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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-22-2921-2018</article-id><title-group><article-title><?xmltex \hack{\vspace{-3mm}}?>Dendrohydrology and water resources management in south-central Chile:
lessons from the Río Imperial streamflow reconstruction</article-title><alt-title>Dendrohydrology and water resources management in south-central Chile</alt-title>
      </title-group><?xmltex \runningtitle{Dendrohydrology and water resources management in south-central Chile}?><?xmltex \runningauthor{A.~Fern\'{a}ndez et al.}?>
      <contrib-group>
        <contrib contrib-type="author" corresp="yes" rid="aff1">
          <name><surname>Fernández</surname><given-names>Alfonso</given-names></name>
          <email>alfernandez@udec.cl</email>
        <ext-link>https://orcid.org/0000-0001-6825-0426</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff2">
          <name><surname>Muñoz</surname><given-names>Ariel</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff3">
          <name><surname>González-Reyes</surname><given-names>Álvaro</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff2 aff4">
          <name><surname>Aguilera-Betti</surname><given-names>Isabella</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff2">
          <name><surname>Toledo</surname><given-names>Isadora</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff2 aff5">
          <name><surname>Puchi</surname><given-names>Paulina</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff6">
          <name><surname>Sauchyn</surname><given-names>David</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff2">
          <name><surname>Crespo</surname><given-names>Sebastián</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff7">
          <name><surname>Frene</surname><given-names>Cristian</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff8">
          <name><surname>Mundo</surname><given-names>Ignacio</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff9">
          <name><surname>González</surname><given-names>Mauro</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff10">
          <name><surname>Vignola</surname><given-names>Raffaele</given-names></name>
          
        </contrib>
        <aff id="aff1"><label>1</label><institution>Departamento de Geografía, Universidad de Concepción, Concepción, Chile</institution>
        </aff>
        <aff id="aff2"><label>2</label><institution>Instituto de Geografía, Pontificia Universidad Católica de Valparaíso, Valparaíso, Chile</institution>
        </aff>
        <aff id="aff3"><label>3</label><institution>Instituto de Ciencias de la Tierra, Facultad de Ciencias, Universidad Austral de Chile, Valdivia, Chile</institution>
        </aff>
        <aff id="aff4"><label>4</label><institution>Centro Transdisciplinario de Estudios Ambientales y Desarrollo Humano Sostenible (CEAM), <?xmltex \hack{\break}?>Universidad Austral
de Chile, Valdivia, Chile</institution>
        </aff>
        <aff id="aff5"><label>5</label><institution>Dipartimento Territorio e Sistemi Agro-Forestali (TESAF), Università degli Studi di Padova, Agripolis, Italia</institution>
        </aff>
        <aff id="aff6"><label>6</label><institution>Prairie Adaptation Research Collaborative, University of Regina, Saskatchewan, Canada</institution>
        </aff>
        <aff id="aff7"><label>7</label><institution>Instituto de Ecología y Biodiversidad, Pontificia Universidad Católica de Chile, Santiago, Chile</institution>
        </aff>
        <aff id="aff8"><label>8</label><institution>Instituto Argentino de Glaciología, Nivología and Ciencias Ambientales and Facultad de Ciencias Exactas y
Naturales, Universidad Nacional de Cuyo, Mendoza, Argentina</institution>
        </aff>
        <aff id="aff9"><label>9</label><institution>Instituto de Conservación, Biodiversidad y Territorio, Universidad Austral de Chile, Valdivia, Chile</institution>
        </aff>
        <aff id="aff10"><label>10</label><institution>Cátedra Latinoamericana en Decisiones Ambientales para el Cambio Global, Turrialba, Costa Rica</institution>
        </aff>
      </contrib-group>
      <author-notes><corresp id="corr1">Alfonso Fernández (alfernandez@udec.cl)</corresp></author-notes><pub-date><day>17</day><month>May</month><year>2018</year></pub-date>
      
      <volume>22</volume>
      <issue>5</issue>
      <fpage>2921</fpage><lpage>2935</lpage>
      <history>
        <date date-type="received"><day>1</day><month>August</month><year>2017</year></date>
           <date date-type="rev-request"><day>28</day><month>August</month><year>2017</year></date>
           <date date-type="rev-recd"><day>11</day><month>April</month><year>2018</year></date>
           <date date-type="accepted"><year/></date>
      </history>
      <permissions>
        <copyright-statement>Copyright: © 2018 Alfonso Fernández et al.</copyright-statement>
        <copyright-year>2018</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/articles/22/2921/2018/hess-22-2921-2018.html">This article is available from https://hess.copernicus.org/articles/22/2921/2018/hess-22-2921-2018.html</self-uri><self-uri xlink:href="https://hess.copernicus.org/articles/22/2921/2018/hess-22-2921-2018.pdf">The full text article is available as a PDF file from https://hess.copernicus.org/articles/22/2921/2018/hess-22-2921-2018.pdf</self-uri>
      <abstract><title>Abstract</title>
    <p id="d1e246">Streamflow in south-central Chile (SCC, <inline-formula><mml:math id="M1" display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 37–42<inline-formula><mml:math id="M2" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S) is vital
for agriculture, forestry production, hydroelectricity, and human
consumption. Recent drought episodes have generated hydrological deficits
with damaging effects on these activities. This region is projected to
undergo major reductions in water availability, concomitant with projected
increases in water demand. However, the lack of long-term records hampers the
development of accurate estimations of natural variability and trends. In
order to provide more information on long-term streamflow variability and
trends in SCC, here we report findings of an analysis of instrumental records
and a tree-ring reconstruction of the summer streamflow of the Río Imperial
(<inline-formula><mml:math id="M3" display="inline"><mml:mo lspace="0mm">∼</mml:mo></mml:math></inline-formula> 37<inline-formula><mml:math id="M4" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> 40<inline-formula><mml:math id="M5" display="inline"><mml:msup><mml:mi/><mml:mo>′</mml:mo></mml:msup></mml:math></inline-formula> S–38<inline-formula><mml:math id="M6" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> 50<inline-formula><mml:math id="M7" display="inline"><mml:msup><mml:mi/><mml:mo>′</mml:mo></mml:msup></mml:math></inline-formula> S). This is the first
reconstruction in Chile targeted at this season. Results from the
instrumental streamflow record (<inline-formula><mml:math id="M8" display="inline"><mml:mo lspace="0mm">∼</mml:mo></mml:math></inline-formula> 1940 onwards) indicated that the
hydrological regime is fundamentally pluvial with a small snowmelt
contribution during spring, and evidenced a decreasing trend, both for the
summer and the full annual record. The reconstruction showed that streamflow
below the average characterized the post-1980 period, with more frequent, but
not more intense, drought episodes. We additionally found that the recent
positive phase of the Southern Annular Mode has significantly influenced
streamflow. These findings agree with previous studies, suggesting a robust
regional signal and a shift to a new hydrological scenario. In this paper, we
also discuss implications of these results for water managers and
stakeholders; we provide rationale and examples that support the need for the
incorporation of tree-ring reconstructions into water resources management.</p>
  </abstract>
    </article-meta>
  </front>
<body>
      

<sec id="Ch1.S1" sec-type="intro">
  <label>1</label><title>Introduction</title>
      <p id="d1e325">Streamflow in south-central Chile (SCC,
<inline-formula><mml:math id="M9" display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 37–42<inline-formula><mml:math id="M10" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S) is vital for
agriculture, forestry production, hydroelectricity, and human consumption
<xref ref-type="bibr" rid="bib1.bibx29 bib1.bibx43" id="paren.1"/>. With more than 55 % of Chilean
agriculture and forestry production delivered from this region
<xref ref-type="bibr" rid="bib1.bibx27" id="paren.2"/>, the drought episodes that
occurred in the last few decades and the associated hydrological deficit have
had damaging effects <xref ref-type="bibr" rid="bib1.bibx20" id="paren.3"/>. These<?pagebreak page2922?> drought episodes have been
linked to a significant decreasing trend in regional precipitation
<xref ref-type="bibr" rid="bib1.bibx40 bib1.bibx2 bib1.bibx23" id="paren.4"/>, with amounts 40 % below the
1901–2005 mean <xref ref-type="bibr" rid="bib1.bibx51" id="paren.5"/>. SCC is expected to undergo
important climate changes. Analysis of the multimodel ensemble for the
scenario RCP4.5 presented in the Atlas of Global and Regional Climate
Projections <xref ref-type="bibr" rid="bib1.bibx28" id="paren.6"/> indicates 10 to 30 % reduction in spring and
summer (October to March) precipitation by 2016–2035 and 2046–2065 relative
to 1986–2005. The same projection forecasts 0.5 to 2 <inline-formula><mml:math id="M11" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>C
warming for summer (December–February). Drier and warmer summers may make
SCC more vulnerable to water scarcity, given that this is the season of
highest water demand in this region <xref ref-type="bibr" rid="bib1.bibx20" id="paren.7"/>.</p>
      <p id="d1e375">Current and projected increases in water demand in this region are likely a
source of high uncertainty for future scenarios of water use
<xref ref-type="bibr" rid="bib1.bibx29" id="paren.8"/>. However, the lack of long-term observational records of
hydrometeorological variables makes difficult the development of accurate
estimations of natural variability, useful for determining the severity of
the recent observed deficit in streamflow <xref ref-type="bibr" rid="bib1.bibx30" id="paren.9"/>. Therefore, there
is a need to extend the observational record to better understand long-term
(e.g., centuries to millennia) variability and trends in streamflow, thus
providing useful information for hydrological assessment of governmental and
private planning initiatives within watersheds of SCC
<xref ref-type="bibr" rid="bib1.bibx31 bib1.bibx37" id="paren.10"/>.</p>

      <fig id="Ch1.F1" specific-use="star"><?xmltex \currentcnt{1}?><label>Figure 1</label><caption><p id="d1e388">Map showing the Río Imperial hydrological basin in the context of
the SCC region. Locations of instrumental records and tree-ring sampling
sites are also included.</p></caption>
        <?xmltex \igopts{width=284.527559pt}?><graphic xlink:href="https://hess.copernicus.org/articles/22/2921/2018/hess-22-2921-2018-f01.pdf"/>

