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  <front>
    <journal-meta><journal-id journal-id-type="publisher">HESS</journal-id><journal-title-group>
    <journal-title>Hydrology and Earth System Sciences</journal-title>
    <abbrev-journal-title abbrev-type="publisher">HESS</abbrev-journal-title><abbrev-journal-title abbrev-type="nlm-ta">Hydrol. Earth Syst. Sci.</abbrev-journal-title>
  </journal-title-group><issn pub-type="epub">1607-7938</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/hess-23-139-2019</article-id><title-group><article-title>Microbial community changes induced by Managed Aquifer Recharge activities: linking hydrogeological<?xmltex \hack{\break}?> and biological processes</article-title><alt-title>Microbial communities in MAR</alt-title>
      </title-group><?xmltex \runningtitle{Microbial communities in MAR}?><?xmltex \runningauthor{C. Barba et al.}?>
      <contrib-group>
        <contrib contrib-type="author" corresp="yes" rid="aff1 aff2">
          <name><surname>Barba</surname><given-names>Carme</given-names></name>
          <email>carme.barba@upc.edu</email>
        <ext-link>https://orcid.org/0000-0001-7513-3754</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1 aff2">
          <name><surname>Folch</surname><given-names>Albert</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff3">
          <name><surname>Gaju</surname><given-names>Núria</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1 aff2">
          <name><surname>Sanchez-Vila</surname><given-names>Xavier</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-1234-9897</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff3">
          <name><surname>Carrasquilla</surname><given-names>Marc</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff4">
          <name><surname>Grau-Martínez</surname><given-names>Alba</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff3">
          <name><surname>Martínez-Alonso</surname><given-names>Maira</given-names></name>
          
        </contrib>
        <aff id="aff1"><label>1</label><institution>Department of Civil and Environmental Engineering, Universitat Politècnica de Catalunya (UPC),<?xmltex \hack{\break}?> C/Jordi Girona 1–3, 08034 Barcelona, Spain</institution>
        </aff>
        <aff id="aff2"><label>2</label><institution>Associated unit: Hydrogeology Group (UPC-CSIC), Barcelona, Spain</institution>
        </aff>
        <aff id="aff3"><label>3</label><institution>Department of Genetics and Microbiology, Universitat Autònoma de Barcelona (UAB), 08193 Bellaterra, Spain</institution>
        </aff>
        <aff id="aff4"><label>4</label><institution>Grup de Mineralogia Aplicada i Geoquímica de Fluids, Departament de Mineralogia, Petrologia i Geologia Aplicada,
Facultat de Ciències de la Terra, Universitat de
Barcelona (UB), C/Martí i Franquès s/n, 08028 Barcelona, Spain</institution>
        </aff>
      </contrib-group>
      <author-notes><corresp id="corr1">Carme Barba (carme.barba@upc.edu)</corresp></author-notes><pub-date><day>11</day><month>January</month><year>2019</year></pub-date>
      
      <volume>23</volume>
      <issue>1</issue>
      <fpage>139</fpage><lpage>154</lpage>
      <history>
        <date date-type="received"><day>3</day><month>April</month><year>2018</year></date>
           <date date-type="rev-request"><day>17</day><month>April</month><year>2018</year></date>
           <date date-type="rev-recd"><day>13</day><month>December</month><year>2018</year></date>
           <date date-type="accepted"><day>14</day><month>December</month><year>2018</year></date>
      </history>
      <permissions>
        
        
      <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/articles/23/139/2019/hess-23-139-2019.html">This article is available from https://hess.copernicus.org/articles/23/139/2019/hess-23-139-2019.html</self-uri><self-uri xlink:href="https://hess.copernicus.org/articles/23/139/2019/hess-23-139-2019.pdf">The full text article is available as a PDF file from https://hess.copernicus.org/articles/23/139/2019/hess-23-139-2019.pdf</self-uri>
      <abstract>
    <p id="d1e159">Managed Aquifer Recharge (MAR) is a technique used worldwide to increase the
availability of water resources. We study how MAR modifies microbial
ecosystems and its implications for enhancing biodegradation processes to
eventually improve groundwater quality. We compare soil and groundwater
samples taken from a MAR facility located in NE Spain during recharge (with
the facility operating continuously for several months) and after 4 months
of no recharge. The study demonstrates a strong correlation between soil and
water microbial prints with respect to sampling location along the mapped
infiltration path. In particular, managed recharge practices disrupt
groundwater ecosystems by modifying diversity indices and the composition of
microbial communities, indicating that infiltration favors the growth of
certain populations. Analysis of the genetic profiles showed the presence of
nine different bacterial phyla in the facility, revealing high biological
diversity at the highest taxonomic range. In fact, the microbial population
patterns under recharge conditions agree with the intermediate disturbance
hypothesis (IDH). Moreover, DNA sequence analysis of excised denaturing gradient gel electrophoresis (DGGE) band patterns
revealed the existence of indicator species linked to MAR, most notably
<italic>Dehalogenimonas sp.</italic>, <italic>Nitrospira sp.</italic> and <italic>Vogesella sp.</italic>. Our real facility multidisciplinary study (hydrological, geochemical and
microbial), involving soil and groundwater samples, indicates that MAR is a
naturally based, passive and efficient technique with broad implications for
the biodegradation of pollutants dissolved in water.</p>
  </abstract>
    </article-meta>
  </front>
<body>
      

<sec id="Ch1.S1" sec-type="intro">
  <title>Introduction</title>
      <p id="d1e178">As the Intergovernmental Panel on Climate Change has stated for years,
climate change is affecting and will continue to affect the availability and
quality of freshwater resources, with severe consequences to humans and
ecosystems. In particular, the Mediterranean Basin is expected to become
warmer and drier <xref ref-type="bibr" rid="bib1.bibx5" id="paren.1"/>. Therefore, among other actions, claiming
a secure water supply should increase groundwater storage of quality water as
a strategic management tool in times of scarcity.</p>
      <p id="d1e184">Managed Aquifer Recharge (MAR) is a globally used, worldwide extended
technology based on refilling aquifers with water from different sources
(e.g., river, reclaimed or opportunity water). MAR facilities are usually
intended to recover groundwater levels or to become water reservoirs, but
other objectives can be targeted. It is quite common to take advantage of the
potential of soil as a biogeochemical reactor to enhance the quality of water
infiltrating the vadose zone, especially in surface replenishment systems
<xref ref-type="bibr" rid="bib1.bibx13 bib1.bibx39" id="paren.2"/>.</p>
      <?pagebreak page140?><p id="d1e190">The Llobregat River (Catalonia, NE Spain) is fed by about a hundred waste
water treatment plants. While nitrogen, phosphorous and organic matter (chemical oxygen demand, COD)
are eliminated below the legal limits before treated wastewater is discharged
to the river, emerging organic contaminants (EOCs) are not fully removed
<xref ref-type="bibr" rid="bib1.bibx32" id="paren.3"/>. Consequently, significant concentrations of many EOCs have
been detected in the Llobregat River <xref ref-type="bibr" rid="bib1.bibx33" id="paren.4"/> and its
associated groundwater bodies <xref ref-type="bibr" rid="bib1.bibx26" id="paren.5"/>.</p>
      <p id="d1e202">Biodegradation of EOCs strongly depends on redox conditions
<xref ref-type="bibr" rid="bib1.bibx3 bib1.bibx34" id="paren.6"/>. In this regard, it has been shown that MAR
is a feasible technique capable of partially degrading some of these
contaminants <xref ref-type="bibr" rid="bib1.bibx24 bib1.bibx37" id="paren.7"/>, particularly when
bioprocesses are enhanced <xref ref-type="bibr" rid="bib1.bibx17 bib1.bibx51" id="paren.8"/>.
Infiltration through the soil intrinsically leads to two main consequences in
groundwater recharge:
<list list-type="order"><list-item>
      <p id="d1e216">Development of different vertical and temporal redox zonations responding to
organic matter availability as electron acceptors are consumed
<xref ref-type="bibr" rid="bib1.bibx18" id="paren.9"/>.</p></list-item><list-item>
      <p id="d1e223">Development of microbial communities according to the flow paths. Fingering
below the surface of the recharge systems and preferential
flow paths in the saturated zone can create anaerobic microsites <xref ref-type="bibr" rid="bib1.bibx6" id="paren.10"><named-content content-type="pre">e.g.,</named-content></xref>  in which oxygen is consumed faster than it
can be diffused from oxic zones.</p></list-item></list></p>
      <p id="d1e232">Indeed, MAR implies groundwater quality modifications when compared to
natural flow conditions. This includes several parameters such as organic
matter, dissolved oxygen content, temperature, pH, electrical conductivity
and nutrients <xref ref-type="bibr" rid="bib1.bibx47 bib1.bibx59" id="paren.11"/>. Such disturbances have
ecological implications, as all these parameters affect the growth and
activity of microorganisms and the corresponding degradation of emerging
contaminants <xref ref-type="bibr" rid="bib1.bibx4 bib1.bibx46 bib1.bibx57" id="paren.12"/>.</p>
      <p id="d1e241">Microbial studies linked to MAR practices involve mostly laboratory
experiments <xref ref-type="bibr" rid="bib1.bibx2 bib1.bibx15 bib1.bibx29 bib1.bibx50" id="paren.13"/>. As for
microbial MAR field studies, most relevant research is limited to
well-injection systems <xref ref-type="bibr" rid="bib1.bibx16 bib1.bibx44 bib1.bibx59" id="paren.14"/> or riverbank
filtration conditions <xref ref-type="bibr" rid="bib1.bibx25" id="paren.15"/>. <xref ref-type="bibr" rid="bib1.bibx41" id="text.16"/> compared
results from a column experiment and soil samples in a MAR site in the US,
focusing on the microbial populations linked to pharmaceutical and personal
care products removal, and concluded that microbial composition and structure
of both systems were comparable. <xref ref-type="bibr" rid="bib1.bibx45" id="text.17"/> went one step further by
relating the relative abundance of functional genes involved in xenobiotic
pathways with attenuation of some trace organic chemicals and their
byproducts in a combination of laboratory experiments and a full-scale MAR
facility. However, to our knowledge, there are no microbial fingerprinting
studies of MAR surface infiltration basins that integrate results from
surface water, groundwater and soil samples and compare them in two
different operational periods.</p>
      <p id="d1e259">The main goal of this study is to determine how MAR activities induce changes
in the microbial communities in a real facility composed of a settling and
infiltration pond adjacent to the Llobregat River. We evaluate changes on
diversity indices and we incorporate results of the DNA sequence analysis of
excised denaturing gradient gel electrophoresis (DGGE) band patterns for samples taken from different environments and
locations within the site and under conditions of recharge and non-recharge.
Additionally, we link our results with ecological principles and potential
biogeochemical processes (i.e., pollutants degradation) occurring due to MAR
activities.</p>

