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

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

Résultats de recherche: Contribution à un journalArticleRevue par des pairs

Résumé

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.

langue originaleAnglais
Pages (de - à)539-566
Nombre de pages28
journalNatural Hazards and Earth System Sciences
Volume24
Numéro de publication2
Les DOIs
étatPublié - 15 févr. 2024
Modification externeOui

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