Does parameterization influence the performance of slope stability model results? A case study in Rio de Janeiro, Brazil

作者：Neves Seefelder Carolina de Lima; Koide Sergio; Mergili Martin^*

来源：Landslides, 2017, 14(4): 1389-1401.

DOI：10.1007/s10346-016-0783-6

• Parameter sensitivity
• Parameter space
• Slope failure susceptibility index
• Slope stability model
• TRIGRS
• Uncertainty

We produce factor of safety (FOS) and slope failure susceptibility index (SFSI) maps for a 4.4-km(2) study area in Rio de Janeiro, Brazil, in order to explore the sensitivity of the geotechnical and geohydraulic parameterization on the model outcomes. Thereby, we consider parameter spaces instead of combinations of discrete values. SFSI is defined as the fraction of tested parameter combinations within a given space yielding FOS < 1. We repeat our physically based calculations for various parameter spaces, employing the infinite slope stability model and the sliding surface model of the software r.slope.stability for testing the geotechnical parameters and the Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability Model (TRIGRS) for testing the geohydraulic parameters. Whilst the results vary considerably in terms of their conservativeness, the ability to reproduce the spatial patterns of the observed landslide release areas is relatively insensitive to the variation of the parameterization as long as there is sufficient pattern in the results. We conclude that landslide susceptibility maps yielded by catchment-scale physically based models should not be interpreted in absolute terms and suggest that efforts to develop better strategies for dealing with the uncertainties in the spatial variation of the key parameters should be given priority in future slope stability modelling efforts.

• 出版日期2017-8