Investigating Causal Factors of Shallow Landslides in Grassland Regions of Switzerland

Abstract

Abstract. Mountainous grassland slopes can be severely affected by soil erosion. To better understand the regional differences of soil erosion patterns, we determine the locations of shallow landslides across different sites and aim at identifying their triggering causal factors. Ten sites across Switzerland located in the Alps (8 sites), in foothill regions (1 site), and the Jura mountains (1 site) were selected for statistical evaluations. For the shallow landslide inventory, we used aerial images (0.25 m) with a deep learning approach (U-Net) to map the locations of eroded sites. We used logistic regression with a Group Lasso variable selection method to identify important explanatory variables for predicting the mapped shallow landslides. The set of variables consists of traditional susceptibility modelling factors and climate-related factors to represent local as well as cross-regional conditions. This set of explanatory variables (predictors) are used to develop individual site models (regional evaluation) as well as an all-in-one model (cross-regional evaluation) using all shallow landslide points simultaneously. While the local conditions of the ten sites lead to different variable selections, consistently slope and aspect were selected as the essential explanatory variables of shallow landslide susceptibility. Accuracy scores range between 70.2 and 79.8 % for individual site models. The all-in-one model confirms these findings by selecting slope, aspect as well as roughness as the most important explanatory variables (Accuracy = 72.3 %). Our finding suggest that traditional susceptibility variables describing geomorphological and geological conditions yield satisfactory results for all tested regions. However, for two sites with lower model accuracy, important processes may be under-represented with the available explanatory variables. The regression models for sites with an east-west oriented valley axis performed slightly better than models for north-south oriented valleys, which may be due to the influence of exposition related processes. Additionally, model performance is higher for Alpine sites, suggesting that core explanatory variables are understood for these areas.

Temporal and Spatial Distribution Characteristics of Flood Disasters with Different Intensities in Arid-Semiarid Region in Northern Xinjiang, China

“…High precipitation values (300-530 mm) range from 15.1 to 505.8 mm annually. Recently the importance of changes in temporal patterns of heavy precipitation events on agriculturally dominated areas flooding has been highlighted [17,18]. Northern Xinjiang has a relatively humid climate, abundant water sources, relatively fertile land, a relatively dense population, and highly concentrated areas of productivity.…”