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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>
<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-2026-5443</article-id>
<title-group>
<article-title>Numerical Perturbation Assessment of Multiple Controls on Groundwater Flow and Salinity Transport in Heterogeneous Coastal Delta Aquifers</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Zhan</surname>
<given-names>Chuanjun</given-names>
<ext-link>https://orcid.org/0000-0001-7977-3345</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Jiao</surname>
<given-names>Jiu Jimmy</given-names>
<ext-link>https://orcid.org/0000-0002-7180-6488</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Dai</surname>
<given-names>Zhenxue</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Soltanian</surname>
<given-names>Mohamad Reza</given-names>
</name>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Carroll</surname>
<given-names>Kenneth C.</given-names>
<ext-link>https://orcid.org/0000-0003-2097-9589</ext-link>
</name>
<xref ref-type="aff" rid="aff6">
<sup>6</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Dai</surname>
<given-names>Heng</given-names>
</name>
<xref ref-type="aff" rid="aff7">
<sup>7</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>CUG-HKU Joint Centre for Coastal Groundwater and Ecosystem Studies, School of  Environmental Studies, China University of Geosciences, Wuhan, China</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>CUG-HKU Joint Centre for Coastal Groundwater and Ecosystem Studies, Department of Earth and  Planetary Sciences, The University of Hong Kong, Hong Kong SAR, China</addr-line>
</aff>
<aff id="aff3">
<label>3</label>
<addr-line>School of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao, 266520, China</addr-line>
</aff>
<aff id="aff4">
<label>4</label>
<addr-line>College of Construction Engineering, Jilin University, Changchun, 130026, China</addr-line>
</aff>
<aff id="aff5">
<label>5</label>
<addr-line>Departments of Geosciences, University of Cincinnati, Cincinnati, OH, USA</addr-line>
</aff>
<aff id="aff6">
<label>6</label>
<addr-line>Department of Plant &amp; Environmental Science, New Mexico State University, Las Cruces, NM,  USA</addr-line>
</aff>
<aff id="aff7">
<label>7</label>
<addr-line>State Key Laboratory of Geomicrobiology and Environmental Changes, China University of  Geosciences, Wuhan, Hubei, 430074, China</addr-line>
</aff>
<pub-date pub-type="epub">
<day>20</day>
<month>10</month>
<year>2026</year>
</pub-date>
<volume>2026</volume>
<fpage>1</fpage>
<lpage>33</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2026 Chuanjun Zhan 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-2026-5443/">This article is available from https://egusphere.copernicus.org/preprints/2026/egusphere-2026-5443/</self-uri>
<self-uri xlink:href="https://egusphere.copernicus.org/preprints/2026/egusphere-2026-5443/egusphere-2026-5443.pdf">The full text article is available as a PDF file from https://egusphere.copernicus.org/preprints/2026/egusphere-2026-5443/egusphere-2026-5443.pdf</self-uri>
<abstract>
<p>Coastal-delta groundwater models must represent aquifer heterogeneity, hydrologic inputs, river&amp;ndash;aquifer exchange, and lateral and deep hydraulic connections, but their relative importance can change with the forecast target. We used an observation-informed three-dimensional variable-density groundwater-flow and salinity-transport model of the Pearl River Delta to compare 300 configurations over a five-year simulation. Eight controls were examined: facies structure, spatial variability in hydraulic conductivity (&lt;em&gt;K&lt;/em&gt;) within a fixed facies structure, recharge, river stage, riverbed conductance, inland boundaries, coastal boundaries, and model-bottom elevation. Facies structure produced the largest regional head response, and changes in hydrogeologic geometry and connectivity exerted a greater influence than within-facies &lt;em&gt;K&lt;/em&gt; variability. Recharge produced widespread responses and the largest changes in volume-weighted mean total dissolved solids (TDS) and in the volumes of brackish-or-more-saline and high-salinity groundwater. Coastal boundaries generated the largest spatial TDS differences, concentrated in estuarine and nearshore aquifers. River-stage effects exceeded riverbed-conductance effects and followed the distributary network, whereas inland-boundary effects were concentrated near hydraulically connected margins. Within-facies &lt;em&gt;K&lt;/em&gt; variability produced smaller, spatially dispersed responses, and model-bottom elevation had little influence over five years under the tested bedrock conditions. Model-development priorities depend on the prediction target, area of interest, and spatial and temporal scales. Short-term regional forecasts require reliable initial head and salinity fields, a credible three-dimensional heterogeneous hydrogeologic framework, and well-constrained recharge. Boundary and deep-domain detail become more important near hydraulically connected margins and over longer periods. The perturbation approach and resulting insights are applicable to similar coastal-delta and estuarine aquifers.</p>
</abstract>
<counts><page-count count="33"/></counts>
<funding-group>
<award-group id="gs1">
<funding-source>National Natural Science Foundation of China</funding-source>
<award-id>42502245</award-id>
<award-id>42632013</award-id>
</award-group>
<award-group id="gs2">
<funding-source>Natural Science Foundation of Shandong Province</funding-source>
<award-id>ZR2024QD095</award-id>
</award-group>
</funding-group>
</article-meta>
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