      </fig>

      <p id="d1e397">The Río Imperial, a major river in SCC, drains an area of 12 763 km<inline-formula><mml:math id="M12" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msup></mml:math></inline-formula>,
extending from <inline-formula><mml:math id="M13" display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 37 <inline-formula><mml:math id="M14" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>40<inline-formula><mml:math id="M15" display="inline"><mml:msup><mml:mi/><mml:mo>′</mml:mo></mml:msup></mml:math></inline-formula> S to
<inline-formula><mml:math id="M16" display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 38 <inline-formula><mml:math id="M17" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>50<inline-formula><mml:math id="M18" display="inline"><mml:msup><mml:mi/><mml:mo>′</mml:mo></mml:msup></mml:math></inline-formula> S <xref ref-type="bibr" rid="bib1.bibx10" id="paren.11"/> (Fig. 1). The river
begins at the confluence between the Cholchol and Quepe rivers, in the ninth
Chilean administrative region, known as Araucanía. Summer streamflow is
controlled by rainfall, as most snowmelt-dominated discharge (usually
occurring in late austral spring) has vanished <xref ref-type="bibr" rid="bib1.bibx10" id="paren.12"/>. This
river is currently utilized for irrigation, fishing, tourism, and
transportation (in certain sections). For instance, in 2001 4 % of the basin
area was potentially usable for irrigation agriculture, with some projections
suggesting that this proportion will grow to <inline-formula><mml:math id="M19" display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 10 % <xref ref-type="bibr" rid="bib1.bibx3" id="paren.13"/>. Additionally, the Río Imperial has
high hydroelectric potential, ranked 11th in the country, with 455.8 MW
<xref ref-type="bibr" rid="bib1.bibx44" id="paren.14"/>. An emerging sociohydrological problem in this basin is
related to the allocation of water rights by the government: there is more
streamflow allocated than the current river discharge. What seems to prevent
a water availability crisis is that not all the allocated water is being
exploited <xref ref-type="bibr" rid="bib1.bibx3" id="paren.15"/>. Facing scenarios of water
scarcity may obligate some users to fully claim their rights, likely
triggering a regime shift with uncertain implications. However, the ability
to ponder the possible consequences of these predicted changes is limited
because accurate calculations of extreme scenarios are essential but largely
nonexistent. For this reason, long-term evaluations of Río Imperial
discharge are urgently needed.</p>
      <p id="d1e484">Tree-ring analysis has proven to be a useful tool for supplementing available
observations of streamflow. These proxy records can provide time series at
yearly resolution, capable of delivering historical information on natural
variability, estimations of return periods of extreme events such as
droughts, and on the correlation with large-scale climatic forcings
<xref ref-type="bibr" rid="bib1.bibx34 bib1.bibx45" id="paren.16"/>. In Chile, dendrohydrology has already been
utilized for streamflow reconstruction in four major rivers: Maule
(35<inline-formula><mml:math id="M20" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>30<inline-formula><mml:math id="M21" display="inline"><mml:msup><mml:mi/><mml:mo>′</mml:mo></mml:msup></mml:math></inline-formula> S; <xref ref-type="bibr" rid="bib1.bibx52" id="altparen.17"/>), Biobío (37<inline-formula><mml:math id="M22" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>10<inline-formula><mml:math id="M23" display="inline"><mml:msup><mml:mi/><mml:mo>′</mml:mo></mml:msup></mml:math></inline-formula> S; <xref ref-type="bibr" rid="bib1.bibx37" id="altparen.18"/>), Puelo (41<inline-formula><mml:math id="M24" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>39<inline-formula><mml:math id="M25" display="inline"><mml:msup><mml:mi/><mml:mo>′</mml:mo></mml:msup></mml:math></inline-formula> S; <xref ref-type="bibr" rid="bib1.bibx30" id="altparen.19"/>), and Baker
(47<inline-formula><mml:math id="M26" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>40<inline-formula><mml:math id="M27" display="inline"><mml:msup><mml:mi/><mml:mo>′</mml:mo></mml:msup></mml:math></inline-formula> S; <xref ref-type="bibr" rid="bib1.bibx31" id="altparen.20"/>). To date, however, these studies have
not yet been fully utilized for watershed planning and management. In order
to provide more information on long-term streamflow variability and trends in
SCC and thus contribute to improving water resource management in this key
region for the country's economy, here we report findings of a tree-ring-based reconstruction of the summer streamflow of Río Imperial. This is the
first reconstruction of streamflow in summer, the season with the highest
water demand. Our research focused on expanding current understanding of
long-term streamflow, thus providing more evidence of both regional
coincidence among studies and seasonal/local particularities in streamflow.
Therefore, our objectives were to (a) determine whether or not current summer
streamflow changes in the Río imperial are unprecedented at the
multicentury scale, (b) establish if the return period of extreme years of
high and low streamflow has changed in the last few centuries, and (c) estimate
the correlation between the multicentury variability of the Río
Imperial streamflow and climate modes of natural variability such as the El
Niño Southern Oscillation (ENSO), the Southern Annular Mode (SAM), and the
Interdecadal Pacific Oscillation (IPO). Given that this is the fifth
streamflow reconstruction for a Chilean river and that available results from
previous studies have yet to be utilized for water resources planning, in our
discussion section we also (a) summarize arguments related to physical
processes that may support our summer reconstruction as a more robust time
series compared to some of the previous studies, and (b) in light of our
results, evaluate strengths and weaknesses of a recently enacted method to
calculate minimum ecological discharge, hoping to engage authorities,
managers, and stakeholders in considering proxy-data for improving water
resources management and research.</p>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T1" specific-use="star"><?xmltex \currentcnt{1}?><label>Table 1</label><caption><p id="d1e579">Instrumental streamflow records utilized in this study. These
records were retrieved from the Chilean National Water Authority (DGA or
Dirección General de Aguas).</p></caption><oasis:table frame="topbot"><oasis:tgroup cols="7">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="right"/>
     <oasis:colspec colnum="3" colname="col3" align="right"/>
     <oasis:colspec colnum="4" colname="col4" align="right"/>
     <oasis:colspec colnum="5" colname="col5" align="right"/>
     <oasis:colspec colnum="6" colname="col6" align="right"/>
     <oasis:colspec colnum="7" colname="col7" align="right"/>
     <oasis:thead>
       <oasis:row>
         <oasis:entry colname="col1">Name</oasis:entry>
         <oasis:entry colname="col2">Latitude</oasis:entry>
         <oasis:entry colname="col3">Longitude</oasis:entry>
         <oasis:entry colname="col4">Period</oasis:entry>
         <oasis:entry colname="col5">Altitude</oasis:entry>
         <oasis:entry colname="col6">Discharge</oasis:entry>
         <oasis:entry colname="col7">Coefficient</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2">(S)</oasis:entry>
         <oasis:entry colname="col3">(W)</oasis:entry>
         <oasis:entry colname="col4"/>
         <oasis:entry colname="col5">(m)</oasis:entry>
         <oasis:entry colname="col6">(m<inline-formula><mml:math id="M28" display="inline"><mml:msup><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msup></mml:math></inline-formula> s<inline-formula><mml:math id="M29" 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> a<inline-formula><mml:math id="M30" 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>)</oasis:entry>
         <oasis:entry colname="col7">of variation</oasis:entry>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>
         <oasis:entry colname="col1">Cautín at Rari-Ruca</oasis:entry>
         <oasis:entry colname="col2">38<inline-formula><mml:math id="M31" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> 55<inline-formula><mml:math id="M32" display="inline"><mml:msup><mml:mi/><mml:mo>′</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3">72<inline-formula><mml:math id="M33" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> 00<inline-formula><mml:math id="M34" display="inline"><mml:msup><mml:mi/><mml:mo>′</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">1943–2010</oasis:entry>
         <oasis:entry colname="col5">425</oasis:entry>
         <oasis:entry colname="col6">98.1</oasis:entry>
         <oasis:entry colname="col7">16.43</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Quepe at Vilcíun</oasis:entry>
         <oasis:entry colname="col2">38<inline-formula><mml:math id="M35" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> 41<inline-formula><mml:math id="M36" display="inline"><mml:msup><mml:mi/><mml:mo>′</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3">72<inline-formula><mml:math id="M37" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> 13<inline-formula><mml:math id="M38" display="inline"><mml:msup><mml:mi/><mml:mo>′</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">1946–2010</oasis:entry>
         <oasis:entry colname="col5">292</oasis:entry>
         <oasis:entry colname="col6">33.1</oasis:entry>
         <oasis:entry colname="col7">13.57</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Muco at Muco bridge</oasis:entry>
         <oasis:entry colname="col2">38<inline-formula><mml:math id="M39" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> 37<inline-formula><mml:math id="M40" display="inline"><mml:msup><mml:mi/><mml:mo>′</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col3">72<inline-formula><mml:math id="M41" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> 25<inline-formula><mml:math id="M42" display="inline"><mml:msup><mml:mi/><mml:mo>′</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">1951–2010</oasis:entry>
         <oasis:entry colname="col5">250</oasis:entry>
         <oasis:entry colname="col6">26.2</oasis:entry>
         <oasis:entry colname="col7">37.88</oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup></oasis:table></table-wrap>

</sec>
<sec id="Ch1.S2">
  <label>2</label><title>Methods</title>
<sec id="Ch1.S2.SS1">
  <label>2.1</label><title>Analysis of instrumental streamflow records</title>
      <p id="d1e881">In this study, January and February represent summer streamflow, the period
of the year when streamflow is closest to the river's baseflow and when
annual precipitation<?pagebreak page2923?> is at its lowest (Supplement Fig. S1). Streamflow during these
months is sensitive to changes in soil moisture and thus summer precipitation
(or the lack of) during that period or from previous months. We selected
three instrumental records (Fig. 1) representing the natural streamflow
regime of the middle and lower sections within the river basin (Table 1) for the
period 1947–2015. These stations gauge rivers where the water has not been
diverted for irrigation and hydroelectricity and are also located in two
protected areas: Malalcahuello National Reserve and Conguillío National
Park. Flow at downstream stations is highly conditioned by engineered
structures (e.g., water intakes). We tested the “natural regime” represented
by these records by conducting a correlation study between these stations and
other hydroclimatic variables such as rainfall. We utilized double-mass
curves to determine the length of the time series for calibration of the
reconstruction model <xref ref-type="bibr" rid="bib1.bibx37" id="paren.21"/>, discarding records that did not
follow rainfall trends; this resulted in the elimination of a few years in
the earliest section of the time series.</p>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T2"><?xmltex \currentcnt{2}?><label>Table 2</label><caption><p id="d1e890">Rank of the five years with highest and lowest discharges as
calculated from the composite built from the instrumental record (1947–2010).
Departures are expressed as percentages relative to the mean (i.e., % <inline-formula><mml:math id="M43" display="inline"><mml:mo>=</mml:mo></mml:math></inline-formula> Year<inline-formula><mml:math id="M44" display="inline"><mml:mrow><mml:msub><mml:mi/><mml:mtext>x</mml:mtext></mml:msub><mml:mo>/</mml:mo><mml:mo>=</mml:mo><mml:mover accent="true"><mml:mtext>x</mml:mtext><mml:mo mathvariant="normal" stretchy="false">^</mml:mo></mml:mover></mml:mrow></mml:math></inline-formula>, where
Year<inline-formula><mml:math id="M45" display="inline"><mml:msub><mml:mi/><mml:mover accent="true"><mml:mtext>x</mml:mtext><mml:mo mathvariant="normal" stretchy="false">^</mml:mo></mml:mover></mml:msub></mml:math></inline-formula> corresponds to the streamflow of any given
year and <inline-formula><mml:math id="M46" display="inline"><mml:mo>=</mml:mo></mml:math></inline-formula> x to the mean of the period).</p></caption><oasis:table frame="topbot"><oasis:tgroup cols="3">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="right"/>
     <oasis:colspec colnum="3" colname="col3" align="right"/>
     <oasis:thead>
       <oasis:row>
         <oasis:entry colname="col1">Ranking</oasis:entry>
         <oasis:entry colname="col2">High flow</oasis:entry>
         <oasis:entry colname="col3">Low flow</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2">(% of the mean)</oasis:entry>
         <oasis:entry colname="col3">(% of the mean)</oasis:entry>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>
         <oasis:entry colname="col1">1</oasis:entry>
         <oasis:entry colname="col2">1956 (209.8)</oasis:entry>
         <oasis:entry colname="col3">1999 (43.8)</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">2</oasis:entry>
         <oasis:entry colname="col2">1951 (184.1)</oasis:entry>
         <oasis:entry colname="col3">1963 (54.0)</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">3</oasis:entry>
         <oasis:entry colname="col2">1971 (166.8)</oasis:entry>
         <oasis:entry colname="col3">2009 (55.4)</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">4</oasis:entry>
         <oasis:entry colname="col2">1965 (159.8)</oasis:entry>
         <oasis:entry colname="col3">1997 (57.2)</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">5</oasis:entry>
         <oasis:entry colname="col2">1980 (150.1)</oasis:entry>
         <oasis:entry colname="col3">2008 (59.9)</oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup></oasis:table></table-wrap>

