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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-2023-398</article-id>
<title-group>
<article-title>Discrete Global Grid System-based Flow Routing Datasets in the Amazon and Yukon Basins</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Liao</surname>
<given-names>Chang</given-names>
<ext-link>https://orcid.org/0000-0002-7348-8858</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Engwirda</surname>
<given-names>Darren</given-names>
<ext-link>https://orcid.org/0000-0002-3379-9109</ext-link>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Cooper</surname>
<given-names>Matthew</given-names>
<ext-link>https://orcid.org/0000-0002-0165-209X</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Li</surname>
<given-names>Mingke</given-names>
<ext-link>https://orcid.org/0000-0001-6310-4964</ext-link>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Fang</surname>
<given-names>Yilin</given-names>
<ext-link>https://orcid.org/0000-0003-1969-9889</ext-link>
</name>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Atmospheric, Climate, and Earth Sciences, Pacific Northwest National Laboratory, Richland, WA, USA</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>T-3 Fluid Dynamics and Solid Mechanics Group, Los Alamos National Laboratory, Los Alamos, NM, USA</addr-line>
</aff>
<aff id="aff3">
<label>3</label>
<addr-line>Research and Development Group, Geosapiens Inc., Quebec City, QC, Canada</addr-line>
</aff>
<aff id="aff4">
<label>4</label>
<addr-line>Hydrology Group, Pacific Northwest National Laboratory, Richland, WA, USA</addr-line>
</aff>
<pub-date pub-type="epub">
<day>02</day>
<month>04</month>
<year>2024</year>
</pub-date>
<volume>2024</volume>
<fpage>1</fpage>
<lpage>41</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2024 Chang Liao et al.</copyright-statement>
<copyright-year>2024</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-2023-398/">This article is available from https://essd.copernicus.org/preprints/essd-2023-398/</self-uri>
<self-uri xlink:href="https://essd.copernicus.org/preprints/essd-2023-398/essd-2023-398.pdf">The full text article is available as a PDF file from https://essd.copernicus.org/preprints/essd-2023-398/essd-2023-398.pdf</self-uri>
<abstract>
<p>Discrete Global Grid systems (DGGs) are emerging spatial data structures widely used to organize geospatial datasets across scales. While DGGs have found applications in various scientific disciplines, including atmospheric science and ecology, their integration into physically based hydrologic models and Earth System Models (ESMs) has been hindered by the lack of flow-routing datasets based on DGGs. In response to this gap, this study pioneers the development of new flow routing datasets using Icosahedral Snyder Equal Area (ISEA) DGGs and a novel mesh-independent flow direction model. We present flow routing datasets for two large basins, the tropical Amazon River Basin and the Arctic Yukon River Basin. These datasets demonstrate the potential of DGGs-based flow routing datasets to enhance the performance of hydrologic models and provide observationally-based flow routing inputs for immediate application to the Amazon and Yukon River Basins. The data are available at &lt;a href=&quot;https://doi.org/10.5281/zenodo.8377765&quot; target=&quot;_blank&quot; rel=&quot;noopener&quot;&gt;https://doi.org/10.5281/zenodo.8377765&lt;/a&gt; (Liao, 2023).</p>
</abstract>
<counts><page-count count="41"/></counts>
<funding-group>
<award-group id="gs1">
<funding-source>U.S. Department of Energy</funding-source>
<award-id>KP1703110/75415</award-id>
<award-id>9233218CNA000001</award-id>
<award-id>KP1702010</award-id>
</award-group>
</funding-group>
</article-meta>
</front>
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