Authors

Affiliations

Faculty of Meteorology and Hydrology, Hanoi University of Nature resources and Environment; tvanh@hunre.edu.vn

2 Faculty of Geomatics and Land Administration, Hanoi University of Mining and Geology; duonganhquan@humg.edu.vn

3 Faculty of Informatics, Hanoi University of Nature resources and Environment; txquang@hunre.edu.vn

4 Faculty of Resources management, Thai Nguyen University of Agriculture and Forestry; tranthimaianh@tuaf.edu.vn

*Correspondence: duonganhquan@humg.edu.vn. 

Abstracts

In Vietnam, the Central area faced the highest frequency of flood; in 2020, 13 tropical depressions landed in Vietnam, 8 of them came to the Central area within more than one month, from the 7th  October to 15th November caused a loss estimated at 30000 billion in Vietnam Dong(VND), and 249 people died. Flood management in this area is a crucial task for local authorities. In flood management, flood simulation is the critical task needed for every flood management strategy. Many methods can make the flood simulation. In those methods, hydraulic modeling is the widest apply in Vietnam. This method shows its advantages in many aspects, but they also have limitations compare to other methods. The hydraulic model can predict floods with complex conditions and multi–input. In this study, flood simulation is made by applying hydraulic modeling. The study area is downstream of the Ca river basin, affected area by flood in Central Vietnam. The flood simulation is made with four flood scenarios in MIKE packages: 1%, 2%, 5%, and 10%, representing the flooding return period of 100, 50, 20, and 10 years. The flood simulation provides flood map based on the modeling result. Those data is validated and compare with flood areas from satellite images in the study area. The study shows the advantages and disadvantages of hydraulic modeling in flood simulation and flood mapping from satellite images. There is a very high potential of using the hydraulic model together with satellite data for flood hazard assessment.

Keywords

Cite this paper

Van, A.T.; Anh, Q.D.; Ngoc, Q.B.; Van, H.P.; Danh, D.N.; Xuan, Q.T.; Thi, M.A.T. The advantage of using satellite data together with the hydraulic model in flood hazard assessment: A case study in Ca River downstream. VN J. Hydrometeorol. 2021, 8, 28-43. 

References

1. Thuc, T. Vietnam Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation. Vietnam Pulishing House of Natural Resources, Environment and Cartography 2015.

2. Shadmehri Toosi, A.; Calbimonte, G.H.; Nouri, H.; Alaghmand, S. River basin–scale flood hazard assessment using a modified multi–criteria decision analysis approach: A case study. J. Hydrol. 2019, 574, 660–671.

3. Youssef, A.M.; Hegab, M.A. Flood–Hazard Assessment Modeling Using Multicriteria Analysis and GIS: A Case Study—Ras Gharib Area, Egypt. Spatial Modeling in GIS and R for Earth and Environmental Sciences 2019, 229–257.

4. Nhung, L.H.; Perminov, A.V.; Kozyr, I.E. Modeling of Floods and Flood Control Water Reservoirs for Evaluation of Inundation da Nang Province of Vietnam. Procedia Eng. 2016, 154, 1319–1323.

5. Chau, V.N.; Holland, J.; Cassells, S.; Tuohy, M. Using GIS to map impacts upon agriculture from extreme floods in Vietnam. Appl. Geogr. 2013, 41, 65–74.

6. Le, T.V.H.; Nguyen, H.N.; Wolanski, E.; Tran, T.C.; Haruyama, S. The combined impact on the flooding in Vietnam's Mekong River delta of local man–made structures, sea level rise, and dams upstream in the river catchment. Estuar. Coast. Shelf Sci. 2007, 71, 110–116.

7. Phạm, V.B. Flood hazard mapping for Ninh Binh province. Center For Participatory Irrigation Management, 2019, 1–46.

8. Duong, V.N.; Gourbesville, P. Model Uncertainty in Flood Modelling. Case Study at Vu Gia Thu Bon Catchment – Vietnam. Procedia Eng. 2016, 154, 450–458.

9. Vo, N.D.; Gourbesville, P.; Vu, M.T.; Raghavan, S.V.; Liong, S.Y. A deterministic hydrological approach to estimate climate change impact on river flow: Vu Gia–Thu Bon catchment, Vietnam.  J. Hydro–Environment Res. 2016, 11, 59–74.

10. Dang, D.D.; Ngo, A.Q.; Nguyen, H.S.; Nguyen, N.T. Flood mapping for the downstream area of Dak Bla river. Tạp chí Khoa học và Công nghệ Thủy Lợi 2018, 1–9.

11. Khuong, D.V.; Linh, N.M. Application of the SWAT model to assess the importance of forests in flood control in the Vu Gia–Thu Bon river basin. J. Water Resour. Sci. Technol. 2012, 7, 56–63 (in Vietnamese).

12. Vu, T.T.; Ranzi, R. Flood risk assessment and coping capacity of floods in central Vietnam. J. Hydro–Environment Res. 2017, 14, 44–60.

