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

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.

Introduction of a Superconducting Gravimeter as Novel Hydrological Sensor for the Alpine Research Catchment Zugspitze

The Zugspitze Geodynamic Observatory Germany has been set up with a worldwide unique installation of a superconducting gravimeter at the summit of Mount Zugspitze. With regard to hydrology, this karstic high-alpine site is largely dominated by high precipitation amounts and a long seasonal snow cover period with significant importance for water supply to its forelands, while it shows a high sensitivity to climate change. However, regarding the majority of alpine regions worldwide there is only weak knowledge on temporal water storage variations due to only sparsely distributed hydrological and meteorological point sensors and the large variability and complexity of alpine signals. This underlines the importance of well-equipped areas such as Mount Zugspitze serving as natural test laboratories for an 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 Zugspitze. Besides the experimental setup and the available datasets, the required gravimetric prerequisites are presented such as calibration, tidal analysis and signal separation of the superconducting gravimeter observations from the first 2 years. The snowpack is identified as primary contributor to seasonal water storage variations and thus to the gravity residuals with a signal range of up to 750 nm/s2 corresponding to 1957 mm snow water equivalent measured at a representative station at the end of May 2019. First hydro-gravimetric sensitivity analysis are based on simplified assumptions of the snowpack distribution within the area around Mount Zugspitze. These 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 study already shows that the hydro-gravimetric approach can deliver important and representative integral insights into this high-alpine site. This work is regarded as a concept study showing preliminary gravimetric results and sensitivity analysis for upcoming long-term hydro-gravimetric research projects.

On the Ability of LIDAR Snow Depth Measurements to Determine or Evaluate the HRU Discretization in a Land Surface Model

To find the adequate spatial model discretization scheme, which balances the models capabilities and the demand for representing key features in reality, is a challenging task. It becomes even more challenging in high alpine catchments, where the variability of topography and meteorology over short distances strongly influences the distribution of snow cover, the dominant component in the alpine water cycle. For the high alpine Research Catchment Zugspitze (RCZ) a new method for objective delineation of hydrological response units (HRUs) using a time series of high resolution LIDAR derived snow depth maps and the physiographic properties of the RCZ is introduced. Via principle component analysis (PCA) of these maps, a dominant snow depth pattern, that turned out to be largely defined during the (winter) accumulation period was identified. This dominant pattern serves as a reference for HRU delineations on the basis of cluster analyses of the catchment’s physiographic properties. The method guarantees for an appropriate, objective, spatial discretization scheme, which allows for a reliable and meaningful reproduction of snow cover variability with the Cold Regions Hydrological Model — at the same time avoiding significant increase of computational demands. Different HRU schemes were evaluated with measured snow depth and the comparison of their model results identified significant differences in model output and best performance of the scheme which best represents measured snow depth distribution.

Links between the moisture origin and isotopic signature in water vapour, snowfall and snow pack at Finse Alpine Research Center (1222m) in Southern Noway

<p>Seasonal snow cover is a crucial resource for hydropower in Norway. Understanding water sources and processes related to inter-annual snow cover variability is therefore of fundamental societal relevance. The stable water isotope composition of precipitation provides a natural, integrated tracer of the condensation history during atmospheric water transport. The main parameters dD and d18O along with the secondary quantity d-excess give information about the origin and transport history of moisture from its source to its sink. When snow falls and deposits on the ground as a sediment, it creates a record in the form of the seasonal snow pack.</p><p>Here we utilize data acquired during a field campaign in the winter season of 2018-2019 at the Finse Alpine Research Station Center (1222m, 60.6N, 7.5E) in Norway, in order to investigate the transfer of the isotopic signal of source and transport conditions from vapour to snowfall, and to the snow pack.</p><p>Over a main period of two months, snowfall was sampled daily, while the water vapour was continuously measured from ambient air guided through a heated inlet to a Picarro L2130i infrared spectrometer, with daily calibration runs. During five periods with intense snowfall, we carried out higher frequency sampling down to 15 minute intervals. Covering the entire winter season, five snowpits were sampled for isotopic analysis as well as detailed stratigraphy. In total more than 400 snow samples where taken and analysed for their isotopic composition, accompanied by routine meteorological observations over the winter season at the site. In addition, we compare the variations in the observed isotope signal at Finse with one derived from moisture source analysis using the Lagrangian diagnostic WaterSip, based on the FLEXPART model and ERA Interim reanalysis data.</p><p>To investigate to what degree moisture source information is archived in the snow pack, and how it evolves during the season, we compare snow observations at different time resolution (daily and high frequency snowfall samples) with the record of the snow pack, aided by the snow model CROCUS. The meteorological observations supply context for understanding the snow formation conditions. In particular, deviations from isotopic equilibrium between vapour and precipitation at ambient temperature conditions provide insight into the dominant condensation regime during different intense observation periods.</p>

A 3D geological model of a structurally complex Alpine region as a basis for interdisciplinary research

Certain applications, such as understanding the influence of bedrock geology on hydrology in complex mountainous settings, demand 3D geological models that are detailed, high-resolution, accurate, and spatially-extensive. However, developing models with these characteristics remains challenging. Here, we present a dataset corresponding to a renowned tectonic entity in the Swiss Alps - the Nappe de Morcles - that does achieve these criteria. Locations of lithological interfaces and formation orientations were first extracted from existing sources. Then, using state-of-the-art algorithms, the interfaces were interpolated. Finally, an iterative process of evaluation and re-interpolation was undertaken. The geology was satisfactorily reproduced; modelled interfaces correspond well with the input data, and the estimated volumes seem plausible. Overall, 18 formations, including their associated secondary folds and selected faults, are represented at 10 m resolution. Numerous environmental investigations in the study area could benefit from the dataset; indeed, it is already informing integrated hydrological (snow/surface-water/groundwater) simulations. Our work demonstrates the potential that now exists to develop complex, high-quality geological models in support of contemporary Alpine research, augmenting traditional geological information in the process.