</sec>
<sec id="Ch1.S2.SS2">
  <label>2.2</label><title>Reconstruction and analysis using tree-ring chronologies</title>
      <?pagebreak page2924?><p id="d1e1046">We built a multiple regression model relating three tree-ring chronologies
from <italic>Araucaria araucana</italic> to records of the Río Imperial's summer
streamflow (Fig. 1 and Table 2). These chronologies were those showing the
highest correlation with streamflow records, extracted from an initial group
of 19 chronologies taken from <italic>Araucaria araucana</italic> (16) and
<italic>Austrocedrus chilensis</italic> (3). We utilized the softwares ARSTAN
<xref ref-type="bibr" rid="bib1.bibx12" id="paren.22"/> and COFECHA <xref ref-type="bibr" rid="bib1.bibx26" id="paren.23"/> for standardization and
dating of the tree-ring chronologies. This standardization procedure applies
linear and exponential statistical models to suppress temporal
auto-correlation in the series. These statistical procedures minimize the
differences in tree-ring width between individual trees (e.g., due to local
dissimilarities in soil moisture or differences in age) and therefore
maximize our ability to retrieve the common tree-ring pattern related to the
hydroclimate.</p>
      <p id="d1e1064">The three available instrumental records for the basin were transformed into
standardized anomalies and then averaged to constitute a single composite
time series <xref ref-type="bibr" rid="bib1.bibx30 bib1.bibx37" id="paren.24"/>. To obtain a valid simulation of the
streamflow from the tree-ring chronologies, we employed the “leave-one-out”
regression technique using the period 1947–2005 as the validation window,
testing several predictors from the three tree-ring chronologies. The
predictors consisted of chronologies for the growth year
(<inline-formula><mml:math id="M47" display="inline"><mml:mi>t</mml:mi></mml:math></inline-formula>), as well as backward and forward lags of 1 and 2
years (<inline-formula><mml:math id="M48" display="inline"><mml:mrow><mml:mi>t</mml:mi><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:math></inline-formula>, <inline-formula><mml:math id="M49" display="inline"><mml:mrow><mml:mi>t</mml:mi><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:math></inline-formula>,
<inline-formula><mml:math id="M50" display="inline"><mml:mrow><mml:mi>t</mml:mi><mml:mo>+</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:math></inline-formula>, and <inline-formula><mml:math id="M51" display="inline"><mml:mrow><mml:mi>t</mml:mi><mml:mo>+</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:math></inline-formula>, respectively). We
found that the most robust statistical model corresponded to the following:

                <disp-formula specific-use="align" content-type="numbered"><mml:math id="M52" display="block"><mml:mtable displaystyle="true"><mml:mlabeledtr id="Ch1.E1"><mml:mtd><mml:mtext>1</mml:mtext></mml:mtd><mml:mtd><mml:mstyle displaystyle="true" class="stylechange"/></mml:mtd><mml:mtd><mml:mrow><mml:mstyle displaystyle="true" class="stylechange"/><mml:mtext>IS</mml:mtext><mml:mo>=</mml:mo><mml:mn mathvariant="normal">0.07</mml:mn><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2.05</mml:mn><mml:mspace linebreak="nobreak" width="0.25em"/><mml:msub><mml:mtext>PIN</mml:mtext><mml:mrow><mml:mi>t</mml:mi><mml:mo>+</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msub><mml:mo>+</mml:mo><mml:mn mathvariant="normal">2.83</mml:mn><mml:mspace width="0.25em" linebreak="nobreak"/><mml:msub><mml:mtext>LYV</mml:mtext><mml:mi>t</mml:mi></mml:msub><mml:mo>+</mml:mo><mml:mn mathvariant="normal">2.69</mml:mn><mml:mspace width="0.25em" linebreak="nobreak"/><mml:msub><mml:mtext>PAG</mml:mtext><mml:mrow><mml:mi>t</mml:mi><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msub></mml:mrow></mml:mtd></mml:mlabeledtr><mml:mtr><mml:mtd><mml:mstyle class="stylechange" displaystyle="true"/></mml:mtd><mml:mtd><mml:mrow><mml:mstyle class="stylechange" displaystyle="true"/><?xmltex \hspace*{3.5mm}?><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1.46</mml:mn><mml:mspace linebreak="nobreak" width="0.25em"/><mml:msub><mml:mtext>PAG</mml:mtext><mml:mrow><mml:mi>t</mml:mi><mml:mo>+</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msub><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1.97</mml:mn><mml:mspace linebreak="nobreak" width="0.25em"/><mml:msub><mml:mtext>LYV</mml:mtext><mml:mrow><mml:mi>t</mml:mi><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msub><mml:mo>,</mml:mo></mml:mrow></mml:mtd></mml:mtr></mml:mtable></mml:math></disp-formula>

            where IS is the reconstructed summer streamflow for the Río Imperial,
while PIN, LYV, and PAG correspond to the tree-ring chronologies as
described in Table 3. The forward-lagged time series included suggest that
the statistical model has predictive skill, as shown in previous studies
(e.g., <xref ref-type="bibr" rid="bib1.bibx46" id="altparen.25"/>). In this model, LYV and PAG correlated positively
with same-year streamflow (0.38 and 0.43, respectively), with that of the
previous year (0.53 and 0.41), and with streamflow recorded 2 years before
(0.3 and 0.23). Conversely, PIN correlated negatively with streamflow
recorded in previous years (<inline-formula><mml:math id="M53" display="inline"><mml:mo lspace="0mm">-</mml:mo></mml:math></inline-formula>0.56 for the first and <inline-formula><mml:math id="M54" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.38 for the second
previous year). We conjecture that the negative correlation between PIN and
the instrumental data is related to features of the sampling site, located in
a narrow sector with recurrent fog, where atmospheric moisture and
precipitation in summer may produce a relative reduction in incoming
radiation and temperature; these conditions may reduce the rate of the
tree-ring growth. <xref ref-type="bibr" rid="bib1.bibx35" id="text.26"/> reported similar findings for PIN when
analyzing as larger group of chronologies.</p>
      <p id="d1e1247">During the verification period we utilized (a) the <inline-formula><mml:math id="M55" display="inline"><mml:mrow><mml:msup><mml:mi>R</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula>
(<inline-formula><mml:math id="M56" display="inline"><mml:mrow><mml:msup><mml:mi>R</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula>adj) to assess the explained variance, (b) the reduction
of error (RE) statistic to account for the relationship between the actual
value and its estimate, (c) the F statistic for assessing the accuracy of the
regression, (d) the root mean square error (RMSE) as well as the standard
error (SE) as measures of uncertainty, (e) the Durbin–Watson test for
determining the degree of auto-correlation of the residuals, and (f) the
variance inflation factor (VIF) to check the possibility of multicollinearity
in the regression (see <xref ref-type="bibr" rid="bib1.bibx39" id="altparen.27"/>, for details). The VIF evaluates the multicollinearity of the predictors: a
VIF close to 1 means a low or no multicollinearity <xref ref-type="bibr" rid="bib1.bibx25" id="paren.28"/> while a
value above 10 is associated with multicollinearity problems between
predictors <xref ref-type="bibr" rid="bib1.bibx38" id="paren.29"/>.</p>
      <p id="d1e1281">For studying the return period of extreme low flows in the streamflow
reconstruction, we applied the peak over threshold (POT) approach, using the
low flows corresponding to a threshold <inline-formula><mml:math id="M57" display="inline"><mml:mo>≤</mml:mo></mml:math></inline-formula> 20 percentile. We also estimated the recurrence rate of drought events utilizing
a kernel estimation technique with a Gaussian function and 50-year bandwidth.
The kernel-based estimation of drought recurrence allows for the detection of
nonlinear and nonmonotonic trends without imposing parametric restrictions.
Furthermore, a smooth kernel function produces more realistic estimation of
drought recurrence. We calculated a confidence interval at the 95 % level
based on 1000 bootstrap resampling steps <xref ref-type="bibr" rid="bib1.bibx14" id="paren.30"/> to estimate bias
and variance properties of drought recurrence in the reconstruction. The
kernel estimation, bandwidth selection, and bootstrap algorithm were computed
in the free R Project platform software <xref ref-type="bibr" rid="bib1.bibx42" id="paren.31"/>. We assessed
frequency of cycles in the reconstruction by applying the following methods:
Blackman–Tukey <xref ref-type="bibr" rid="bib1.bibx21" id="paren.32"/>, multitaper, singular spectral analysis, and
a continuous wavelet transform analysis.</p>
      <p id="d1e1301">We further performed a number of statistical analyses comparing observed,
reconstructed streamflow time series, and other relevant hydroclimatic time
series. For the period with available instrumental data (second half of the
20th century), we calculated Pearson correlations between
these records and the Temuco rainfall gauge (TEM in Fig. 1;
38 <inline-formula><mml:math id="M58" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>46<inline-formula><mml:math id="M59" display="inline"><mml:msup><mml:mi/><mml:mo>′</mml:mo></mml:msup></mml:math></inline-formula> S–72 <inline-formula><mml:math id="M60" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>38<inline-formula><mml:math id="M61" display="inline"><mml:msup><mml:mi/><mml:mo>′</mml:mo></mml:msup></mml:math></inline-formula> W), one of the few
continuous records available in this watershed. We further analyzed the
coherence of dominant periods of streamflow between the instrumental record
and the tree-ring reconstruction, derived from a singular spectral analysis
(<xref ref-type="bibr" rid="bib1.bibx31" id="altparen.33"/>, and references herein). In addition, we compared the summer
streamflow reconstruction of the Río Imperial with a November–December
rainfall reconstruction of northern Patagonia <xref ref-type="bibr" rid="bib1.bibx54" id="paren.34"/>. These
chronologies are statistically independent, since the latter derives from
samples extracted from <italic>Austrocedrus chilensis</italic>. This comparison is
justified by the fact that studies in other watersheds in the SCC region have
shown a relatively fast response of the discharge to changes in precipitation
(e.g., <xref ref-type="bibr" rid="bib1.bibx60" id="altparen.35"/>). Finally, we studied the correlations between
observed and reconstructed streamflow and time series representing modes of
regional climate variability, namely the ENSO,
IPO, and SAM. For the ENSO, we utilized the Southern Oscillation Index (SOI)
provided by the Climate Analysis Section, Climate and Global Dynamics
Laboratory at
NCAR<fn id="Ch1.Footn1"><p id="d1e1353"><uri>http://www.cgd.ucar.edu/cas/catalog/climind/soi.html</uri> (last
access: 3 December 2018)</p></fn>. This SOI is computed from monthly mean sea level
pressure anomalies at Tahiti and Darwin and has became standard for climatic
studies <xref ref-type="bibr" rid="bib1.bibx50" id="paren.36"/>. Negative SOI anomalies correspond to
relatively warmer conditions in the eastern Pacific Ocean (or more El
Niño-like conditions). The IPO time series is from the reconstruction
presented in <xref ref-type="bibr" rid="bib1.bibx53" id="text.37"/>. For the time series representing the activity
of the SAM, we selected the Antarctic Oscillation (AAO) index, defined as the
leading principal component of sea level pressure in the region south of
20<inline-formula><mml:math id="M62" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S <xref ref-type="bibr" rid="bib1.bibx49" id="paren.38"/> and also calculated from the
NCAR–NCEP reanalysis<fn id="Ch1.Footn2"><p id="d1e1378">For details, go to
<uri>http://www.cpc.ncep.noaa.gov/products/precip/CWlink/daily_ao_index/aao/monthly.aao.index.b79.current.ascii.table</uri> (last access: 11 May 2018)</p></fn>.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F2"><?xmltex \currentcnt{2}?><label>Figure 2</label><caption><p id="d1e1387">Hydrological regime of the instrumental records utilized in this
study. These records were combined to develop a composite summer streamflow
record for the period 1947–2010. The plots showing “streamflow departures”
correspond to standardized anomalies for the common period of the records.
The hydrographs depict the average streamflow of each month (bars) and the
proportion of yearly discharge each month contributes (curves).</p></caption>
          <?xmltex \igopts{width=236.157874pt}?><graphic xlink:href="https://hess.copernicus.org/articles/22/2921/2018/hess-22-2921-2018-f02.pdf"/>

