (MP) and six cumulus, were evaluated to determine the most suitable combination of WRF MPCU in simulating rainfall over KRB. All the obtained results were validated against observed moderate to extreme rainfall events. Among all, the combination scheme Stony Brook University and Betts–Miller–Janjic (SBUBMJ) was found to be the most suitable to capture both spatial and temporal rainfall, with average percentage error of about ±17.5% to ±25.2% for heavy and moderate rainfall. However, the estimated PE ranges of −58.1% to 68.2% resulted in uncertainty while simulating extreme rainfall events, requiring more simulation tests for the schemes’ combinations using different boundary layer conditions and domain configurations. Findings also indicate that for the region where hydro-meteorological data are limited, WRF, as an alternative approach, can be used to achieve more sustainable water resource management and reliable hydrological forecasting.

Suggested Citation

  • Syeda Maria Zaidi & Jacqueline Isabella Anak Gisen & Mohamed Eltahan & Qian Yu & Syarifuddin Misbari & Su Kong Ngien, 2022. "Assessment of Weather Research and Forecasting (WRF) Physical Schemes Parameterization to Predict Moderate to Extreme Rainfall in Poorly Gauged Basin," Sustainability, MDPI, vol. 14(19), pages 1-41, October.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:19:p:12624-:d:933350
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    References listed on IDEAS

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    1. Olkeba Tolessa Leta & Aly I. El-Kadi & Henrietta Dulai, 2018. "Impact of Climate Change on Daily Streamflow and Its Extreme Values in Pacific Island Watersheds," Sustainability, MDPI, vol. 10(6), pages 1-22, June.
    2. Mariana L. R. Goncalves & Jonatan Zischg & Sven Rau & Markus Sitzmann & Wolfgang Rauch & Manfred Kleidorfer, 2018. "Modeling the Effects of Introducing Low Impact Development in a Tropical City: A Case Study from Joinville, Brazil," Sustainability, MDPI, vol. 10(3), pages 1-19, March.
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