Dr. Xinli Hu is currently a Professor and PhD supervisor at Faculty of Engineering, China University of Geosciences, Wuhan, China. She is the member of International Association for Engineering Geology and the Environment (IAEG) and Engineering Geology Branch of China Geological Society. She has participated in a large number of research projects. Her research interests include (1) geohazard prevention and slope stability analysis; (2) deformation characteristics and failure mechanisms of reservoir landslides; (3) stabilizing pile-landslide interactions; and (4) physical and numerical modeling of landslide aspects.
Traditional deterministic numerical simulation often has a poor prediction performance for landslide-induced wave run-up (LIWR) hazards, as it neglects the effects of uncertainty. The limitation for efficiently quantifying the uncertainties in primary parameters remains largely unsolved. In this study, we propose a probabilistic evaluation method, integrating the adaptive Kriging (AK) metamodel method and probability density evolution method (PDEM) based on generalized F-discrepancy. A Taylor expansion-based adaptive design strategy is applied to construct the global AK model over representative points generated by generalized F-discrepancy, thereby approximating the numerical physical response (i.e., maximum LIWR). Using these approximate responses, the PDEM is used to compute the exceedance probabilities that LIWR heights exceed elements at risk based on a construction of virtual time, and then a probabilistic criterion is introduced to classify hazard zones. The proposed method is demonstrated via two examples: Example Ⅰ, which possesses risk element (building), and Example Ⅱwith water-level variations. The results indicate that the proposed method has an acceptable performance (showing a 1.7 % difference in exceedance probability compared to Monte Carlo simulation with 50,000 samples) with low computation cost (requiring 284 deterministic analyses). For two specific scenarios in this study, the wave induced by the landslide exhibits a solitary-like leading wave. The proposed probabilistic method provides promising prospects for quantifying LIWR uncertainties, and is helpful for direct, efficient, and low-cost quantification assessment of cascading hazards.
| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |