Rock glaciers are capable of storing water in solid (permafrost ice) as well as in liquid form (groundwater within the unfrozen base layer). The latter is relevant no matter the actual state of the rock glacier (intact, containing ice versus relict, no more ice present). A nation-wide comparison of the water equivalent of glacier ice within the Austrian Alps is conducted to evaluate the role of rock glaciers in the hydrological cycle at its current state and potentially in the future. Estimates of ice volumes and their uncertainties, especially related to thickness estimates of permafrost-ice bodies, are discussed in the light of available data and need to be seen as order-of-magnitude estimates. With intact rock glaciers covering almost 123 km² and an assumed ice content of 40% within the permafrost body, ice volumes are estimated to be 0.93 Gigatons. This corresponds to 8.3% of the ice volume estimated for the most recent glacier inventory of the Austrian Alps. Thus, with the currently available data, a water equivalent ratio of ~1: 12 for rock glacier ice versus glacier ice is estimated. In addition to the solid water storage, the dynamic storage potential within rock glaciers in liquid form needs to be considered. While this volume is relatively small compared to the ice volume in glaciers and rock glaciers (ratio of ~1: 20), the time-scales of hydrological relevance (when they become runoff due to ice melt) are very different. This dynamic liquid water storage is replenishable and therefore available over shorter time scales (seasonal drainage pattern), and moreover relatively stable and may potentially even slightly increase as pore space becomes available due to increased melting of permafrost ice. In the light of climate warming and projected glacier recession, the relative hydrological importance of rock glaciers as water stores (in solid as well as in liquid form) in the European Alps is expected to increase and their storage-discharge patterns need to be accounted for in water management considerations.

Earth observation offers a variety of techniques for monitoring and characterizing geomorphic processes in high mountain environments. Terrestrial laserscanning and unmanned aerial vehicles provide very high resolution data with high accuracy. Automatic cameras have become a valuable source of information—mostly in a qualitative manner—in recent years. The availability of satellite data with very high revisiting time has gained momentum through the European Space Agency’s Sentinel missions, offering new application potential for Earth observation. This paper reviews the status of recent techniques such as terrestrial laserscanning, remote sensed imagery, and synthetic aperture radar in monitoring high mountain environments with a particular focus on the impact of new platforms such as Sentinel-1 and -2 as well as unmanned aerial vehicles. The study area comprises the high mountain glacial environment at the Pasterze Glacier, Austria. The area is characterized by a highly dynamic geomorphological evolution and by being subject to intensive scientific research as well as long-term monitoring. We primarily evaluate landform classification and process characterization for: (i) the proglacial lake; (ii) icebergs; (iii) the glacier river; (iv) valley-bottom processes; (v) slope processes; and (vi) rock wall processes. We focus on assessing the potential of every single method both in spatial and temporal resolution in characterizing different geomorphic processes. Examples of the individual techniques are evaluated qualitatively and quantitatively in the context of: (i) morphometric analysis; (ii) applicability in high alpine regions; and (iii) comparability of the methods among themselves. The final frame of this article includes considerations on scale dependent process detectability and characterization potentials of these Earth observation methods, along with strengths and limitations in applying these methods in high alpine regions.

Multi‐temporal digital terrain models (DTMs) derived from airborne or uncrewed aerial vehicle (UAV)‐borne light detection and ranging (LiDAR) platforms are frequently used tools in geomorphic impact studies. Accurate estimation of mobilized sediments from multi‐temporal DTMs is indispensable for hazard assessment. To study volumetric changes in alpine environments it is crucial to identify and discuss different kind of error sources in multi‐temporal data. We subdivided errors into those caused by data acquisition, data processing, and spatial properties of the terrain. In terms of the quantification of surface changes, the propagation of errors can lead to high uncertainties.Three alpine catchments with different LiDAR point clouds of different origins (airborne laser scanning [ALS], UAV‐borne laser scanning [ULS]), varying point densities, accuracies and qualities were analysed, and used as basis for interpolating DTMs. The workflow was developed in the Schöttlbach area in Styria and later applied to further catchments in Austria. The main aim of the presented work is a comprehensive DTM uncertainty analysis specially designed for geomorphic impact studies, with a resulting uncertainty analysis serving as input for a change detection tool. Our findings reveal that geomorphic impact studies need the careful distinction between actual surface changes and different data uncertainties. ULS combines the benefits of terrestrial laser scanning with all the benefits of ALS. However, the use of ULS data does not necessarily improve the results of the analysis since the high level of detail is not always helpful in geomorphic impact studies. In order to make the different point clouds and DTMs comparable the quality of the ULS point cloud had to be reduced to fit the accuracy of the reference data (older ALS point clouds). Using a point cloud with a high point density with a regular planimetric point spacing and less data gaps, in the best case collected during leaf‐off conditions (e.g., cross‐flight strategy) turned out to be sufficient for our geomorphic research purposes.