No abstract

A statistical approach was employed to model the spatial distribution of rainfall-triggered landslides in two areas in Sicily (Italy) that occurred during the winter of 2004-2005. The investigated areas are located within the Belice River basin and extend for 38.5 and 10.3 km2, respectively. A landslide inventory was established for both areas using two Google Earth images taken on October 25th 2004 and on March 18th 2005, to map slope failures activated or reactivated during this interval. Geographic Information Systems (GIS) were used to prepare 5 m grids of the dependent variables (absence/presence of landslide) and independent variables (lithology and 13 DEM-derivatives). Multivariate Adaptive Regression Splines (MARS) were applied to model landslide susceptibility whereas receiver operating characteristic (ROC) curves and the area under the ROC curve (AUC) were used to evaluate model performance. To evaluate the robustness of the whole procedure, we prepared 10 different samples of positive (landslide presence) and negative (landslide absence) cases for each area. Absences were selected through two different methods: (i) extraction from randomly distributed circles with a diameter corresponding to the mean width of the landslide source areas; and (ii) selection as randomly distributed individual grid cells. A comparison was also made between the predictive performances of models including and not including the lithology parameter.The models trained and tested on the same area demonstrated excellent to outstanding fit (AUC > 0.8). On the other hand, predictive skill decreases when measured outside the calibration area, although most of the landslides occur where susceptibility is high and the overall model performance is acceptable (AUC > 0.7). The results also showed that the accuracy of the landslide susceptibility models is higher when lithology is included in the statistical analysis. Models whose absences were selected using random circles showed a significantly better performance when learning and validation samples were extracted from the same area; whereas, conversely, no significant difference was observed when testing the models outside the training area

No abstract

No abstract

No abstract

Calanchi are erosion landforms characterised by a heavily dissected terrain with steep, unvegetated slopes and channels with a dendritic pattern, which rapidly incise and extend headwards. Recent literature focusing on badland systems highlights their similarity with other larger fluvial landforms, stating that these behave as a full size laboratory, due to their rapid development in space and time and to the diversity of geomorphic processes involved.In this paper, a brief review of the most important results on badland research is firstly presented. Then, the morphometric similarity between calanchi and other erosion landforms is discussed. Finally, models quantitatively relating the volume of sediments eroded from calanchi landforms and a set of geometric features of their tributary areas, by exploiting the dimensional analysis and the self-similarity theory, are presented.

Calanchi, a type of Italian badlands created by a combination of water erosion processes and local geomorphological and tectonic controls, is a striking example of long‐term landscape evolution. In small temporal/spatial scales, the calanchi exhibit many of the geomorphic processes and landforms that may be observed in fluvial landscapes; hence, they may be considered as microbasins where geomorphic dynamics and landscape features can be related. The goal of this research is testing the use of simple morphometric variables for assessing sediment connectivity of calanchi landforms. In order to detect the morphological characteristics controlling the landscape connectivity of calanchi basins, 2 areas located in Sicily (Italy) were examined. The investigated features were identified on 119 calanchi basins and mapped using orthophotographs and 2‐m‐resolution digital elevation models. Application of Hack's law to the calanchi basins showed that the width/length ratio increases with the drainage area, suggesting that calanchi may have a limited connectivity of their hillslopes to the main channel. Moreover, the analysis of the drainage network composition suggested that calanchi are sediment removal systems more efficient than river basins. The empirical frequency distribution of the travel time, which is the ratio between the length and the square root of the hillslope steepness, of each cell of the calanchi digital elevation model was established. Finally, for each calanchi basin, an index of hillslope connectivity was devised. This was explored as a function of the sediment transport efficiency itself estimated by the travel time and the corresponding sediment delivery ratio of each calanco hillslope cell.

No abstract