EconPapers    
Economics at your fingertips  
 

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

Doan Quang Tri (), Nguyen Vinh Thu, Bui Thi Khanh Hoa, Hoang Anh Nguyen-Thi, Vo Van Hoa, Le Thi Hue, Dao Tien Dat and Ha T. T. Pham
Additional contact information
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

Sustainability, 2024, vol. 16, issue 9, 1-26

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.

Keywords: QPE and QPF radar; MIKE URBAN model; inundation; Nam Dinh city; Vietnam (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/16/9/3736/pdf (application/pdf)
https://www.mdpi.com/2071-1050/16/9/3736/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:16:y:2024:i:9:p:3736-:d:1385937

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().

 
Page updated 2025-03-19
Handle: RePEc:gam:jsusta:v:16:y:2024:i:9:p:3736-:d:1385937