<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-04-13T00:49:23Z</responseDate><request verb="GetRecord" identifier="oai:www.recercat.cat:2072/476616" metadataPrefix="marc">https://recercat.cat/oai/request</request><GetRecord><record><header><identifier>oai:recercat.cat:2072/476616</identifier><datestamp>2025-05-08T15:43:48Z</datestamp><setSpec>com_2072_98</setSpec><setSpec>col_2072_378192</setSpec></header><metadata><record xmlns="http://www.loc.gov/MARC21/slim" xmlns:dcterms="http://purl.org/dc/terms/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.loc.gov/MARC21/slim http://www.loc.gov/standards/marcxml/schema/MARC21slim.xsd">
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      <subfield code="a">Hawker, Laurence</subfield>
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      <subfield code="a">Neal, Jeffrey</subfield>
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      <subfield code="a">Zylberberg, Yanos</subfield>
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      <subfield code="a">Gröger, Andre</subfield>
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      <subfield code="a">Thuy, Truong Dang</subfield>
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      <subfield code="a">Fox, Sean</subfield>
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      <subfield code="a">Agyemang, Felix</subfield>
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      <subfield code="a">Nam, Pham Khanh</subfield>
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      <subfield code="a">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.</subfield>
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      <subfield code="a">Assessing LISFLOOD-FP with the next-generation digital elevation model FABDEM using household survey and remote sensing data in the Central Highlands of Vietnam</subfield>
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