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<front>
<journal-meta>
<journal-id journal-id-type="publisher">HESSD</journal-id>
<journal-title-group>
<journal-title>Hydrology and Earth System Sciences Discussions</journal-title>
<abbrev-journal-title abbrev-type="publisher">HESSD</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">Hydrol. Earth Syst. Sci. Discuss.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">1812-2116</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/hess-2024-369</article-id>
<title-group>
<article-title>Multi-variable process-based calibration of a behavioural hydrological model</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Heuer</surname>
<given-names>Moritz M.</given-names>
<ext-link>https://orcid.org/0000-0003-4013-6482</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>Mohajerani</surname>
<given-names>Hadysa</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>Casper</surname>
<given-names>Markus C.</given-names>
<ext-link>https://orcid.org/0000-0002-1163-8988</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Department of Physical Geography, University Trier, Trier, 54296, Germany</addr-line>
</aff>
<pub-date pub-type="epub">
<day>22</day>
<month>01</month>
<year>2025</year>
</pub-date>
<volume>2025</volume>
<fpage>1</fpage>
<lpage>38</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2025 Moritz M. Heuer et al.</copyright-statement>
<copyright-year>2025</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://hess.copernicus.org/preprints/hess-2024-369/">This article is available from https://hess.copernicus.org/preprints/hess-2024-369/</self-uri>
<self-uri xlink:href="https://hess.copernicus.org/preprints/hess-2024-369/hess-2024-369.pdf">The full text article is available as a PDF file from https://hess.copernicus.org/preprints/hess-2024-369/hess-2024-369.pdf</self-uri>
<abstract>
<p>Behavioural hydrological modelling aims not only at predicting the discharge of an area within a model, but also at understanding and correctly depicting the underlying hydrological processes. Here, we present a new approach for the calibration and evaluation of water balance models, exemplarily applied to the Riveris catchment in Rhineland-Palatinate, Germany. For our approach, we used the behavioural model WaSiM. The first calibration step is the adjustment of the evapotranspiration (ETa) parameters based on MODIS evaporation data. This aims at providing correct evaporation behaviour of the model and at closing the water balance at the gauging station. In a second step, geometry and transmissivity of the aquifer are determined using the Characteristic Delay Curve (CDC). The portion of groundwater recharge was calibrated using the Delayed Flow Index (DFI). In a third step, inappropriate pedotransfer functions (PTFs) could be filtered out by comparing dominant runoff process patterns under a synthetic precipitation event with a soil hydrological reference map, Then, the discharge peaks were adjusted based on so-called signature indices. This ensured a correct depiction of high-flow volume in the model. Finally, the overall model performance was determined using signature indices and efficiency measures. The results show a very good model fit with values for the NSE of 0.88 and 0.9 for the KGE in the calibration period and an NSE of 0.81 and a KGE of 0.89 for the validation period. Simultaneously, our calibration approach ensured a correct depiction of the underlying processes (groundwater behaviour, runoff patterns). This means that our calibration approach allows selecting a behaviourally faithful one from many possible parameterisation variants.</p>
</abstract>
<counts><page-count count="38"/></counts>
<funding-group>
<award-group id="gs1">
<funding-source>Deutsche Forschungsgemeinschaft</funding-source>
<award-id>426111700</award-id>
</award-group>
</funding-group>
</article-meta>
</front>
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