13. Van Khanh Triet, N.; Viet Dung, N.; Merz, B.; Apel, H. Towards risk–based flood management in highly productive paddy rice cultivation–concept development and application to the Mekong Delta. Nat. Hazards Earth Syst. Sci. 2018, 18, 2859–2876.

14. Apel, H.; Martínez Trepat, O.; Nghia Hung, N.; Thi Chinh, D.; Merz, B.; Dung, N.V. Combined fluvial and pluvial urban flood hazard analysis: Concept development and application to Can Tho city, Mekong Delta, Vietnam. Nat. Hazards Earth Syst. Sci. 2016, 16, 941–961.

15. Wright, D.B.;  Ramirez–cort, F.; Ishizawa, O.A.; Rogelis, M.C. Methods in flood hazard and risk assessment. 1–20.

16. UK Centre for Ecology & Hydrology, Flood Estimation Handbook. 1999. Online Available: https://www.ceh.ac.uk/services/flood–estimation–handbook (Accessed: 10–May–2021).

17. Castellarin, A. European procedures for flood (FloodFreq, COST Action ES0901) FloodFreq – ES0901. 2010, 22–24.

18. McKerchar, A.I.; Macky, G. Comparison of a regional method for estimating design floods with two rainfall–based methods. J. Hydrol. 2001, 40, 129–138.

19. Calver, A.; Stewart, E.; Goodsell, G. Comparative analysis of statistical and catchment modelling approaches to river flood frequency estimation. J. Flood Risk Manag. 2009, 2, 24–31.

20. Ministry of Science and Technology. TCVN 9845:2013 Calculation of flood flow characteristics. 2013.

21. Ministry of Science and Technology. TCVN 7957:2008 Drainage and sewerage – External Networks and Facilities – Design Standard, 2008, 3–98.

22. Klein, T.; Nilsson, M.; Persson, A.;  Håkansson, B. From open data to open analyses—new opportunities for environmental applications? Environ. 2017, 4(2), 1–17.

23. Turner, W. Free and open–access satellite data are key to biodiversity conservation. Biol. Conserv. 2015, 182, 173–176.

24. Tavus, B.; Kocaman, S.; Gokceoglu, C.; Nefeslioglu, H.A. Considerations on the Use of Sentinel–1 Data in Flood Mapping in Urban Areas: Ankara (Turkey) 2018 Floods. ISPRS – Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2018, XLII–5, 575–581.

25. Mason, D.C.; Dance, S.L.; Cloke, H.L. Floodwater detection in urban areas using Sentinel–1 and WorldDEM data. J. Appl. Remote Sens. 2001, 15(3), 1–22.

26. Singha, M. Identifying floods and flood–affected paddy rice fields in Bangladesh based on Sentinel–1 imagery and Google Earth Engine ISPRS. J. Photogramm. Remote Sens. 2020, 166, 278–293.

27. Conde, F.C.; De Mata Muñoz, M. Flood monitoring based on the study of Sentinel–1 SAR images: The Ebro River case study. Water 2019, 11, 1–25.

28. Uddin, K.; Matin, M.A.; Meyer, F.J. Operational flood mapping using multi–temporal Sentinel–1 SAR images: A case study from Bangladesh. Remote Sens. 2019, 11(13), 1581.

29. Nguyen, T.H.D.; Nguyen, T.C.; Nguyen, T.N.T.; Doan, T.N. Flood inundation mapping using Sentinel–1A in An Giang province in 2019. Vietnam J. Sci. Technol. Eng. 2020, 62, 36–42.

30. Dinh, D.A.; Elmahrad, B.; Leinenkugel, P.; Newton, A. Time series of flood mapping in the Mekong Delta using high resolution satellite images Time series of flood mapping in the Mekong Delta using high resolution satellite images. IOP Conf. Ser.: Earth Environ. Sci. 2019, 266, 012011.

31. Phan, A.; Ha, D.N.; Man, C,D.; Nguyen, T.T.; Bui, H.Q.; Nguyen, T.T.N. Rapid assessment of flood inundation and damaged rice area in Red River Delta from Sentinel 1A imagery. Remote Sens. 2019, 11(17), 2034.

32. Duc, P.B.; Tran, T. Potential Of Sentinel–1 SAR Observations To Monitor Floods In The North Vietnam. Int. J. Sci. Technol. Res. 2020, 9(4), 326–331.

33. UN–SPIDER. In Detail: Recommended Practice: Flood Mapping and Damage Assessment using Sentinel–1 SAR data in Google Earth Engine. UN, 2021. Online Available:https://un–spider.org/advisory–support/recommended–practices/recommended–practice–google–earth–engine–flood–mapping/in–detail.

34. Hoang, N.Q.; Phan, T.D. Water resource and water quality in Ca river basin. VN J. Hydrometeorol. 2003, 507, 26–31.

35. Giandotti. Previsione delle piene e delle magre dei corsid’acqua. Istituto Poligrafico dello Stato 1934, 8, 107–117.

36. USDA–SCS. Urban Hydrology for Small Watersheds. Technical Release 55. Washington, DC, 1986.