Abstract. 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 floodprone 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 shortduration precipitation has been observed especially in stations located along the coastline; however, no clear and welldefined 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.

In this study we propose a probabilistic approach for coupled distributed hydrological-hillslope stability models that accounts for soil\ud parameters uncertainty at basin scale. The geotechnical and soil retention curve parameters are treated as random variables across the\ud basin and theoretical probability distributions of the Factor of Safety (FS) are estimated. The derived distributions are used to obtain the\ud spatio-temporal dynamics of probability of failure, in terms of parameters uncertainty, conditioned to soil moisture dynamics. The\ud framework has been implemented in the tRIBS-VEGGIE (Triangulated Irregular Network (TIN)-based Real-time Integrated Basin\ud Simulator-VEGetation Generator for Interactive Evolution)-Landslide model and applied to a basin in the Luquillo Experimental\ud Forest (Puerto Rico) where shallow landslides are common. In particular, the methodology was used to evaluate how the spatial and\ud temporal patterns of precipitation, whose variability is significant over the basin, affect the distribution of probability of failure, through\ud event scale analyses. Results indicate that hyetographs where heavy precipitation is near the end of the event lead to the most critical\ud conditions in terms of probability of failur

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Abstract. The probabilistic description of soil moisture dynamics is a relatively new topic in hydrology. The most common ecohydrological models start from a stochastic differential equation describing the soil water balance, where the unknown quantity, the soil moisture, depends both on spaces and time. Most of the solutions existing in literature are obtained in a probabilistic framework and under steady-state condition; even if this last condition allows the analytical handling of the problem, it has considerably simplified the same problem by subtracting generalities from it.The steady-state hypothesis, appears perfectly applicable in arid and semiarid climatic areas like those of African's or middle American's savannas, but it seems to be no more valid in areas with Mediterranean climate, where, notoriously, the wet season foregoes the growing season, recharging water into the soil. This moisture stored at the beginning of the growing season (known as soil moisture initial condition) has a great importance, especially for deep-rooted vegetation, by enabling survival in absence of rainfalls during the growing season and, however, keeping the water stress low during the first period of the same season.The aim of this paper is to analyze the soil moisture dynamics using a simple non-steady numerical ecohydrological model. The numerical model here proposed is able to reproduce soil moisture probability density function, obtained analytically in previous studies for different climates and soils in steady-state conditions; consequently it can be used to compute both the soil moisture time-profile and the vegetation static water stress time-profile in non-steady conditions.Here the differences between the steady-analytical and the non-steady numerical probability density functions are analyzed, showing how the proposed numerical model is able to capture the effects of winter recharge on the soil moisture.Correspondence to: D. Pumo (pumo@idra.unipa.it)The dynamic water stress is also numerically evaluated, implicitly taking into account the soil moisture condition at the beginning of the growing season. It is also shown the role of different annual climatic parameterizations on the soil moisture probability density function and on the vegetation water stress evaluation.The proposed model is applied to a case study characteristic of Mediterranean climate: the watershed of Eleuterio in Sicily (Italy).

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