Alpine Terrain Research Articles

To the Origin of a Wintertime Screen-Level Temperature Bias at High Altitude in a Kilometric NWP Model

Abstract High-resolution numerical weather prediction (NWP) systems present a strong potential to provide meteorological information in alpine terrain for diverse applications. However, they still suffer from biases highly detrimental for practical purposes. In this study, we investigate the origin of a significant wintertime screen-level temperature bias in forecasts of the AROME-France NWP system in high-altitude, snow-covered alpine terrain. For this purpose, a thorough set of meteorological and snow observations from two high-altitude instrumental sites is used. Targeted numerical simulations are carried out to disentangle the contributions to this bias coming from atmospheric fields, from the snow scheme, and from the coupling between the snowpack and the atmosphere. At both sites, the wind speed and incoming longwave radiation appear significantly negatively biased in AROME in the winter season. Using targeted offline simulations, we show that the simulation errors in these screen-level fields contribute to an average of 67% of the screen-level temperature bias of AROME, while the contribution of errors in the incoming shortwave radiation is negligible. Additionally, the screen-level temperature of AROME is not majorly impacted by changes in the complexity and especially the vertical layering of the snow model. However, it appears particularly sensitive to the parameterization of turbulent fluxes in stable conditions. Evidence suggest that these findings could at least partially be generalized to the whole AROME-France alpine domain. Hence, reducing the high-altitude, winter screen-level temperature bias in AROME may in great part proceed from improving the simulation of atmospheric fields and eliminating some bias compensations in the model.

Water Balance in Alpine Catchments by Sentinel Data

AbstractA comprehensive and reliable water balance of snow‐dominated alpine catchments is required for a holistic analysis of the hydrological and hydrogeological processes. A major limitation to the elaboration of this balance in alpine terrain is the difficulty of data acquisition as well as the limited presence of meteorological stations. Remotely sensed data can provide valuable information for the water balance assessment on a regional scale. We exploited Sentinel‐satellite data to estimate the groundwater storage for one hydrologic year in an extensive Alpine catchment located in northern Italy by means of the residual water balance approach. In particular, Evapotranspiration (ET) and Snow Water Equivalent were estimated with the combined use of Sentinel data, at a spatial resolution of 20 and 30 m, respectively. The results show that the adopted satellite‐based methods allow obtaining consistent and physically realistic values to describe the groundwater storage dynamics. In the period 2018–2020, a positive storage occurred only during the snowmelt period and the overall storage was negative, leading to a net lowering of the groundwater level in the floodplain. In addition, the influence of physiographic parameters (altitude, slope, and aspect) and seasonality on the estimates of ET and snow‐depth were investigated.

Das ÖBB‐Kraftwerk Tauernmoos – Energiespeicher für die Bahn

AbstractIn 2004, ÖBB‐Infrastruktur AG started the first studies for the construction of a pumped‐storage hydro power plant between the two largest reservoirs of the existing Stubach Valley power plant group in Salzburg's Pinzgau region. Two reversible pump‐turbine units including a full converter with a total capacity of 170 MW and a maximum flow of 80 m3/s are planned. The construction of the 335 million. euro project started in 2020 and will be completed by autumn 2025. In addition to a 50,000 m3 cavern, an 11.5 km tunnel system including the access tunnels and the power water ways have been built. Most of the 11.5 km tunnel system is situated in stable gneiss. A greater challenge is the construction of the two inlet and outlet structures in the high mountain region during the winter season, when the lakes can be held on the lowest reservoir level. Since the remaining construction work is also carried out at an altitude of 1500 to 2250 m above sea level in alpine terrain, the construction company has been facing recurring problems such as snow, cold, wind, mudslides and the associated logistical difficulties. Despite these challenges, the excavation work was completed in summer 2022. The main focus is currently placed on the concrete works in the cavern, which is scheduled to be completed in autumn 2023. This will be followed by the installation of mechanical and electrical equipment as well as the control systems.

