ALBERT

All Library Books, journals and Electronic Records Telegrafenberg

feed icon rss

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    Publication Date: 2019-07-17
    Description: Report of the Liquid Water in Snow Workshop, Davos, Switzerland, 2–4 April 2014
    Repository Name: EPIC Alfred Wegener Institut
    Type: Miscellaneous , NonPeerReviewed
    Format: application/pdf
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 2
    Publication Date: 2017-01-18
    Description: The temporal evolution of Alpine snowpacks is important for assessing water supply, hydropower generation, flood predictions and avalanche forecasts. Especially in high mountain regions with an extremely varying topography, it is until now often difficult to derive continuous and non-destructive information on snow parameters. Since autumn 2012, we are running a new low-cost GPS (Global Positioning System) snow measurement experiment at the high alpine study site Weissfluhjoch (2450 m a.s.l.) in Switzerland. The globally and freely broadcasted GPS L1-band (1.57542 GHz) was continuously recorded with GPS antennas, which are installed at the ground surface underneath the snowpack. GPS raw data, containing carrier-to-noise power density ratio (C/N0) as well as elevation and azimuth angle information for each time step of 1 s, was stored and analyzed for all 32 GPS satellites. Since the dielectric permittivity of an overlying wet snowpack influences microwave radiation, the bulk volumetric liquid water content as well as daily melt-freeze cycles can be derived non-destructively from GPS signal strength losses and external snow height information. This liquid water content information is qualitatively in good accordance with meteorological and snow-hydrological data and quantitatively highly agrees with continuous data derived from an upward-looking ground-penetrating radar (upGPR) working in a similar frequency range. As a promising novelty, we combined the GPS signal strength data with upGPR travel-time information of active impulse radar rays to the snow surface and back from underneath the snow cover. This combination allows determining liquid water content, snow height and snow water equivalent from beneath the snow cover without using any other external information. The snow parameters derived by combining upGPR and GPS data are in good agreement with conventional sensors as e.g. laser distance gauges or snow pillows. As the GPS sensors are cheap, they can easily be installed in parallel with further upGPR systems or as sensor networks to monitor the snowpack evolution in avalanche paths or at a larger scale in an entire hydrological basin to derive distributed melt-water runoff information.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Conference , NonPeerReviewed
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 3
    Publication Date: 2015-12-14
    Description: The widely used detailed SNOWPACK model has undergone constant development over the years. A notable recent extension is the introduction of a Richards equation (RE) solver as an alternative for the bucket-type approach for describing water transport in the snow and soil layers. In addition, continuous updates of snow settling and new snow density parameterizations have changed model behavior. This study presents a detailed evaluation of model performance against a comprehensive multiyear data set from Weissfluhjoch near Davos, Switzerland. The data set is collected by automatic meteorological and snowpack measurements and manual snow profiles. During the main winter season, snow height (RMSE: 〈 4.2 cm), snow water equivalent (SWE, RMSE: 〈 40 mm w.e.), snow temperature distributions (typical deviation with measurements: 〈 1.0 °C) and snow density (typical deviation with observations: 〈 50 kg m−3) as well as their temporal evolution are well simulated in the model and the influence of the two water transport schemes is small. The RE approach reproduces internal differences over capillary barriers but fails to predict enough grain growth since the growth routines have been calibrated using the bucket scheme in the original SNOWPACK model. However, the agreement in both density and grain size is sufficient to parameterize the hydraulic properties successfully. In the melt season, a pronounced underestimation of typically 200 mm w.e. in SWE is found. The discrepancies between the simulations and the field data are generally larger than the differences between the two water transport schemes. Nevertheless, the detailed comparison of the internal snowpack structure shows that the timing of internal temperature and water dynamics is adequately and better represented with the new RE approach when compared to the conventional bucket scheme. On the contrary, the progress of the meltwater front in the snowpack as detected by radar and the temporal evolution of the vertical distribution of melt forms in manually observed snow profiles do not support this conclusion. This discrepancy suggests that the implementation of RE partly mimics preferential flow effects.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , NonPeerReviewed
    Format: application/pdf
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 4
    Publication Date: 2017-01-16
    Description: Wet-snow avalanches can be difficult to forecast. However, recent studies have shown that an index (LWCindex) related to the mean liquid water content of the entire snowpack can be used to predict the onset of periods with high wet-snow avalanche activity. Nevertheless, this index has not yet been verified. We therefore compared modelled and measured liquid water content to wet-snow avalanche activity for four winter seasons at the Dorfberg test site, above Davos, Switzerland. Using the 1-D snow cover model SNOWPACK, we simulated snow stratigraphy, the mean liquid water content and water infiltration within the snowpack. Simultaneously, we used an upward-looking ground penetrating radar (upGPR) to monitor mean liquid water content and changes in percolation depth. Measurement and simulations agreed well and showed that increased wet-snow avalanche activity started when the mean liquid water content of the snowpack reached 0.6-1% by volume. Concurrently, at the onset, a significant diurnal increase in liquid water content was also observed. In three out of four melt seasons, the first arrival of water at the bottom of the snowpack coincided with the onset of high wet-snow avalanche activity. Overall, these results show that the index could improve prediction of wet-snow avalanche activity. The model approach might be particularly helpful for narrowing down the period of temporary avalanche mitigation measures (e.g., preventive closures, artificial release by explosives), since conditions favoring wet-snow avalanches usually persist only for a short period of time. Combined with a numerical weather prediction model, this approach may allow for effective wet-snow avalanche forecasting.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , NonPeerReviewed