      <?xmltex \floatpos{p}?><fig id="Ch1.F1" specific-use="star"><caption><p id="d1e264">Geographical location of the Llobregat MAR system and location of
the established transect. <bold>(a)</bold> Transect section with piezometers (P1
and P2 are projected) and displaying sampling depths (red diamonds).
<bold>(b)</bold> Blue line shows groundwater level in July 2014 (wet scenario –
recharge) and March 2015 (dry scenario – non-recharge).</p></caption>
        <?xmltex \igopts{width=455.244094pt}?><graphic xlink:href="https://hess.copernicus.org/articles/23/139/2019/hess-23-139-2019-f01.png"/>

      </fig>

</sec>
<sec id="Ch1.S2">
  <title>Material and methods</title>
<sec id="Ch1.S2.SS1">
  <title>The Llobregat MAR site</title>
      <p id="d1e290">The Llobregat MAR system is located 15 km inland from the Mediterranean Sea,
close to Barcelona city (Fig. 1). The aquifer thickness in the vicinity is
10–15 m, with alternating sands and gravels. Non-continuous fine-grained
sediments are widely present <xref ref-type="bibr" rid="bib1.bibx42" id="paren.18"/>. The distance from the
bottom of the pond to the water table oscillated from 9 m (July 2014) to
7 m (March 2015) in the period under study.</p>
      <p id="d1e296">Water entering is diverted from upstream of the river to a pre-sedimentation
basin. After 2–4 days of residence time, it is diverted to an infiltration
basin of 6500 m<inline-formula><mml:math id="M1" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msup></mml:math></inline-formula>. The infiltration capacity has been estimated at
1 m<inline-formula><mml:math id="M2" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msup></mml:math></inline-formula> m<inline-formula><mml:math id="M3" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> d<inline-formula><mml:math id="M4" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> on average, and the local transmissivity of
the aquifer is estimated as 14 000 m<inline-formula><mml:math id="M5" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msup></mml:math></inline-formula> d<inline-formula><mml:math id="M6" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> (unpublished).</p>
      <p id="d1e363">In 2011, a reactive barrier was installed at the bottom of the infiltration
basin to increase the organic load of the infiltration water, thus
promoting biological processes through the soil and the vadose zone. The
barrier was composed of organic compost (50 % in volume) mixed with sand
and gravel. Small amounts of clay and iron oxides were added to foster
adsorption and ion exchange. Previous studies demonstrated that the reactive
barrier enhanced the removal of some emergent contaminants, such as
sulfamethoxazole or caffeine <xref ref-type="bibr" rid="bib1.bibx56" id="paren.19"/>. More information about
the site and the performance of the reactive barrier can be found in
<xref ref-type="bibr" rid="bib1.bibx56" id="text.20"/>.</p>
      <p id="d1e372">There are six piezometers distributed in a 500 m transect across the study
area (Fig. 1). P1, P3, P2, P5 and P10 are fully screened. P8 is a multilevel
piezometer drilled at three different depths. Water from piezometer P1
represents background conditions (not affected by recharge).</p><?xmltex \hack{\newpage}?>
</sec>
<?pagebreak page142?><sec id="Ch1.S2.SS2">
  <title>Hydrochemistry sampling surveys</title>
      <p id="d1e382">Two recharge situations were compared to evaluate the effect of MAR on
groundwater chemical signature. After 6 months of continuous recharge
operation, a sampling campaign took place in July 2014 (wet campaign).
Samples were collected from surface water in both basins and in the existing
piezometers at different depths (from <inline-formula><mml:math id="M7" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">5</mml:mn></mml:mrow></mml:math></inline-formula> to 3 m a.s.l.; see diamonds in
Fig. 1). The second sampling campaign was performed in March 2015 after
recharge had been discontinued for 4 months. In this case, groundwater was
also sampled.</p>
      <p id="d1e395">Water was analyzed for cations, anions (<inline-formula><mml:math id="M8" display="inline"><mml:mrow class="chem"><mml:msup><mml:mi mathvariant="normal">Cl</mml:mi><mml:mo>-</mml:mo></mml:msup></mml:mrow></mml:math></inline-formula>, <inline-formula><mml:math id="M9" display="inline"><mml:mrow class="chem"><mml:msubsup><mml:mi mathvariant="normal">NO</mml:mi><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>,
<inline-formula><mml:math id="M10" display="inline"><mml:mrow class="chem"><mml:msubsup><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">4</mml:mn><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msubsup></mml:mrow></mml:math></inline-formula>, <inline-formula><mml:math id="M11" display="inline"><mml:mrow class="chem"><mml:msubsup><mml:mi mathvariant="normal">HCO</mml:mi><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>), dissolved organic carbon (DOC) and
total organic carbon (TOC). Analytical procedures
are widely described in the Supplement.</p>
      <p id="d1e451">In both campaigns, temperature and electrical-conductivity vertical profiles
were mapped along the transect from data obtained at 50 cm intervals
(MPS-D8, SEBA Hydrometrie).</p>
</sec>
<sec id="Ch1.S2.SS3">
  <title>Microbial community characterization</title>
      <p id="d1e460">Water samples were extracted from the pre-sedimentation and infiltration
basins at three locations (entrance, middle and end) during recharge
conditions (from now on, wet scenario). On the contrary, three soil samples were
extracted at the same locations in the infiltration basin under non-recharge
conditions (termed dry scenario). Soil samples were obtained from around 10
to 50 cm in depth. The sampling procedure for soil was done taking into
account <xref ref-type="bibr" rid="bib1.bibx31" id="text.21"/> recommendations, especially regarding the
variability of microbial communities along a field transect. Soil samples
were taken by means of cores, individually disassembled and kept in a sterile
bag. Groundwater samples were taken from <inline-formula><mml:math id="M12" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">5</mml:mn></mml:mrow></mml:math></inline-formula> to 3 m a.s.l. depending on
the piezometers (10 samples for wet scenario and 7 for dry), at the same
location as samples for the hydrochemical characterization. All soil and
groundwater samples were taken in duplicate, kept in sterile conditions and
preserved in the dark at <inline-formula><mml:math id="M13" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">4</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M14" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C until being taken to the laboratory for
molecular analyses.</p>
      <p id="d1e495">Protocols for molecular analyses of liquid and soil samples are thoroughly
described in the Supplement.</p>
      <p id="d1e498">Once the main microbial communities were characterized, three diversity
indices were calculated. The first one is richness <inline-formula><mml:math id="M15" display="inline"><mml:mrow><mml:mo>(</mml:mo><mml:mi>S</mml:mi><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula>, defined as the
proportional number of microbial species present in a sample, i.e., equal to
the total number of bands; the other two, Shannon <inline-formula><mml:math id="M16" display="inline"><mml:mrow><mml:mo>(</mml:mo><mml:mi>H</mml:mi><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula> and evenness <inline-formula><mml:math id="M17" display="inline"><mml:mrow><mml:mo>(</mml:mo><mml:mi>E</mml:mi><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula>,
were calculated for each sample as follows:

                <disp-formula specific-use="align" content-type="numbered"><mml:math id="M18" display="block"><mml:mtable displaystyle="true"><mml:mtr><mml:mtd><mml:mstyle displaystyle="true" class="stylechange"/></mml:mtd><mml:mtd><mml:mrow><mml:mstyle displaystyle="true" class="stylechange"/><mml:mi>H</mml:mi><mml:mo>=</mml:mo><mml:munderover><mml:mo movablelimits="false">∑</mml:mo><mml:mrow><mml:mi>i</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow><mml:mi>S</mml:mi></mml:munderover><mml:msub><mml:mi>p</mml:mi><mml:mi mathvariant="normal">i</mml:mi></mml:msub><mml:mi mathvariant="normal">ln</mml:mi><mml:mo>(</mml:mo><mml:msub><mml:mi>p</mml:mi><mml:mi mathvariant="normal">i</mml:mi></mml:msub><mml:mo>)</mml:mo><mml:mo>,</mml:mo></mml:mrow></mml:mtd></mml:mtr><mml:mlabeledtr id="Ch1.E1"><mml:mtd/><mml:mtd><mml:mstyle displaystyle="true" class="stylechange"/></mml:mtd><mml:mtd><mml:mrow><mml:mstyle displaystyle="true" class="stylechange"/><mml:mi>E</mml:mi><mml:mo>=</mml:mo><mml:mstyle displaystyle="true"><mml:mfrac style="display"><mml:mi>H</mml:mi><mml:mrow><mml:msub><mml:mi>H</mml:mi><mml:mi mathvariant="normal">max</mml:mi></mml:msub></mml:mrow></mml:mfrac></mml:mstyle><mml:mo>,</mml:mo></mml:mrow></mml:mtd></mml:mlabeledtr></mml:mtable></mml:math></disp-formula>

            where <inline-formula><mml:math id="M19" display="inline"><mml:mrow><mml:msub><mml:mi>H</mml:mi><mml:mi mathvariant="normal">max</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> equals <inline-formula><mml:math id="M20" display="inline"><mml:mrow><mml:mi mathvariant="normal">ln</mml:mi><mml:mi>S</mml:mi></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M21" display="inline"><mml:mrow><mml:msub><mml:mi>p</mml:mi><mml:mi mathvariant="normal">i</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula> is the relative
intensity of each band of the sample. Values reported correspond to the
average of the two replicas. The evenness index is proportional to the equitable
distribution of bands in the gel. Shannon is an entropy index, reaching
maximum <inline-formula><mml:math id="M22" display="inline"><mml:mrow><mml:mo>(</mml:mo><mml:msub><mml:mi>H</mml:mi><mml:mi mathvariant="normal">max</mml:mi></mml:msub><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula> for the most equally distributed band patterns
and with the higher value of richness.</p>
</sec>
<sec id="Ch1.S2.SS4">
  <title>Soil characterization</title>
      <p id="d1e660">To complement the soil microbial community's characterization, particle size
measurements of soil samples were taken according to the ASTM guidelines. The
soil was sampled in the pre-sedimentation basin and at the entrance, middle
and end of the infiltration basin. Soil sampling was performed close to the
location where samples were taken for microbial analyses.</p>