The impact of terrain model source and resolution on snow avalanche modeling

Abstract. Natural hazard models need accurate digital elevation models (DEMs) to simulate mass movements on real-world terrain. A variety of platforms (terrestrial, drones, aerial, satellite) and sensor technologies (photogrammetry, lidar, interferometric synthetic aperture radar) are used to generate DEMs at a range of spatial resolutions with varying accuracy. As the availability of high-resolution DEMs continues to increase and the cost to produce DEMs continues to fall, hazard modelers must often choose which DEM to use for their modeling. We use satellite photogrammetry and topographic lidar to generate high-resolution DEMs and test the sensitivity of the Rapid Mass Movement Simulation (RAMMS) software to the DEM source and spatial resolution when simulating a large and complex snow avalanche along Milford Road in Aotearoa/New Zealand. Holding the RAMMS parameters constant while adjusting the source and spatial resolution of the DEM reveals how differences in terrain representation between the satellite photogrammetry and topographic lidar DEMs (2 m spatial resolution) affect the reliability of the simulation estimates (e.g., maximum core velocity, powder pressure, runout length, final debris pattern). At the same time, coarser representations of the terrain (5 and 15 m spatial resolution) simulate avalanches that run too far and produce a powder cloud that is too large, though with lower maximum impact pressures, compared to the actual event. The complex nature of the alpine terrain in the avalanche path (steep, rough, rock faces, treeless) makes it a suitable location to specifically test the model sensitivity to digital surface models (DSMs) where both ground and above-ground features on the topography are included in the elevation model. Considering the nature of the snowpack in the path (warm, deep with a steep elevation gradient) lying on a bedrock surface and plunging over a cliff, RAMMS performed well in the challenging conditions when using the high-resolution 2 m lidar DSM, with 99 % of the simulated debris volume located in the documented debris area.

The role of ice-sheet topography in the Alpine hydro-climate at glacial times

Abstract. In this study, we investigate the sensitivity of the glacial Alpine hydro-climate to northern hemispheric and local ice-sheet changes. Bridging the scale gap by using a chain of global and regional climate models, we perform sensitivity simulations of up to 2 km horizontal resolution over the Alps for the Last Glacial Maximum (LGM) and the Marine Isotope Stage 4 (MIS4). In winter, we find wetter conditions in the southern part of the Alps during LGM compared to present day, to which dynamical processes, i.e. changes in the wind speed and direction, contribute substantially. During summer, we find the expected drier conditions in most of the Alpine region during LGM, as thermodynamics suggests drier conditions under lower temperatures. The MIS4 climate shows enhanced winter precipitation compared to the LGM, which is explained by its warmer climate compared to the LGM – thus, again explained by thermodynamics. The sensitivity simulations of the northern hemispheric ice-sheet changes show that an increase of the ice-sheet thickness leads to a significant intensification of glacial Alpine hydro-climate conditions, which is mainly explained by dynamical processes. Changing only the Fennoscandian ice sheet is less influential on the Alpine precipitation, whereas modifications in the local Alpine ice-sheet topography significantly alter the Alpine precipitation; in particular, we find a reduction of summer precipitation at the southern face of the Alps when lowering the Alpine ice sheet. The findings demonstrate that the northern hemispheric and local ice-sheet topography play an important role in regulating the Alpine hydro-climate and thus permits a better understanding of the precipitation patterns in the complex Alpine terrain at glacial times.

Rapid prototyping of a lightweight splitboard clip using 3D printing of composite base filaments

The objective of this work is to develop a novel splitboard clip using fiber-reinforced 3D printing. Since the sport is practiced in alpine terrain under sometimes difficult conditions, particularly high demands are placed on the equipment and its development. On the other hand, splitboarding is still a niche sport, with comparatively low numbers of followers, which limits the budget for development costs. Therefore, the improvement of components and the development of new parts can benefit a lot from rapid prototyping. Especially the process of fiber-reinforced 3D printing using carbon fiber filament offers great potential, since the prototypes could be tested directly under real conditions. A 4-point bending test, comparing the strength of the new designed parts and of other clips, which are already available on the market, has shown that the new parts, produced in an additive manufacturing process, are not as strong as some other clips on the market. However, field tests have verified, that these new splitboard clips could withstand the forces of a test ride, harsh alpine conditions and so far meet all requirements.

