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Application of Radar-Based Precipitation Data Improves the Effectiveness of Urban Inundation Forecasting

Author

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  • Doan Quang Tri

    (Journal of Hydro-Meteorology, Information and Data Center, Viet Nam Meteorological and Hydrological Administration, Hanoi 10000, Vietnam)

  • Nguyen Vinh Thu

    (National Centre for Hydro-Meteorological Network, Viet Nam Meteorological and Hydrological Administration, Hanoi 10000, Vietnam)

  • Bui Thi Khanh Hoa

    (National Centre for Hydro-Meteorological Network, Viet Nam Meteorological and Hydrological Administration, Hanoi 10000, Vietnam)

  • Hoang Anh Nguyen-Thi

    (National Centre for Hydro-Meteorological Network, Viet Nam Meteorological and Hydrological Administration, Hanoi 10000, Vietnam)

  • Vo Van Hoa

    (Northern Delta and Midland Regional Hydro-Meteorological Center, Viet Nam Meteorological and Hydrological Administration, Hanoi 10000, Vietnam)

  • Le Thi Hue

    (Northern Delta and Midland Regional Hydro-Meteorological Center, Viet Nam Meteorological and Hydrological Administration, Hanoi 10000, Vietnam)

  • Dao Tien Dat

    (Northern Delta and Midland Regional Hydro-Meteorological Center, Viet Nam Meteorological and Hydrological Administration, Hanoi 10000, Vietnam)

  • Ha T. T. Pham

    (Faculty of Environmental Sciences, University of Science, Vietnam National University, Hanoi 10000, Vietnam)

Abstract

Using radar to estimate and forecast precipitation as input for hydrological models has become increasingly popular in recent years because of its superior spatial and temporal simulation compared with using rain gauge data. This study used radar-based quantitative precipitation estimation (QPE) to select the optimal parameter set for the MIKE URBAN hydrological model and radar-based quantitative precipitation forecasting (QPF) to simulate inundation in Nam Dinh city, Vietnam. The results show the following: (1) radar has the potential to improve the modeling and provide the data needed for real-time smart control if proper bias adjustment is obtained and the risk of underestimated flows after heavy rain is minimized, and (2) the MIKE URBAN model used to calculate two simulation scenarios with rain gauge data and QPE data showed effectiveness in combining the application of radar-based precipitation for the forecasting and warning of urban floods in Nam Dinh city. The results in Scenario 2 with rainfall forecast data from radar provide better simulation results. The average relative error in Scenario 2 is 9%, while the average relative error in Scenario 1 is 15%. Using the grid radar-based precipitation forecasting as input data for the MIKE URBAN model significantly reduces the error between the observed water depth and the simulated results compared with the case using an input rain gauge measured at Nam Dinh station (the difference in inundation level of Scenario 2 using radar-based precipitation is 0.005 m, and it is 0.03 m in Scenario 1). The results obtained using the QPE and QPF radar as input for the MIKE URBAN model will be the basis for establishing an operational forecasting system for the Northern Delta and Midland Regional Hydro-Meteorological Center, Viet Nam Meteorological and Hydrological Administration.

Suggested Citation

  • Doan Quang Tri & Nguyen Vinh Thu & Bui Thi Khanh Hoa & Hoang Anh Nguyen-Thi & Vo Van Hoa & Le Thi Hue & Dao Tien Dat & Ha T. T. Pham, 2024. "Application of Radar-Based Precipitation Data Improves the Effectiveness of Urban Inundation Forecasting," Sustainability, MDPI, vol. 16(9), pages 1-26, April.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:9:p:3736-:d:1385937
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    References listed on IDEAS

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    1. Albert S. Chen & Michael J. Hammond & Slobodan Djordjević & David Butler & David M. Khan & William Veerbeek, 2016. "From hazard to impact: flood damage assessment tools for mega cities," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 82(2), pages 857-890, June.
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