      <?xmltex \floatpos{p}?><fig id="Ch1.F2" specific-use="star"><caption><p id="d1e665">Temperature distribution at the local scale in
<bold>(a)</bold> July 2014 (wet) and <bold>(b)</bold> March 2015 (dry). Red diamonds
indicate sampling points for microbial and water analysis in each campaign.</p></caption>
          <?xmltex \igopts{width=398.338583pt}?><graphic xlink:href="https://hess.copernicus.org/articles/23/139/2019/hess-23-139-2019-f02.png"/>

        </fig>

      <?xmltex \floatpos{p}?><fig id="Ch1.F3" specific-use="star"><caption><p id="d1e682">Electrical-conductivity distribution at the local scale in
<bold>(a)</bold> July 2014 (wet) and <bold>(b)</bold> March 2015 (dry).</p></caption>
          <?xmltex \igopts{width=398.338583pt}?><graphic xlink:href="https://hess.copernicus.org/articles/23/139/2019/hess-23-139-2019-f03.png"/>

        </fig>

</sec>
</sec>
<sec id="Ch1.S3">
  <title>Results</title>
<sec id="Ch1.S3.SS1">
  <title>Microbial differences in groundwater linked to recharge conditions</title>
<sec id="Ch1.S3.SS1.SSS1">
  <title>Closing the conceptual flow model</title>
      <p id="d1e714">Understanding the flow pattern in MAR basins is essential to explain
microbial community dynamics. In this regard, 2-D transects of temperature
and conductivity alterations obtained at the time of the sampling campaigns
(Figs. 2a and 3a) based on vertical profiles indicate that (1) the vertical
flow gradient pushes the existing groundwater downwards and forms a shallow
front that travels approximately 120 m downstream, eventually mixing with
the background water; (2) the background water is mostly found near the
recharge pond and at the deepest sampling points below the pond.</p>
      <p id="d1e717">From this conceptual model, four main groups of groundwater can be defined
under recharge conditions:
<list list-type="bullet"><list-item>
      <p id="d1e722">Type I water represents the background environment of the aquifer, unaffected
by MAR activities. Water sampled in P1 is an example of this type.</p></list-item><list-item>
      <p id="d1e726">Type II water is the infiltrating one (best observed in P8 at both sampling
depths). It flows vertically through the vadose zone to the aquifer, creating
a small water mound that pushes down the Type I water.</p></list-item><list-item>
      <p id="d1e730">Type III water, characteristic of points P2(3), P5(2.3) and P5(<inline-formula><mml:math id="M23" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2.2</mml:mn></mml:mrow></mml:math></inline-formula>), is a
mixture between types I and II waters, with a high proportion of the latter.</p></list-item><list-item>
      <p id="d1e744">Type IV water is again a mixture, but with a lower proportion of Type II
water. It is present in piezometers P3(0.8), P3(<inline-formula><mml:math id="M24" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">4.2</mml:mn></mml:mrow></mml:math></inline-formula>), P2(<inline-formula><mml:math id="M25" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">5</mml:mn></mml:mrow></mml:math></inline-formula>) and
P10(<inline-formula><mml:math id="M26" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:math></inline-formula>).</p></list-item></list></p>
      <p id="d1e777">Apart from temperature and conductivity, major ion composition does not show
any significant trend related with groundwater zonation below the pond (see
Table S1 in the Supplement). The role of nitrate and DOC in microbial
community patterns is discussed further below.</p>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T1" specific-use="star"><caption><p id="d1e783">Summary of values of the Shannon, richness and evenness indices at the
Llobregat MAR site in different scenarios.</p></caption><oasis:table frame="topbot"><oasis:tgroup cols="9">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="left"/>
     <oasis:colspec colnum="3" colname="col3" align="left"/>
     <oasis:colspec colnum="4" colname="col4" align="right"/>
     <oasis:colspec colnum="5" colname="col5" align="right" colsep="1"/>
     <oasis:colspec colnum="6" colname="col6" align="right"/>
     <oasis:colspec colnum="7" colname="col7" align="right" colsep="1"/>
     <oasis:colspec colnum="8" colname="col8" align="right"/>
     <oasis:colspec colnum="9" colname="col9" align="right"/>
     <oasis:thead>
       <oasis:row>

         <oasis:entry rowsep="1" namest="col1" nameend="col2" morerows="1">Environment </oasis:entry>

         <oasis:entry colname="col3">Sampling location</oasis:entry>

         <oasis:entry rowsep="1" namest="col4" nameend="col5" align="center" colsep="1">Shannnon (SD)<inline-formula><mml:math id="M28" display="inline"><mml:msup><mml:mi/><mml:mo>*</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>

         <oasis:entry rowsep="1" namest="col6" nameend="col7" align="center" colsep="1">Richness (SD)<inline-formula><mml:math id="M29" display="inline"><mml:msup><mml:mi/><mml:mo>*</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>

         <oasis:entry rowsep="1" namest="col8" nameend="col9" align="center">E (SD)<inline-formula><mml:math id="M30" display="inline"><mml:msup><mml:mi/><mml:mo>*</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>

       </oasis:row>
       <oasis:row rowsep="1">

         <oasis:entry colname="col3">(<bold>depth</bold>, m a.s.l.)</oasis:entry>

         <oasis:entry colname="col4">Wet</oasis:entry>

         <oasis:entry colname="col5">Dry</oasis:entry>

         <oasis:entry colname="col6">Wet</oasis:entry>

         <oasis:entry colname="col7">Dry</oasis:entry>

         <oasis:entry colname="col8">Wet</oasis:entry>

         <oasis:entry colname="col9">Dry</oasis:entry>

       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>

         <oasis:entry colname="col1"/>

         <oasis:entry rowsep="1" colname="col2">T.I</oasis:entry>

         <oasis:entry rowsep="1" colname="col3">P1(<inline-formula><mml:math id="M31" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="bold">0.6</mml:mn></mml:mrow></mml:math></inline-formula>)</oasis:entry>

         <oasis:entry rowsep="1" colname="col4"><inline-formula><mml:math id="M32" display="inline"><mml:mn mathvariant="normal">2.57</mml:mn></mml:math></inline-formula> <italic>(0.04)</italic></oasis:entry>

         <oasis:entry rowsep="1" colname="col5"><inline-formula><mml:math id="M33" display="inline"><mml:mn mathvariant="normal">2.73</mml:mn></mml:math></inline-formula></oasis:entry>

         <oasis:entry rowsep="1" colname="col6"><inline-formula><mml:math id="M34" display="inline"><mml:mn mathvariant="normal">22</mml:mn></mml:math></inline-formula> <italic>(4.1)</italic></oasis:entry>

         <oasis:entry rowsep="1" colname="col7"><inline-formula><mml:math id="M35" display="inline"><mml:mn mathvariant="normal">19</mml:mn></mml:math></inline-formula></oasis:entry>

         <oasis:entry rowsep="1" colname="col8"><inline-formula><mml:math id="M36" display="inline"><mml:mn mathvariant="normal">0.61</mml:mn></mml:math></inline-formula> <italic>(0.01)</italic></oasis:entry>

         <oasis:entry rowsep="1" colname="col9"><inline-formula><mml:math id="M37" display="inline"><mml:mn mathvariant="normal">0.64</mml:mn></mml:math></inline-formula></oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col1" morerows="1">Groundwater</oasis:entry>

         <oasis:entry rowsep="1" colname="col2" morerows="1">T.II</oasis:entry>

         <oasis:entry colname="col3">P8(<inline-formula><mml:math id="M38" display="inline"><mml:mn mathvariant="bold">1</mml:mn></mml:math></inline-formula>)</oasis:entry>

         <oasis:entry colname="col4"><inline-formula><mml:math id="M39" display="inline"><mml:mn mathvariant="normal">1.43</mml:mn></mml:math></inline-formula> <italic>(0.05)</italic></oasis:entry>

         <oasis:entry colname="col5"><inline-formula><mml:math id="M40" display="inline"><mml:mn mathvariant="normal">1.73</mml:mn></mml:math></inline-formula></oasis:entry>

         <oasis:entry colname="col6"><inline-formula><mml:math id="M41" display="inline"><mml:mn mathvariant="normal">10</mml:mn></mml:math></inline-formula> <italic>(2.0)</italic></oasis:entry>

         <oasis:entry colname="col7"><inline-formula><mml:math id="M42" display="inline"><mml:mn mathvariant="normal">11</mml:mn></mml:math></inline-formula></oasis:entry>

         <oasis:entry colname="col8"><inline-formula><mml:math id="M43" display="inline"><mml:mn mathvariant="normal">0.34</mml:mn></mml:math></inline-formula> <italic>(0.01)</italic></oasis:entry>

