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            <title xml:lang="en">Are rivers becoming more intermittent in France?</title>
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            <idno type="stamp" n="RESEAU-EAU">Réseau "Systèmes Agricoles et Eau"</idno>
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                    <forename type="first">Tristan</forename>
                    <surname>Jaouen</surname>
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                    <forename type="first">Lionel</forename>
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                    <forename type="first">Aurélien</forename>
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                  <persName>
                    <forename type="first">Benoit</forename>
                    <surname>Terrier</surname>
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                  <idno type="halauthorid">851952-0</idno>
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                  <title>Conférence internationale I.S.Rivers 2025</title>
                  <date type="start">2025-06-30</date>
                  <date type="end">2025-07-04</date>
                  <settlement>Lyon</settlement>
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                <term xml:lang="en">No-flow events</term>
                <term xml:lang="en">Multi-scenario projections</term>
                <term xml:lang="en">Machine learning</term>
                <term xml:lang="en">Headwater streams</term>
                <term xml:lang="en">Climate change</term>
                <term xml:lang="fr">Rivières en tête de bassin</term>
                <term xml:lang="fr">Projections multi-scénarios</term>
                <term xml:lang="fr">Machine learning</term>
                <term xml:lang="fr">Intermittence</term>
                <term xml:lang="fr">Changement climatique</term>
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              <p>The French Office for Biodiversity created the Observatoire National Des Etiages (ONDE) to monitor over 3,300 sites located on headwater rivers prone to no-flow events. Since 2012, the flow or no-flow state of each site has been systematically observed every month from May to September.Our study aims to project the evolution of no-flow events at the 3,300 ONDE monitoring sites under climate change in the 21st century. This study builds on the national Explore2 project, led by the French Ministry of Ecology, which updates knowledge on the impacts of climate change on hydrology in France through multi-scenario and multi-model climate and hydrological simulations across the country for the 21st century.We calibrate machine learning models using climate and hydrological data from Explore2 to predict observed no-flow events at ONDE sites between 2012 and 2019. In practice we calibrate random forest on historical data, and after training the models identify no-flow events with a sensitivity of 70% (Q1-Q3: 53%-82%) depending on the region, and flow conditions with a specificity of 97% (Q1-Q3: 93%-99%). Afterwards, the models are fed using Explore2 projections in order to estimate the future trends in no-flow events throughout the 21st century. Results suggest that by 2040 over 20% of the ONDE sites in the Rhône-Mediterranean-Corsica region could experience no-flow conditions for more than half the time between July and October, compared to 7% currently.</p>
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              <p>L’Office Français pour la Biodiversité (OFB) a créé l’Observatoire National des Etiages (ONDE) pour surveiller plus de 3 300 sites sur des rivières en tête de bassin, susceptibles de s'assécher. Depuis 2012, l’état d’écoulement (présence/absence d’écoulement) de ces sites est observé systématiquement chaque mois de mai à septembre.Notre étude vise à projeter l’évolution des assèchements de ces sites sous changement climatique au XXIe siècle. Elle s’appuie sur le projet national Explore2 (https://entrepot.recherche.data.gouv.fr/dataverse/explore2), soutenu par le ministère français de l’Ecologie et l’OFB, qui actualise les connaissances sur les impacts du changement climatique sur l’hydrologie en France à partir de modélisations climatiques et hydrologiques multi-scénarios et multi-modèles appliquées uniformément sur le territoire pour le 21e siècle.Notre étude propose d’exploiter l’intelligence artificielle pour projeter l’assèchement des sites ONDE à partir des données climatiques et hydrologiques simulées par Explore2 et des données ONDE entre 2012 et 2019. Des Random Forests ont été appris sur la période historique : elles détectent les assèchements avec une sensibilité de 70% (Q1-Q3 : 53%-82%) selon les régions et les écoulements avec une spécificité de 97% (Q1-Q3 : 93%-99%). A l’issue de la phase d’apprentissage, ces modèles sont utilisés avec les simulations d’Explore2 comme entrée. Les résultats suggèrent que dès 2040 plus de 20% des sites ONDE de la région Rhône-Méditerranée-Corse pourraient être en assec plus de la moitié du temps entre juillet et octobre contre 7% actuellement.</p>
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