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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.

Extremely great floods are among environmental events with the most disastrous consequences for the entire world. Estimates of their return periods and design values are of great importance in hydrologic modeling, engineering practice for water resources and reservoirs design and management, planning for weatherrelated emergencies, etc. Regional flood frequency analysis resolves the problem of estimating the extreme flood events for catchments having short data records or ungauged catchments. This paper analyzes annual maximum peak flood discharge data recorded from more than 50 stream flow gauging sites in Sicily, Italy, in order to derive regional flood frequency curves. First these data are analyzed to point out some problems concerning the homogeneity of the single time series. On the basis of the L-moments and using cluster analysis techniques, the entire region is subdivided in five subregions whose homogeneity is tested using the L-moments based heterogeneity measure. Comparative regional flood frequency analysis studies are carried out employing the L-moments based commonly used frequency distributions. Based on the L-moment ratio diagram and other statistic criteria, generalized extreme value (GEV) distribution is identified as the robust distribution for the study area. Regional flood frequency relationships are developed to estimate floods at 2208 L.V. Noto, G. La Loggia various return periods for gauged and ungauged catchments in different subregions of the Sicily. These relationships have been implemented using the L-moment based GEV distribution and a regional relation between mean annual peak flood and some geomorphologic and climatic parameters of catchments.

Abstract. This paper presents the development of a rainfalltriggered 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.