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LI Zhanfei, LIU Jing, SHAO Yanxiu, ZHANG Jinyu, YUAN Zhaode, WANG Peng, TANG Maoyun, WANG Pengtao. 2016: Tecto-geomorphic analysis and selection of trench sites along Haiyuan fault in Songshan site based on high-resolution airbone LiDAR data. Geological Bulletin of China, 35(1): 104-116.
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In this paper, the authors first carried out a large-scale(1:1000) tecto-geomorphic mapping in the vicinity of the Song-shan paleoseismic study site on the Laohushan section of the Haiyuan fault by using high resolution(1m) airborne LiDAR DEM and with the aid of topographic enhancement through GIS tools. New paleoseismic results in two trenches opened near two previously published ones less than 150m to the east were reported, which allows a comprehensive comparison of four trenches in such aspects as geomorphic setting, sedimentary environment, number of paleoseismic events and their deformation styles. The new paleoseismic results reveal a discontinuous paleoseismic sequence at 37380±880BP including 5 events with different levels of certainty. The authors found that despite the fact that these trenches are located within short distances from each other, the stratigraphic resolution and paleoseismic event evidence exposed considerable difference from trench to trench. This implies that paleosiesmic results, such as the total number and robustness of stratigraphic evidence of paleoearthquakes, strongly depend on site location. Favorable depositional environmenrts for an excellent preservation of paleoseismic record include topographic lows such as pull-apart basins allowing for low-energy and fine graine size deposition as well as high sedimentation rate for strike-slip fault. Examples presented here suggest that largescale tecto-geomorphic mapping, especially based on the high-resolution topography, is important for site selection, and such an exercise is a necesssary reconnaissance step before opening a trench to maximize the quality of paleoseismic investigation. Such a practice also shows the great potential and usefulness of airborne LiDAR data in better quantification of fault rupture behavior and fault activity in general.
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