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One major controlling factor of water erosion is rainfall erosivity, which is quantified as the product of total storm energy and a maximum 30 min intensity (I30). Rainfall erosivity is often expressed as R-factor in soil erosion risk models like the Universal Soil Loss Equation (USLE) and its revised version (RUSLE). As rainfall erosivity is closely correlated with rainfall amount and intensity, the rainfall erosivity of Switzerland can be expected to have a regional characteristic and seasonal dynamic throughout the year. This intra-annual variability was mapped by a monthly modeling approach to assess simultaneously spatial and monthly patterns of rainfall erosivity. So far only national seasonal means and regional annual means exist for Switzerland. We used a network of 87 precipitation gauging stations with a 10 min temporal resolution to calculate long-term monthly mean R-factors. Stepwise generalized linear regression (GLM) and leave-one-out cross-validation (LOOCV) were used to select spatial covariates which explain the spatial and temporal patterns of the R-factor for each month across Switzerland. The monthly R-factor is mapped by summarizing the predicted R-factor of the regression equation and the corresponding residues of the regression, which are interpolated by ordinary kriging (regression–kriging). As spatial covariates, a variety of precipitation indicator data has been included such as snow depths, a combination product of hourly precipitation measurements and radar observations (CombiPrecip), daily Alpine precipitation (EURO4M-APGD), and monthly precipitation sums (RhiresM). Topographic parameters (elevation, slope) were also significant explanatory variables for single months. The comparison of the 12 monthly rainfall erosivity maps showed a distinct seasonality with the highest rainfall erosivity in summer (June, July, and August) influenced by intense rainfall events. Winter months have the lowest rainfall erosivity. A proportion of 62 % of the total annual rainfall erosivity is identified within four months only (June–September). The highest erosion risk can be expected in July, where not only rainfall erosivity but also erosivity density is high. In addition to the intra-annual temporal regime, a spatial variability of this seasonality was detectable between different regions of Switzerland. The assessment of the dynamic behavior of the R-factor is valuable for the identification of susceptible seasons and regions.

The mean transit time (MTT) of water in a catchment gives information about storage, flow paths, sources of water and thus also about retention and release of solutes in a catchment. To our knowledge there are only a few catchment studies on the influence of vegetation cover changes on base flow MTTs. The main changes in vegetation cover in the Swiss Alps are massive shrub encroachment and forest expansion into formerly open habitats. Four small and relatively steep headwater catchments in the Swiss Alps (Ursern Valley) were investigated to relate different vegetation cover to water transit times. Time series of water stable isotopes were used to calculate MTTs. The high temporal variation of the stable isotope signals in precipitation was strongly dampened in stream base flow samples. MTTs of the four catchments were 70 to 102 weeks. The strong dampening of the stable isotope input signal as well as stream water geochemistry points to deeper flow paths and mixing of waters of different ages at the catchments' outlets. MTTs were neither related to topographic indices nor vegetation cover. The major part of the quickly infiltrating precipitation likely percolates through fractured and partially karstified deeper rock zones, which increases the control of bedrock flow paths on MTT. Snow accumulation and the timing of its melt play an important role for stable isotope dynamics during spring and early summer. We conclude that, in mountainous headwater catchments with relatively shallow soil layers, the hydrogeological and geochemical patterns (i.e. geochemistry, porosity and hydraulic conductivity of rocks) and snow dynamics influence storage, mixing and release of water in a stronger way than vegetation cover or topography do.

Empirical measurements on fine sediment dynamics and fine sediment infiltration and accumulation have been conducted worldwide, but it is difficult to compare the results because the applied methods differ widely. We compared common methods to capture temporal and spatial dynamics of suspended sediment (SS), fine sediment infiltration and accumulation and tested them for their suitability in a small, canalized river of the Swiss Plateau. Measurement suitability was assessed by data comparison, relation to hydrological data and in the context of previously published data. SS concentration and load were assessed by optical backscatter (OBS) sensors and SS samplers. The former exhibit a better temporal resolution, but were associated with calibration problems. Due to the relatively low cost and easy mounting of SS samplers, they can provide a higher spatial distribution in the river's cross section. The latter resulted in a better correlation between sediment infiltration and SS load assessed by SS samplers than SS concentrations measured with OBS sensors. Sediment infiltration baskets and bedload traps capture the temporal and spatial distribution of fine sediment infiltration. Data obtained by both methods were positively correlated with water level and SS. In contrast, accumulation baskets do not assess the temporal behaviour of fine sediment, but the net accumulation over a certain time period. Less fine sediment accumulated in upwelling zones and within areas of higher mean water level due to scouring of fine sediments. Even though SS and sediment infiltration assessed with the bedload traps increased from up- to downstream, less fine sediment accumulated downstream. This is probably also attributable to more scouring downstream.

