Predictive GIS-based model of rockfall activity in Mountain Cliffs

被引:45
作者
Marquínez, J
Duarte, RM
Farias, P
Sánchez, MJ
机构
[1] Univ Oviedo, INDUROT, Oviedo 33004, Spain
[2] Univ Oviedo, Dept Geol, E-33005 Oviedo, Spain
关键词
rockfall activity; GIS; prediction; GIS-based models; statistical analysis;
D O I
10.1023/B:NHAZ.0000007170.21649.e1
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Rockfall susceptibility has been analysed in mountain cliffs of the Cantabrian Range, North Spain. The main aim of this analysis has been to build a predictive model of rockfall activity from a low number of environmental and geological variables. The rockfall activity has been quantified in a GIS. The cartographic information used shows the spatial distribution of all the recent talus screes as well as their associated source areas in the rock- slopes. The area relation At/ Ar ( recent talus scree polygon/ source basins) in the rock slopes has been used as the rockfall activity indicator. This relation has been validated in 50 pilot rock- slopes and compared with the relation number of recent rock fragments/ source basin, obtained from field work. The environmental factors causing rockfall depend on the rock slope situation, and these are: altitude and sun radiation on the rock cliff. The geological factors considered are: lithology, relative position of the main discontinuities with respect to the topographic surface and two morphologic parameters: the roughness and slope gradient. A logistic regression analysis has been applied to a population of 442 limestone and quartzite rock cliffs. The dependent variable is the rockfall activity indicator, which allows the definition of two classes of rock cliff units: low and high activity. The independent variables are altitude, sun radiation ( equinox radiation, summer solstice radiation, winter solstice radiation), slope roughness, slope gradient, anisotropy and lithology. Results suggest that it is possible to build a valid cartographic predictive model for rockfall activity in mountain rock cliffs from a limited number of easily obtainable variables. The method is especially applicable in massive rock slopes or in regions with uniform rock mass characteristics.
引用
收藏
页码:341 / 360
页数:20
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