Abstract. The mountain cryosphere of mainland Europe is recognized to have important impacts on a range of environmental processes. In this paper, we provide an overview on the current knowledge on snow, glacier, and permafrost processes, as well as their past, current, and future evolution. We additionally provide an assessment of current cryosphere research in Europe and point to the different domains requiring further research. Emphasis is given to our understanding of climate–cryosphere interactions, cryosphere controls on physical and biological mountain systems, and related impacts. By the end of the century, Europe's mountain cryosphere will have changed to an extent that will impact the landscape, the hydrological regimes, the water resources, and the infrastructure. The impacts will not remain confined to the mountain area but also affect the downstream lowlands, entailing a wide range of socioeconomical consequences. European mountains will have a completely different visual appearance, in which low- and mid-range-altitude glaciers will have disappeared and even large valley glaciers will have experienced significant retreat and mass loss. Due to increased air temperatures and related shifts from solid to liquid precipitation, seasonal snow lines will be found at much higher altitudes, and the snow season will be much shorter than today. These changes in snow and ice melt will cause a shift in the timing of discharge maxima, as well as a transition of runoff regimes from glacial to nival and from nival to pluvial. This will entail significant impacts on the seasonality of high-altitude water availability, with consequences for water storage and management in reservoirs for drinking water, irrigation, and hydropower production. Whereas an upward shift of the tree line and expansion of vegetation can be expected into current periglacial areas, the disappearance of permafrost at lower altitudes and its warming at higher elevations will likely result in mass movements and process chains beyond historical experience. Future cryospheric research has the responsibility not only to foster awareness of these expected changes and to develop targeted strategies to precisely quantify their magnitude and rate of occurrence but also to help in the development of approaches to adapt to these changes and to mitigate their consequences. Major joint efforts are required in the domain of cryospheric monitoring, which will require coordination in terms of data availability and quality. In particular, we recognize the quantification of high-altitude precipitation as a key source of uncertainty in projections of future changes. Improvements in numerical modeling and a better understanding of process chains affecting high-altitude mass movements are the two further fields that – in our view – future cryospheric research should focus on.

Abstract. The spatial distribution of alpine snow covers is characterised by large variability. Taking this variability into account is important for many tasks including hydrology, glaciology, ecology or natural hazards. Statistical modelling is frequently applied to assess the spatial variability of the snow cover. For this study, we assembled seven data sets of high-resolution snow-depth measurements from different mountain regions around the world. All data were obtained from airborne laser scanning near the time of maximum seasonal snow accumulation. Topographic parameters were used to model the snow depth distribution on the catchment-scale by applying multiple linear regressions. We found that by averaging out the substantial spatial heterogeneity at the metre scales, i.e. individual drifts and aggregating snow accumulation at the landscape or hydrological response unit scale (cell size 400 m), that 30 to 91 % of the snow depth variability can be explained by models that are calibrated to local conditions at the single study areas. As all sites were sparsely vegetated, only a few topographic variables were included as explanatory variables, including elevation, slope, the deviation of the aspect from north (northing), and a wind sheltering parameter. In most cases, elevation, slope and northing are very good predictors of snow distribution. A comparison of the models showed that importance of parameters and their coefficients differed among the catchments. A "global" model, combining all the data from all areas investigated, could only explain 23 % of the variability. It appears that local statistical models cannot be transferred to different regions. However, models developed on one peak snow season are good predictors for other peak snow seasons.