Mountain areas are widely affected by soil erosion, which is generally linked to runoff processes occurring in the growing season and snowmelt period. Also processes like snow gliding and full-depth snow avalanches may be important factors that can enhance soil erosion, however the role and importance of snow movements as agents of soil redistribution are not well understood yet. The aim of this study was to provide information on the relative importance of snow related processes in comparison to runoff processes. In the study area, which is an avalanche path characterized by intense snow movements, soil redistribution rates were quantified with two methods: (i) by field measurements of sediment yield in an avalanche deposition area during 2009 and 2010 winter seasons; (ii) by caesium-137 method, which supplies the cumulative net soil loss/gain since 1986, including all the soil erosion processes. The snow related soil accumulation estimated with data from the deposit area (27.5 Mg ha−1 event−1 and 161.0 Mg ha−1 event−1) was not only higher than the yearly sediment amounts, reported in literature, due to runoff processes, but it was even more intense than the yearly total deposition rate assessed with 137Cs (12.6 Mg ha−1 yr−1). The snow related soil erosion rates estimated from the sediment yield at the avalanche deposit area (3.7 Mg ha−1 and 20.8 Mg ha−1) were greater than the erosion rates reported in literature and related to runoff processes; they were comparable to the yearly total erosion rates assessed with the 137Cs method (13.4 Mg ha−1 yr−1 and 8.8 Mg ha−1 yr−1). The 137Cs method also showed that, where the ground avalanche does not release, the erosion and deposition of soil particles from the upper part of the basin was considerable and likely related to snow gliding. Even though the comparison of both the approaches is linked to high methodological uncertainties, mainly due to the different spatial and temporal scales considered, we still can deduce, from the similarity of the erosion rates, that soil redistribution in this catchment is driven by snow movement, with a greater impact in comparison to the runoff processes occurring in the snow-free season. Nonetheless, the study highlights that soil erosion processes due to the snow movements should be considered in the assessment of soil vulnerability in mountain areas, as they significantly determine the pattern of soil redistribution.

Rainfall erosivity, considering rainfall amount and intensity, is an important parameter for soil erosion risk assessment under future land use and climate change. Despite its importance, rainfall erosivity is usually implemented in models with a low spatial and temporal resolution. The purpose of this study is to assess the temporal- and spatial distribution of rainfall erosivity in form of the (Revised) Universal Soil Loss Equation R-factor for Switzerland. Time series of 22 yr for rainfall (10 min resolution) and temperature (1 h resolution) data were analysed for 71 automatic gauging stations distributed throughout Switzerland. Regression-kriging was used to interpolate the rainfall erosivity values of single stations and to generate a map for Switzerland. Latitude, longitude, average annual precipitation, biogeographic units (Jura, Midland, etc.), aspect and elevation were used as covariates, of which average annual precipitation, elevation and the biographic unit (Western Central Alps) were significant (p−1 h−1 yr−1 with a range of lowest values of 124 MJ mm ha−1 h−1 yr−1 at an elevated station in Grisons to highest values of 5611 MJ mm ha−1 h−1 yr−1 in Ticino. All stations have highest erosivity values from July to August and lowest values in the winter months. Swiss-wide the month May to October show significantly increasing trends of rainfall erosivity for the observed period (pp

International audience; Water quality data for 56 long-term monitoring sites in eight European countries are used to assess freshwater responses to reductions in acid deposition at a large spatial scale. In a consistent analysis of trends from 1980 onwards, the majority of surface waters (38 of 56) showed significant (p ?0.05) decreasing trends in pollution-derived sulphate. Only two sites showed a significant increase. Nitrate, on the other hand, had a much weaker and more varied pattern, with no significant trend at 35 of 56 sites, decreases at some sites in Scandinavia and Central Europe, and increases at some sites in Italy and the UK. The general reduction in surface water acid anion concentrations has led to increases in acid neutralising capacity (significant at 27 of 56 sites) but has also been offset in part by decreases in base cations, particularly calcium (significant at 26 of 56 sites), indicating that much of the improvement in runoff quality to date has been the result of decreasing ionic strength. Increases in acid neutralising capacity have been accompanied by increases in pH and decreases in aluminium, although fewer trends were significant (pH 19 of 56, aluminium 13 of 53). Increases in pH appear to have been limited in some areas by rising concentrations of organic acids. Within a general trend towards recovery, some inter-regional variation is evident, with recovery strongest in the Czech Republic and Slovakia, moderate in Scandinavia and the United Kingdom, and apparently weakest in Germany. Keywords: acidification, recovery, European trends, sulphate, nitrate, acid neutralising capacity