        </fig>

</sec>
</sec>
<?pagebreak page2925?><sec id="Ch1.S3">
  <label>3</label><title>Results</title>
<sec id="Ch1.S3.SS1">
  <label>3.1</label><title>Streamflow trends and variability from the instrumental record</title>
      <p id="d1e1412">Our analysis of instrumental data corroborated previous studies where the
regime of the Río Imperial was characterized as fundamentally pluvial with
a small snowmelt contribution during spring <xref ref-type="bibr" rid="bib1.bibx10" id="paren.39"/>. The
hydrographs in Fig. 2 show that around 40 to 50 % of the streamflow occurs
between June and August, although at the Cautín station spring months
contribute slightly more to the overall flow relative to the other stations.
Conversely, summer streamflow represents 5 to 10 % of the total yearly
amount. We also found a high correlation, as high as 0.61 for TEM, between
summer discharge and rainfall of the same season as well as with rainfall
observations of previous months.</p>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T3" specific-use="star"><?xmltex \currentcnt{3}?><label>Table 3</label><caption><p id="d1e1421">Main features of the tree-ring chronologies developed for this
study. The Lanín (LAN) and Villarrica (VILL) chronologies correspond to
those presented in <xref ref-type="bibr" rid="bib1.bibx35" id="text.40"/> and <xref ref-type="bibr" rid="bib1.bibx22" id="text.41"/>,
respectively.</p></caption><oasis:table frame="topbot"><oasis:tgroup cols="7">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="left"/>
     <oasis:colspec colnum="3" colname="col3" align="right"/>
     <oasis:colspec colnum="4" colname="col4" align="right"/>
     <oasis:colspec colnum="5" colname="col5" align="right"/>
     <oasis:colspec colnum="6" colname="col6" align="right"/>
     <oasis:colspec colnum="7" colname="col7" align="left"/>
     <oasis:thead>
       <oasis:row>
         <oasis:entry colname="col1">Location</oasis:entry>
         <oasis:entry colname="col2">Code</oasis:entry>
         <oasis:entry colname="col3">Latitude</oasis:entry>
         <oasis:entry colname="col4">Longitude</oasis:entry>
         <oasis:entry colname="col5">Period</oasis:entry>
         <oasis:entry colname="col6">Altitude</oasis:entry>
         <oasis:entry colname="col7">Source</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2"/>
         <oasis:entry colname="col3">(S)</oasis:entry>
         <oasis:entry colname="col4">(W)</oasis:entry>
         <oasis:entry colname="col5"/>
         <oasis:entry colname="col6">(m)</oasis:entry>
         <oasis:entry colname="col7"/>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>
         <oasis:entry colname="col1">Pinalada Redonda</oasis:entry>
         <oasis:entry colname="col2">PIN</oasis:entry>
         <oasis:entry colname="col3">39 <inline-formula><mml:math id="M63" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>18<inline-formula><mml:math id="M64" display="inline"><mml:msup><mml:mi/><mml:mo>′</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">71 <inline-formula><mml:math id="M65" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>17<inline-formula><mml:math id="M66" display="inline"><mml:msup><mml:mi/><mml:mo>′</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col5">1606–2006</oasis:entry>
         <oasis:entry colname="col6">1119</oasis:entry>
         <oasis:entry colname="col7">
                    <xref ref-type="bibr" rid="bib1.bibx35" id="text.42"/>
                  </oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Piedra del Águila</oasis:entry>
         <oasis:entry colname="col2">PAG</oasis:entry>
         <oasis:entry colname="col3">37 <inline-formula><mml:math id="M67" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>50<inline-formula><mml:math id="M68" display="inline"><mml:msup><mml:mi/><mml:mo>′</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">73 <inline-formula><mml:math id="M69" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>02<inline-formula><mml:math id="M70" display="inline"><mml:msup><mml:mi/><mml:mo>′</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col5">1239–2009</oasis:entry>
         <oasis:entry colname="col6">1300</oasis:entry>
         <oasis:entry colname="col7">
                    <xref ref-type="bibr" rid="bib1.bibx36" id="text.43"/>
                  </oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Lanín y Villarrica</oasis:entry>
         <oasis:entry colname="col2">LYV</oasis:entry>
         <oasis:entry colname="col3">39 <inline-formula><mml:math id="M71" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>35<inline-formula><mml:math id="M72" display="inline"><mml:msup><mml:mi/><mml:mo>′</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col4">71 <inline-formula><mml:math id="M73" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>30<inline-formula><mml:math id="M74" display="inline"><mml:msup><mml:mi/><mml:mo>′</mml:mo></mml:msup></mml:math></inline-formula></oasis:entry>
         <oasis:entry colname="col5">1291–2006</oasis:entry>
         <oasis:entry colname="col6">1350</oasis:entry>
         <oasis:entry colname="col7">Composite LAN <inline-formula><mml:math id="M75" display="inline"><mml:mo>+</mml:mo></mml:math></inline-formula> VILL</oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup></oasis:table></table-wrap>

      <p id="d1e1692">All observations showed a decreasing trend since the beginning of the
records, both for the annual as well as for the summer mean (Fig. 2). Four of
five lowest discharge records occurred after 1995, notably 1999, whereas the
five highest are detected before 1981, with four of them before 1974 (Table 2).
We calculated the proportional departures of each of these years (in
percentage) relative to the long-term average, finding that the five
lowest-flow years showed little spread, with a mean departure of 54.06 % <inline-formula><mml:math id="M76" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 6.14
(1 standard deviation), whereas for the five highest-flow ones
there was more spread (74.12 % <inline-formula><mml:math id="M77" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 23.49). Furthermore, the record suggested
that high-flow years tended to be more extreme (relative to the mean) than
low-flow years.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F3"><?xmltex \currentcnt{3}?><label>Figure 3</label><caption><p id="d1e1712"><italic>Araucaria araucana</italic> tree-ring chronologies utilized for the
Río Imperial streamflow reconstruction. Gray areas represent the number of
tree-growth series included in each chronology. The longest time series
corresponds to the one sampled in the Nahuelbuta National Park (PAG),
representing the period 1239–2009.</p></caption>
          <?xmltex \igopts{width=236.157874pt}?><graphic xlink:href="https://hess.copernicus.org/articles/22/2921/2018/hess-22-2921-2018-f03.png"/>

        </fig>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T4"><?xmltex \currentcnt{4}?><label>Table 4</label><caption><p id="d1e1726">Statistical description of the tree-ring chronologies developed for
this study. The column labeled as “EPS” depicts the year when that
statistic began to be larger than 0.85.</p></caption><oasis:table frame="topbot"><oasis:tgroup cols="5">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="right"/>
     <oasis:colspec colnum="3" colname="col3" align="right"/>
     <oasis:colspec colnum="4" colname="col4" align="right"/>
     <oasis:colspec colnum="5" colname="col5" align="right"/>
     <oasis:thead>
       <oasis:row>
         <oasis:entry colname="col1">Code</oasis:entry>
         <oasis:entry colname="col2">EPS</oasis:entry>
         <oasis:entry colname="col3">Autocorrelation</oasis:entry>
         <oasis:entry colname="col4">Average</oasis:entry>
         <oasis:entry colname="col5">VIF</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2"/>
         <oasis:entry colname="col3"/>
         <oasis:entry colname="col4">sensitivity</oasis:entry>
         <oasis:entry colname="col5"/>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>
         <oasis:entry colname="col1">PIN</oasis:entry>
         <oasis:entry colname="col2">1750</oasis:entry>
         <oasis:entry colname="col3">0.591</oasis:entry>
         <oasis:entry colname="col4">0.230</oasis:entry>
         <oasis:entry colname="col5">1.011</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">PAG</oasis:entry>
         <oasis:entry colname="col2">1450</oasis:entry>
         <oasis:entry colname="col3">0.490</oasis:entry>
         <oasis:entry colname="col4">0.170</oasis:entry>
         <oasis:entry colname="col5">1.739</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">LYV</oasis:entry>
         <oasis:entry colname="col2">1525</oasis:entry>
         <oasis:entry colname="col3">0.566</oasis:entry>
         <oasis:entry colname="col4">0.206</oasis:entry>
         <oasis:entry colname="col5">1.724</oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup></oasis:table></table-wrap>

<?xmltex \hack{\vspace*{10mm}}?><?xmltex \hack{\newpage}?>
</sec>
<?pagebreak page2926?><sec id="Ch1.S3.SS2">
  <label>3.2</label><title>Streamflow reconstruction: features and interpretation</title>
      <p id="d1e1848">Two of three <italic>Araucaria araucana</italic> tree-ring chronologies extended 800
years or more (PAG and LYV; Fig. 3 and Table 3), which corroborates findings
from a previous study <xref ref-type="bibr" rid="bib1.bibx35" id="paren.44"/> on the potential of this species for
providing long paleoclimatic reconstructions. Combining the resultant common
period among the tree-ring chronologies (1606–2005) with the expressed
population signal (EPS) statistic yielded a 296-year (1709–2005) time series
of reconstructed summer streamflow. Although the EPS for the PIN chronology
was 0.85 only after 1750 (Table 4), the large number of tree-growth series in
the PAG and LYV chronologies (20 and 34 by 1709, respectively; see Fig. 3)
allowed for the reconstruction to begin in 1709. An EPS greater than 0.85 for
a given tree-ring chronology is often assumed as proof of its reliability,
because it indicates that at least 85 % of the chronology variance
corresponds to a common signal <xref ref-type="bibr" rid="bib1.bibx56" id="paren.45"/>. Additionally, the VIF for
the reconstruction period had values close to 1, especially for the PAG
chronology, indicating that the regression model had no problems of
multicollinearity (Table 4). From Table 4 we also noted that the chronologies
presented high autocorrelation, consistent with the fact that tree growth has
a temporal memory associated with trees' capacity to store carbon and water,
and the uptake rate of soil moisture remaining from previous seasons and
years. Some of the statistical procedures applied to the tree-ring
chronologies are meant to minimize these effects, but it is virtually
impossible to eliminate all. However, when calculated for the reconstruction
the autocorrelation reduced to 0.25 which, although high considering that the
instrumental record is essentially free from autocorrelation (<inline-formula><mml:math id="M78" display="inline"><mml:mo lspace="0mm">-</mml:mo></mml:math></inline-formula>0.093), is
nevertheless better than the individual chronologies. We extended this record
using the composite instrumental record and the variance of the
reconstruction. This way, the reconstruction allowed us to cover and assess
the hydroclimatic significance of the latest anomalous dry period detected
for central Chile (2011–2015), referred to as the “megadrought”
<xref ref-type="bibr" rid="bib1.bibx20" id="paren.46"/>.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F4" specific-use="star"><?xmltex \currentcnt{4}?><label>Figure 4</label><caption><p id="d1e1872">Summer streamflow reconstruction for the Río Imperial. Panel (<bold>a</bold>) compares standardized anomalies of observed (instrumental)
streamflow and our tree-ring reconstruction. Panel (<bold>b</bold>) depicts the
coherence of cycles between both time series. Panel (<bold>c</bold>)  corresponds to
the streamflow reconstruction, including the envelope for the <inline-formula><mml:math id="M79" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula>2 standard
error (SE), a spline filter, and a classification of each year in the
percentiles of the probability distribution (bottom section).</p></caption>
          <?xmltex \igopts{width=341.433071pt}?><graphic xlink:href="https://hess.copernicus.org/articles/22/2921/2018/hess-22-2921-2018-f04.pdf"/>

