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<front>
<journal-meta>
<journal-id journal-id-type="publisher">NHESS</journal-id>
<journal-title-group>
<journal-title>Natural Hazards and Earth System Sciences</journal-title>
<abbrev-journal-title abbrev-type="publisher">NHESS</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">Nat. Hazards Earth Syst. Sci.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">1684-9981</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/nhess-15-853-2015</article-id>
<title-group>
<article-title>Technical Note: An operational landslide early warning system at regional scale based on space–time-variable rainfall thresholds</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Segoni</surname>
<given-names>S.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Battistini</surname>
<given-names>A.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Rossi</surname>
<given-names>G.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Rosi</surname>
<given-names>A.</given-names>
<ext-link>https://orcid.org/0000-0001-8930-5705</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Lagomarsino</surname>
<given-names>D.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Catani</surname>
<given-names>F.</given-names>
<ext-link>https://orcid.org/0000-0001-5185-4725</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Moretti</surname>
<given-names>S.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Casagli</surname>
<given-names>N.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Department of Earth Sciences, University of Firenze, Florence, Italy</addr-line>
</aff>
<pub-date pub-type="epub">
<day>16</day>
<month>04</month>
<year>2015</year>
</pub-date>
<volume>15</volume>
<issue>4</issue>
<fpage>853</fpage>
<lpage>861</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2015 S. Segoni et al.</copyright-statement>
<copyright-year>2015</copyright-year>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit <ext-link ext-link-type="uri"  xlink:href="https://creativecommons.org/licenses/by/3.0/">https://creativecommons.org/licenses/by/3.0/</ext-link></license-p>
</license>
</permissions>
<self-uri xlink:href="https://nhess.copernicus.org/articles/15/853/2015/nhess-15-853-2015.html">This article is available from https://nhess.copernicus.org/articles/15/853/2015/nhess-15-853-2015.html</self-uri>
<self-uri xlink:href="https://nhess.copernicus.org/articles/15/853/2015/nhess-15-853-2015.pdf">The full text article is available as a PDF file from https://nhess.copernicus.org/articles/15/853/2015/nhess-15-853-2015.pdf</self-uri>
<abstract>
<p>We set up an early warning system for rainfall-induced landslides in Tuscany
(23 000 km&lt;sup&gt;2&lt;/sup&gt;). The system is based on a set of state-of-the-art
intensity–duration rainfall thresholds (Segoni et al., 2014b) and makes use
of LAMI (Limited Area Model Italy) rainfall forecasts and real-time rainfall
data provided by an automated network of more than 300 rain gauges.
&lt;br&gt;&lt;br&gt;
The system was implemented in a WebGIS to ease the operational use in civil
protection procedures: it is simple and intuitive to consult, and it provides
different outputs. When switching among different views, the system is able to
focus both on monitoring of real-time data and on forecasting at different
lead times up to 48 h. Moreover, the system can switch between a basic
data view where a synoptic scenario of the hazard can be shown all over the
region and a more in-depth view were the rainfall path of rain gauges can be
displayed and constantly compared with rainfall thresholds.
&lt;br&gt;&lt;br&gt;
To better account for the variability of the geomorphological and
meteorological settings encountered in Tuscany, the region is subdivided
into 25 alert zones, each provided with a specific threshold. The warning
system reflects this subdivision: using a network of more than 300 rain
gauges, it allows for the monitoring of each alert zone separately so that
warnings can be issued independently.
&lt;br&gt;&lt;br&gt;
An important feature of the warning system is that the visualization of the
thresholds in the WebGIS interface may vary in time depending on when the
starting time of the rainfall event is set. The starting time of the
rainfall event is considered as a variable by the early warning system: whenever new rainfall data are available, a recursive algorithm identifies the starting
time for which the rainfall path is closest to or overcomes the threshold.
This is considered the most hazardous condition, and it is displayed by the
WebGIS interface.
&lt;br&gt;&lt;br&gt;
The early warning system is used to forecast and monitor the landslide
hazard in the whole region, providing specific alert levels for 25 distinct
alert zones. In addition, the system can be used to gather, analyze,
display, explore, interpret and store rainfall data, thus representing a
potential support to both decision makers and scientists.</p>
</abstract>
<counts><page-count count="9"/></counts>
</article-meta>
</front>
<body/>
<back>
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