         <oasis:entry colname="col9"><inline-formula><mml:math id="M44" display="inline"><mml:mn mathvariant="normal">0.41</mml:mn></mml:math></inline-formula></oasis:entry>

       </oasis:row>
       <oasis:row rowsep="1">

         <oasis:entry colname="col3">P8(<inline-formula><mml:math id="M45" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="bold">3</mml:mn></mml:mrow></mml:math></inline-formula>)</oasis:entry>

         <oasis:entry colname="col4"><inline-formula><mml:math id="M46" display="inline"><mml:mn mathvariant="normal">1.69</mml:mn></mml:math></inline-formula> <italic>(0.20)</italic></oasis:entry>

         <oasis:entry colname="col5"><inline-formula><mml:math id="M47" display="inline"><mml:mn mathvariant="normal">2.03</mml:mn></mml:math></inline-formula> <italic>(0.14)</italic></oasis:entry>

         <oasis:entry colname="col6"><inline-formula><mml:math id="M48" display="inline"><mml:mn mathvariant="normal">11</mml:mn></mml:math></inline-formula></oasis:entry>

         <oasis:entry colname="col7"><inline-formula><mml:math id="M49" display="inline"><mml:mn mathvariant="normal">10</mml:mn></mml:math></inline-formula> <italic>(2.0)</italic></oasis:entry>

         <oasis:entry colname="col8"><inline-formula><mml:math id="M50" display="inline"><mml:mn mathvariant="normal">0.40</mml:mn></mml:math></inline-formula> <italic>(0.05)</italic></oasis:entry>

         <oasis:entry colname="col9"><inline-formula><mml:math id="M51" display="inline"><mml:mn mathvariant="normal">0.48</mml:mn></mml:math></inline-formula> <italic>(0.03)</italic></oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col1"/>

         <oasis:entry rowsep="1" colname="col2" morerows="3">T.III</oasis:entry>

         <oasis:entry colname="col3">P2(<inline-formula><mml:math id="M52" display="inline"><mml:mn mathvariant="bold">3</mml:mn></mml:math></inline-formula>)</oasis:entry>

         <oasis:entry colname="col4"><inline-formula><mml:math id="M53" display="inline"><mml:mn mathvariant="normal">2.29</mml:mn></mml:math></inline-formula> <italic>(0.13)</italic></oasis:entry>

         <oasis:entry colname="col5"/>

         <oasis:entry colname="col6"><inline-formula><mml:math id="M54" display="inline"><mml:mn mathvariant="normal">18.5</mml:mn></mml:math></inline-formula> <italic>(7.2)</italic></oasis:entry>

         <oasis:entry colname="col7"/>

         <oasis:entry colname="col8"><inline-formula><mml:math id="M55" display="inline"><mml:mn mathvariant="normal">0.54</mml:mn></mml:math></inline-formula> <italic>(0.03)</italic></oasis:entry>

         <oasis:entry colname="col9"/>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col1"/>

         <oasis:entry colname="col3">P2(<inline-formula><mml:math id="M56" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="bold">2</mml:mn></mml:mrow></mml:math></inline-formula>)</oasis:entry>

         <oasis:entry colname="col4"/>

         <oasis:entry colname="col5"><inline-formula><mml:math id="M57" display="inline"><mml:mn mathvariant="normal">2.67</mml:mn></mml:math></inline-formula> <italic>(0.13)</italic></oasis:entry>

         <oasis:entry colname="col6"/>

         <oasis:entry colname="col7"><inline-formula><mml:math id="M58" display="inline"><mml:mn mathvariant="normal">18</mml:mn></mml:math></inline-formula> <italic>(2.0)</italic></oasis:entry>

         <oasis:entry colname="col8"/>

         <oasis:entry colname="col9"><inline-formula><mml:math id="M59" display="inline"><mml:mn mathvariant="normal">0.63</mml:mn></mml:math></inline-formula><italic> (0.03)</italic></oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col1"/>

         <oasis:entry colname="col3">P5(<inline-formula><mml:math id="M60" display="inline"><mml:mn mathvariant="bold">2.3</mml:mn></mml:math></inline-formula>)</oasis:entry>

         <oasis:entry colname="col4"><inline-formula><mml:math id="M61" display="inline"><mml:mn mathvariant="normal">1.91</mml:mn></mml:math></inline-formula> <italic>(0.01)</italic></oasis:entry>

         <oasis:entry colname="col5"><inline-formula><mml:math id="M62" display="inline"><mml:mn mathvariant="normal">2.41</mml:mn></mml:math></inline-formula></oasis:entry>

         <oasis:entry colname="col6"><inline-formula><mml:math id="M63" display="inline"><mml:mn mathvariant="normal">14.5</mml:mn></mml:math></inline-formula> <italic>(1.0)</italic></oasis:entry>

         <oasis:entry colname="col7"><inline-formula><mml:math id="M64" display="inline"><mml:mn mathvariant="normal">14</mml:mn></mml:math></inline-formula></oasis:entry>

         <oasis:entry colname="col8"><inline-formula><mml:math id="M65" display="inline"><mml:mn mathvariant="normal">0.45</mml:mn></mml:math></inline-formula> <inline-formula><mml:math id="M66" display="inline"><mml:mrow><mml:mo>(</mml:mo><mml:mn mathvariant="italic">1</mml:mn><mml:mo>×</mml:mo><mml:msup><mml:mn mathvariant="italic">10</mml:mn><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="italic">3</mml:mn></mml:mrow></mml:msup><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula></oasis:entry>

         <oasis:entry colname="col9"><inline-formula><mml:math id="M67" display="inline"><mml:mn mathvariant="normal">0.56</mml:mn></mml:math></inline-formula></oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col1"/>

         <oasis:entry rowsep="1" colname="col3">P5(<inline-formula><mml:math id="M68" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="bold">2.2</mml:mn></mml:mrow></mml:math></inline-formula>)</oasis:entry>

         <oasis:entry rowsep="1" colname="col4"><inline-formula><mml:math id="M69" display="inline"><mml:mn mathvariant="normal">2.22</mml:mn></mml:math></inline-formula> <italic>(0.01)</italic></oasis:entry>

         <oasis:entry rowsep="1" colname="col5"/>

         <oasis:entry rowsep="1" colname="col6"><inline-formula><mml:math id="M70" display="inline"><mml:mn mathvariant="normal">12.5</mml:mn></mml:math></inline-formula> <italic>(1.0)</italic></oasis:entry>

         <oasis:entry rowsep="1" colname="col7"/>

         <oasis:entry rowsep="1" colname="col8"><inline-formula><mml:math id="M71" display="inline"><mml:mn mathvariant="normal">0.52</mml:mn></mml:math></inline-formula> <inline-formula><mml:math id="M72" display="inline"><mml:mrow><mml:mo>(</mml:mo><mml:mn mathvariant="italic">2</mml:mn><mml:mo>×</mml:mo><mml:msup><mml:mn mathvariant="italic">10</mml:mn><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="italic">3</mml:mn></mml:mrow></mml:msup><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula></oasis:entry>

         <oasis:entry rowsep="1" colname="col9"/>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col1"/>

         <oasis:entry rowsep="1" colname="col2" morerows="3">T.IV</oasis:entry>

         <oasis:entry colname="col3">P3(<inline-formula><mml:math id="M73" display="inline"><mml:mn mathvariant="bold">0.8</mml:mn></mml:math></inline-formula>)</oasis:entry>

         <oasis:entry colname="col4"><inline-formula><mml:math id="M74" display="inline"><mml:mn mathvariant="normal">2.65</mml:mn></mml:math></inline-formula> <italic>(0.09)</italic></oasis:entry>

         <oasis:entry colname="col5"><inline-formula><mml:math id="M75" display="inline"><mml:mn mathvariant="normal">2.01</mml:mn></mml:math></inline-formula> <italic>(0.28)</italic></oasis:entry>

         <oasis:entry colname="col6"><inline-formula><mml:math id="M76" display="inline"><mml:mn mathvariant="normal">21</mml:mn></mml:math></inline-formula></oasis:entry>

         <oasis:entry colname="col7"><inline-formula><mml:math id="M77" display="inline"><mml:mn mathvariant="normal">10.5</mml:mn></mml:math></inline-formula> <italic>(3.07)</italic></oasis:entry>

         <oasis:entry colname="col8"><inline-formula><mml:math id="M78" display="inline"><mml:mn mathvariant="normal">0.63</mml:mn></mml:math></inline-formula> <italic>(0.02)</italic></oasis:entry>

         <oasis:entry colname="col9"><inline-formula><mml:math id="M79" display="inline"><mml:mn mathvariant="normal">0.48</mml:mn></mml:math></inline-formula> <italic>(0.07)</italic></oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col1"/>

         <oasis:entry colname="col3">P3(<inline-formula><mml:math id="M80" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="bold">4.2</mml:mn></mml:mrow></mml:math></inline-formula>)</oasis:entry>

         <oasis:entry colname="col4"><inline-formula><mml:math id="M81" display="inline"><mml:mn mathvariant="normal">2.65</mml:mn></mml:math></inline-formula> <italic>(0.13)</italic></oasis:entry>

         <oasis:entry colname="col5"/>

         <oasis:entry colname="col6"><inline-formula><mml:math id="M82" display="inline"><mml:mn mathvariant="normal">20</mml:mn></mml:math></inline-formula></oasis:entry>

         <oasis:entry colname="col7"/>

         <oasis:entry colname="col8"><inline-formula><mml:math id="M83" display="inline"><mml:mn mathvariant="normal">0.63</mml:mn></mml:math></inline-formula> <italic>(0.03)</italic></oasis:entry>

         <oasis:entry colname="col9"/>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col1"/>

         <oasis:entry colname="col3">P2(<inline-formula><mml:math id="M84" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="bold">5</mml:mn></mml:mrow></mml:math></inline-formula>)</oasis:entry>

