Landslide Susceptibility Mapping and Evaluation along a River Valley in China

: Landslide susceptibility evaluation at regional scale is commonly performed based dominantly on the analysis of geological and geomorphological conditions of historical landslide cases. The main content of this type of evaluation covers identifying key casual factors, their critical groupings and relative importance. The present study demonstrates an application of the above concept to a 90 km long segment of Jinshajiang River valley in China. Correlations of landslide occurrence with potential causative factors are derived according to interpretation of field investigation. Lithology, orientation of bedding planes, slope angle, stream action, rainfall and earthquake intensity are selectively recognized as identifiable/measurable causative factors to establish a factor domain. The membership grades, for field values of quantitative factors, to the susceptibility classes are determined based on the construction of fuzzy sets, while those for descriptive factors are assigned from a fuzzy score table. The analytic hierarchy process (AHP) is adopted for assigning weights to each individual factor. Subsequently, the evaluation is implemented in a GIS program IDRISI, where four classes of landslide susceptibility are identified and delineated in the subject area. The approach described in the present paper showed consistence with the nature and availability of data for evaluating landslide susceptibility at regional scale. The methodology presented can be effectively employed by relevant authorities to identify risky areas for dislocating major infrastructural project, and develop management strategies for land use.

[1]  Majid H. Tangestani,et al.  Landslide susceptibility mapping using the fuzzy gamma operation in a GIS, Kakan catchment area, Iran , 2003 .

[2]  C. F. Lee,et al.  Assessment of landslide susceptibility on the natural terrain of Lantau Island, Hong Kong , 2001 .

[3]  Yoshinori Tsukamoto,et al.  Runoff process on a steep forested slope , 1988 .

[4]  P. Aleotti,et al.  Landslide hazard assessment: summary review and new perspectives , 1999 .

[5]  Ryuichi Yatabe,et al.  GIS-based landslide susceptibility zonation for roadside slope repair and maintenance in the Himalayan region , 2008 .

[6]  Analysis of a failed slope , 1971 .

[7]  R. Soeters,et al.  Landslide hazard and risk zonation—why is it still so difficult? , 2006 .

[8]  J. Corominas,et al.  A GIS-Based Multivariate Statistical Analysis for Shallow Landslide Susceptibility Mapping in La Pobla de Lillet Area (Eastern Pyrenees, Spain) , 2003 .

[9]  Rapid Identification and Emergency Investigation of Surface Ruptures and Geohazards Induced by the Ms 7.1 Yushu Earthquake , 2010 .

[10]  T. Ramachandra,et al.  Landslide susceptibility mapping in the downstream region of Sharavathi river basin, Central Western Ghats , 2008 .

[11]  M. Arora,et al.  GIS-based Landslide Hazard Zonation in the Bhagirathi (Ganga) Valley, Himalayas , 2002 .

[12]  Xuwen Qin,et al.  RS and GIS‐based Statistical Analysis of Secondary Geological Disasters after the 2008 Wenchuan Earthquake , 2009 .

[13]  Debi Prasanna Kanungo,et al.  Landslide hazard zonation : a case study in Garhwal Himalaya,India , 1995 .

[14]  O. Petrucci,et al.  The use of historical data for the characterisation of multiple damaging hydrogeological events , 2003 .

[15]  T. L. Saaty A Scaling Method for Priorities in Hierarchical Structures , 1977 .