EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Evaluating the next generation of global flood models in the Central Highlands of Vietnam

Jeffrey Neal1,2, Laurence Hawker1, James Savage2, Tom Kirkpatrick1, Yanos Zylberberg3, and Pham Khanh Nam4
Jeffrey Neal et al.
  • 1School of Geographical Sciences, University of Bristol, Bristol, United Kingdom (
  • 2Fathom, Square Works, 17-18 Berkeley Square, Clifton, Bristol, UK
  • 3School of Economics, University of Bristol, Bristol, United Kingdom
  • 4School of Economics, University of Economics Ho Chi Minh city (UEH), Ho Chi Minh City, Vietnam

Global flood models have undergone rapid development over the past decade. However, with each new generation of model it is essential to systematically evaluate simulation performance for a range of tests and against multiple sources of data. It is also important to take stock, document lessons learnt and contribute to the formation of better practice and modelling standards in the field. Here we illustrate some of the progress being made in global flood modelling by evaluating the latest 30 m resolution implementation of the LISFLOOD-FP/Fathom global flood model over the Central Highlands of Vietnam, and benchmark it against several previous incarnations of the model.

Two independent data sources are used to evaluate the model. The first of these maps recent flood extents using remotely sensed data from the Sentinal-1 missions and compares them to global flood model outputs of commensurate return periods. The second data set identifies land parcels (properties and agricultural fields) that flooded during the same events from a household survey, where uniquely all household land parcels in four villages were sampled. The independence of the date sets also allowed for cross-validation of the observations.

Substantial simulation enhancements are associated with the transition from SRTM and MERIT DEM’s at 90 m resolution to FABDEM, a version of Copernicus DEM at 30 m with forests and buildings removed. In addition to improvements derived from the DEM, more accurate river location, river width and discharge estimates combined with the inversion of river bathymetry via gradually varied rather than uniform flow theory also have an impact on performance.

How to cite: Neal, J., Hawker, L., Savage, J., Kirkpatrick, T., Zylberberg, Y., and Nam, P. K.: Evaluating the next generation of global flood models in the Central Highlands of Vietnam, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11682,, 2022.