Unravelling the Deformation of Paleoproterozoic Marbles and Zn-Pb Ore Bodies by Combining 3D-Photogeology and Hyperspectral Data (Black Angel Mine, Central West Greenland)

The Black Angel Zn-Pb ore deposit is hosted in folded Paleoproterozoic marbles of the Mârmorilik Formation. It is exposed in the southern part of the steep and inaccessible alpine terrain of the Rinkian Orogen, in central West Greenland. Drill-core data integrated with 3D-photogeology and hyperspectral imagery of the rock face allow us to identify stratigraphic units and extract structural information that contains the geological setting of this important deposit. The integrated stratigraphy distinguishes chemical/mineralogical contrast within lithologies dominated by minerals that are difficult to distinguish with the naked eye, with a similar color of dolomitic and scapolite-rich marbles and calcitic, graphite-rich marbles. These results strengthen our understanding of the deformation style in the marbles and allow a subdivision between evaporite-carbonate platform facies and carbonate slope facies. Ore formation appears to have been mainly controlled by stratigraphy, with mineralizing fluids accumulating within permeable carbonate platform facies underneath carbonate slope facies and shales as cap rock. Later, folding and shearing were responsible for the remobilization and improvement of ore grades along the axial planes of shear folds. The contact between dolomitic scapolite-rich and calcitic graphite-rich marbles probably represents a direct stratigraphic marker, recognizable in the drill-cores, to be addressed for further 3D-modeling and exploration in this area.

Accuracy of UAV Photogrammetry in Glacial and Periglacial Alpine Terrain: A Comparison With Airborne and Terrestrial Datasets

Unoccupied Aerial Vehicles (UAVs) equipped with optical instruments are increasingly deployed in high mountain environments to investigate and monitor glacial and periglacial processes. The comparison and fusion of UAV data with airborne and terrestrial data offers the opportunity to analyse spatio-temporal changes in the mountains and to upscale findings from local UAV surveys to larger areas. However, due to the lack of gridded high-resolution data in alpine terrain, the specific challenges and uncertainties associated with the comparison and fusion of multi-temporal data from different platforms in this environment are not well known. Here we make use of UAV, airborne, and terrestrial data from four (peri)glacial alpine study sites with different topographic settings. The aim is to assess the accuracy of UAV photogrammetric products in complex terrain, to point out differences to other products, and to discuss best practices regarding the fusion of multi-temporal data. The surface geometry and characteristic geomorphological features of the four alpine sites are well captured by the UAV data, but the positional accuracies vary greatly. They range from 15 cm (root-mean-square error) for the smallest survey area (0.2 km2) with a high ground control point (GCP) density (40 GCPs km−2) to 135 cm for the largest survey area (>2.5 km2) with a lower GCP density (<10 GCPs km−2). Besides a small number and uneven distribution of GCPs, a low contrast, and insufficient lateral image overlap (<50–70%) seem to be the main causes for the distortions and artefacts found in the UAV data. Deficiencies both in the UAV and airborne data are the reason for horizontal deviations observed between the datasets. In steep terrain, horizontal deviations of a few decimetres may result in surface elevation change errors of several metres. An accurate co-registration and evaluation of multi-temporal UAV, airborne, and terrestrial data using tie points in stable terrain is therefore of utmost importance when it comes to the investigation of surface displacements and elevation changes in the mountains. To enhance the accuracy and quality of UAV photogrammetry, the use of UAVs equipped with multi-spectral cameras and high-precision positioning systems is recommended, especially in rugged terrain and snow-covered areas.

Alpine huts: Architectural innovations and development in the High Tatras until the first half of the 20th century

Abstract For man, the mountain environment was a source of raw materials and a place of economic activity until the end of the 18th century. This paper examines how the exploration of mountain valleys lead from the first ascents to the peaks to today’s exploitation of the mountain environment. We are currently following efforts to protect the unique environment of the mountains and to preserve the architectural heritage of the 20th century. In the paper, we look at the architecture of the High Tatras of the first half of the 20th century, which is lost under the coatings of today. The article traces the line of innovation in the 20th century and examines the causes and consequences of the origin and development of architecture in the alpine environment, with a focus on changes in the paradigm of social thinking in the relationship between architecture and the original landscape. The subject of the paper is mapping of the architectural heritage embedded in the unique environment of the world natural heritage of alpine terrains in the High Tatras and the study of the settlement process with innovative technologies and materials that have enabled architecture to enter difficult terrains. As industrialization, mechanization and electrification have greatly simplified and streamlined the construction process, the work identifies not only the development of new design, technological and material solutions, but also the resilience of the environment to innovation. It focuses on the analysis of innovative progress and monitors its development in contact with the mountain architecture from the moment of planning, work implementation and possible construction changes. The work focuses on the typology of mountain huts and the process of their architectural design.

