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<publisher>HAL CCSD</publisher>
<title lang=en>Quantification of erosion and sedimentation using time-lapse gravimetry and Lidar in southern Taiwan</title>
<creator>Mouyen, Maxime</creator>
<creator>Steer, Philippe</creator>
<creator>Croissant, Thomas</creator>
<creator>Lemoigne, Nicolas</creator>
<creator>Hwang, Cheinway</creator>
<creator>Cheng, Ching-Chung</creator>
<creator>Masson, Frédéric</creator>
<creator>Davy, Philippe</creator>
<creator>Lague, Dimitri</creator>
<creator>Longuevergne, Laurent</creator>
<contributor>Géosciences Rennes (GR) ; Université de Rennes 1 (UR1) - Institut national des sciences de l'Univers (INSU - CNRS) - Observatoire des Sciences de l'Univers de Rennes (OSUR) - Centre National de la Recherche Scientifique (CNRS)</contributor>
<contributor>Risques ; Géosciences Montpellier ; Université des Antilles et de la Guyane (UAG) - Institut national des sciences de l'Univers (INSU - CNRS) - Université de Montpellier (UM) - Centre National de la Recherche Scientifique (CNRS) - Université des Antilles et de la Guyane (UAG) - Institut national des sciences de l'Univers (INSU - CNRS) - Université de Montpellier (UM) - Centre National de la Recherche Scientifique (CNRS)</contributor>
<contributor>Department of Civil Engineering [Hsinchu] ; National Chiao Tung University (NCTU)</contributor>
<contributor>Institut de physique du globe de Strasbourg (IPGS) ; Institut national des sciences de l'Univers (INSU - CNRS) - Centre National de la Recherche Scientifique (CNRS)</contributor>
<description>International audience</description>
<source>European Geosciences Union General Assembly 2016</source>
<coverage>Vienne, Austria</coverage>
<contributor>European Geosciences Union</contributor>
<identifier>insu-01308554</identifier>
<identifier>https://hal-insu.archives-ouvertes.fr/insu-01308554</identifier>
<source>https://hal-insu.archives-ouvertes.fr/insu-01308554</source>
<source>European Geosciences Union General Assembly 2016, Apr 2016, Vienne, Austria. Geophysical Research Abstracts, 18, pp.EGU2016-12916-1, 2016</source>
<language>en</language>
<subject>[SDU.STU.GM] Sciences of the Universe [physics]/Earth Sciences/Geomorphology</subject>
<type>info:eu-repo/semantics/conferenceObject</type>
<type>Poster communications</type>
<description lang=en>After the 2009 Morakot typhoon, which triggered numerous large landslides in Taiwan, Mouyen et al. (2013)showed for the first time the potential of time-lapse gravity survey to infer the mass of sediments transferringby landsliding or through rivers. By providing an integrated measurement of masses, gravimetry might thus becomplementary to common methods used to assess the sediments discharge of rivers. But the masses of rocksdisplaced by Morakot were exceptionally large as a result of the record-breaking rainfalls brought by this typhoonand one might wonder to what extent time-lapse gravimetry could record such sediment transfers. In order tobetter assess the capabilities of this method, we set a time-lapse gravity network dedicated to the monitoring ofsuch sediments transfers in Paolai village (south-central Taiwan). Paolai is located near the large Laonong riverwhere temporary alluvial deposits of sediments exist and face steep mountain slopes likely to experience landslides.Both features are considered as potential source of mass transfers, and in turn of temporal gravity changes. Thefirst base gravity measurements were done in November 2015, using absolute and relative gravimeters, and will berepeated every year, before and after the typhoon season. In the same time, we also use a terrestrial lidar to scan thegeometry of both the river and the mountain slopes, hence providing a detailed topographical survey of the studiedarea. Adding Lidar measurements is an efficient strategy to solve for the non-uniqueness of gravity solutions.Meanwhile, we use the Eros morphodynamic model, that combine landsliding and flooding models, to investigatevarious scenarios of landsliding and subsequent sediment transport and compute the gravity changes on a virtualnetwork of gravimeters. This gives us insights on the expected order of magnitudes for these surface sedimenttransfers, which are useful to unravel the induced gravity signal from others sources such as local hydrology orvertical ground displacements. The modeling results also enable us to set network location that are best defined todetect mass changes associated with sediment transfer. The main objective of this study is to test whether timelapsegravity brings a new and reliable information compared to present methods monitoring sediments transfersand landscape evolution.</description>
<date>2016-04-12</date>
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