Changes in rainfall characteristics are one of the most relevant signs of current climate alterations. Many studies have demonstrated an increase in rainfall intensity and a reduction of frequency in several areas of the world, including Mediterranean areas. Rainfall characteristics may be crucial for vegetation patterns formation and evolution in Mediterranean ecosystems, with important implications, for example, in vegetation water stress or coexistence and competition dynamics. At the same time, characteristics of extreme rainfall events are fundamental for the estimation of flood peaks and quantiles that can be used in many hydrological applications, such as design of the most common hydraulic structures, or planning and management of flood-prone areas. In the past, Sicily has been screened for several signals of possible climate change. Annual, seasonal and monthly rainfall data in the entire Sicilian region have been analyzed, showing a global reduction of total annual rainfall. Moreover, annual maximum rainfall series for different durations have been rarely analyzed in order to detect the presence of trends. Results indicated that for short durations, historical series generally exhibit increasing trends, while for longer durations the trends are mainly negative. Starting from these premises, the aim of this study is to investigate and quantify changes in rainfall statistics in Sicily, during the second half of the last century. Time series of about 60 stations over the region have been processed and screened by using the nonparametric Mann–Kendall test. In particular, extreme events have been analyzed using annual maximum rainfall series at 1, 3, 6, 12 and 24 h duration, while daily rainfall properties have been analyzed in terms of frequency and intensity, also characterizing seasonal rainfall features. Results of extreme events analysis confirmed an increasing trend for rainfall of short durations, especially for 1 h rainfall duration. Conversely, precipitation events of long durations have exhibited a decreased trend. Increase in short-duration precipitation has been observed especially in stations located along the coastline; however, no clear and well-defined spatial pattern has been outlined by the results. Outcomes of analysis for daily rainfall properties have showed that heavy–torrential precipitation events tend to be more frequent at regional scale, while light rainfall events exhibited a negative trend at some sites. Values of total annual precipitation events confirmed a significant negative trend, mainly due to the reduction during the winter season.

Landslides are a serious threat to life and property throughout the world. The causes of landslides are various since multiple dynamic processes are involved in driving slope failures. One of these causes is prolonged rainfall, which affects slope stability in different ways. Water infiltrating in a hillslope may cause a rise of the piezometric surface, which, in turn, involves an increase of the pore water pressure and a decrease of the soil shear resistance. For this reason, knowledge of spatio-temporal dynamics of soil water content, infiltration processes and groundwater dynamics, is of considerable importance in the understanding and prediction of landslides dynamics.In this paper a spatially distributed and physically based approach is presented, which embeds a slope failure method in a hydrological model. The hydrological model here used is the tRIBS model (Triangulated Irregular Network Real-Time Integrated Basin Simulator) that allows simulation of most of spatial-temporal hydrologic processes (infiltration, evapotranspiration, groundwater dynamics and soil moisture conditions) that can influence landsliding. Slope stability is assessed by implementing the infinite slope model in tRIBS. The model, based on geotechnical and geomorphological characteristics, classifies each computational cell as unconditionally stable or conditionally stable. Soil moisture conditions resulting from precipitation can trigger landslides at conditionally stable locations. When a landslide occurs, the model also computes the amount of detached soil and its possible path downslope.Model performance has been initially tested on a small catchment with very steep slopes, located in the northern part of Sicily (Italy), after a sensitivity analysis concerning some model parameters

This paper presents the development of a rainfall-triggered landslide module within an existing physically based spatially distributed ecohydrologic model. The model, tRIBS-VEGGIE (Triangulated Irregular Networks-based Real-time Integrated Basin Simulator and Vegetation Generator for Interactive Evolution), is capable of a sophisticated description of many hydrological processes; in particular, the soil moisture dynamics are resolved at a temporal and spatial resolution required to examine the triggering mechanisms of rainfall-induced landslides. The validity of the tRIBS-VEGGIE model to a tropical environment is shown with an evaluation of its performance against direct observations made within the study area of Luquillo Forest. The newly developed landslide module builds upon the previous version of the tRIBS landslide component. This new module utilizes a numerical solution to the Richards' equation (present in tRIBS-VEGGIE but not in tRIBS), which better represents the time evolution of soil moisture transport through the soil column. Moreover, the new landslide module utilizes an extended formulation of the factor of safety (FS) to correctly quantify the role of matric suction in slope stability and to account for unsaturated conditions in the evaluation of FS. The new modeling framework couples the capabilities of the detailed hydrologic model to describe soil moisture dynamics with the infinite slope model, creating a powerful tool for the assessment of rainfall-triggered landslide risk.