In recent years airborne laser scanning (ALS) evolved into a state-of-the-art technology for topographic data acquisition. We present a novel, automatic method for water surface classification and delineation by combining the geometrical and signal intensity information provided by ALS. The reflection characteristics of water surfaces in the near-infrared wavelength (1064 nm) of the ALS system along with the surface roughness information provide the basis for the differentiation between water and land areas. Water areas are characterized by a high number of laser shot dropouts and predominant low backscatter energy. In a preprocessing step, the recorded intensities are corrected for spherical loss and atmospheric attenuation, and the locations of laser shot dropouts are modeled. A seeded region growing segmentation, applied to the point cloud and the modeled dropouts, is used to detect potential water regions. Object-based classification of the resulting segments determines the final separation of water and non-water points. The water-land-boundary is defined by the central contour line of the transition zone between water and land points. We demonstrate that the proposed workflow succeeds for a regulated river (Inn, Austria) with smooth water surface as well as for a pro-glacial braided river (Hintereisfernerbach, Austria). A multi-temporal analysis over five years of the pro-glacial river channel emphasizes the applicability of the developed method for different ALS systems and acquisition settings (e.g. point density). The validation, based on real time kinematic (RTK) global positioning system (GPS) field survey and a terrestrial orthophoto, indicate point cloud classification accuracy above 97% with 0·45 m planimetric accuracy (root mean square error) of the water-land boundary. This article shows the capability of ALS data for water surface mapping with a high degree of automation and accuracy. This provides valuable datasets for a number of applications in geomorphology, hydrology and hydraulics, such as monitoring of braided rivers, flood modeling and mapping.

No abstract

Abstract. Many studies have investigated potential climate change impacts on regional hydrology; less attention has been given to the components of uncertainty that affect these scenarios. This study quantifies uncertainties resulting from (i) General Circulation Models (GCMs), (ii) Regional Climate Models (RCMs), (iii) bias-correction of RCMs, and (iv) hydrological model parameterization using a multi-model framework. This consists of three GCMs, three RCMs, three bias-correction techniques, and sets of hydrological model parameters. The study is performed for the Lech watershed (∼ 1000 km 2 ), located in the Northern Limestone Alps, Austria. Bias-corrected climate data are used to drive the hydrological model HQsim to simulate runoff under present and future (2070-2099) climate conditions. Hydrological model parameter uncertainty is assessed by Monte Carlo sampling. The model chain is found to perform well under present climate conditions. However, hydrological projections are associated with high uncertainty, mainly due to the choice of GCM and RCM. Uncertainty due to bias-correction is found to have greatest influence on projections of extreme river flows, and the choice of method(s) is an important consideration in snowmelt systems. Overall, hydrological model parameterization is least important. The study also demonstrates how an improved understanding of the physical processes governing future river flows can help focus attention on the scientifically tractable elements of the uncertainty.

The drumlin field at Múlajökull, Iceland, is considered to be an active field in that partly and fully ice‐covered drumlins are being shaped by the current glacier regime. We test the hypothesis that the drumlins form by a combination of erosion and deposition during successive surge cycles. We mapped and measured 143 drumlins and studied their stratigraphy in four exposures. All exposures reveal several till units where the youngest till commonly truncates older tills on the drumlin flanks and proximal slope. Drumlins inside a 1992 moraine are relatively long and narrow whereas drumlins outside the moraine are wider and shorter. A conceptual model suggests that radial crevasses create spatial heterogeneity in normal stress on the bed so that deposition is favoured beneath crevasses and erosion in adjacent areas. Consequently, the crevasse pattern of the glacier controls the location of proto‐drumlins. A feedback mechanism leads to continued crevassing and increased sedimentation at the location of the proto‐drumlins. The drumlin relief and elongation ratio increases as the glacier erodes the sides and drapes a new till over the landform through successive surges. Our observations of this only known active drumlin field may have implications for the formation and morphological evolution of Pleistocene drumlin fields with similar composition, and our model may be tested on modern drumlins that may become exposed upon future ice retreat.

Abstract. This study presents a reanalysis of the glaciologically obtained annual glacier mass balances at Hintereisferner, Ötztal Alps, Austria, for the period 2001–2011. The reanalysis is accomplished through a comparison with geodetically derived mass changes, using annual high-resolution airborne laser scanning (ALS). The grid-based adjustments for the method-inherent differences are discussed along with associated uncertainties and discrepancies of the two methods of mass balance measurements. A statistical comparison of the two datasets shows no significant difference for seven annual, as well as the cumulative, mass changes over the 10-year record. Yet, the statistical view hides significant differences in the mass balance years 2002/03 (glaciological minus geodetic records  = +0.92 m w.e.), 2005/06 (+0.60 m w.e.), and 2006/07 (−0.45 m w.e.). We conclude that exceptional meteorological conditions can render the usual glaciological observational network inadequate. Furthermore, we consider that ALS data reliably reproduce the annual mass balance and can be seen as validation or calibration tools for the glaciological method.

No abstract