        </fig>

      <p id="d1e1897">Comparison between standardized anomalies of the reconstruction and
observations during the calibration period (1947–2010) suggested a high
reconstruction skill for summer streamflow record (Fig. 4a). We
also computed<?pagebreak page2927?> correlations between observed and reconstructed streamflow and TEM
for each month of the previous year, finding significant figures for December
and February of the previous year (<inline-formula><mml:math id="M80" display="inline"><mml:mi>p</mml:mi></mml:math></inline-formula> value <inline-formula><mml:math id="M81" display="inline"><mml:mo>&lt;</mml:mo></mml:math></inline-formula> 0.1 and <inline-formula><mml:math id="M82" display="inline"><mml:mo>&lt;</mml:mo></mml:math></inline-formula> 0.05, respectively) in
the case of the instrumental record; for the reconstruction, the correlation
is significant for June and December (<inline-formula><mml:math id="M83" display="inline"><mml:mi>p</mml:mi></mml:math></inline-formula> value &lt; 0.05; see details in Fig. S3).
In addition, an analysis of coherence between dominant periods showed that
both time series presented similar cycles of 3, 5, and 30 years (Fig. 4b). This good performance was further corroborated with these
statistics: (a) <inline-formula><mml:math id="M84" display="inline"><mml:mrow><mml:msup><mml:mi>R</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula>adj <inline-formula><mml:math id="M85" display="inline"><mml:mo>=</mml:mo></mml:math></inline-formula> 0.47, indicating that the regression
model explained 47 % of the variance in the predictand; (b) small errors,
with RMSE <inline-formula><mml:math id="M86" display="inline"><mml:mo>=</mml:mo></mml:math></inline-formula> 0.71, RE <inline-formula><mml:math id="M87" display="inline"><mml:mo>=</mml:mo></mml:math></inline-formula> 0.36, and SE <inline-formula><mml:math id="M88" display="inline"><mml:mo>=</mml:mo></mml:math></inline-formula> 0.66; (c) a statistically significant model
as reflected by the F statistic (10.08, <inline-formula><mml:math id="M89" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">0.0001</mml:mn></mml:mrow></mml:math></inline-formula>); while (d) the residuals
were not auto-correlated (Durbin–Watson <inline-formula><mml:math id="M90" display="inline"><mml:mo>=</mml:mo></mml:math></inline-formula> 2.25, <inline-formula><mml:math id="M91" display="inline"><mml:mi>p</mml:mi></mml:math></inline-formula> value <inline-formula><mml:math id="M92" display="inline"><mml:mo>&lt;</mml:mo></mml:math></inline-formula> 0.01). Previous
studies have found similar performances for reconstructions in other regions
of the world (e.g., <xref ref-type="bibr" rid="bib1.bibx58" id="altparen.47"/>), which lead us to assert that our
reconstruction is a reliable representation of the Río Imperial's summer
streamflow. Another proof is the detection of significant agreement between
the reconstruction and observations for the period 1980–2010 for the region
<inline-formula><mml:math id="M93" display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 35–42<inline-formula><mml:math id="M94" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S (Fig. S2).</p>
      <p id="d1e2022">We evaluated trends and frequency of extreme events for the whole
reconstructed period. This analysis revealed a negative, although not
statistically significant, trend for the reconstruction. What we did observe
was a low frequency of extreme flows, although during most of the
20th century (<inline-formula><mml:math id="M95" display="inline"><mml:mo lspace="0mm">∼</mml:mo></mml:math></inline-formula> 1910–1970) high flows (above the 60th
percentile) clustered. However, low-flow periods (below the 20th
percentile) occurred more frequently in the late 1800s, early 1900s, and
after 1980. Importantly, streamflow below the historical average
characterized the post-1980 period (Fig. 4c). The application of
the Blackman–Tukey method allowed us to detect high frequency cycles (2–7
years) and mid-to-low frequency (<inline-formula><mml:math id="M96" display="inline"><mml:mo lspace="0mm">&gt;</mml:mo></mml:math></inline-formula> 8 years). The multitaper method and the
singular spectral analysis revealed that a <inline-formula><mml:math id="M97" display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 4-year cycle captures 10 %
of the variance, a <inline-formula><mml:math id="M98" display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 7-year cycle captures 7 %, while we also found a
16–20-years cycle, corresponding to 20 % of the variance. This last long
cycle was also found when applying a<?pagebreak page2928?> continuous wavelet transform analysis,
in this case a significant 16–32-year frequency between 1800 and 1950; higher
frequency cycles occur along the whole period but appear to be more significant
after 1900 (Fig. S4).</p>
      <p id="d1e2053">In order to assess the uniqueness of this recent period of extreme summer
streamflow, we (a) divided the tree-ring reconstruction into continuous
periods of 1, 5, 10, and 20 years, and (b) ranked those periods
according to their departure from the mean. Although somewhat arbitrary,
the length of these windows are defined as a mean for providing context for
the occurrence of extreme flows along the whole study period in way that is
easier to understand for water managers. According to this classification,
the dry period 1996–2000, one of the driest in the instrumental record, ranks
fourth in the reconstruction, closely followed by 1987–1991. Results also
indicated that the lowest flow events since the mid-20th
century are somewhat relevant at the 5-year scale. However, the period
2011–2015 did not show low flows as extreme as other periods in the
reconstruction; it only ranked high in the instrumental record. At the
10-year scale, post-1980 low discharges ranked only third and fourth. The
most striking relevance of modern low flow appeared at the 20-year scale,
where the period 1986–2005 ranked first, suggesting that this period was the driest
since the beginning of the reconstruction. The same analysis for extremely
high streamflow showed that the mid-20th century was
persistently ranked among the five in all the timescales considered (Table 5).</p>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T5" specific-use="star"><?xmltex \currentcnt{5}?><label>Table 5</label><caption><p id="d1e2059">Rank of the five periods showing highest and lowest discharges as
calculated from the tree-ring reconstruction. These periods were organized
according to windows of 5, 10, and 20 years. At the bottom of each period
we included the highest and lowest streamflow from the instrumental record.
Periods in bold represent coincidence between instrumental and reconstructed
streamflow.</p></caption><oasis:table frame="topbot"><oasis:tgroup cols="4">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="left"/>
     <oasis:colspec colnum="3" colname="col3" align="right"/>
     <oasis:colspec colnum="4" colname="col4" align="right"/>
     <oasis:thead>
       <oasis:row>
         <oasis:entry colname="col1">Period length</oasis:entry>
         <oasis:entry colname="col2">Rank</oasis:entry>
         <oasis:entry colname="col3">High flow</oasis:entry>
         <oasis:entry colname="col4">Low flow</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">(years)</oasis:entry>
         <oasis:entry colname="col2"/>
         <oasis:entry colname="col3"/>
         <oasis:entry colname="col4"/>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2">1</oasis:entry>
         <oasis:entry colname="col3">1951</oasis:entry>
         <oasis:entry colname="col4">1755</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2">2</oasis:entry>
         <oasis:entry colname="col3">1838</oasis:entry>
         <oasis:entry colname="col4">1897</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">1</oasis:entry>
         <oasis:entry colname="col2">3</oasis:entry>
         <oasis:entry colname="col3">1832</oasis:entry>
         <oasis:entry colname="col4">1901</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2">4</oasis:entry>
         <oasis:entry colname="col3">1858</oasis:entry>
         <oasis:entry colname="col4">1902</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2">5</oasis:entry>
         <oasis:entry colname="col3">1940</oasis:entry>
         <oasis:entry colname="col4">1867</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2">Instrumental record</oasis:entry>
         <oasis:entry colname="col3">1956</oasis:entry>
         <oasis:entry colname="col4">1999</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2">1</oasis:entry>
         <oasis:entry colname="col3">1951–1955</oasis:entry>
         <oasis:entry colname="col4">1897–1901</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2">2</oasis:entry>
         <oasis:entry colname="col3">1829–1833</oasis:entry>
         <oasis:entry colname="col4">1753–1757</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">5</oasis:entry>
         <oasis:entry colname="col2">3</oasis:entry>
         <oasis:entry colname="col3">1938–1942</oasis:entry>
         <oasis:entry colname="col4">1811–1815</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2">4</oasis:entry>
         <oasis:entry colname="col3">1797–1801</oasis:entry>
         <oasis:entry colname="col4">1996–2000</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2">5</oasis:entry>
         <oasis:entry colname="col3">1935–1939</oasis:entry>
         <oasis:entry colname="col4">1987–1991</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2">Instrumental record</oasis:entry>
         <oasis:entry colname="col3">1955–1959</oasis:entry>
         <oasis:entry colname="col4">2011–2015</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2">1</oasis:entry>
         <oasis:entry colname="col3">1829–1838</oasis:entry>
         <oasis:entry colname="col4">1896–1905</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2">2</oasis:entry>
         <oasis:entry colname="col3">1933–1942</oasis:entry>
         <oasis:entry colname="col4">1751–1760</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">10</oasis:entry>
         <oasis:entry colname="col2">3</oasis:entry>
         <oasis:entry colname="col3"><bold>1950–1959</bold></oasis:entry>
         <oasis:entry colname="col4"><bold>1990–1999</bold></oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2">4</oasis:entry>
         <oasis:entry colname="col3">1796–1805</oasis:entry>
         <oasis:entry colname="col4">1982–1991</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2">5</oasis:entry>
         <oasis:entry colname="col3">1964–1973</oasis:entry>
         <oasis:entry colname="col4">1810–1819</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2">Instrumental record</oasis:entry>
         <oasis:entry colname="col3"><bold>1950–1959</bold></oasis:entry>
         <oasis:entry colname="col4"><bold>1990–1999</bold></oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2">1</oasis:entry>
         <oasis:entry colname="col3">1934–1953</oasis:entry>
         <oasis:entry colname="col4"><bold>1986–2005</bold></oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2">2</oasis:entry>
         <oasis:entry colname="col3">1823–1842</oasis:entry>
         <oasis:entry colname="col4">1753–1772</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">20</oasis:entry>
         <oasis:entry colname="col2">3</oasis:entry>
         <oasis:entry colname="col3"><bold>1953–1972</bold></oasis:entry>
         <oasis:entry colname="col4">1883–1902</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2">4</oasis:entry>
         <oasis:entry colname="col3">1728–1744</oasis:entry>
         <oasis:entry colname="col4">1803–1865</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2">5</oasis:entry>
         <oasis:entry colname="col3">1785–1804</oasis:entry>
         <oasis:entry colname="col4">1843–1865</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1"/>
         <oasis:entry colname="col2">Instrumental record</oasis:entry>
         <oasis:entry colname="col3"><bold>1953–1972</bold></oasis:entry>
         <oasis:entry colname="col4"><bold>1986–2005</bold></oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup></oasis:table></table-wrap>