         <oasis:entry colname="col4"><inline-formula><mml:math id="M85" display="inline"><mml:mn mathvariant="normal">2.80</mml:mn></mml:math></inline-formula> <italic>(0.12)</italic></oasis:entry>

         <oasis:entry colname="col5"/>

         <oasis:entry colname="col6"><inline-formula><mml:math id="M86" display="inline"><mml:mn mathvariant="normal">23</mml:mn></mml:math></inline-formula> <italic>(4.1)</italic></oasis:entry>

         <oasis:entry colname="col7"/>

         <oasis:entry colname="col8"><inline-formula><mml:math id="M87" display="inline"><mml:mn mathvariant="normal">0.66</mml:mn></mml:math></inline-formula> <italic>(0.12)</italic></oasis:entry>

         <oasis:entry colname="col9"/>

       </oasis:row>
       <oasis:row rowsep="1">

         <oasis:entry colname="col1"/>

         <oasis:entry colname="col3">P10(<inline-formula><mml:math id="M88" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="bold">1</mml:mn></mml:mrow></mml:math></inline-formula>)</oasis:entry>

         <oasis:entry colname="col4"><inline-formula><mml:math id="M89" display="inline"><mml:mn mathvariant="normal">2.51</mml:mn></mml:math></inline-formula> <italic>(0.20)</italic></oasis:entry>

         <oasis:entry colname="col5"><inline-formula><mml:math id="M90" display="inline"><mml:mn mathvariant="normal">2.49</mml:mn></mml:math></inline-formula> <italic>(0.09)</italic></oasis:entry>

         <oasis:entry colname="col6"><inline-formula><mml:math id="M91" display="inline"><mml:mn mathvariant="normal">17</mml:mn></mml:math></inline-formula></oasis:entry>

         <oasis:entry colname="col7"><inline-formula><mml:math id="M92" display="inline"><mml:mn mathvariant="normal">16</mml:mn></mml:math></inline-formula> <italic>(4.1)</italic></oasis:entry>

         <oasis:entry colname="col8"><inline-formula><mml:math id="M93" display="inline"><mml:mn mathvariant="normal">0.59</mml:mn></mml:math></inline-formula> <italic>(0.01)</italic></oasis:entry>

         <oasis:entry colname="col9"><inline-formula><mml:math id="M94" display="inline"><mml:mn mathvariant="normal">0.59</mml:mn></mml:math></inline-formula> <italic>(0.02)</italic></oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry rowsep="1" namest="col1" nameend="col2" morerows="3">Water of basins </oasis:entry>

         <oasis:entry colname="col3">Pre-sedimentation</oasis:entry>

         <oasis:entry colname="col4"><inline-formula><mml:math id="M95" display="inline"><mml:mn mathvariant="normal">2.93</mml:mn></mml:math></inline-formula> <italic>(0.28)</italic></oasis:entry>

         <oasis:entry colname="col5"/>

         <oasis:entry colname="col6"><inline-formula><mml:math id="M96" display="inline"><mml:mn mathvariant="normal">29</mml:mn></mml:math></inline-formula> <italic>(14.3)</italic></oasis:entry>

         <oasis:entry colname="col7"/>

         <oasis:entry colname="col8"><inline-formula><mml:math id="M97" display="inline"><mml:mn mathvariant="normal">0.69</mml:mn></mml:math></inline-formula> <italic>(0.07)</italic></oasis:entry>

         <oasis:entry colname="col9"/>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col3">Infiltration entrance</oasis:entry>

         <oasis:entry colname="col4"><inline-formula><mml:math id="M98" display="inline"><mml:mn mathvariant="normal">2.78</mml:mn></mml:math></inline-formula> <italic>(0.53)</italic></oasis:entry>

         <oasis:entry colname="col5"/>

         <oasis:entry colname="col6"><inline-formula><mml:math id="M99" display="inline"><mml:mn mathvariant="normal">28.5</mml:mn></mml:math></inline-formula> <italic>(17.4)</italic></oasis:entry>

         <oasis:entry colname="col7"/>

         <oasis:entry colname="col8"><inline-formula><mml:math id="M100" display="inline"><mml:mn mathvariant="normal">0.66</mml:mn></mml:math></inline-formula> <italic>(0.12)</italic></oasis:entry>

         <oasis:entry colname="col9"/>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col3">Infiltration midfield</oasis:entry>

         <oasis:entry colname="col4"><inline-formula><mml:math id="M101" display="inline"><mml:mn mathvariant="normal">2.66</mml:mn></mml:math></inline-formula> <italic>(0.14)</italic></oasis:entry>

         <oasis:entry colname="col5"/>

         <oasis:entry colname="col6"><inline-formula><mml:math id="M102" display="inline"><mml:mn mathvariant="normal">25.5</mml:mn></mml:math></inline-formula> <italic>(3.1)</italic></oasis:entry>

         <oasis:entry colname="col7"/>

         <oasis:entry colname="col8"><inline-formula><mml:math id="M103" display="inline"><mml:mn mathvariant="normal">0.63</mml:mn></mml:math></inline-formula> <italic>(0.03)</italic></oasis:entry>

         <oasis:entry colname="col9"/>

       </oasis:row>
       <oasis:row rowsep="1">

         <oasis:entry colname="col3">Infiltration end</oasis:entry>

         <oasis:entry colname="col4"><inline-formula><mml:math id="M104" display="inline"><mml:mn mathvariant="normal">2.58</mml:mn></mml:math></inline-formula> <italic>(0.08)</italic></oasis:entry>

         <oasis:entry colname="col5"/>

         <oasis:entry colname="col6"><inline-formula><mml:math id="M105" display="inline"><mml:mn mathvariant="normal">24</mml:mn></mml:math></inline-formula> <italic>(2.0)</italic></oasis:entry>

         <oasis:entry colname="col7"/>

         <oasis:entry colname="col8"><inline-formula><mml:math id="M106" display="inline"><mml:mn mathvariant="normal">0.61</mml:mn></mml:math></inline-formula> <italic>(0.02)</italic></oasis:entry>

         <oasis:entry colname="col9"/>

       </oasis:row>
       <oasis:row>

         <oasis:entry namest="col1" nameend="col2" morerows="3">Soil of basins </oasis:entry>

         <oasis:entry colname="col3">Pre-sedimentation</oasis:entry>

         <oasis:entry colname="col4"><inline-formula><mml:math id="M107" display="inline"><mml:mn mathvariant="normal">2.89</mml:mn></mml:math></inline-formula> <italic>(0.16)</italic></oasis:entry>

         <oasis:entry colname="col5"/>

         <oasis:entry colname="col6"><inline-formula><mml:math id="M108" display="inline"><mml:mn mathvariant="normal">25.5</mml:mn></mml:math></inline-formula> <italic>(7.2)</italic></oasis:entry>

         <oasis:entry colname="col7"/>

         <oasis:entry colname="col8"><inline-formula><mml:math id="M109" display="inline"><mml:mn mathvariant="normal">0.68</mml:mn></mml:math></inline-formula> <italic>(0.04)</italic></oasis:entry>

         <oasis:entry colname="col9"/>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col3">Infiltration entrance</oasis:entry>

         <oasis:entry colname="col4"><inline-formula><mml:math id="M110" display="inline"><mml:mn mathvariant="normal">3.22</mml:mn></mml:math></inline-formula> <italic>(0.09)</italic></oasis:entry>

         <oasis:entry colname="col5"><inline-formula><mml:math id="M111" display="inline"><mml:mn mathvariant="normal">2.93</mml:mn></mml:math></inline-formula> <italic>(0.21)</italic></oasis:entry>

         <oasis:entry colname="col6"><inline-formula><mml:math id="M112" display="inline"><mml:mn mathvariant="normal">35.5</mml:mn></mml:math></inline-formula> <italic>(1.0)</italic></oasis:entry>

         <oasis:entry colname="col7"><inline-formula><mml:math id="M113" display="inline"><mml:mn mathvariant="normal">25</mml:mn></mml:math></inline-formula> <italic>(7.6)</italic></oasis:entry>

         <oasis:entry colname="col8"><inline-formula><mml:math id="M114" display="inline"><mml:mn mathvariant="normal">0.76</mml:mn></mml:math></inline-formula> <italic>(0.02)</italic></oasis:entry>

         <oasis:entry colname="col9"><inline-formula><mml:math id="M115" display="inline"><mml:mn mathvariant="normal">0.69</mml:mn></mml:math></inline-formula> <italic>(0.08)</italic></oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col3">Infiltration midfield</oasis:entry>

         <oasis:entry colname="col4"><inline-formula><mml:math id="M116" display="inline"><mml:mn mathvariant="normal">3.36</mml:mn></mml:math></inline-formula> <italic>(0.14)</italic></oasis:entry>

         <oasis:entry colname="col5"><inline-formula><mml:math id="M117" display="inline"><mml:mn mathvariant="normal">2.90</mml:mn></mml:math></inline-formula> <italic>(0.05)</italic></oasis:entry>

         <oasis:entry colname="col6"><inline-formula><mml:math id="M118" display="inline"><mml:mn mathvariant="normal">30.5</mml:mn></mml:math></inline-formula> <italic>(3.1)</italic></oasis:entry>

         <oasis:entry colname="col7"><inline-formula><mml:math id="M119" display="inline"><mml:mn mathvariant="normal">21</mml:mn></mml:math></inline-formula></oasis:entry>

         <oasis:entry colname="col8"><inline-formula><mml:math id="M120" display="inline"><mml:mn mathvariant="normal">0.79</mml:mn></mml:math></inline-formula> <italic>(0.03)</italic></oasis:entry>

         <oasis:entry colname="col9"><inline-formula><mml:math id="M121" display="inline"><mml:mn mathvariant="normal">0.68</mml:mn></mml:math></inline-formula> <italic>(0.01)</italic></oasis:entry>

