Introducing intense rainfall and snowmelt variables to implement a process-related non-stationary shallow landslide susceptibility analysis

作     者：Camera, Corrado A. S. Bajni, Greta Corno, Irene Raffa, Mattia Stevenazzi, Stefania Apuani, Tiziana 

作者机构：Univ Milan Dipartimento Sci Terra A Desio Milan Italy 

出 版 物：《SCIENCE OF THE TOTAL ENVIRONMENT》 (整体环境科学)

年 卷 期：2021年第786卷

页      面：147360-147360页

核心收录：

学科分类：0830[工学-环境科学与工程（可授工学、理学、农学学位）] 08[工学] 

基　　金：MIUR - Ministero dell'Istruzione  dell'Universita e della Ricerca 

主　　题：Climate variables Slides in soil Flowslides Generalized Additive Models Snow Water Equivalent Aosta Valley 

摘      要：The study objective was to derive a susceptibility model for shallow landslides that could include process-related non-stationary variables, to be adaptable to climate changes. We selected the territory of the Mont-Emilius and Mont-Cervin Mountain Communities (northern Italy) as the study area. To define summary variables related to landslide predisposing and triggering processes, we investigated the relationships between landslide occurrences and intense rainfall and snowmelt events (period 1991-2020). For landslide susceptibility mapping, we set up a Generalized Additive Model. We defined a reference model through variable penalization (relief, NDVI, land cover and geology predictors). Similarly, we optimized a model including the climate variables, checking their smooth functions to ensure physical plausibility. Finally, we validated the optimized model through a k-fold cross-validation and performed an evaluation based on contingency tables, area under the receiver operating characteristic curve (AUROC) and variable importance (decrease in explained variance). The climate variables that resulted as being statistically and physically significant are the effective annual number of rainfall events with intensity-duration characteristics above a defined threshold (EAT(ean)) and the average number of melting events occurring in a hydrological year (MEn). In the optimized model, EAT(ean) and MEn accounted for 5% of the explained deviance. Compared to the reference model, their introduction led to an increase in true positive rate and AUROC of 2.4% and 0.8%, respectively. Also, their inclusion caused a transition of the vulnerability class in 11.0% of the study area. The k-fold validation confirmed the statistical significance and physical plausibility of the meteorological variables in 74% (EAT(ean)) and 93% (MEn) of the fitted models. Our results demonstrate the validity of the proposed approach to introduce process-related, non-stationary, physically-plausible clima