      <?xmltex \floatpos{t}?><fig id="Ch1.F5"><?xmltex \currentcnt{5}?><label>Figure 5</label><caption><p id="d1e2463">Summer streamflow reconstruction and the periods of low flow. In
<bold>(a)</bold> the 10th (red) and 20th (purple)
percentiles are plotted over the time series. Panel <bold>(b)</bold> shows the return period of
each low flow (below the 10 and 20th
percentiles) for the whole record.</p></caption>
          <?xmltex \igopts{width=236.157874pt}?><graphic xlink:href="https://hess.copernicus.org/articles/22/2921/2018/hess-22-2921-2018-f05.pdf"/>

        </fig>

      <p id="d1e2478">Since 1980, the frequency of years in the lowest percentile has increased. We calculated the return period of
these low-flow years in different periods of the reconstruction. We found
(a) that during 1709–1750 and 1940–1960, events with streamflow below the
20th percentile had a 20-year return period; (b) a 5-year return
period in 1750–1880; (c) a predominantly 2- to 3-year period for 1880–1930;
and (d) a trend toward a 2-year return period since 1960. In addition, we
found that since <inline-formula><mml:math id="M99" display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 1980 droughts below the 10th
percentile have become more frequent (Fig. 5).</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F6"><?xmltex \currentcnt{6}?><label>Figure 6</label><caption><p id="d1e2491">Comparison between the tree-ring reconstruction of Río Imperial
streamflow versus the tree-ring precipitation reconstruction
presented in <xref ref-type="bibr" rid="bib1.bibx54" id="text.48"/> and the AAO tree-ring reconstruction from
<xref ref-type="bibr" rid="bib1.bibx55" id="text.49"/> that also utilized an index of SAM based on pressure
fields from NCAR–NCEP reanalysis <xref ref-type="bibr" rid="bib1.bibx49" id="paren.50"/>. In <bold>(a)</bold>, these time
series are displayed at annual resolution while <bold>(b)</bold> shows the same time
series after the application of a 30-year spline filter. In both panels, the
AAO index has been inverted to facilitate comparison with respect to tree-ring
reconstructions. Pearson correlations between the streamflow reconstruction
and the other time series are included at the bottom of each panel, with
asterisks representing statistically significant correlations at <inline-formula><mml:math id="M100" display="inline"><mml:mi>p</mml:mi></mml:math></inline-formula> value <inline-formula><mml:math id="M101" display="inline"><mml:mo>&lt;</mml:mo></mml:math></inline-formula> 0.001.</p></caption>
          <?xmltex \igopts{width=236.157874pt}?><graphic xlink:href="https://hess.copernicus.org/articles/22/2921/2018/hess-22-2921-2018-f06.pdf"/>

        </fig>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T6"><?xmltex \currentcnt{6}?><label>Table 6</label><caption><p id="d1e2533">Comparison between streamflow observations and streamflow
reconstructed versus ENSO and SAM for the period 1948–2005, where “<inline-formula><mml:math id="M102" display="inline"><mml:mi>r</mml:mi></mml:math></inline-formula>”
corresponds to the Pearson correlation coefficient</p></caption><oasis:table frame="topbot"><oasis:tgroup cols="4">
     <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:thead>
       <oasis:row>
         <oasis:entry colname="col1">Streamflow</oasis:entry>
         <oasis:entry colname="col2">Index</oasis:entry>
         <oasis:entry colname="col3">Months</oasis:entry>
         <oasis:entry colname="col4"><inline-formula><mml:math id="M103" display="inline"><mml:mi>r</mml:mi></mml:math></inline-formula></oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1">record</oasis:entry>
         <oasis:entry colname="col2"/>
         <oasis:entry colname="col3"/>
         <oasis:entry colname="col4"/>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>
         <oasis:entry colname="col1">Instrumental</oasis:entry>
         <oasis:entry colname="col2">AAO</oasis:entry>
         <oasis:entry colname="col3">October–September</oasis:entry>
         <oasis:entry colname="col4"><inline-formula><mml:math id="M104" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.58</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Instrumental</oasis:entry>
         <oasis:entry colname="col2">SOI</oasis:entry>
         <oasis:entry colname="col3">February–March</oasis:entry>
         <oasis:entry colname="col4">0.32</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Instrumental</oasis:entry>
         <oasis:entry colname="col2">AAO</oasis:entry>
         <oasis:entry colname="col3">September–December</oasis:entry>
         <oasis:entry colname="col4"><inline-formula><mml:math id="M105" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.54</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Reconstruction</oasis:entry>
         <oasis:entry colname="col2">AAO</oasis:entry>
         <oasis:entry colname="col3">September–August</oasis:entry>
         <oasis:entry colname="col4"><inline-formula><mml:math id="M106" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.66</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Reconstruction</oasis:entry>
         <oasis:entry colname="col2">AAO</oasis:entry>
         <oasis:entry colname="col3">December–February</oasis:entry>
         <oasis:entry colname="col4"><inline-formula><mml:math id="M107" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.50</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Reconstruction</oasis:entry>
         <oasis:entry colname="col2">SOI</oasis:entry>
         <oasis:entry colname="col3">March</oasis:entry>
         <oasis:entry colname="col4">0.36</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1">Reconstruction</oasis:entry>
         <oasis:entry colname="col2">AAO</oasis:entry>
         <oasis:entry colname="col3">September–December</oasis:entry>
         <oasis:entry colname="col4"><inline-formula><mml:math id="M108" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.54</oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup></oasis:table></table-wrap>

