Drei-Schluchten-Region / China) ------Geotechnical Mapping and Landslide Susceptibility Analysis in Badong County (Three Gorges Region / China)

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Drei-Schluchten-Region / China) ------Geotechnical Mapping and Landslide Susceptibility Analysis in Badong County (Three Gorges Region / China) Geotechnische Kartierung und Suszeptibilitätsanalyse für Hangrutschungen in der Gemeinde Badong (Drei-Schluchten-Region / China) --------------------------------------------------------------------------- Geotechnical mapping and landslide susceptibility analysis in Badong county (Three Gorges Region / China) der Naturwissenschaftlichen Fakultät der Friedrich-Alexander-Universität Erlangen-Nürnberg zur Erlangung des Doktorgrades Dr. rer. nat. vorgelegt von Renneng Bi aus Jingzhou, Hubei, VR China Als Dissertation genehmigt von der Naturwissenschaftlichen Fakultät der Friedrich-Alexander-Universität Erlangen-Nürnberg Tag der mündlichen Prüfung: 01.04.2015 Vorsitzender des Promotionsorgans: Prof. Dr. Jörn Wilms Gutachter: Prof. Dr. Joachim Rohn Prof. Dr. Wei Xiang Selbständigkeitserklärung zur Dissertation Ich erkläre ausdrücklich, dass es sich bei der von mir eingereichten Dissertation mit dem Titel: Geotechnical mapping and landslide susceptibility analysis in Badong county (Three Gorges Region / China) um eine von mir selbstständig und ohne fremde Hilfe verfasste Arbeit handelt. Ich erkläre, dass ich sämtliche in der oben genannten Arbeit verwendeten fremden Quellen, auch aus dem Internet (einschließlich Tabellen, Grafiken u. Ä.) als solche kenntlich gemacht habe. Insbesondere bestätige ich, dass ich ausnahmslos sowohl bei wörtlich übernommenen Aussagen bzw. unverändert übernommenen Tabellen, Grafiken u. Ä. (Zitaten) als auch bei in eigenen Worten wiedergegebenen Aussagen bzw. von mir abgewandelten Tabellen, Grafiken u. Ä. anderer Autorinnen und Autoren (Paraphrasen) die Quelle angegeben habe. Ich erkläre hiermit weiterhin, dass die vorgelegte Arbeit zuvor weder von mir noch – soweit mir bekannt ist – von einer anderen Person an dieser oder einer anderen Hochschule eingereicht wurde. Mir ist bewusst, dass Verstöße gegen die Grundsätze der Selbstständigkeit als Täuschung betrachtet und dass die Unrichtigkeit dieser Erklärung eine Benotung der Arbeit mit der Note ΢nicht ausreichend΢ zur Folge hat und dass Verletzungen des Urheberrechts strafrechtlich verfolgt werden können. _______________________ Erlangen, _______________________ Unterschrift Datum Abstract The Three Gorges Dam Project (TGDP) on the Yangtze River is the dam project with the largest installed capacity in the world. In the Three Gorges Reservoir Area (ca. 56,700 km2), 4,469 landslides have been registered. The study area lies in Badong county, 70 km upstream of the Three Gorges Dam in the foreland of the reservoir and has an extremely high density of landslides. In the study area (ca. 64 km2), 103 landslides with a total area of 4.8 km2 are mapped. Tectonically the study area is located in regional folding belt in the middle part of the Yangtze plate. In the study area mainly the bedrocks of the Badong formation (Middle Triassic) crop out. They are mainly composed of clayey limestones and clayey siltstones. Due to the extremely strong tectonic pressure from north-south direction, different types of tectonic structures can be observed in the bedding layers and the bedrocks are intensely fractured. A geotechnical mapping was performed in order to find all landslides in the investigation area. The geological and geotechnical mapping in the area showed that tectonic structures and the river incision are the essential factors of the landslide development in this region. Especially the occurrences of rock slides and large scale debris slides are tightly correlated with the longitudinal extension of the Guandukou syncline and its secondary folds. In order to investigate the susceptibility for landslides in a local and in a regional scale an artificial neural network (ANN) method was applied. The multilayer feed-forward (MLF) neural network in the artificial neural network method is a computational tool for classification. It is firstly applied for lithology recognition for the study area. The results show that areas with two definitely different lithologies can be well discriminated in most parts of the study area. Secondly the MLF neural network is used for classification of landslide susceptibility in a local scale in the study. The results show that the riversides in the west part of North Badong and in South Badong are the areas at most sensitive for new landslides. As a comparison, a study with the MLF neural network in a large catchment in the Three Gorges region is also attached. The study shows that the MLF neural network is also an efficient tool for recognition of existing landslides in a regional scale. Kurzfassung Das Three Gorges Dam Project (TGDP) am Yangtze Fluss ist das Dammprojekt mit der größten installierten Leistung der Welt. Im