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            <title xml:lang="en">Estimating karst groundwater recharge from soil moisture observations – a new method tested at the Swabian Alb, southwest Germany</title>
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                <forename type="first">Romane</forename>
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                <forename type="first">Andreas</forename>
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                <forename type="first">Matías</forename>
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                <forename type="first">Dominic</forename>
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            <funder>This research has been supported by the Deutsche Forschungsgemeinschaft (grant no. HA 8113/1-1).</funder>
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            <idno type="halRefHtml">&lt;i&gt;Hydrology and Earth System Sciences&lt;/i&gt;, 2023, 27 (2), pp.385-400. &lt;a target="_blank" href="https://dx.doi.org/10.5194/hess-27-385-2023"&gt;&amp;#x27E8;10.5194/hess-27-385-2023&amp;#x27E9;&lt;/a&gt;</idno>
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                <title xml:lang="en">Estimating karst groundwater recharge from soil moisture observations – a new method tested at the Swabian Alb, southwest Germany</title>
                <author role="aut">
                  <persName>
                    <forename type="first">Romane</forename>
                    <surname>Berthelin</surname>
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                    <forename type="first">Andreas</forename>
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                    <forename type="first">Tunde</forename>
                    <surname>Olarinoye</surname>
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                    <forename type="first">Michael</forename>
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                  <idno type="idhal" notation="numeric">1268445</idno>
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                <author role="aut">
                  <persName>
                    <forename type="first">Matías</forename>
                    <surname>Mudarra</surname>
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                  <idno type="idhal" notation="numeric">1268446</idno>
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                  <persName>
                    <forename type="first">Dominic</forename>
                    <surname>Demand</surname>
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                    <forename type="first">Mirjam</forename>
                    <surname>Scheller</surname>
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                <idno type="issn">1027-5606</idno>
                <idno type="eissn">1607-7938</idno>
                <title level="j">Hydrology and Earth System Sciences</title>
                <imprint>
                  <publisher>European Geosciences Union</publisher>
                  <biblScope unit="volume">27</biblScope>
                  <biblScope unit="issue">2</biblScope>
                  <biblScope unit="pp">385-400</biblScope>
                  <date type="datePub">2023</date>
                  <date type="dateEpub">2023-01-19</date>
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              <p>Understanding groundwater recharge processes is important for sustainable water resource management. Experimental approaches to study recharge in karst areas often focus on analysing the aquifer response using a disintegration of its outlet signals, but only a few approaches directly investigate the recharge processes that occur at the surface of the system. Soil moisture measurements have a high potential to investigate water infiltration to deeper soil depth or epikarst with an easy and not too intrusive installation. They can yield long-term measurements with high temporal resolution. Using these advantages, we developed and tested a method to estimate recharge based on soil moisture measurements. The method consists of the extraction of linked events in rainfall, soil moisture, and discharge time series, as well as a subsequent fitting of the parameters of a simple drainage model to calculate karst recharge from soil moisture metrics of individual events. The fitted parameters could be interpreted in physically meaningful terms and were related to the properties of the karstic system. The model was tested and validated in a karst catchment located in southwest Germany with hourly precipitation, soil moisture, and discharge data of 8 years duration. The soil moisture measurements were distributed among grassland (n = 8) and woodland areas (n = 7) at 20 cm depth. A threshold of about 35 % (± 8 %) of volumetric water content was necessary to initiate effective infiltration. Soil moisture averaged during the wetting period of each event was the best metric for the prediction of recharge. The model performed reasonably well, estimating recharge during single rainfall events. It was also capable of simulating 88 % of the average annual recharge volume despite considerable differences in the performance between years. The event-based approach is potentially applicable to other karstic systems where soil moisture and precipitation measurements are available to predict karst groundwater recharge.</p>
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          <orgName>Albert-Ludwigs-Universität Freiburg = University of Freiburg</orgName>
          <date type="start">1820-01-01</date>
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              <addrLine>Georges-Köhler Allee 51 79110 Freiburg im Breisgau (Germany)</addrLine>
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          <orgName>Technical University of Dresden</orgName>
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              <addrLine>Avda. Cervantes, 2   29071 MÁLAGA</addrLine>
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