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<front>
<journal-meta>
<journal-id journal-id-type="publisher">EGUsphere</journal-id>
<journal-title-group>
<journal-title>EGUsphere</journal-title>
<abbrev-journal-title abbrev-type="publisher">EGUsphere</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">EGUsphere</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub"></issn>
<publisher><publisher-name>Copernicus Publications</publisher-name>
<publisher-loc>Göttingen, Germany</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.5194/egusphere-2026-3497</article-id>
<title-group>
<article-title>Unraveling Local and Upwind Controls on Terrestrial ET-Runoff Partitioning in China: Grid-Scale Analysis and Explanatory Diagnostics</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Luo</surname>
<given-names>Zhiwei</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>Ji</surname>
<given-names>Ling</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>Xie</surname>
<given-names>Yulei</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>School of Economics and Management, Beijing University of Technology, Beijing, 100124, China</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>Institute of Environmental and Ecological Engineering, Guangdong University of Technology, Guangzhou, Guangdong,  510006, China</addr-line>
</aff>
<pub-date pub-type="epub">
<day>03</day>
<month>09</month>
<year>2026</year>
</pub-date>
<volume>2026</volume>
<fpage>1</fpage>
<lpage>27</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2026 Zhiwei Luo 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://egusphere.copernicus.org/preprints/2026/egusphere-2026-3497/">This article is available from https://egusphere.copernicus.org/preprints/2026/egusphere-2026-3497/</self-uri>
<self-uri xlink:href="https://egusphere.copernicus.org/preprints/2026/egusphere-2026-3497/egusphere-2026-3497.pdf">The full text article is available as a PDF file from https://egusphere.copernicus.org/preprints/2026/egusphere-2026-3497/egusphere-2026-3497.pdf</self-uri>
<abstract>
<p>How water is divided between evapotranspiration and runoff controls regional water availability, but this partition is usually attributed mainly to local climate and land-surface conditions. Because part of precipitation is supplied by evaporation from upwind land areas, downwind partitioning may also reflect the ecohydrological state of terrestrial moisture-source regions. Here we analyze monthly evapotranspiration-runoff partitioning across mainland China from 2008 to 2017 using a geographically weighted random forest that separates local hydroclimatic and land-surface covariates from upwind land-surface covariates aggregated along atmospheric moisture trajectories. The evapotranspiration share varies non-monotonically with aridity, remaining near 0.80&amp;ndash;0.82 from hyper-arid to dry sub-humid regions before declining to 0.62 in humid regions. Local controls dominate the explainable variability nationally, with mean cross-validated R2 increasing only from 0.468 to 0.471 when upwind covariates are added. However, the terrestrial upwind signal is geographically and seasonally concentrated, being most evident in dry sub-humid transition zones and in autumn. Upwind vegetation density, soil wetness, and precipitation show inverted-U relationships with the downwind green-water share, whereas upwind evaporative demand shows a monotone-negative relationship. These patterns persist across alternative evapotranspiration and runoff product combinations, but their interpretation remains limited by gridded product uncertainty, the terrestrial-only definition of upwind covariates, and the observational attribution design. The results suggest that assessments of blue-green water partitioning may benefit from considering upwind land-surface conditions alongside local hydroclimate, particularly in dry sub-humid transition zones.</p>
</abstract>
<counts><page-count count="27"/></counts>
<funding-group>
<award-group id="gs1">
<funding-source>National Natural Science Foundation of China</funding-source>
<award-id>52379001</award-id>
<award-id>52222901</award-id>
</award-group>
<award-group id="gs2">
<funding-source>Beijing Nova Program</funding-source>
<award-id>20220484034</award-id>
</award-group>
</funding-group>
</article-meta>
</front>
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<back>
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