Learning Resource Allocation in Active-Passive Radar Sensor Networks

Recent advances in Passive Coherent Location (PCL) systems make combined active and passive radar sensor networks very attractive for both military and civilian air surveillance. PCL systems seem promising as cost-effective gap fillers of active radar coverage especially in alpine terrain and also as covert early warning sensors. However, PCL systems are sensitive to changes of Transmitters of Opportunity (ToO). Many approaches for energy-efficient target detection have been proposed for active radar sensor networks. However, energy-efficiency and topology optimization of combined active-passive radar sensor networks in realistic scenarios have been poorly studied until today. We here propose an unsupervised learning approach for topology optimization and energy-efficient detection in combined active-passive radar sensor networks. The interdependence of active and passive sensors in the network and the given target scenario is naturally accounted for by our approach. Optimal power budget and detection sectors of active radars and the most useful ToOs for each PCL sensor are simultaneously learned over time. This is a critical contribution for minimizing the need for active radar power budget and PCL computational resources. The power budget of active radars is minimized in a way that the added value of PCL sensors is fully exploited. We also demonstrate how our approach dynamically relearns to achieve robust performance when changes in the ToO of PCL sensors occur. We test our approach in a simulation suite for active-passive radar sensor networks using real-world air surveillance data and ToOs under real-world topographical conditions.

Direct photogrammetry with multispectral imagery for UAV-based snow depth estimation

More accurate snow quality predictions are needed to economically and socially support communities in a changing Arctic environment. This contrasts with the current availability of affordable and efficient snow monitoring methods. In this study, a novel approach is presented to determine spatial snow depth distribution in challenging alpine terrain that was tested during a field campaign performed in the Tarfala valley, Kebnekaise mountains, northern Sweden, in April 2019. The combination of a multispectral camera and an Unmanned Aerial Vehicle (UAV) was used to derive three-dimensional (3D) snow surface models via Structure from Motion (SfM) with direct georeferencing. The main advantage over conventional photogrammetric surveys is the utilization of accurate Real-Time Kinematic (RTK) positioning which enables direct georeferencing of the images, and therefore eliminates the need for ground control points. The proposed method is capable of producing high-resolution 3D snow-covered surface models (<7 cm/pixel) of alpine areas up to eight hectares in a fast, reliable and affordable way. The test sites’ average snow depth was 160 cm with an average standard deviation of 78 cm. The overall Root-Mean-Square Errors (RMSE) of the snow depth range from 11.52 cm for data acquired in ideal surveying conditions to 41.03 cm in aggravated light and wind conditions. Results of this study suggest that the red components in the electromagnetic spectrum, i.e., the red, red edge, and near-infrared (NIR) band, contain the majority of information used in photogrammetric processing. The experiments highlighted a significant influence of the multi-spectral imagery on the quality of the final snow depth estimation as well as a strong potential to reduce processing times and computational resources by limiting the dimensionality of the imagery through the application of a Principal Component Analysis (PCA) before the photogrammetric 3D reconstruction. The proposed method is part of closing the scale gap between discrete point measurements and regional-scale remote sensing and complements large-scale remote sensing data and snow model output with an adequate validation source.