      <p id="d1e2731">We found the Río Imperial reconstruction and the precipitation
reconstruction for northern Patagonia <xref ref-type="bibr" rid="bib1.bibx54" id="paren.51"/> to be significantly
correlated. Closer inspection of the year-to-year correspondence between
these two reconstructions (Fig. 6a) revealed that the interannual variability
was somewhat different, especially for the most negative departures in which
there was occasional coincidence. A 30-year spline filter shows the similarity
at lower frequency between these two time series, although with noticeable
lags (nevertheless irregular in length) between peaks and troughs, as for
example in the period <inline-formula><mml:math id="M109" display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 1730–1740 (Fig. 6b). Overall, the reconstructions
coincided with the number and length of high and low periods.</p><?xmltex \hack{\newpage}?>
</sec>
<?pagebreak page2929?><sec id="Ch1.S3.SS3">
  <label>3.3</label><title>Streamflow correlation with regional climate modes of variability</title>
      <?pagebreak page2930?><p id="d1e2753">The instrumental discharge record correlated with the ENSO and the SAM
(Table 6). While summer discharge had a Pearson correlation of 0.32 with the SOI
from February to March of the previous year, the coefficient was as high as
<inline-formula><mml:math id="M110" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.66 with the AAO of the previous 12 months (September to August). The
AAO-streamflow correlation of streamflow with the instrumental record and
tree-ring reconstruction were identical when calculated for the period
September-December of the immediate previous year. This correlation was
weaker (<inline-formula><mml:math id="M111" display="inline"><mml:mo lspace="0mm">-</mml:mo></mml:math></inline-formula>0.3) when we removed the linear trend, indicating that a significant
portion of the streamflow trend is shared with the trend in the AAO. The
agreement for September–December, as well as the relatively similar
correlations observed for February–March (instrumental record) and March
(tree-ring), reaffirmed the previous finding about the high skill of the
reconstruction to reproduce essential properties of the instrumental record.
An additional confirmation of the influence of the SAM on streamflow can be
observed in Fig. 6, where we found a similar correlation between a long-term
reconstruction of the AAO <xref ref-type="bibr" rid="bib1.bibx55" id="paren.52"/> and our streamflow
reconstruction, with a statistically significant Pearson <inline-formula><mml:math id="M112" display="inline"><mml:mi>r</mml:mi></mml:math></inline-formula> of <inline-formula><mml:math id="M113" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.33 for both
high and low frequencies. In order to discard the possibility of a
nonsignificant correlation, we performed further correlations between the
AAO and a prewhitened version of (a) the reconstruction and (b) the
observations (removing the lag-1 autocorrelation). Results reaffirmed the
negative and statistically significant correlation, with <inline-formula><mml:math id="M114" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.287
(<inline-formula><mml:math id="M115" display="inline"><mml:mi>p</mml:mi></mml:math></inline-formula> value <inline-formula><mml:math id="M116" display="inline"><mml:mo>=</mml:mo></mml:math></inline-formula> 0.033) for the reconstruction and <inline-formula><mml:math id="M117" display="inline"><mml:mo>-</mml:mo></mml:math></inline-formula>0.29 (<inline-formula><mml:math id="M118" display="inline"><mml:mi>p</mml:mi></mml:math></inline-formula> value <inline-formula><mml:math id="M119" display="inline"><mml:mo>=</mml:mo></mml:math></inline-formula> 0.029) for the
observation. In the case of the IPO, we found a statistically
significant negative correlation between that time series and the 16–20-year
cycle of our reconstruction (<inline-formula><mml:math id="M120" display="inline"><mml:mo lspace="0mm">-</mml:mo></mml:math></inline-formula>0.38, <inline-formula><mml:math id="M121" display="inline"><mml:mrow><mml:mi>n</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">295</mml:mn></mml:mrow></mml:math></inline-formula>), although it looks more coherent
during the 20th century.</p>
</sec>
</sec>
<sec id="Ch1.S4">
  <label>4</label><title>Discussion</title>
      <p id="d1e2859">The tree-ring reconstruction for the Río Imperial has revealed new
information on and insights into long-term streamflow variability, thus
allowing for the assessment of changes in summer water availability
in the SCC region, including the long-term significance of recent
extreme hydrological events throughout the region. This streamflow
reconstruction corresponds to the fifth record for Chilean rivers, but the
very first focused on summer streamflow. Some of our findings agree with
those of previous studies, which strongly suggests that our reconstruction
represents well the summer hydroclimate of a large region in SCC. This is
manifested by the good skill of our reconstruction in simulating instrumental
records along the wider region 35–42<inline-formula><mml:math id="M122" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> S (Fig. S2), which further
supports findings by <xref ref-type="bibr" rid="bib1.bibx24" id="text.53"/>, who stated that this region
configures a hydroclimatic cluster.</p>
      <p id="d1e2874">The noticeable decreasing trend post-1980 observed in the instrumental record
as well as in our reconstruction, which was to a certain extent identified in
all previous reconstructions <xref ref-type="bibr" rid="bib1.bibx30 bib1.bibx31 bib1.bibx52 bib1.bibx37" id="paren.54"/>,
corroborates the occurrence of an ongoing and unprecedented long-lasting
summer low flow in SCC, which also includes the recent drought detected for
central Chile <xref ref-type="bibr" rid="bib1.bibx20" id="paren.55"/>. We note that the post-1980 period
represents <inline-formula><mml:math id="M123" display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 50 % of the composite instrumental time series, while it only
represents <inline-formula><mml:math id="M124" display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 10 % of the reconstructed period; we posit this highlights the
uniqueness of the post-1980 period. Thus, this period is noteworthy as the
one with the lowest summer streamflow of the whole reconstruction. This low-flow period gradually emerged as the most acute as the time window was
broadened (Table 5), despite the fact that no year during this timespan
ranked high in the lowest percentile of the reconstruction. As shown above,
the decreasing trend observed in our results has already been detected in
other rivers of the region, specifically south of
<inline-formula><mml:math id="M125" display="inline"><mml:mo>∼</mml:mo></mml:math></inline-formula> 37 <inline-formula><mml:math id="M126" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>30<inline-formula><mml:math id="M127" display="inline"><mml:msup><mml:mi/><mml:mo>′</mml:mo></mml:msup></mml:math></inline-formula> S <xref ref-type="bibr" rid="bib1.bibx33 bib1.bibx43" id="paren.56"/>. The
implications of this finding for water management and planning purposes are
related to the ability to detect the effect of regional climate changes in
the area. The increasing number of low-flow years may indicate a regime shift
in the summer dynamics, which can be exacerbated with predicted increased
warming and precipitation reduction in SCC <xref ref-type="bibr" rid="bib1.bibx20" id="paren.57"/>. Our results
indicated a decreasing trend in summer streamflow with a smaller natural
variability when compared with the rest of the tree-ring record.</p>
      <p id="d1e2929">Our results additionally posited the SAM as the most influential climate mode
driving the variability of the Río Imperial's summer streamflow, especially
during the second half of the 20th century. The correlation we found
between SAM and the reconstruction establishes the tree-ring time series as
independent new proof of the importance of the SAM in modulating
precipitation and streamflow in a large region of central and southern Chile
<xref ref-type="bibr" rid="bib1.bibx55 bib1.bibx37" id="paren.58"/>. The SAM has been extensively described as a
strong modulator of precipitation variability in SCC
<xref ref-type="bibr" rid="bib1.bibx2 bib1.bibx55 bib1.bibx23" id="paren.59"/>. The tree-ring
reconstruction showed a statistically significant correlation with the SAM
reconstruction presented in <xref ref-type="bibr" rid="bib1.bibx55" id="text.60"/>, especially for the
long-term trend; we consider that this result confirms that the
reconstruction of summer streamflow for the Río Imperial captures
characteristics of the regional hydroclimate. The reconstruction featured in
<xref ref-type="bibr" rid="bib1.bibx55" id="text.61"/> contains two of the tree-ring chronologies presented in
our study (PIN and LAN), in a pool of more than 1000 series developed from
different species of the Southern Hemisphere. Our summer streamflow
reconstruction is key in further supporting the SAM–streamflow relationship,
because in this season and overall, snowmelt is a minor contributor to
discharge (see Fig. 2). This makes rainfall the principal source of water for
the river. During the last 75 years or so, the SAM has been shifting to a
positive phase, unprecedented in the last 1000 years
<xref ref-type="bibr" rid="bib1.bibx1" id="paren.62"/>. A positive phase means that the pressure gradient
between the midlatitudes and the polar latitudes is negative, that is, more
positive or less negative in the midlatitudes relative to polar latitudes.
This gradient shifts the core of the southern westerly winds towards the
south, limiting the effect of storm tracks over midlatitudes. In the past,
the SAM has been shown to be negatively correlated with the frontal activity
and hence precipitation amounts, especially for the spring season
<xref ref-type="bibr" rid="bib1.bibx48" id="paren.63"/>. Given the relatively short delay between precipitation
and discharge in the region (e.g., <xref ref-type="bibr" rid="bib1.bibx60" id="altparen.64"/>), this relationship
may well explain the decreasing summer streamflow trend observed for recent
decades, as detected in the September–December negative correlation between
the AAO in relation to both instrumental records and the tree-ring
reconstruction (Table 5). This way, the post-1980 trend in summer streamflow
of the Río Imperial may be linked to the aforementioned positive phase of
the SAM <xref ref-type="bibr" rid="bib1.bibx1" id="paren.65"/>. This evidence suggests an unprecedented
decreasing trend of the Río Imperial's summer streamflow for at least the
last 3 centuries, which may well be extrapolated to the last few millennia
considering the correlation with the SAM. However, it is important to
consider results according to <xref ref-type="bibr" rid="bib1.bibx8" id="text.66"/> on the relationship
between precipitation, frontal activity, the ENSO, and the SAM in the
Southern Hemisphere. In that study, ENSO (defined as the second empirical
orthogonal function (EOF) from monthly anomalies at the 500 hPa geopotential
level) had higher correlation with frontal activity in spring at the
interannual timescale, although the correlation was also<?pagebreak page2931?> statistically
significant with the SAM (defined as the first EOF from monthly anomalies of
the 500 hPa geopotential level). <xref ref-type="bibr" rid="bib1.bibx8" id="text.67"/> also demonstrated that
precipitation in SCC is significantly correlated with frontal activity. These
studies suggest that the impact of the SAM on precipitation in the study area
can also be associated with ENSO dynamics. For example, the low flow for the
summer 1999 was concomitant with a high AAO and a strong La Niña event in
1998–1999. Recent studies have found that in-phase (e.g., positive ENSO and
positive SAM) and out-of-phase occurrences of these climate modes can lead to
varying strength of the associated atmospheric circulation
<xref ref-type="bibr" rid="bib1.bibx18 bib1.bibx57" id="paren.68"/>, possibly controlling the intensity of their
impacts on precipitation and hence streamflow. In fact, <xref ref-type="bibr" rid="bib1.bibx41" id="text.69"/>
in a study analyzing the changes in rainfall in central and south-central
Chile found that ENSO and AAO are not independent modes of variability but
rather they both affect precipitation regimes. It is also important to
consider possible different seasonal effects of these modes of variability,
for example those found by <xref ref-type="bibr" rid="bib1.bibx4" id="text.70"/>, who, utilizing a 11-year
moving average of a 300-year tree-ring streamflow reconstruction for the
upper Biobío river, determined a negative correlation between the Pacific
Decadal Oscillation (PDO) and streamflow during the snowmelt season
(October–March) while a positive correlation between the SAM and that
seasonal streamflow. Thus, we believe that the SAM–streamflow statistical
relationship we found should be tested further in order to develop more
accurate predictive models of extreme interannual dynamics. Using output from
the CMIP5, <xref ref-type="bibr" rid="bib1.bibx32" id="text.71"/> predicted that the positive phase of the SAM will
continue in some climate change projections, likely (but not certainly, given
the difficulties in simulating the ENSO–SAM interactions) impacting
precipitation in the midlatitudes. In this scenario, the SAM could provide
more accurate statistical models of return periods.</p>
      <p id="d1e2976">Another relevant aspect of our reconstruction is that, like previous studies,
it seemed to better represent low-flow conditions rather than high flows.
<xref ref-type="bibr" rid="bib1.bibx52" id="text.72"/> discussed this finding in their reconstruction of the
Río Maule, arguing, following <xref ref-type="bibr" rid="bib1.bibx54" id="text.73"/>, that this was likely a
consequence of a smaller sensitivity of tree growth to precipitation above a
certain threshold. However, the <inline-formula><mml:math id="M128" display="inline"><mml:mrow><mml:msup><mml:mi>R</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula>adj values of previous studies
do not completely support that argument as the highest
<inline-formula><mml:math id="M129" display="inline"><mml:mrow><mml:msup><mml:mi>R</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula>adj (54 %) was found in the Río Baker streamflow
reconstruction <xref ref-type="bibr" rid="bib1.bibx31" id="paren.74"/>, the southernmost and the wettest landscape
of all sampled locations in Chile. In terms of <inline-formula><mml:math id="M130" display="inline"><mml:mrow><mml:msup><mml:mi>R</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula>adj, our
reconstruction ranks second (47 %), followed by Biobío (45 %,
<xref ref-type="bibr" rid="bib1.bibx37" id="altparen.75"/>), while Puelo <xref ref-type="bibr" rid="bib1.bibx30" id="text.76"/> and Maule
<xref ref-type="bibr" rid="bib1.bibx52" id="text.77"/> rank together with the lowest explained variance (42 %).
Notice that the two highest ranked reconstructions represent summer to fall
streamflow, when the soil moisture is at its lowest in the annual cycle.
<xref ref-type="bibr" rid="bib1.bibx16" id="text.78"/> summarized empirical and theoretical arguments to
better understand, on the one hand, the physical process linking tree growth
and streamflow and, on the other hand, what determines whether tree-ring
reconstructions reproduce dry conditions. In that study, the authors
presented data from the Oldman River basin (<inline-formula><mml:math id="M131" display="inline"><mml:mo lspace="0mm">∼</mml:mo></mml:math></inline-formula> 49<inline-formula><mml:math id="M132" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula> 40<inline-formula><mml:math id="M133" display="inline"><mml:msup><mml:mi/><mml:mo>′</mml:mo></mml:msup></mml:math></inline-formula> N),
a cold semiarid watershed in western Canada. They suggested the likelihood
of spurious self-correlation in the statistical models relating streamflow
and tree-rings because precipitation may be considered as a confounding
factor. The mechanism these authors suggested is that soil moisture modulates
the relationship between tree growth and other hydrometeorological variables
(e.g., evaporation or runoff), more so in areas (and perhaps seasons) where
(when) soil moisture is relatively constant. Following these arguments, one
should expect streamflow reconstructions to better represent years or periods
of water scarcity rather than high flows. <xref ref-type="bibr" rid="bib1.bibx16" id="text.79"/> indeed found
higher correlations between low flow and tree-ring width in the Oldman River
basin. Our analysis, and the fact that the two of the previously reported
reconstructions for Chile with the highest <inline-formula><mml:math id="M134" display="inline"><mml:mrow><mml:msup><mml:mi>R</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula>adj aimed
to include summer months, suggest that reconstructions focusing on summer
streamflow (at least partially as in the case in <xref ref-type="bibr" rid="bib1.bibx31" id="altparen.80"/>) have physical
meaning and not just statistical significance. This renders the Río
Imperial reconstruction as a representative time series of summer streamflow
for the last 301 years, with a high capacity for capturing the occurrence of dry
years. However, further research is needed because the Río Puelo
reconstruction <xref ref-type="bibr" rid="bib1.bibx30" id="paren.81"/>, also aiming for summer to fall streamflow, did
not rank as high as our reconstruction and the one for Río Baker.</p>
      <p id="d1e3081">Given the crucial role that summer streamflow plays in a number of economic
activities, such as agriculture and human consumption in the basin, the
tree-ring reconstruction we have presented here can provide water managers
and stakeholders with improved support for decision-making and regional
planning. For example, the post-1980 generalized regional decrease in
streamflow, both instrumental <xref ref-type="bibr" rid="bib1.bibx43" id="paren.82"/> and reconstructed
(e.g., <xref ref-type="bibr" rid="bib1.bibx30" id="altparen.83"/>), paralleled paradigmatic legal and institutional
changes in national water management, whereby the policy to assign water
rights (and hence rights to use a proportion of the streamflow) transited
into a model “with strong private property rights, broad private economic
freedoms, and weak government regulation” (verbatim <xref ref-type="bibr" rid="bib1.bibx5" id="altparen.84"/>).
There is growing evidence of increasing water conflicts in SCC despite recent
reform in this legal framework of water rights allocation <xref ref-type="bibr" rid="bib1.bibx6" id="paren.85"/>.
Some have argued that at least part of the problem resides in the
insufficient hydrological information for users, managers, and decision
makers <xref ref-type="bibr" rid="bib1.bibx15" id="paren.86"/>. The relevance for water management in Chile is
related to the mechanism for granting water rights, since it relies on the
average river flow. By using this system, water rights have often exceeded
the actual flow of rivers, specifically for the summer, forcing authorities
to decree zones of water scarcity<fn id="Ch1.Footn3"><p id="d1e3100">An example of a decree for
watersheds in the north of Chile can be found here
<uri>https://goo.gl/S3n8d3</uri> (last access: 17 April 2017).</p></fn>. With the
information obtained from tree-ring reconstructions, it is feasible for
authorities to anticipate scenarios of future crises, particularly in drought
cycles such as those described here. In this regard, a recently enacted (and
modified) official decree defined the minimum ecological discharge as the
lowest 50 % of the 95 % confidence interval below the average discharge,
determined from a probability distribution using a period of at least 25
years of instrumental observations<fn id="Ch1.Footn4"><p id="d1e3107">See modification to decree
N <inline-formula><mml:math id="M135" display="inline"><mml:msup><mml:mi/><mml:mo>∘</mml:mo></mml:msup></mml:math></inline-formula>12, 2013, Ministerio del Medio Ambiente, Chile, available at
<uri>https://goo.gl/uWyH9R</uri> (last access: 17 April 2017).</p></fn>. The minimum
ecological discharge is the current measure to determine when a given stream
is so depleted that no more water rights must be allocated. Certainly, the
25-year window reflects the limited number of long-term records to reliably
characterize streamflow throughout the country, obligating authorities to
assume that the hydroclimatic regime of a given river is captured by a
relatively short instrumental record. Interestingly, the text of the decree
may likewise allow for the incorporation of tree-rings to inform the process
of water rights allocation, since it actually (a) establishes the 25-year
term as a minimum criteria for using available records to define the average
river flow and (b) empowers the Chilean National Water Authority to
incorporate other methods for river flow determination. On the other hand,
this new decree defines explicitly that streamflow information has to be
retrieved from an intake point, potentially limiting the use of tree-ring
data because they usually represent hydroclimatic variability at the
watershed scale. We argue that information derived from the multicentennial
view of streamflow that tree-rings provide can help to better contextualize
calculations from instrumental records, providing an additional “watershed”
or regional perspective on water management. Our results indicated that the
years of lowest discharge from the instrumental record did not classify as
the most extreme droughts when contextualized in the longer tree-ring
reconstruction. This suggests that, for instance, the drought in 1998–1999
was not as extreme as other events in the past 301 years. Episodes such as
the 1968–1969 (which in the case of the decree would need a period of at
least 48 years to be detected) and 1998–1999 droughts impacted the regional
economy with national repercussions, such as a 40 % reduction in
electricity supply <xref ref-type="bibr" rid="bib1.bibx17" id="paren.87"/>. Another example is the dry period
after 2010 <xref ref-type="bibr" rid="bib1.bibx20 bib1.bibx9" id="paren.88"/>, where our reconstructed
streamflow indicates that period was not as extreme as others that occurred
in the last 301 years in SCC. In fact, our analysis indicates that 1996–2000
was a drier period in the reconstruction, although it only ranked fourth in
Table 5. This finding implies that persistent rain deficits or meteorological
droughts do not necessarily translate into extreme low streamflow because the
storage capacity of certain hydrological basins can buffer these effects. We
argue that, in order to understand the impacts and extent of extreme events
such as droughts, tree-ring reconstructions from watersheds representing
diverse hydroclimatic gradients, land-cover characteristics, and
geomorphometry are sorely needed.</p>
</sec>
<?pagebreak page2932?><sec id="Ch1.S5" sec-type="conclusions">
  <label>5</label><title>Conclusions</title>
      <p id="d1e3138">The significance of our findings for planning is related to the need to
consider a long-term view of the natural variability that defines the
discharge regimes across the region. Planning governmental responses for
periods of low flow based upon the 1, 2, or 5-year events detected in
the available instrumental record may lead to ineffective mitigation actions,
because those events may not be the most extreme on record. Considering the
implications of our results, we assert that the extended record we have
provided can be utilized as a complementary source of information for water
resources managers to more accurately determine the range of
“worst-scenario” or “more-recurrent” droughts, thus helping the planning and
implementation of more efficient mitigation policies. There are several
examples where dendrohydrology has provided key information for the
decision-making process. <xref ref-type="bibr" rid="bib1.bibx47" id="text.89"/> presented an example in which a
series of hydroclimatic scenarios derived from tree-ring chronologies were
formally included in a government-supported hypothetical decision-making
exercise where relevant stakeholders were tasked with developing adaptation
measures for drought episodes. In that paper, and in the context of Canadian
water policy, these authors stated that dendrohydrological research is a
legitimate source of information for water resource planning and management.
Another study, which aimed to characterize long-term Athabasca River streamflow in
Alberta, Canada, found that whereas a trend analysis of instrumental data
depicted declining regional flows, a tree-ring reconstruction showed periods
of severe and prolonged low flows not captured by the instrumental record
<xref ref-type="bibr" rid="bib1.bibx46" id="paren.90"/>; suggesting that worst-case scenarios estimated from
historical gauge data likely underestimate the potential magnitudes of
natural droughts in that region <xref ref-type="bibr" rid="bib1.bibx13" id="paren.91"/>. <xref ref-type="bibr" rid="bib1.bibx34" id="text.92"/>
described another application, where the Denver Water Board, the oldest and
largest water supplier in the State of Colorado, USA, wanted to predict
drought scenarios using reconstructions capable of capturing an episode that
occurred during the 1950s as well as other more recent droughts.
<xref ref-type="bibr" rid="bib1.bibx19" id="text.93"/> asserted that dendrohydrology can help in
determining drivers of periods of extreme hydrological episodes in the Upper
Colorado River basin.</p>
      <p id="d1e3156">The evidence presented in our study regarding the relatively dry post-1980
period, the higher frequency of droughts detected in the present for the
Río Imperial relative to previous centuries, and the SAM projected to
follow a positive phase leading to less precipitation altogether suggest that
the<?pagebreak page2933?> regional hydrology is moving toward a new regime of more frequent
(although not necessarily more intense) droughts. In a similar manner, as
has been documented in several recent studies targeting other regions of the world
(e.g., <xref ref-type="bibr" rid="bib1.bibx59" id="altparen.94"/>, and <xref ref-type="bibr" rid="bib1.bibx47" id="altparen.95"/>, among others), our
reconstruction of natural hydroclimatic variability of the Río Imperial can
provide a valuable framework to ponder the impact of anthropogenic climate
change on future hydroclimatic changes in SCC, thus leading to a prudent
water resource management strategy. Furthermore, water managers could use the
reconstructed flows of the Río Imperial to plan mitigation strategies for
drought events with return periods of 5, 10 and 20 years. As this
hydrological application of dendrochronology becomes widely accepted as valid
and water managers realize that this kind of historical information can guide
operational strategies in the forthcoming decades <xref ref-type="bibr" rid="bib1.bibx7" id="paren.96"/>, the
possible regime shift needs to be incorporated into adaptation and mitigation
plans associated with the regional impacts of future global climate changes.
This will avoid, or at least mitigate, the negative consequences of these changes
on the management of water resources for municipal and agricultural water
supplies, electrical power, ecological habitats
(e.g., <xref ref-type="bibr" rid="bib1.bibx11" id="altparen.97"/>),
and impacts on the economic activities in the region as water sources become
stressed.</p>
</sec>

