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<front>
<journal-meta>
<journal-id journal-id-type="publisher">ESSDD</journal-id>
<journal-title-group>
<journal-title>Earth System Science Data Discussions</journal-title>
<abbrev-journal-title abbrev-type="publisher">ESSDD</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">Earth Syst. Sci. Data Discuss.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">1866-3591</issn>
<publisher><publisher-name></publisher-name>
<publisher-loc>Göttingen, Germany</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.5194/essd-2026-279</article-id>
<title-group>
<article-title>GRIT-ADB: A Global Attribute Database for the GRIT Hydrography</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Zhang</surname>
<given-names>Boen</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff6">
<sup>6</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Wortmann</surname>
<given-names>Michel</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Liu</surname>
<given-names>Yinxue</given-names>
<ext-link>https://orcid.org/0000-0002-5250-0184</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Kratzert</surname>
<given-names>Frederik</given-names>
<ext-link>https://orcid.org/0000-0002-8897-7689</ext-link>
</name>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Moulds</surname>
<given-names>Simon</given-names>
<ext-link>https://orcid.org/0000-0002-7297-482X</ext-link>
</name>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Slater</surname>
<given-names>Louise</given-names>
<ext-link>https://orcid.org/0000-0001-9416-488X</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>School of Geography and the Environment, University of Oxford, Oxford, UK</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>European Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading, UK</addr-line>
</aff>
<aff id="aff3">
<label>3</label>
<addr-line>Geography and Environment, Loughborough University, Loughborough, UK</addr-line>
</aff>
<aff id="aff4">
<label>4</label>
<addr-line>Google Research, Vienna, Austria</addr-line>
</aff>
<aff id="aff5">
<label>5</label>
<addr-line>School of Geosciences, University of Edinburgh, Edinburgh, UK</addr-line>
</aff>
<aff id="aff6">
<label>6</label>
<addr-line>School of Geography and Planning, Sun Yat-sen University, Guangzhou, China</addr-line>
</aff>
<pub-date pub-type="epub">
<day>26</day>
<month>06</month>
<year>2026</year>
</pub-date>
<volume>2026</volume>
<fpage>1</fpage>
<lpage>22</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2026 Boen Zhang et al.</copyright-statement>
<copyright-year>2026</copyright-year>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit <ext-link ext-link-type="uri"  xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link></license-p>
</license>
</permissions>
<self-uri xlink:href="https://essd.copernicus.org/preprints/essd-2026-279/">This article is available from https://essd.copernicus.org/preprints/essd-2026-279/</self-uri>
<self-uri xlink:href="https://essd.copernicus.org/preprints/essd-2026-279/essd-2026-279.pdf">The full text article is available as a PDF file from https://essd.copernicus.org/preprints/essd-2026-279/essd-2026-279.pdf</self-uri>
<abstract>
<p>Global hydro-environmental databases provide essential information for large-scale hydrological, ecological, geomorphological, and Earth system analyses. Most existing global databases are built upon convergent river representations that do not explicitly capture bifurcating, multi-channel river systems. In addition, these databases primarily characterise long-term climatological means or static representations of environmental conditions derived from earlier-generation global datasets, limiting their applicability for time-varying analyses of hydroclimatic and geomorphological processes. Here we present GRIT-ADB, a new attribute database for the vectorised Global River Topology (GRIT), a new river hydrography dataset created from a 30 m resolution river mask and terrain data that provides a topology-explicit and physically realistic representation of river networks including divergent flow pathways. GRIT-ADB provides standardised hydro-environmental information for 19.6 million km of rivers and streams. It currently comprises 64 time-varying (multi-dimensional embeddings) and 35 static variables (&amp;gt;300 attributes), spanning five categories: hydrology, physiography, climate, land cover and use, and soils and geology. Attributes are derived by aggregating and harmonising data from state-of-the-art global datasets and are accumulated along the river network from headwaters to basin outlets, while preserving the topology of divergent and complex flow pathways. The attributes are linked to multiple GRIT scales, including hierarchically-nested subbasins, individual river reaches of up to 1 km long, and coarser-scale river segments of several kilometres long, providing a flexible framework that can accommodate future extensions of GRIT and additional attributes. By combining a standardised attribute framework with explicit representation of bifurcating river hydrography, GRIT-ADB enables improved large-scale yet high-resolution analyses of river connectivity, hydrological extremes, hydro-ecological processes, and climate impacts in complex river systems, supporting a wide range of global hydrological and environmental applications.</p>
</abstract>
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<funding-group>
<award-group id="gs1">
<funding-source>UK Research and Innovation</funding-source>
<award-id>UKRI2054</award-id>
<award-id>MR/V022008/1</award-id>
</award-group>
</funding-group>
</article-meta>
</front>
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<back>
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