Technical note: Introduction of a superconducting gravimeter as novel hydrological sensor for the Alpine research catchment Zugspitze

Abstract. GFZ (German Research Centre for Geosciences) set up the Zugspitze Geodynamic Observatory Germany with a worldwide unique installation of a superconducting gravimeter at the summit of Mount Zugspitze on top of the Partnach spring catchment. This high alpine catchment is well instrumented, acts as natural lysimeter and has significant importance for water supply to its forelands, with a large mean annual precipitation of 2080 mm and a long seasonal snow cover period of 9 months, while showing a high sensitivity to climate change. However, regarding the majority of alpine regions worldwide, there is only limited knowledge on temporal water storage variations due to sparsely distributed hydrological and meteorological sensors and the large variability and complexity of signals in alpine terrain. This underlines the importance of well-equipped areas such as Mount Zugspitze serving as natural test laboratories for improved monitoring, understanding and prediction of alpine hydrological processes. The observatory superconducting gravimeter, OSG 052, supplements the existing sensor network as a novel hydrological sensor system for the direct observation of the integral gravity effect of total water storage variations in the alpine research catchment at Zugspitze. Besides the experimental set-up and the available data sets, the gravimetric methods and gravity residuals are presented based on the first 27 months of observations from 29 December 2018 to 31 March 2021. The snowpack is identified as being a primary contributor to seasonal water storage variations and, thus, to the gravity residuals with a signal range of up to 750 nm s−2 corresponding to 1957 mm snow water equivalent measured with a snow scale at an altitude of 2420 m at the end of May 2019. Hydro-gravimetric sensitivity analysis reveal a snow–gravimetric footprint of up to 4 km distance around the gravimeter, with a dominant gravity contribution from the snowpack in the Partnach spring catchment. This shows that the hydro-gravimetric approach delivers representative integral insights into the water balance of this high alpine site.

Seasonal Freeze‐Thaw Cycles and Permafrost Degradation on Mt. Zugspitze (German/Austrian Alps) Revealed by Single‐Station Seismic Monitoring

AbstractThawing of mountain permafrost in response to rising temperatures degrades the stability of rock walls and thereby affects infrastructure integrity in Alpine terrain. In this study, we use 15 yr of passive seismic data from a single station deployed near a known permafrost body on Mt. Zugspitze (Germany), to monitor freeze‐thaw processes. The recordings reveal a persistent cultural seismic noise source, which we utilize to compute single‐station cross‐correlations and extract relative seismic velocity changes. We find that parts of the cross‐correlations show seasonal velocity variations (≈3% peak‐to‐peak amplitude) and a long‐term velocity decrease (≈0.1%/yr). Comparison with meteorological data and a previous electrical resistivity tomography study suggests that these velocity changes are caused by freeze‐thaw cycles and by permafrost degradation, respectively. The results demonstrate the potential of passive seismology for permafrost monitoring and suggest that denser instrumentation will provide detailed spatio‐temporal insights on permafrost dynamics in future studies.

A USLE-based model with modified LS-factor combined with sediment delivery module for Alpine basins

Sedimentation in reservoirs constitutes a major issue worldwide, especially when hydropower, and hence profit, is involved. In this study, the sedimentation rates, due to soil erosion and sediment yields, are analyzed in the reservoir of the Rio di Pusteria hydropower dam, in South Tyrol (Italian Alps). The focus is on a five-year period, between two consecutive sediment flushing operations occurred in June 2014 and May 2019. Based on the difference between the pre- and post-flushing bathymetries, the five-year aggregated sediment yield was determined. The soil erosion from the basin surface and the sediment budget in the reservoir are calculated by means of a gridded Universal Soil Loss Equation (USLE), combined with a Sediment Delivery Ratio (SDR) module. The topographic factor is improved by the use of a fine-scale DEM and the slope length factor is adjusted to the Alpine terrain by means of a fitting threshold. The rainfall erosivity factor is determined in two different ways, one representing the precipitation regime of the study area and one the specific rainfall conditions of the study period. The two different applications result to calculated reservoir sedimentation rates of 439,279.2 tons and 589,520.5 tons with deviations from the measured value of 3.1% and −23.2%, respectively, while the sediment delivery ratio to the reservoir was found to be 12.5%. The calculations are also compared with results of the application of the conventional six-factor USLE. The comparison between calculations and measurements shows that the methods used can be efficiently applied in an Alpine basin for the estimation of reservoir sedimentation rates.

