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Table 3 Summary of all tests performed

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

Test Description
A1 The infinite slope stability model is applied with a constant soil depth d = 3 m; the entire OIA is considered for evaluation. This means that all observed landslide pixels are considered OP whilst all observed non-landslide pixels are considered ON.
A2 Infinite slope stability model, constant soil depth d = 3 m; only the ORA is considered for evaluation: the pixels in the upper third of each observed landslide are considered OP, all other observed landslide pixels are considered no data; all observed non-landslide pixels are considered ON. This procedure helps to exclude pixels possibly representing transit or deposition areas from the evaluation procedure.
A3 Infinite slope stability model, variable soil depth and OIA considered for evaluation. According to Guimarães et al. (2003), d is varied between 1 and 3 m. We assume a linear increase of d within a certain range of the topographic wetness index (Moore et al. 1991).
A4 Infinite slope stability model, variable soil depth and ORA considered for evaluation
B The sliding surface model implemented in r.slope.stability is applied along with the optimized parameters derived from the tests A1–A4. The ellipsoid density per pixel (Mergili et al. 2014a, b) is set to 2500. The ellipsoid dimensions are constrained by the dimensions of the release areas of the observed landslides. All ellipsoids are truncated at the depth of the soil.
C1 TRIGRS, rectangular hydrograph and an assumed rainfall duration of 6 h. The rainfall is considered constant throughout the entire period, resulting in an intensity of 24 mm/h.
C2 TRIGRS, rectangular hydrograph and rainfall duration of 10 h (intensity 14.4 mm/h)
C3 TRIGRS, triangular hydrograph with central peak and rainfall duration of 6 h, resulting in a peak intensity of 48 mm/h
C4 TRIGRS, triangular hydrograph with central peak and duration of 10 h and peak intensity of 28.8 mm/h
D Simple statistical model employing the slope angle as the only predictor layer. Overlay of a classified slope map with the ORA map and, for each class, computation of the fraction of observed landslide release pixels related to all pixels.
  1. For more details such as the parameters spaces applied please refer to the text