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               <dc:title>Assessing LISFLOOD-FP with the next-generation digital elevation model FABDEM using household survey and remote sensing data in the Central Highlands of Vietnam</dc:title>
               <dc:creator>Hawker, Laurence</dc:creator>
               <dc:creator>Neal, Jeffrey</dc:creator>
               <dc:creator>Savage, James</dc:creator>
               <dc:creator>Kirkpatrick, Thomas</dc:creator>
               <dc:creator>Lord, Rachel</dc:creator>
               <dc:creator>Zylberberg, Yanos</dc:creator>
               <dc:creator>Gröger, Andre</dc:creator>
               <dc:creator>Thuy, Truong Dang</dc:creator>
               <dc:creator>Fox, Sean</dc:creator>
               <dc:creator>Agyemang, Felix</dc:creator>
               <dc:creator>Nam, Pham Khanh</dc:creator>
               <dc:description>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.</dc:description>
               <dc:date>2024</dc:date>
               <dc:type>Article</dc:type>
               <dc:relation>Natural Hazards and Earth System Sciences ; Vol. 24, Issue 2 (February 2024), p. 539-566</dc:relation>
               <dc:rights>open access</dc:rights>
               <dc:rights>Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.</dc:rights>
               <dc:rights>https://creativecommons.org/licenses/by/4.0/</dc:rights>
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