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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-2026-426</article-id>
<title-group>
<article-title>Extending Daily River Discharge Records Across China Using Satellite-Derived River Widths</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Wang</surname>
<given-names>Yong</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Gong</surname>
<given-names>Yulin</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Jing</surname>
<given-names>Yinghong</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>She</surname>
<given-names>Xiaojun</given-names>
</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>Yao</given-names>
<ext-link>https://orcid.org/0000-0001-8745-191X</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 Geographical Sciences, Southwest University, Chongqing 400715, China</addr-line>
</aff>
<pub-date pub-type="epub">
<day>19</day>
<month>06</month>
<year>2026</year>
</pub-date>
<volume>2026</volume>
<fpage>1</fpage>
<lpage>34</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2026 Yong Wang 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-2026-426/">This article is available from https://essd.copernicus.org/preprints/essd-2026-426/</self-uri>
<self-uri xlink:href="https://essd.copernicus.org/preprints/essd-2026-426/essd-2026-426.pdf">The full text article is available as a PDF file from https://essd.copernicus.org/preprints/essd-2026-426/essd-2026-426.pdf</self-uri>
<abstract>
<p>Long-term monitoring of global river discharge has been hindered by the uneven distribution of gauging stations and limited data accessibility, a challenge that is particularly acute in China. Although China contains one of the world&amp;rsquo;s densest river networks, high-frequency in situ discharge observations remain largely unavailable in the international public domain. To address this gap, we compiled daily discharge records from 1,196 gauges across China, comprising approximately 2.33 million observations &amp;ndash; 39 times as many gauges as are currently available for the region in the Global Runoff Data Centre (GRDC). Leveraging this unprecedented collection of in situ discharge records, along with river width time series derived from Landsat and Sentinel-2 imagery and gauge-specific hydraulic geometry relationships, we reconstructed and extended daily river discharge observations for 310 gauges from 1990 to 2024, resulting in the China Daily River Discharge Records (CDR&lt;sup&gt;2&lt;/sup&gt;) dataset. Compared with existing global satellite-derived discharge products, CDR&lt;sup&gt;2&lt;/sup&gt; increases the number of available gauges in China by at least fivefold. It achieves substantially improved performance, with a median Kling&amp;ndash;Gupta efficiency of 0.66 during validation. Sensitivity analyses further indicate that discharge estimation accuracy increases markedly with greater river width variability and stronger hydraulic sensitivity. Trend analysis reveals that nearly 65% of gauges exhibit declining discharge over 1990&amp;ndash;2024, with a median relative trend of &amp;minus;0.21%/yr, most pronounced in the Haihe, Liaohe, Yellow River, and middle Yangtze River basins. As the most extensive satellite-derived, gauge-constrained daily discharge dataset currently available for China, CDR&lt;sup&gt;2&lt;/sup&gt; bridges a critical geographic gap in global river monitoring and provides a valuable benchmark for future discharge estimation, hydrological studies, and satellite calibration efforts.</p>
</abstract>
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<funding-group>
<award-group id="gs1">
<funding-source>National Natural Science Foundation of China</funding-source>
<award-id>42571446</award-id>
<award-id>42201349</award-id>
</award-group>
<award-group id="gs2">
<funding-source>Chongqing Municipal Science and Technology Bureau</funding-source>
<award-id>CSTB2024YCJH-KYXM0054</award-id>
<award-id>cstc2024ycjh-bgzxm0043</award-id>
</award-group>
</funding-group>
</article-meta>
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