Study On The Temporal And Spatial Distribution Of Landslide Resurrection By Tree - Ring Reconstruction

Tree ring records play an important role in the study of geomorphic processes because of their characteristics:accurately dating, high resolution and long time span. Many papers have shown that tree rings can be a reliable tool for historical evidence of past landslides, which can explain what is happening now and predict landslide deformation in the future. Often, there were not detailed historical records of landslide sliding. In many cases, the archive data only documented landslide events that cause significant loss of human life and property, while slight movements in non-inhabited areas or events that did not cause serious losses were not recorded. Tree ring analyses can make up for this shortcoming, accurately record each movement activation in the sequence of the tree rings. This reconstruction results are helpful to grasp of the reactivation of the landslide mechanism in detail.There are many researches using tree-ring to reconstruct the spatial and temporal distribution pattern of landslide reactivation, but most of these studies were concentrated in Europe and North America. Studies applying this method to reconstruct landslide in China are rarely reported. In order to fill this gap, we use tree-ring analysis to study the Xiakou landslide, which is located in the east of Qinghai-Tibet Plateau in China. Hereby, mainly the landslide mechanism of reactivation of the past40years and the temporal and spatial distribution patterns of each reactivation phase of Xiakou landslide was analysed.Xiakou landslide is an old reactivated landslide. According to the local archive data, Xiakou landslide was active in1978,1981,1987,1995and2006, and geomorphological signs of reactivation phases can be found on the landslide body. In the foot area of Xiakou landslide, there are Yabi Road and Longxi River. During landslide reactivation phases, the slipped material can cause traffic disruption, river dammingwith potenitally disastrous consequences. There are many trees in the landslide body, and the dominant species is fir. These trees witnessed each reactivation phase of this landslide. The strong and fast sliding speed of the sliding will lead all of the trees live on the landslide body to death, while trees only survived in areas of lower intensity movement. These trees recorded the reactivation phases in their tree ring sequences. Based on the two points above, we chose Xiakou landslide as our study site. The following researches steps were carried out:According to the number of growth disturbances (GD) recorded in the tree ring sequences to explore the relationship between GD and tree age; the landslide reactivation phases were determined; According to the different spatial distribution of each landslide event year, the spatio-temporal distribution patterns were reconstructed; the different return period in the different area of the landslide body was make certain; and the development trends in the next20years was predicted. Thereafter, we find out10landslide event years (i.e.1987,1988,1989,1992,1993,1995,1997,2004,2006and2007) in the past40years, in which the year of1987,1995and2006were consistent with the local historical records. These results indicate that the reconstructed results can accurately record phases of low intensity landslide movements, which are not covered by the local archive data. The tree-ring reconstruction results can be used as a supplement to local historical data records. The reconstructed result and the interpolated return periods and reactivition probability showed that a high sliding activity of Xialou landslide occurs in the southern part of the landslide body, where new landslides are formed on the deformable main body. This result is consistent with the results of the fieldwork.The tree ring method differs from conventional approaches based on statistical analyses or physical modeling that have demonstrated limitations in the prediction of spatiotemporal reactivation of landslides. Our approach is, in contrast, based on extensive data on past landslides and therefore allowed determination of quantitative probability maps of reactivation derived directly from the frequency of past events. The method can also be extended to the study of glacier activity, debris-flow, avalanches and other geomorphic events.