The post-earthquake field investigations reveal that the MW7.9 Wenchuan earthquake of 12th May 2008 ruptured three NE-striking imbricate reverse faults and another NW-trending reverse fault, along the middle Longmensh...The post-earthquake field investigations reveal that the MW7.9 Wenchuan earthquake of 12th May 2008 ruptured three NE-striking imbricate reverse faults and another NW-trending reverse fault, along the middle Longmenshan fold-and-thrust belt at the eastern margin of the Tibetan plateau. The fault-scarp features can be categorized into eight groups: simple thrust scarp, hanging-wall collapse scarp, simple pressure ridge, dextral pressure ridge, fault-related fold scarp, back-thrust pressure ridge, local normal fault scarp and crocodile-mouth-like scarp. The local normal scarp is first discovered in the reverse-faulting earthquakes as ever reported in the world. Field observation indicates that the Wenchuan earthquake surface rupture is dominated by reverse faulting with a minus right-lateral component, but the relative ratio varies from site to site. Also, the surface ruptures can be divided, for the first order, into two segments, the Yingxiu and Beichuan segments, corresponding to MW7.8 and MW7.57 events, respectively. The two segments further can be divided, for the second order, into four sub-segments in total, which are equivalent to four sub-events of MW7.46, MW7.69, MW6.99 and MW7.52, respectively. The fault segmentation, for different orders, shows a cascade-rupturing pattern and can explain why the quake time of the Wenchuan earthquake was so long as up to 100 second. Aftershock focal mechanisms are also used to constrain the fault geometry for the sub-segments, indicating that the seismogenic faults are listric at depth and in general, the fault plane becomes steeper northward, which enables the fault to accommodate larger strike-slip motion. This earthquake also confirms that the crustal shortening across the Longmenshan fold-and-thrust belt should be responsible for the growth of high topographic relief along the eastern margin of the Tibetan Plateau.展开更多
Tens of thousands of landslides were triggered by May 12, 2008 earthquake over a broad area. The main purpose of this article is to apply and verify earthquake-triggered landslide hazard analysis techniques by using w...Tens of thousands of landslides were triggered by May 12, 2008 earthquake over a broad area. The main purpose of this article is to apply and verify earthquake-triggered landslide hazard analysis techniques by using weight of evidence modeling in Qingshui （清水） River watershed, Deyang （德阳） City, Sichuan （四川） Province, China. Two thousand three hundred and twenty-one landslides were interpreted in the study area from aerial photographs and multi-source remote sensing imageries post-earthquake, verified by field surveys. The landslide inventory in the study area was established. A spatial database, including landslides and associated controlling parameters that may have influence on the occurrence of landslides, was constructed from topographic maps, geological maps, and enhanced thematic mapper （ETM＋） remote sensing imageries. The factors that influence landslide occurrence,such as slope angle, aspect, curvature, elevation, flow accumulation, distance from drainages, and distance from roads were calculated from the topographic maps. Lithology, distance from seismogenic fault, distance from all faults, and distance from stratigraphic boundaries were derived from the geological maps. Normalized difference vegetation index （NDV1） was extracted from ETM＋ images. Seismic intensity zoning was collected from Wenchuan （汶川） Ms8.0 Earthquake Intensity Distribution Map published by the China Earthquake Administration.Landslide hazard indices were calculated using the weight of evidence model, and landslide hazard maps were calculated from using different controlling parameters cases. The hazard map was compared with known landslide locations and verified. The success accuracy percentage of using all 13 controlling parameters was 71.82%. The resulting landslide hazard map showed five classes of landslide hazard, i.e., very high, high, moderate, low, and very low. The validation results showed satisfactory agreement between the hazard map and the existing landslides distribution data. The landslide hazard map can be used to identify and delineate unstable hazard-prone areas. It can also help planners to choose favorable locations for development schemes, such as infrastructural, buildings, road constructions, and environmental protection.展开更多
Predicting approximate earthquake-induced landslide displacements is helpful for assessing earthquake hazards and designing slopes to withstand future earth- quake shaking. In this work, the basic methodology outlined...Predicting approximate earthquake-induced landslide displacements is helpful for assessing earthquake hazards and designing slopes to withstand future earth- quake shaking. In this work, the basic methodology outlined by Jibson （1993） is applied to derive the Newmark displacement of landslides based on strong ground-motion recordings during the 2013 Lushan Ms 7.0 earthquake. By analyzing the relationships between Arias intensity, New- mark displacement, and critical acceleration of the Lushan earthquake, formulas of the Jibson93 and its modified models are shown to be applicable to the Lushan earthquake dataset. Different empirical equations with new fitting coefficients for estimating Newmark displace- ment are then developed for comparative analysis. The results indicate that a modified model has a better goodness of fit and a smaller estimation error for the Jibson93 formula. It indicates that the modified model may be more reasonable for the dataset of the Lushan earthquake. The analysis of results also suggests that a global equation is not ideally suited to directly estimate the Newmark displacements of landslides induced by one specific earthquake. Rather it is empirically better to perform a new multivariate regression analysis to derive new coefficients for the global equation using the dataset of the specific earthquake. The results presented in this paper can be applied to a future co-seismic landslide hazard assessment to inform reconstruction efforts in the area affected by the 2013 Lushan Ms 7.0 earthquake, and for future disaster prevention and mitigation.展开更多
文摘The post-earthquake field investigations reveal that the MW7.9 Wenchuan earthquake of 12th May 2008 ruptured three NE-striking imbricate reverse faults and another NW-trending reverse fault, along the middle Longmenshan fold-and-thrust belt at the eastern margin of the Tibetan plateau. The fault-scarp features can be categorized into eight groups: simple thrust scarp, hanging-wall collapse scarp, simple pressure ridge, dextral pressure ridge, fault-related fold scarp, back-thrust pressure ridge, local normal fault scarp and crocodile-mouth-like scarp. The local normal scarp is first discovered in the reverse-faulting earthquakes as ever reported in the world. Field observation indicates that the Wenchuan earthquake surface rupture is dominated by reverse faulting with a minus right-lateral component, but the relative ratio varies from site to site. Also, the surface ruptures can be divided, for the first order, into two segments, the Yingxiu and Beichuan segments, corresponding to MW7.8 and MW7.57 events, respectively. The two segments further can be divided, for the second order, into four sub-segments in total, which are equivalent to four sub-events of MW7.46, MW7.69, MW6.99 and MW7.52, respectively. The fault segmentation, for different orders, shows a cascade-rupturing pattern and can explain why the quake time of the Wenchuan earthquake was so long as up to 100 second. Aftershock focal mechanisms are also used to constrain the fault geometry for the sub-segments, indicating that the seismogenic faults are listric at depth and in general, the fault plane becomes steeper northward, which enables the fault to accommodate larger strike-slip motion. This earthquake also confirms that the crustal shortening across the Longmenshan fold-and-thrust belt should be responsible for the growth of high topographic relief along the eastern margin of the Tibetan Plateau.
