Backward automatic calibration for three-dimensional landslide models |
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| Authors: | Giacomo Titti Giulia Bossi Gordon GD Zhou Gianluca Marcato Alessandro Pasuto |
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| Institution: | DICAM-UNIBO, Department of Civil, Chemical, Environmental and Materials Engineering, Alma Mater Studiorum University of Bologna, Viale Risorgimento 2, Bologna,40136, Italy;IRPI-CNR, Research Institute for Geo-Hydrological Protection, National Research Council, C.so Stati Uniti, 4, Padova, 35127, Italy;IRPI-CNR, Research Institute for Geo-Hydrological Protection, National Research Council, C.so Stati Uniti, 4, Padova, 35127, Italy;IMHE-CAS, Key Laboratory of Mountain Hazards and Earth Surface Process/Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Block 4,Renminnanlu Road, Chengdu, 610041, China |
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| Abstract: | Back-analysis is broadly used for approaching geotechnical problems when monitoring data are available and information about the soils properties is of poor quality. For landslide stability assessment back-analysis calibration is usually carried out by time consuming trial-and-error procedure. This paper presents a new automatic Decision Support System that supports the selection of the soil parameters for three-dimensional models of landslides based on monitoring data. The method considering a pool of possible solutions, generated through permutation of soil parameters, selects the best ten configurations that are more congruent with the measured displacements. This reduces the operator biases while on the other hand allows the operator to control each step of the computation. The final selection of the preferred solution among the ten best-fitting solutions is carried out by an operator. The operator control is necessary as he may include in the final decision process all the qualitative elements that cannot be included in a qualitative analysis but nevertheless characterize a landslide dynamic as a whole epistemological subject, for example on the base of geomorphological evidence. A landslide located in Northeast Italy has been selected as example for showing the system potentiality. The proposed method is straightforward, scalable and robust and could be useful for researchers and practitioners. |
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| Keywords: | Automatic landslide modelling Back-analysis Optimization Decision Support System |
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