       </oasis:row>
       <oasis:row>

         <oasis:entry colname="col3">Infiltration end</oasis:entry>

         <oasis:entry colname="col4"><inline-formula><mml:math id="M122" display="inline"><mml:mn mathvariant="normal">3.29</mml:mn></mml:math></inline-formula> <italic>(0.05)</italic></oasis:entry>

         <oasis:entry colname="col5"><inline-formula><mml:math id="M123" display="inline"><mml:mn mathvariant="normal">2.40</mml:mn></mml:math></inline-formula> <italic>(0.07)</italic></oasis:entry>

         <oasis:entry colname="col6"><inline-formula><mml:math id="M124" display="inline"><mml:mn mathvariant="normal">34</mml:mn></mml:math></inline-formula> <italic>(2.0)</italic></oasis:entry>

         <oasis:entry colname="col7"><inline-formula><mml:math id="M125" display="inline"><mml:mn mathvariant="normal">16</mml:mn></mml:math></inline-formula></oasis:entry>

         <oasis:entry colname="col8"><inline-formula><mml:math id="M126" display="inline"><mml:mn mathvariant="normal">0.78</mml:mn></mml:math></inline-formula> <italic>(0.01)</italic></oasis:entry>

         <oasis:entry colname="col9"><inline-formula><mml:math id="M127" display="inline"><mml:mn mathvariant="normal">0.57</mml:mn></mml:math></inline-formula> <italic>(0.02)</italic></oasis:entry>

       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup></oasis:table><table-wrap-foot><p id="d1e786"><inline-formula><mml:math id="M27" display="inline"><mml:msup><mml:mi/><mml:mo>*</mml:mo></mml:msup></mml:math></inline-formula> Numbers in parenthesis after each index value indicate
standard deviation, not reported whenever one replica was damaged.</p></table-wrap-foot></table-wrap>

</sec>
<?pagebreak page145?><sec id="Ch1.S3.SS1.SSS2">
  <title>Clustering groundwater microbial communities according to presence and abundance</title>
      <p id="d1e2153">To characterize differences in microbial communities due to recharge,
groundwater samples were subjected to molecular analysis. Post-processing of
DGGE gels allowed for non-metric multidimensional scaling (NMDS), showing
similarities among band patterns (Fig. 4) and strong clustering of microbial
communities. Samples from both scenarios were completely separated; blue
squares (dry) and triangles (wet) represent groundwater samples, and are
clearly clustered in top and bottom halves of the plot, respectively.
Moreover, samples from the wet scenario grouped according to water types.
Types I and II are displayed on opposite sides; types III and IV (mixed) are
displayed in between. The two green triangles in the center of the plot
correspond to groundwater samples from P10, which are samples that are slightly affected by
recharge. These Type IV samples remain among different sets of groundwater
samples from the wet and dry scenario. It seems that the theory of P10 as a
location with a high proportion of mixing is also valid for the microbial
community composition behavior.</p>

      <?xmltex \floatpos{p}?><fig id="Ch1.F4" specific-use="star"><caption><p id="d1e2158">Non-metric multidimensional scaling clustering for all groundwater
samples. Blue squares and triangles represent samples in dry and wet
scenarios, respectively. Colors in triangles represent water types. Black
circles correspond to band migration numbers in DGGE gels that were sequenced
(phylogenetic affiliation corresponding to each black circle). Non-sequenced
bands are also portrayed (empty circles).</p></caption>
            <?xmltex \igopts{width=469.470472pt}?><graphic xlink:href="https://hess.copernicus.org/articles/23/139/2019/hess-23-139-2019-f04.png"/>

          </fig>

      <?xmltex \floatpos{t}?><fig id="Ch1.F5" specific-use="star"><caption><p id="d1e2169">DGGE band patterns of bacterial 16S rRNA gene fragments and UPGMA
cluster analysis for fingerprints obtained from wet (July 2014)
<bold>(a)</bold> and dry (March 2015) <bold>(b)</bold> periods. The bar indicates 9 %
divergence. Each sample is defined by a code indicating piezometer number and
sampling depth (see Table 1). Black triangles indicate the position of bands
recovered and sequenced, and the numbers correspond to their phylogenetic
affiliation (see Table S2).</p></caption>
            <?xmltex \igopts{width=398.338583pt}?><graphic xlink:href="https://hess.copernicus.org/articles/23/139/2019/hess-23-139-2019-f05.png"/>

          </fig>

      <p id="d1e2185">Discrete bands are also portrayed (circles), allowing linkage of the bands'
contribution to sample assemblages. Filled circles report the class and genus
of the sequenced bands, whereas empty circles symbolize non-sequenced bands.</p>
      <p id="d1e2188">Figure 5 shows DGGE profiles and UPGMA clustering analysis of groundwater
samples. The genetic fingerprints revealed high dissimilarities in the
bacterial assemblage of about 70 % and 80 % during the active recharge
period and the dry campaign, respectively (Fig. 5). Moreover, most replicas
grouped together, indicating sampling quality. Under active recharge (wet)
conditions (Fig. 5a), the dendrogram reproduces the water types
postulated by the conceptual flow model quite well: in the first group, we can include
four out of the five samples that were strongly influenced by recharge
(P5(<inline-formula><mml:math id="M128" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2.2</mml:mn></mml:mrow></mml:math></inline-formula>), P5(2.3), P8(1) and P8(<inline-formula><mml:math id="M129" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:math></inline-formula>)), while in the second group, P2(3),
P3(<inline-formula><mml:math id="M130" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">4.2</mml:mn></mml:mrow></mml:math></inline-formula>) and P3(0.8) clustered together with P1 (not affected by recharge).
In the dry campaign (Fig. 5b), although no infiltration occurred, P8 appears
separated from the other piezometers, indicating the still marked influence
of the water infiltrated during the wet period, which occurred over 4 months earlier.</p>
</sec>
<sec id="Ch1.S3.SS1.SSS3">
  <title>Variations in microbial diversity indices in groundwater</title>
      <?pagebreak page147?><p id="d1e2227">The structure and processes of ecosystems change when a disturbance occurs
<xref ref-type="bibr" rid="bib1.bibx21" id="paren.22"/>. Such changes in microbial communities have been quantified
and described by means of diversity indices (Table 1). Such indices, grouped
according to water types during wet conditions, were ordered along an
imaginary line from low to highly perturbed as a consequence of water
infiltration (Fig. 6). The lowest diversity indices were obtained for the
recharging water (Type II), indicating low species richness and a highly
dissimilar proportion. In contrast, Type IV water, only slightly affected by
water infiltration, displayed higher Shannon and evenness indices, similar to
Type I (unaffected by recharge).</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F6"><caption><p id="d1e2235">Average of Shannon indices in piezometer samples under wet
conditions. Standard deviation is shown in error bars. Horizontal axis
reflects the degree of perturbation of original groundwater due to recharge.</p></caption>
            <?xmltex \igopts{width=241.848425pt}?><graphic xlink:href="https://hess.copernicus.org/articles/23/139/2019/hess-23-139-2019-f06.png"/>

          </fig>

</sec>
<sec id="Ch1.S3.SS1.SSS4">
  <title>Role of MAR activities for the microbial community structure</title>
      <p id="d1e2250">Prominent bands were recovered from the DGGE gels (Fig. 5) and sequenced.
Table S2 shows the sequenced bands, their similarity values compared to the
closest related GenBank sequences and their phylogenetic affiliations.
Overall, sequences fell into nine different bacterial phyla and eleven
classes: Proteobacteria (Alphaproteobacteria, Betaproteobacteria and
Gammaproteobacteria), Cyanobacteria, Chloroflexi (Dehalococcoidia), Chlorobi
(Chlorobia), Nitrospirae (Nitrospira), Acidobacteria, Actinobacteria,
Firmicutes (Bacilli) and Bacteroidetes (Cytophagia) (Fig. 7). The group
designated as “others” includes unclassified and non-sequenced fine bands.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F7" specific-use="star"><caption><p id="d1e2255">Bacterial community structure of groundwater samples. Class relative
abundances calculated for wet <bold>(a)</bold> and dry <bold>(b)</bold> scenarios.</p></caption>
            <?xmltex \igopts{width=341.433071pt}?><graphic xlink:href="https://hess.copernicus.org/articles/23/139/2019/hess-23-139-2019-f07.png"/>

          </fig>

      <?pagebreak page148?><p id="d1e2270">The two main classes displaying the largest differences between the two
scenarios are Betaproteobacteria and Dehalococcoidia, which were favored
under recharge conditions. In particular, Dehalococcoidia is present in
moderately and weakly influenced waters, and it is absent from the highly
recharge-influenced groundwater (P8(1) and P8(<inline-formula><mml:math id="M131" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">3</mml:mn></mml:mrow></mml:math></inline-formula>)). This phylotype was
identified at the genus level as <italic>Dehalogenimonas sp.</italic> (Table S2).
Similar behavior was found in the Nitrospira class, appearing in
weakly influenced groundwater in the wet scenario.</p>
      <p id="d1e2286">Patterns in the structure of microbial populations correlated with water
types. For Type I, differences in the bacterial assemblage between both
campaigns were attributed to seasonal changes (Table S1). Dehalococcoidia and
Chlorobia were only detected in the wet scenario, while Cytophagia and
Nitrospira could only be detected under dry conditions.</p>
      <p id="d1e2290">During the active recharge period and for Type IV water, Dehalococcoidia was
found in three out of four sampling points and was the most abundant
phylotype. For Type III water, significant differences were observed among in
the samples analyzed. Populations with the highest relative abundance in P5(2.3) were Betaproteobacteria and Bacilli. The former was also prominent in
P5(<inline-formula><mml:math id="M132" display="inline"><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2.2</mml:mn></mml:mrow></mml:math></inline-formula>), together with Cytophagia, while Dehalococcoidia were dominant in
P2(3). Finally, in the case of groundwater Type II (recharge water), the
bacterial assemblage was dominated by members of the Betaproteobacteria
class. During the dry period, no clear distribution patterns in the bacterial
relative abundances at the phylum and class level were observed, in part due
to the DGGE profiles, mainly composed by fine bands (Fig. 5); these were
difficult to recover and purify and thus could not be characterized.
However, it should be mentioned that Betaproteobacteria were dominant in both
P8 samples, contributing more than 50 % to the relative abundance.</p>
</sec>
</sec>
<sec id="Ch1.S3.SS2">
  <title>Microbial community indicators of MAR in soil and surface water</title>
      <p id="d1e2310">To study the impact of MAR on microbial community structure, recharge water
from pre-sedimentation and infiltration basins, as well as soils, were
analyzed. Figures 8 and 9 show the relative abundance of bacterial phylotypes
at the taxonomical level of classes for surface water and soil samples. The
results are displayed according to the distance to the recharge basin inlet.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F8" specific-use="star"><caption><p id="d1e2315">Bacterial community structure of soil samples from pre-sedimentation
and infiltration basins. Class relative abundances calculated for wet
<bold>(a)</bold> and dry <bold>(b)</bold> scenarios.</p></caption>
          <?xmltex \igopts{width=341.433071pt}?><graphic xlink:href="https://hess.copernicus.org/articles/23/139/2019/hess-23-139-2019-f08.png"/>

        </fig>

      <?xmltex \floatpos{t}?><fig id="Ch1.F9"><caption><p id="d1e2332">Bacterial community structure from water samples of
pre-sedimentation and infiltration basins. Class relative abundance
calculated for wet scenario.</p></caption>
          <?xmltex \igopts{width=213.395669pt}?><graphic xlink:href="https://hess.copernicus.org/articles/23/139/2019/hess-23-139-2019-f09.png"/>

        </fig>

      <p id="d1e2342">Microbial richness in soil samples was controlled by water content.
Non-recharge conditions had a primarily negative effect on the populations of
Dehalococcoidia, Acidobacteria and Chlorobia, but favored the presence of
Nitrospira, Cytophagia and Actinobacteria (Fig. 8). Shannon and evenness
indices demonstrated that soils were more diverse under wet conditions than
under dry ones (Table 1).</p>
      <p id="d1e2345">For surface water samples (Fig. 9), there was a decreasing gradient in
community complexity along the ponds. Acidobacteria, Betaproteobacteria and
Cyanobacteria were the main phylotypes present.</p>
</sec>
</sec>
<sec id="Ch1.S4">
  <title>Discussion</title>
      <p id="d1e2355">We contend that interdisciplinary analysis of geochemical characterization,
recharge evaluation and microbial fingerprinting, can provide relevant
information about the fate of microbial ecosystems in soil and groundwater.</p>
<sec id="Ch1.S4.SS1">
  <title>Matching groundwater model, ecological disturbance principle and microbial communities</title>
      <p id="d1e2363">Groundwater is a quite stable aquatic environment <xref ref-type="bibr" rid="bib1.bibx19" id="paren.23"/> as it
is shown by the low variability in the hydrochemical data (Table S1). One
could expect that microbial communities in groundwater should also display
low variability that could be reflected in the diversity indices. In this
way, piezometer P1, which is unaffected by recharge, showed stable diversity
indices regardless of the sampling campaign. However, disturbances produced
by recharge, evidenced by temperature and conductivity gradients below the
pond (Figs. 2 and 3), favor the highest Shannon values for the
moderately disturbed samples. As a result, the average of diversity indices
remains constant between both scenarios but with a higher standard deviation
during the wet scenario. These two facts combined suggest that perturbations
caused by recharge influence much more the composition of microbial
communities in groundwater than the natural variability of the background
aquifer water between scenarios.</p>
      <?pagebreak page150?><p id="d1e2369">MAR is a passive treatment technique that can provide simultaneously oxic and
anoxic conditions <xref ref-type="bibr" rid="bib1.bibx35" id="paren.24"/>. This has wide implications for the
potential biological removal of selected emerging contaminants, as each
micropollutant is most efficiently removed under specific redox conditions
<xref ref-type="bibr" rid="bib1.bibx52" id="paren.25"/>. Some can even be degraded by co-metabolism, involving
different redox states in the process <xref ref-type="bibr" rid="bib1.bibx48" id="paren.26"/>. In this
sense, MAR is an efficient remediation system. In addition, many sequenced
phylotypes, such as <italic>Nitrospira sp.</italic>, <italic>Stenotrophomonas sp.</italic> and
<italic>Methylobacterium sp.</italic>, have been associated with degradation
capabilities <xref ref-type="bibr" rid="bib1.bibx10 bib1.bibx11 bib1.bibx58" id="paren.27"/>. In short, the MAR
microbial ecosystem studied in this work presents many more phylotypes than
previous studies reported in groundwater systems <xref ref-type="bibr" rid="bib1.bibx30" id="paren.28"/>, and
thus MAR can be considered an efficient remediation system.</p>
      <p id="d1e2397">We further tested the intermediate disturbance hypothesis (IDH) for microbial
communities in groundwater (Fig. 6) related to MAR activities. IDH was
originally proposed for tropical rain forests and coral reefs
<xref ref-type="bibr" rid="bib1.bibx9" id="paren.29"/> and supports the idea that small perturbations create new
access to resources for species which have overlapping niches, allowing their
coexistence. This mechanism, known as a competition–colonization trade-off,
can explain IDH in local communities, leading to an increase in diversity.
However, when the degree of disturbance rises, only eurytolerant populations
can survive and grow. Thus, an inverse correlation between diversity and the
degree of disturbance (reflected in the temperature and conductivity
profiles) was expected (see Table 1). Such correlations have also been
reported in recharge wells and snowmelt-influenced aquifers
<xref ref-type="bibr" rid="bib1.bibx16 bib1.bibx60" id="paren.30"/>.</p>
      <p id="d1e2406">In the Llobregat MAR system, the initial diversity in the microbial community
increased with perturbation caused by recharge (Fig. 6), with maximum
diversity associated with Type IV water, and was lowest for the most disturbed
water (Type II). In ecological terms, Type III and Type IV waters represent
different proportions of perturbation.</p>
      <p id="d1e2410">In the most altered groundwater zone (represented by P8 samples),
Betaproteobacteria grew above 50 % of the relative abundance (Fig. 7). The
main phylogenetic affiliation of this phylotype at the genus level is
<italic>Vogesella</italic>. Strains of this genus are able to catabolize
monosaccharides under aerobic conditions, but not under low-oxygen
conditions. Furthermore, all <italic>Vogesella</italic> strains are denitrifiers
<xref ref-type="bibr" rid="bib1.bibx20" id="paren.31"/>. Indeed, P8, located below the pond, receives oxygen-rich
water during the recharge process, driven by fingering in the vadose zone.
Although dissolved oxygen was not measured in the present study, data from
other campaigns confirm this behavior for oxygen in P8 samples (data not
shown). Moreover, nitrate concentration in the surface water was low
(Table S1), and thus most denitrification is expected to occur under the
pond. <xref ref-type="bibr" rid="bib1.bibx17" id="text.32"/> recently confirmed that nitrate was consumed
via the denitrification pathway under the infiltration pond in the Llobregat
MAR system, supporting the idea that <italic>Vogesella sp.</italic> could be one of
the genera involved in nitrate consumption. Likely, depending on the oxygen
content, <italic>Vogesella sp.</italic> will adapt its metabolic function in favor of
aerobic oxidation of organic matter or by means of denitrification, thus
becoming a good indicator of highly disturbed MAR environments.</p>
      <p id="d1e2432">For Type III and Type IV waters, <italic>Dehalogenimonas sp.</italic>, within the
Dehalococcoidia class, is characteristic of medium-disturbance groundwater
(Figs. 4 and 7). <italic>Dehalogenimonas sp.</italic> has been studied in recent years
because some strains are associated with dechlorination in contaminated
sites. This genus is strictly anaerobic and mesophilic, and some species can
reductively dehalogenate polychlorinated aliphatic alkanes
<xref ref-type="bibr" rid="bib1.bibx36 bib1.bibx38" id="paren.33"/>. As a result, recharge creates
reducing conditions, likely indicating the existence of microzones or
microsites <xref ref-type="bibr" rid="bib1.bibx6 bib1.bibx22" id="paren.34"/>, defined as local anoxic
areas that coexist with fast-traveling oxygen-rich paths. Thus, microbial
analysis can be used to unmask the apparent mishap of water samples that are
oxic and display some typical anaerobic species. Moreover, some species of
<italic>Dehalogenimonas</italic> can dechlorinate some trichloroethane isomers
<xref ref-type="bibr" rid="bib1.bibx12" id="paren.35"/>, a pollutant reported in the Llobregat lower valley at
levels as high as 300 <inline-formula><mml:math id="M133" display="inline"><mml:mi mathvariant="normal">µ</mml:mi></mml:math></inline-formula>g L<inline-formula><mml:math id="M134" display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> <xref ref-type="bibr" rid="bib1.bibx56" id="paren.36"/>, thus opening the door for the development of enhanced
remediation activities.</p>
      <p id="d1e2476">The evenness index is an indicator of the equity of a community and can be
quite informative for observing perturbations to microbial communities. In
the wet scenario, the lowest values of <inline-formula><mml:math id="M135" display="inline"><mml:mi>E</mml:mi></mml:math></inline-formula> were obtained for the samples most
affected by recharge (Table 1), indicating that some species developed into
predominant members of the microbial assemblage. Groundwater samples
displayed the highest evenness values in the area less affected by recharge
and in the dry scenario. In the latter case, values indicate the recovery of
microbial communities from the disruption caused by recharge. In<?pagebreak page151?> fact, P8(1)
samples in the dry scenario were not fully consistent with this conceptual model,
with a low evenness index and very low nitrate concentration. Furthermore, the
presence of <italic>Methylotenera mobilis</italic> (Betaproteobacteria class) in both
P8 sampling points was more than 40 %, on average, of the relative
abundance. <italic>Methylotenera mobilis</italic> is a methylotroph species with
denitrification abilities <xref ref-type="bibr" rid="bib1.bibx8" id="paren.37"/>. These results suggest
that P8 denitrification processes occur below the basin even when it is
empty, indicating that 4 months is not enough time to revert back to
natural conditions at this sampling point. This assumption is consistent with
nitrate isotopic data presented in <xref ref-type="bibr" rid="bib1.bibx17" id="text.38"/> and is also in
agreement with the study of <xref ref-type="bibr" rid="bib1.bibx49" id="text.39"/> in which biomass
decay acted as an endogenous carbon source for respiration once the input
carbon was reduced, maintaining denitrification rates.</p>
</sec>
<sec id="Ch1.S4.SS2">
  <title>Microbial community structure in soils and surface waters</title>
      <p id="d1e2508">We analyzed the heterogeneity of the microbial community structure in soil
and surface water in terms of the distance to the infiltration basin entry
point (Fig. 9 and Table 1). Patterns in surface water microbial composition
are linked to sequential sedimentation processes as revealed by granulometric
analyses of soil samples (Table S3). The result was that surface water became
poorer in terms of the presence of microbial communities between the
pre-sedimentation basin and the end of the infiltration basin. The main
reason could be the decrease in solids suspended throughout the system due to
the sequential decantation of particles and their attached biomass.
Furthermore, surface water displays relatively higher values of Cyanobacteria
and Acidobacteria classes compared to groundwater. Cyanobacteria constitute
the largest, most diverse, and most widely distributed group of
photosynthetic prokaryotes, which are capable of conducting nitrogen fixation
<xref ref-type="bibr" rid="bib1.bibx54" id="paren.40"/>. However, members of the phylum Acidobacteria are
physiologically diverse and ubiquitous in soils, degrade a wide range of
carbon sources (from substances with a wide range of complexity), and are
capable of reducing nitrates and nitrites <xref ref-type="bibr" rid="bib1.bibx27" id="paren.41"/>. This
heterogeneous effect with distance to the entry point of the basin is also
observed in the diversity indices, which lose diversity with distance and are
inversely correlated to the proportion of fine particles. Similar behavior
for richness correlated to soil texture was reported elsewhere
<xref ref-type="bibr" rid="bib1.bibx7" id="paren.42"/>.</p>
      <p id="d1e2520">Differences in the microbial communities in soils between the two basins were
concentrated in the large organic matter content provided by the reactive
barrier present in the latter, being a source for the growth of bacterial
communities and enhanced diversity under recharge conditions. The role of the
humidity on microbial diversity is also significant, as was previously
reported in horizontal subsurface constructed wetlands <xref ref-type="bibr" rid="bib1.bibx40" id="paren.43"/>.
Furthermore, phylotype distribution changes among scenarios. Whereas
Dehalococcoidia and Chlorobia classes appear in wet soils, Nitrospira,
Cytophagia and Actinobacteria are favored under dry conditions.</p>
      <p id="d1e2526">The role of the reactive layer at the infiltration pond could be extrapolated
as a system fed with a considerable organic carbon load. Laboratory
experiments and constructed wetlands demonstrate that concentration of
microbial activity and TOC degradation is concentrated in the first
centimeters of the filter material <xref ref-type="bibr" rid="bib1.bibx43 bib1.bibx53 bib1.bibx55" id="paren.44"/> in response to oxygen concentration vertical distribution.
Although rapid oxygen depletion and consequent denitrification conditions
have been evidenced in lab-scale MAR experiments <xref ref-type="bibr" rid="bib1.bibx1 bib1.bibx14" id="paren.45"/>, this effect may not happen rapidly under real infiltration
conditions, where entrapped gas <xref ref-type="bibr" rid="bib1.bibx23" id="paren.46"/> or fingering processes
<xref ref-type="bibr" rid="bib1.bibx28" id="paren.47"/> may provide higher oxygen concentrations than in
lower-dimension systems (e.g., columns). Lab experiments are doubtlessly useful to
elucidate the behavior of microbial communities under controlled conditions.
However, sometimes it may be difficult to transfer conclusions obtained from lab samples to real sites.</p>
</sec>
<sec id="Ch1.S4.SS3">
  <title>Transferability of results and future work</title>
      <p id="d1e2547">Field studies are indeed realistic, but their transferability to other areas
becomes challenging. Following an ecological argument, this study evidences
that the intermediate disturbance hypothesis has been accomplished in the
Llobregat MAR site. Therefore, we could expect the same behavior in other
impacted areas under similar recharge conditions. Despite the novelty and
transferability of this study being quite clear, future work is needed to keep
evaluating the relationship between different ecological, microbial,
hydrochemical and physical variables in different sites worldwide. An
improvement of this multidisciplinary understanding of processes could be
achieved by combining statistical techniques with process-based models. This
would allow the direct extension of the results from one experiment to other
sites.</p>
</sec>
</sec>
<sec id="Ch1.S5" sec-type="conclusions">
  <title>Conclusions</title>
      <p id="d1e2558">This study aims at integrating different fields such as hydrogeology, ecology
and microbiology applied to a real MAR facility, relating flow (infiltration)
conditions, physicochemical water parameters and microbial changes induced
by managed recharge along vertical transect. We observed that infiltration
ponds modify the hydrochemistry and ecology of the groundwater environment,
especially in terms of microbial communities. Comparing recharge and
non-recharge scenarios, we found that microbial diversity indices (Shannon)
correlate inversely with the degree of perturbation caused by the induced
recharge, substantiating an intermediate disturbance hypothesis distribution.
In fact, MAR<?pagebreak page152?> (surface) basin operation can promote different levels of
disturbance at the same time, and microbial community structures change
accordingly. From microbial fingerprinting analysis, we observed the boosting
of Betaproteobacteria and Dehalococcoidia classes correlate to recharge
practices. Furthermore, genera such as <italic>Dehalogenimonas</italic>,
<italic>Nitrospira</italic>, <italic>Stenotrophomonas</italic> and <italic>Methylobacterium</italic>
were also detected, indicating a wide spectrum of biodegradation
capabilities. Likewise, sequencing tasks revealed characteristic phylotypes
from each water type, particularly <italic>Vogesella sp.</italic> for highly perturbed
water or <italic>Dehalogenimonas sp.</italic> for moderately perturbed water. Microbial
populations in soil are quite diverse when comparing wet with dry scenarios.
Soil moisture and sediment grain size appear to be the key factors explaining
diversity patterns. Furthermore, variations in recharge conditions do not
translate immediately to changes in communities. All these results combined
confirm the difficulty of extending laboratory experiment results to the
field scale.</p>
</sec>