基金supported by the International Scientific Joint Project of China (No. 2009DFA21280)the National Natural Science Foundation of China (No. 40821160550)the Doctoral Candidate Innovation Research Support Program by Science & Technology Review (No. kjdb200902-5)
文摘Tens of thousands of landslides were triggered by May 12, 2008 earthquake over a broad area. The main purpose of this article is to apply and verify earthquake-triggered landslide hazard analysis techniques by using weight of evidence modeling in Qingshui （清水） River watershed, Deyang （德阳） City, Sichuan （四川） Province, China. Two thousand three hundred and twenty-one landslides were interpreted in the study area from aerial photographs and multi-source remote sensing imageries post-earthquake, verified by field surveys. The landslide inventory in the study area was established. A spatial database, including landslides and associated controlling parameters that may have influence on the occurrence of landslides, was constructed from topographic maps, geological maps, and enhanced thematic mapper （ETM＋） remote sensing imageries. The factors that influence landslide occurrence,such as slope angle, aspect, curvature, elevation, flow accumulation, distance from drainages, and distance from roads were calculated from the topographic maps. Lithology, distance from seismogenic fault, distance from all faults, and distance from stratigraphic boundaries were derived from the geological maps. Normalized difference vegetation index （NDV1） was extracted from ETM＋ images. Seismic intensity zoning was collected from Wenchuan （汶川） Ms8.0 Earthquake Intensity Distribution Map published by the China Earthquake Administration.Landslide hazard indices were calculated using the weight of evidence model, and landslide hazard maps were calculated from using different controlling parameters cases. The hazard map was compared with known landslide locations and verified. The success accuracy percentage of using all 13 controlling parameters was 71.82%. The resulting landslide hazard map showed five classes of landslide hazard, i.e., very high, high, moderate, low, and very low. The validation results showed satisfactory agreement between the hazard map and the existing landslides distribution data. The landslide hazard map can be used to identify and delineate unstable hazard-prone areas. It can also help planners to choose favorable locations for development schemes, such as infrastructural, buildings, road constructions, and environmental protection.
基金Acknowledgements The authors would like to express sincere appreciation to the reviewers for their valuable comments and suggestions, which were helpful for improving the MS. This work was financially supported by the Basic Science Fund of the Institute of Geology, China Earthquake Administration （IGCEA-1401）, and the National Natural Science Foundation of China Projects （Grant Nos. 41372219, 41272298, and 41172193）, for which grateful appreciation is expressed. We also would like to state our deep appreciation to the China Strong Motion Networks Center for supplying recordings of strong motion.
文摘Predicting approximate earthquake-induced landslide displacements is helpful for assessing earthquake hazards and designing slopes to withstand future earth- quake shaking. In this work, the basic methodology outlined by Jibson （1993） is applied to derive the Newmark displacement of landslides based on strong ground-motion recordings during the 2013 Lushan Ms 7.0 earthquake. By analyzing the relationships between Arias intensity, New- mark displacement, and critical acceleration of the Lushan earthquake, formulas of the Jibson93 and its modified models are shown to be applicable to the Lushan earthquake dataset. Different empirical equations with new fitting coefficients for estimating Newmark displace- ment are then developed for comparative analysis. The results indicate that a modified model has a better goodness of fit and a smaller estimation error for the Jibson93 formula. It indicates that the modified model may be more reasonable for the dataset of the Lushan earthquake. The analysis of results also suggests that a global equation is not ideally suited to directly estimate the Newmark displacements of landslides induced by one specific earthquake. Rather it is empirically better to perform a new multivariate regression analysis to derive new coefficients for the global equation using the dataset of the specific earthquake. The results presented in this paper can be applied to a future co-seismic landslide hazard assessment to inform reconstruction efforts in the area affected by the 2013 Lushan Ms 7.0 earthquake, and for future disaster prevention and mitigation.
