Assessing LISFLOOD-FP with the next-generation digital elevation model FABDEM using household survey and remote sensing data in the Central Highlands of Vietnam

Peer Reviewed
14 February 2024

Laurence Hawker, Jeffrey Neal, James Savage, Thomas Kirkpatrick, Rachel Lord, Yanos Zylberberg, Andre Groeger, Truong Dang Thuy, Sean Fox, Felix Agyemang, Pham Khanh Nam

Flooding is an endemic global challenge with annual damages totalling billions of dollars. Impacts are felt most acutely in low- and middle-income countries, where rapid demographic change is driving increased exposure. These areas also tend to lack high-precision hazard mapping data with which to better understand or manage risk. To address this information gap a number of global flood models have been developed in recent years. However, there is substantial uncertainty over the performance of these data products. Arguably the most important component of a global flood model is the digital elevation model (DEM), which must represent the terrain without surface artifacts such as forests and buildings. Here we develop and evaluate a next generation of global hydrodynamic flood model based on the recently released FABDEM DEM. We evaluate the model and compare it to a previous version using the MERIT DEM at three study sites in the Central Highlands of Vietnam using two independent validation data sets based on a household survey and remotely sensed observations of recent flooding. The global flood model based on FABDEM consistently outperformed a model based on MERIT, and the agreement between the model and remote sensing was greater than the agreement between the two validation data sets.

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Hawker, L., Neal, J., Savage, J., Kirkpatrick, T., Lord, R., Zylberberg, Y., Groeger, A., Thuy, T. D., Fox, S., Agyemang, F., & Nam, P. K. (2024). Assessing LISFLOOD-FP with the next-generation digital elevation model FABDEM using household survey and remote sensing data in the Central Highlands of Vietnam. Natural Hazards and Earth System Sciences, 24(2), 539–566. https://doi.org/10.5194/nhess-24-539-2024
Publication | 9 March 2024