Einzugsgebiet des Drei-Schluchten-Stausees (ca. 56.700km²), wurden 4.469 Hangrutschungen registriert. Im Forschungsgebiet liegt der Kreis Badong ca. 70 km stromaufwärts des Drei-Schluchten-Staudamms im Vorland des Stausees und zeigt eine extrem hohe Verteilungsdichte von Hangrutschungen. Im Untersuchungsgebiet (ca. 64 km²) wurden 103 Rutschungen mit einer Fläche von 4,8 km² kartiert. Tektonisch liegt das Untersuchungsgebiet im regionalen Faltengürtel im mittleren Teil der Yangtze-Platte. Im Untersuchungsgebiet ist hauptsächlich das Felsgestein der Badong-Formation (Mittlere Trias) aufgeschlossen. Es setzt sich zum größten Teil aus tonhaltigen Kalkstein und tonhaltigen Siltstein. Aufgrund des extrem starken tektonischen Drucks aus nordsüdlicher Richtung, sind verschiedene Typen tektonischer Strukturen in den Bankung sichtbar und das anstehende Gestein ist stark zerklüftet. Es wurde eine geotechnische Kartierung in diesem Gebiet durchgeführt, um alle Hangrutuschungen im Untersuchungsgebiet aufzufinden. Die geologische und geotechnische Kartierung im Gebiet zeigten, dass tektonische Strukturen und die Einschneidungen der Flüsse die Hauptfaktoren der Entwicklung von Hangrutschungen in dieser Region sind. Besonders das Auftreten von Felsrutschungen sowie großräumigen Schuttrutschungen steht besonders eng in Wechselwirkung mit der Längenausdehnung der Guandukou-Synkline und ihren sekundären Falten. Zur Untersuchung der Suszeptibilität für Hangrutschungen im lokalen und regionalen Maßstab wurde eine künstliche neuronale Netz-Methode verwendet. Das mehrschichtige Feedforward (MLF) neuronale Netz der künstlichen neuronalen Netz-Methode ist ein computergesteuertes Klassifizierungswerkzeug. Dieses Werkzeug wurde zunächst zur Erkennung der Lithologie des Untersuchungsgebiets angewendet. Das Ergebnis zeigt, dass Gebiete mit zwei definitiv differierenden Lithologien gut in den meisten Teilen des Untersuchungsgebietes unterschieden werden können. Darüber hinaus wurde das MLF-neuronale Netz für die Klassifizierung der Suszeptibilität für Hangrutschungen im lokalen Maßstab der Studie angewendet. Die Ergebnisse zeigen, dass sich die Uferregionen im Westen von Nord- und Süd-Badong als besonders suszeptibel für neue Hangrutschungen erweisen. Zum Vergleich wurde eine Studie mit dem MLF-neuronalem Netz in einem großräumigen Reservoir der Drei-Schluchten-Region angefügt. Die Studie ergab, dass das MLF-neuronale Netz auch ein effizientes Werkzeug zur Erkennung existierender Hangrutschungen in regionalem Maßstab ist. Acknowledgements Firstly I owe my deepest gratitude to Prof. Dr. Joachim Rohn for your outstanding supervision over my dissertation with extraordinary patience and constructive critics. I feel lucky I have such an approachable, supportive and generous supervisor. I thank you for all your help in the last years. I also would like to thank Prof. Dr. Xiang Wei from the China University of Geosciences (Wuhan). I am very grateful for your support and encouragement in any situation for so many years. Under the supervision from you and Mr. Rohn, the experiences in Xiangxi and Badong have greatly enriched my field knowledge. Thank you for all the chances that you gave me, especially for connecting my life with Germany. Many thanks go to my good friends and colleagues Markus Schleier, Johannes Wiedenmann, Christian Dumperth, Luo Jin and Dominik Ehret, who helped me in intensive discussions in discovering flaws and solving problems. You also helped me to get used to living in Germany and made my studies here interesting and colorful. I also want to thank many students of Xiang Wei, especially Gong Siyi, for your accompaniment and support in the field. I thank all my Chinese friends in Erlangen. I will always remember the time we spent together. Without you I would have felt much lonelier. And last but not least I thank my parents and my wife who always believe in me. Your lovely and sincere encouragement has strengthened me to finish my doctoral study. Contents Contents 1 Introduction................................................................................................... 1 1.1 Landslides in the Three Gorges Dam area.............................................................. 1 1.2 Targets of the study ................................................................................................... 2 1.3 Approaches of the study............................................................................................ 2 2 Overview ........................................................................................................ 4 2.1 Location ...................................................................................................................... 4 2.1.1 The Yangtze River.............................................................................................. 4 2.1.2 The Three Gorges..............................................................................................
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