Effect of Rockfall Spatial Representation on the Accuracy and Reliability of Susceptibility Models (The Case of the Haouz Dorsale Calcaire, Morocco)

Abstract

Rockfalls can cause loss of life and material damage. In Northern Morocco, rockfalls and rock avalanche-deposits are frequent, especially in the Dorsale Calcaire morpho-structural unit, which is mostly formed by Jurassic limestone and dolostone formations. In this study, we focus exclusively on its northern segment, conventionally known as “the Haouz subunit”. First, a rockfall inventory was conducted. Then, two datasets were prepared: one covering exclusively the source area and the other representing the entirety of the mass movements (source + propagation area). Two algorithms were then used to build rockfall susceptibility models (RSMs). The first one (Logistic Regression: LR) yielded the most unreliable results, where the RSM derived from the source area dataset significantly outperformed the one based on the entirety of the rockfall affected area, despite the lack of significant visual differences between both models. However, the RSMs produced using Artificial Neural Networks (ANNs) were more or less similar in terms of accuracy, despite the source area model being more conservative. This result is unexpected given the fact that previous studies proved the robustness of the LR algorithm and the sensitivity of ANN models. However, we believe that the non-linear correlation between the spatial distribution of the rockfall propagation area and that of the conditioning factors used to compute the models explains why modeling rockfalls in particular differs from other types of landslides.

Erosion Susceptibility Analysis in Bingöl (Türkiye) using Logistic Regression, Frequency Ratio, Weight of Evidence and Shannon’s Entropy methods

“…In natural disaster studies, the ROC curve and AUC values method is widely used for assessing the model performances of susceptibility models generated to understand flood, landslide, rockfall, and erosion events. ROC ve AUC method currently, most of the researchers are actively using this approach (Tehrany et al 2013;Miao et al 2023;Utlu 2023;El Miloudi et al 2024). Data from the susceptibility model's event inventory is required to measure model performances with accuracy and reliability.…”