The European Alps stretch over a range of climate zones which affect the spatial distribution of snow. Previous analyses of station observations of snow were confined to regional analyses. Here, we present an Alpine-wide analysis of snow depth from six Alpine countries – Austria, France, Germany, Italy, Slovenia, and Switzerland – including altogether more than 2000 stations of which more than 800 were used for the trend assessment. Using a principal component analysis and k-means clustering, we identified five main modes of variability and five regions which match the climatic forcing zones: north and high Alpine, north-east, north-west, south-east, and south and high Alpine. Linear trends of monthly mean snow depth between 1971 and 2019 showed decreases in snow depth for most stations from November to May. The average trend among all stations for seasonal (November to May) mean snow depth was −8.4 % per decade, for seasonal maximum snow depth −5.6 % per decade, and for seasonal snow cover duration −5.6 % per decade. Stronger and more significant trends were observed for periods and elevations where the transition from snow to snow-free occurs, which is consistent with an enhanced albedo feedback. Additionally, regional trends differed substantially at the same elevation, which challenges the notion of generalizing results from one region to another or to the whole Alps. This study presents an analysis of station snow depth series with the most comprehensive spatial coverage in the European Alps to date.

Classic (polybromodiphenyl ethers, PBDEs) and emerging halogenated flame retardants (HFRs) such as decabromodiphenyl ethane (DBDPE) and halogenated norbornenes, as well as organophosphate flame retardants (OPFRs) were analysed in 52 sediments and 27 fish samples from three European river basins, namely the Evrotas (Greece), the Adige (Italy) and the Sava (Slovenia, Croatia, Bosnia and Herzegovina and Serbia). This is the first time that FR levels have been reported in these three European river basins. The highest contamination was found in the Adige and Sava rivers, whereas lower values were obtained for the Evrotas. The levels in sediment samples ranged between 0.25 and 34.0ng/g dw, and between 0.31 and 549ng/g dw, for HFRs and OPFRs respectively. As regards levels in fish, concentrations ranged between 9.32 and 461ng/g lw and between 14.4 and 650ng/g lw, for HFRs and OPFRs, respectively. Thus, whereas OPFR values were higher in sediments, similar concentrations (in the Evrotas) and even lower concentrations than HFRs (Sava) were found for OPFRs in the fish samples, indicating the lower bioaccumulation potential of OPFRs. Biota to sediment accumulation factors (BSAFs) were calculated and higher values were obtained for HFRs compared to those assessed for OPFRs.

This study analyses how indicators of water quality (thirteen physico-chemical variables) and drivers of change (i.e., monthly aggregated air temperature and streamflow, population density, and percentage of agricultural land use) coevolve in three large European river basins (i.e., Adige, Ebro, Sava) with different climatic, soil and water use conditions. Spearman rank correlation, Principal Component Analysis, and Mann-Kendall trend tests were applied to long-term time series of water quality data during the period 1990-2015 in order to investigate the relationships between water quality parameters and the main factors controlling them. Results show that air temperature, considered as a proxy of climatic change, has a significant impact, in particular in the Adige and Ebro: positive trends of water temperature and negative of dissolved oxygen are correlated with upward trends of air temperatures. The aquatic ecosystems of these rivers are, therefore, experiencing a reduction in oxygen, which may exacerbate in the future given the projected further increase in temperature. Furthermore, monthly streamflow has been shown to reduce in the Ebro, thereby reducing the beneficial effect of dilution, which appears evident from the observed upward patterns of chloride concentrations and electrical conductivity. Upward trends of chloride and biological oxygen demand in the Adige and Sava, and of phosphate in the Adige appears to be related to increasing human population density, whereas phosphates in the Sava and biological oxygen demand in the Ebro are highly correlated with agricultural land use, considered as a proxy of the impact of agricultural practises. The present study shows the complex relationships between drivers and observed changes in water quality parameters. Such analysis can represent, complementary to a deep knowledge of the investigated systems, a reliable tool for decision makers in river basin planning by providing an overview of the potential impacts on the aquatic ecosystem of the three basins.

Water temperature in lakes is governed by a complex heat budget, where the estimation of the single fluxes requires the use of several hydro-meteorological variables that are not generally available. In order to address this issue, we developed Air2Water, a simple physically based model to relate the temperature of the lake superficial layer (epilimnion) to air temperature only. The model has the form of an ordinary differential equation that accounts for the overall heat exchanges with the atmosphere and the deeper layer of the lake (hypolimnion) by means of simplified relationships, which contain a few parameters (from four to eight in the different proposed formulations) to be calibrated with the combined use of air and water temperature measurements. The calibration of the parameters in a given case study allows for one to estimate, in a synthetic way, the influence of the main processes controlling the lake thermal dynamics, and to recognize the atmospheric temperature as the main factor driving the evolution of the system. In fact, under certain hypotheses the air temperature variation implicitly contains proper information about the other major processes involved, and hence in our approach is considered as the only input variable of the model. In particular, the model is suitable to be applied over long timescales (from monthly to interannual), and can be easily used to predict the response of a lake to climate change, since projected air temperatures are usually available by large-scale global circulation models. In this paper, the model is applied to Lake Superior (USA–Canada) considering a 27 yr record of measurements, among which 18 yr are used for calibration and the remaining 9 yr for model validation. The calibration of the model is obtained by using the generalized likelihood uncertainty estimation (GLUE) methodology, which also allows for a sensitivity analysis of the parameters. The results show remarkable agreement with measurements over the entire data period. The use of air temperature reconstructed by satellite imagery is also discussed.