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<journal-meta>
<journal-id journal-id-type="publisher">EGUsphere</journal-id>
<journal-title-group>
<journal-title>EGUsphere</journal-title>
<abbrev-journal-title abbrev-type="publisher">EGUsphere</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">EGUsphere</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub"></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/egusphere-2026-2156</article-id>
<title-group>
<article-title>Review article: Rainfall-Induced Landslide Early Warning System: Advances, Gaps, and Perspectives</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Salam</surname>
<given-names>Roquia</given-names>
<ext-link>https://orcid.org/0000-0002-1317-4603</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>Ahmed</surname>
<given-names>Bayes</given-names>
<ext-link>https://orcid.org/0000-0001-5092-5528</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>Sammonds</surname>
<given-names>Peter</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 Risk and Disaster Reduction (RDR), University College London  (UCL), Gower Street, London, WC1E 6BT, UK</addr-line>
</aff>
<pub-date pub-type="epub">
<day>29</day>
<month>04</month>
<year>2026</year>
</pub-date>
<volume>2026</volume>
<fpage>1</fpage>
<lpage>40</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2026 Roquia Salam et al.</copyright-statement>
<copyright-year>2026</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://egusphere.copernicus.org/preprints/2026/egusphere-2026-2156/">This article is available from https://egusphere.copernicus.org/preprints/2026/egusphere-2026-2156/</self-uri>
<self-uri xlink:href="https://egusphere.copernicus.org/preprints/2026/egusphere-2026-2156/egusphere-2026-2156.pdf">The full text article is available as a PDF file from https://egusphere.copernicus.org/preprints/2026/egusphere-2026-2156/egusphere-2026-2156.pdf</self-uri>
<abstract>
<p>This review is necessary at this time to provide a comprehensive evaluation of the rainfall-induced landslide early warning system (LEWS) through the lens of the United Nations &amp;lsquo;Early Warnings for All&amp;rsquo; (EW4All) framework. This study integrates EW4All pillars, incorporates overlooked literature, examines information sharing in academic publications, and evaluates the global feasibility of implementing EW4All for LEWS. Of 61 rainfall-induced LEWS identified in the literature covering 23 countries, 14 are considered operational, meaning they are currently implemented and actively used for warning purposes, across only 10 countries. Among local, regional, and national systems, local LEWS is often less scalable and more resource-intensive. Most operational systems target debris flows and shallow landslides and rely mainly on rainfall thresholds. While some include susceptibility maps, risk maps are largely absent. Real-time sensor data are used in some systems; however, high maintenance costs limit scalability. Reliability is further constrained by data scarcity, limited forecast verification, suboptimal use of AI, and the lack of standardised forecasting approaches. Community engagement and multi-hazard integration remain limited. Although EW4All is transformative, implementing effective LEWS in rainfall-induced landslide-prone areas worldwide by 2027 remains impractical without localised approaches, sufficient funds, and resources.</p>
</abstract>
<counts><page-count count="40"/></counts>
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