Finite element numerical modeling is an important tool for evaluating the stability of weak rock slopes, but developing a model requires a substantial amount of data to constrain slope geometry and material behavior. When proprietary data are unavailable, publicly available data can help fill the knowledge gaps for some parameters. However, these data are not consistently available for all locations. In addition, field data can be difficult or impossible to collect because of danger from actively-moving landslides. In the case of the Zarzal Landslide, Southern Peru, both of these data-limiting factors are at play. Basic geologic and topographic data for the region are available, but detailed information on soil thicknesses, rock strengths, and groundwater elevations are not. Active, slow movement in the slide mass and rockfall at the head scarp make new on-site data collection both difficult and hazardous. In this study, we present our methods for overcoming these data availability challenges, followed by discussion of model parameter back-calculation using pre-slide topography. Finally, we discuss insights into the kinematics of the Zarzal Landslide gained from pre-and post-slide models, as well as general principles for model calibration and interpretation when using limited data.
The Zarzal Landslide (16.369816° S, -72.155377°; Arequipa Department, Southern Peru) is a large landslide in relatively weak rock that presents significant hazards to nearby communities, including loss of cropland, undercutting of a major highway, damming of a river causing upstream flooding, and damage to an industrial milk processing plant. Finite element method (FEM) analysis has the capacity to inform understanding of the stability and kinematic behavior of this landslide. However, data from the site is very limited, which complicates construction of FEM models. This paper presents relevant background on the landslide, followed by a discussion of the methods used to estimate reasonable ranges of model parameters and construct 2D FEM models using Rocscience RS2 software. Calibration of model strength parameters is presented, followed by kinematic observations based on a post-failure model. Finally, we discuss principles for modeling landslides with FEM analysis when data is limited.