      
      </body>
    <back><notes notes-type="dataavailability">

      <p id="d1e2584">All data are available from the corresponding author upon request.</p>
  </notes><app-group>
        <supplementary-material position="anchor"><p id="d1e2587">The supplement related to this article is available online at: <inline-supplementary-material xlink:href="https://doi.org/10.5194/hess-23-139-2019-supplement" xlink:title="pdf">https://doi.org/10.5194/hess-23-139-2019-supplement</inline-supplementary-material>.</p></supplementary-material>
        </app-group><notes notes-type="competinginterests">

      <p id="d1e2596">The authors declare that they have no conflict of
interest.</p>
  </notes><ack><title>Acknowledgements</title><p id="d1e2602">This investigation was financially supported by the European Union project
MARSOL grant agreement no. 619120, FP7-ENV-2013-WATER-INNO-DEMO, Generalitat
de Catalunya via the FI scholarship program (FI-DGR 2014), and the Spanish
Government and EU (project ACWAPUR PCIN-2015-239). The authors would like to
acknowledge Marc Vives for his help and Comunitat d'Usuaris d'Aigües de
la Vall Baixa i del Delta del Riu Llobregat (CUADLL) for their
cooperation.<?xmltex \hack{\newline}?><?xmltex \hack{\newline}?> Edited by: Alberto
Guadagnini<?xmltex \hack{\newline}?> Reviewed by: Aronne Dell'Oca and two anonymous
referees</p></ack><ref-list>
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    <!--<article-title-html>Microbial community changes induced by Managed Aquifer Recharge activities: linking hydrogeological and biological processes</article-title-html>
<abstract-html><p>Managed Aquifer Recharge (MAR) is a technique used worldwide to increase the
availability of water resources. We study how MAR modifies microbial
ecosystems and its implications for enhancing biodegradation processes to
eventually improve groundwater quality. We compare soil and groundwater
samples taken from a MAR facility located in NE Spain during recharge (with
the facility operating continuously for several months) and after 4 months
of no recharge. The study demonstrates a strong correlation between soil and
water microbial prints with respect to sampling location along the mapped
infiltration path. In particular, managed recharge practices disrupt
groundwater ecosystems by modifying diversity indices and the composition of
microbial communities, indicating that infiltration favors the growth of
certain populations. Analysis of the genetic profiles showed the presence of
nine different bacterial phyla in the facility, revealing high biological
diversity at the highest taxonomic range. In fact, the microbial population
patterns under recharge conditions agree with the intermediate disturbance
hypothesis (IDH). Moreover, DNA sequence analysis of excised denaturing gradient gel electrophoresis (DGGE) band patterns
revealed the existence of indicator species linked to MAR, most notably
<i>Dehalogenimonas sp.</i>, <i>Nitrospira sp.</i> and <i>Vogesella
sp.</i>. Our real facility multidisciplinary study (hydrological, geochemical and
microbial), involving soil and groundwater samples, indicates that MAR is a
naturally based, passive and efficient technique with broad implications for
the biodegradation of pollutants dissolved in water.</p></abstract-html>
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