      
      </body>
    <back><notes notes-type="codedataavailability"><title>Code and data availability</title>

      <p id="d1e3175">Codes and data associated with this work can be
accessed by emailing the first three authors.</p>
  </notes><app-group>
        <supplementary-material position="anchor"><p id="d1e3178">The supplement related to this article is available online at: <inline-supplementary-material xlink:href="https://doi.org/10.5194/hess-22-2921-2018-supplement" xlink:title="pdf">https://doi.org/10.5194/hess-22-2921-2018-supplement</inline-supplementary-material>.</p></supplementary-material>
        </app-group><notes notes-type="competinginterests"><title>Competing interests</title>

      <p id="d1e3187">The authors declare that they have no conflict of
interest.</p>
  </notes><ack><title>Acknowledgements</title><p id="d1e3193">We first want to acknowledge the reviewers for their thorough assessment of
our paper; we believe their comments have contributed to a better work.
Support for the researchers involved in this work was provided by the
following sources: (a) Chilean Research Council (FONDECYT 11161061, 11160454,
1171065, and 1171400), the Center for Climate and Resilience Research (CR)2 (FONDAP
15110009); (b) Proyectos Internos Pontificia Universidad Católica de
Valparaíso (039.353/2016 and 039.329/2016); (c) Vicerrectoría de
Investigación Universidad de Concepción (DIUC 208.603.009-1.0);
(d) Programa de Mitigación de Riesgos, Ministerio del Interior y Seguridad
Pública “Proyecto de manejo integrado de cuencas abastecedoras de agua en
la Provincia de Malleco”; and (e) the project “Ecosystem-based strategies
and innovations in water governance networks for adaptation to climate change
in Latin American Landscapes” (EcoAdapt) funded by the European Commission
under FP7 contract ENV.2011.4.2.3-1/283163. Special gratitude is extended to
the Chilean Forest Service (Corporación Nacional Forestal: CONAF) for
helping with fieldwork and giving us the support to develop
dendrochronological research in Araucaria ecosystems. We also acknowledge
Nick Crane for his help in an earlier version of this
paper.
<?xmltex \hack{\newline}?><?xmltex \hack{\newline}?>
Edited by: Günter Blöschl<?xmltex \hack{\newline}?>
Reviewed by:  two anonymous referees</p></ack><ref-list>
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    <!--<article-title-html>Dendrohydrology and water resources management in south-central Chile: lessons from the Río Imperial streamflow reconstruction</article-title-html>
<abstract-html><p>Streamflow in south-central Chile (SCC,  ∼ &thinsp;37–42°&thinsp;S) is vital
for agriculture, forestry production, hydroelectricity, and human
consumption. Recent drought episodes have generated hydrological deficits
with damaging effects on these activities. This region is projected to
undergo major reductions in water availability, concomitant with projected
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hydrological regime is fundamentally pluvial with a small snowmelt
contribution during spring, and evidenced a decreasing trend, both for the
summer and the full annual record. The reconstruction showed that streamflow
below the average characterized the post-1980 period, with more frequent, but
not more intense, drought episodes. We additionally found that the recent
positive phase of the Southern Annular Mode has significantly influenced
streamflow. These findings agree with previous studies, suggesting a robust
regional signal and a shift to a new hydrological scenario. In this paper, we
also discuss implications of these results for water managers and
stakeholders; we provide rationale and examples that support the need for the
incorporation of tree-ring reconstructions into water resources management.</p></abstract-html>
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