The Iceman : Life scenarios and pathological findings from 30years of research on the glacier mummy "Ötzi"

The comprehensive investigation of the excellently preserved mummy of Ötzi, the Iceman, and his equipment over the last 30years has provided a wealth of information about the life and disease of this late Neolithic individual. This research has indicated that his origin was from alocal southern Alpine population, that he grew up in the valleys of the Southern Alps, and that he had considerable local mobility. He had well-balanced nutrition with amixed vegetable and animal diet. He was very mobile in the alpine terrain and of athletic constitution. The Iceman suffered from mild to moderate degenerative joint disease primarily of the right hip joint, slight spondylosis of the cervical and lumbar spine, aminor focal (premature) arteriosclerosis, lung anthracosis and possibly silicosis, previous pleuritic inflammation (possibly of post-specific origin), intestinal infections of the stomach by Helicobacter pylori and Trichuris trichiura worm infestation in the intestines, amild osteomalacia of cancellous bone, and diverse pathologies of his teeth with dental caries and periodontitis, as well as hair anomalies. The presence of borreliosis is still under debate. As potential remedies, the Iceman carried some anthelmintic substances with him: abirch polypore and an anthelmintic fern. The numerous tattoos may also have had therapeutic effects. Finally, the last days of Ötzi could be reconstructed quite precisely: his gastrointestinal content indicates that the Iceman moved from Alpine heights to a lower location and then again up to the glacier region where he died. During this journey he encountered two attacks: the first, several days before his death, lead to astabbing wound in his right hand; the second was an arrow hit that wounded the Iceman lethally at his left axilla by laceration of the subclavian artery.

Intercomparison of UAV platforms for mapping snow depth distribution in complex alpine terrain

Unmanned Aerial Vehicles (UAVs) offer great flexibility in acquiring images in inaccessible study areas, which are then processed with stereo-matching techniques through Structure-from-Motion (SfM) algorithms. This procedure allows generating high spatial resolution 3D point clouds. The high accuracy of these 3D models allows the production of detailed snow depth distribution maps through the comparison of point clouds from different dates. In this way, UAVs allow monitoring of remote areas that were not achievable previously. The large number of works evaluating this novel technique has not, to date, conducted a systematic evaluation of concurrent snowpack observations with different UAV devices. Taking into account this, and also bearing in mind that potential users of this technique may be interested in exploiting ready-to-use commercial devices, we conducted an evaluation of the snow depth distribution maps with different commercial UAVs. During the 2018–19 snow season, two multi-rotors (Parrot Anafi and DJI Mavic Pro2) and one fixed-wing device (SenseFly eBee plus) were used on three different dates over a small test area (5 ha) within Izas Experimental Catchment in the Central Pyrenees. Simultaneously, snowpack distribution was retrieved with a Terrestrial Laser Scanner (TLS, RIEGL LPM-321) and was considered as ground truth. Three different georeferencing methods (Ground Control Points, ICP algorithm over snow-free areas and RTK-GPS positioning) were tested, showing equivalent performances under optimum illumination conditions. Additionally, for the three acquisition dates, both multi-rotors were flown at two distinct altitudes (50 and 75 m) to evaluate impact on the obtained snow depth maps. The evaluation with the TLS showed an equivalent performance of the two multi-rotors, with mean RMSE below 0.23 m and maximum volume deviations of less than 5%. Flying altitudes did not show significant differences in the obtained maps. These results were obtained under contrasted snow surface characteristics. This study reveals that under good illumination conditions and in relatively small areas, affordable commercial UAVs provide reliable estimations of snow distribution compared to more sophisticated and expensive close-range remote sensing techniques. Results obtained under overcast skies were poor, demonstrating that UAV observations require clear-sky conditions and acquisitions around noon to guarantee a homogenous illumination of the study area.

Light and Shadow in Mapping Alpine Snowpack With Unmanned Aerial Vehicles in the Absence of Ground Control Points

AbstractRecent developments in unmanned aerial vehicles (UAV) and structure from motion (SfM) algorithms have shown reliable results for retrieving snow depth distribution. However, their ability to obtain accurate results usually relies on deploying and measuring the exact position of ground control points (GCP) for georeferencing the information. Commercial UAVs can now provide real time kinematic (RTK) positioning of the images with centimetric accuracy. Nonetheless, their operational applicability for observing snow distribution in highly heterogeneous mountain areas has not been evaluated. This study presents a complete assessment of the reliability of snow depth observations from a fixed‐wing UAV working in RTK mode with an RGB camera. During the 2018–2019 season, seven field campaigns (13 UAV flights) were undertaken covering 0.48 km2 in complex alpine terrain in the Pyrenees. The UAV observations obtained under different light conditions and flight block configurations (altitude and image overlaps) in the same day were evaluated with terrestrial laser scanner acquisitions. Two SfM processing options of the UAV images were also compared. When the study area received direct solar light, the results were comparable to previous studies that had used GCPs, with an average root mean squared error of 0.19 m and an average absolute snow volume discrepancy lower than 4%. However, when large areas were under shadow from the terrain, or solar light was affected by clouds, the estimated error tripled. The quality of the snow depth maps was little affected by the snow covered area and the flight mission configurations.

Comment on Strauss et al., 2020: Subsidence analysis of salt tectonics‐driven minibasins (Northern Calcareous Alps, Austria)

Comment on Strauss et al., 2020: Subsidence analysis of salt tectonics‐driven minibasins (Northern Calcareous Alps, Austria)

Horizon Line Detection in Historical Terrestrial Images in Mountainous Terrain Based on the Region Covariance

Horizon line detection is an important prerequisite for numerous tasks including the automatic estimation of the unknown camera parameters for images taken in mountainous terrain. In contrast to modern images, historical photographs contain no color information and have reduced image quality. In particular, missing color information in combination with high alpine terrain, partly covered with snow or glaciers, poses a challenge for automatic horizon detection. Therefore, a robust and accurate approach for horizon line detection in historical monochrome images in mountainous terrain was developed. For the detection of potential horizon pixels, an edge detector is learned based on the region covariance as texture descriptor. In combination with shortest path search the horizon in monochrome images is accurately detected. We evaluated our approach on 250 selected historical monochrome images in average dating back to 1950. In 85% of the images the horizon was detected with an error less than 10 pixels. In order to further evaluate the performance, an additional dataset consisting of modern color images was used. Our method, using only grayscale information, achieves comparable results with methods based on color information. In comparison with other methods using only grayscale information, accuracy of the detected horizons is significantly improved. Furthermore, the influence of color, choice of neighborhood for the shortest path calculation, and patch size for the calculation of the region covariance were investigated. The results show that both the availability of color information and increasing the patch size for the calculation of the region covariance improve the accuracy of the detected horizons.

Efficient multi-objective calibration and uncertainty analysis of distributed snow simulations in rugged alpine terrain

In mountainous terrain, reliable snow simulations are crucial for many applications. However, except in highly instrumented research catchments, meteorological data are usually limited, and so the interpolated spatial fields used to force snow models are uncertain. Moreover, certain potentially important processes cannot presently be simulated at catchment scales using entirely physical algorithms. It is therefore often appropriate to introduce empirical parameters into otherwise physically-based snow models. Many opportunities to incorporate snow observations into the parameter estimation process now exist, but they remain to be fully exploited. In this context, a novel approach to the calibration of an energy balance-based snow model that additionally accounts for gravitational redistribution is presented. Several important parameters were estimated using an efficient, gradient-based method with respect to two complementary observation types – Landsat 8-derived snow extent maps, and reconstructed snow water equivalent (SWE) time-series. When assessed on a per-pixel basis, observed patterns were ultimately reproduced with a mean accuracy of 85%. Spatial performance metrics compared favourably with those previously reported, whilst the temporal evolution of SWE at the stations was also satisfactorily captured. Subsequent uncertainty and data worth analyses revealed that: i) the propensity for model predictions to be erroneous was substantially reduced by calibration, ii) pre-calibration uncertainty was largely associated with two parameters which modify the longwave component of the energy balance, but this uncertainty was greatly diminished by calibration, and iii) a lower elevation SWE series was particularly valuable, despite containing comparatively few observations. Overall, our work demonstrates that contemporary snow models, observation technologies, and inverse approaches can be combined to both constrain and quantify the uncertainty associated with simulations of alpine snow dynamics.