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 5
    Publication Date: 2017-01-16
    Description: Snow stratigraphy and water percolation are key parameters in avalanche forecasting. It is, however, difficult to model or measure stratigraphy and water flow in a sloping snowpack. Numerical modeling results depend highly on the type and availability of input data and the parameterization of the physical processes. Furthermore, the sensors themselves may influence the snowpack or be destroyed due to snow gliding and avalanches. Radar technology allows non-destructive scanning of the snowpack and deducing internal snow properties. If the radar system is buried in the ground, it cannot be destroyed by avalanche impacts or snow creep. During the winter seasons 2010-2011 and 2011-2012 we recorded continuous data with upward-looking pulsed radar systems (upGPR) at two test sites. We demonstrate that it is possible to determine the snow height with an accuracy comparable to conventional snow depth measuring devices. We determined the bulk volumetric liquid water content and tracked the position of the first stable wetting front. Wet-snow avalanche activity increased, when melt water penetrated deeper into the snowpack.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Conference , NonPeerReviewed
    Format: application/pdf
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 6
    Publication Date: 2014-05-06
    Description: Forecasting snow avalanche danger in mountainous regions is of major importance for the protection of infrastructure in avalanche run-out zones. Inexpensive measurement devices capable of measuring snow height and layer properties in avalanche starting zones may help to improve the quality of risk assessment. We present a low-cost L-band frequency modulated continuous wave radar system (FMCW) in upward-looking configuration. To monitor the snowpack evolution, the radar system was deployed in fall and subsequently was covered by snowfalls. During two winter seasons we recorded reflections from the overlying snowpack. The influence of reflection magnitude and phase to the measured frequency spectra, as well as the influence of signal processing were investigated. We present a method to extract the phase of the reflection coefficients from the phase response of the frequency spectra and their integration into the presentation of the measurement data. The phase information significantly improved the detectability of the temporal evolution of the snow surface reflection. We developed an automated and a semi-automated snow surface tracking algorithm. Results were compared with independently measured snow height from a laser snow-depth sensor and results derived from an upward-looking impulse radar system (upGPR). The semi-automated tracking used the phase information and had an accuracy of about 6 to 8 cm for dry-snow conditions, similar to the accuracy of the upGPR, compared to measurements from the laser snow-depth sensor. The percolation of water was observable in the radargrams. Results suggest that the upward-looking FMCW system may be a valuable alternative to conventional snow-depth sensors for locations, where fixed installations above ground are not feasible.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , NonPeerReviewed
    Format: application/pdf
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 7
    Publication Date: 2014-05-20
    Description: Snow stratigraphy is a key contributing factor for assessing avalanche danger, but so far only destructive methods can provide this kind of information. Furthermore, continuous monitoring of the temporal evolution of the snowpack is not possible with destructive methods. Radar technology provides information on the snowpack nondestructively and allows deriving internal snow properties from its signal response. In our previous work, we demonstrated that it is feasible to quantitatively derive snowpack properties relevant for avalanche formation and monitor their evolution in time using an upward-looking ground penetrating radar system (upGPR) that was buried in a wooden box underneath the snow. Reliable results could only be obtained for the time when the snow cover was dry. In addition, to determine some properties, we still needed additional information such as independently measured snow height or modeled snow density. Hence, the system was not yet able to provide information from avalanche starting zones, since this type of information is generally not available in avalanche-prone terrain. To fully exploit the information content of upGPR data, and thus to at least partially compensate for the lack of information, we applied full-waveform inversion (FWI) techniques. We refined the model of the snowpack by repeated forward modeling the waveforms and updating the model parameters to match it with recorded data. The forward model took into account both the effect of the snow density on the velocity of the electromagnetic wave, as well as the influence of snow wetness on the attenuation. This allowed the density and the liquid water content for each layer in the snowpack to be determined. As we conducted a measurement every 3 hours (every 30 minutes as soon as the snowpack became wet), we could also simulate the temporal evolution of the density and the liquid water profiles. The method worked without assumptions or external measurements, even when the snow cover was wet.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Conference , NonPeerReviewed
    Format: application/pdf
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 8
    Publication Date: 2019-07-17
    Description: Snow stratigraphy and water percolation are key contributing factors to avalanche formation. So far, only destructive methods can provide this kind of information. Radar technology allows continuous, non-destructive scanning of the snowpack so that the temporal evolution of internal properties can be followed. We installed an upward-looking ground-penetrating radar system (upGPR) at the Weissfluhjoch study site (Davos, Switzerland). During two winter seasons (2010/11 and 2011/12) we recorded data with the aim of quantitatively determining snowpack properties and their temporal evolution. We automatically derived the snow height with an accuracy of about 5 cm, tracked the settlement of internal layers (+-7 cm) and measured the amount of new snow (+-10 cm). Using external snow height measurements, we determined the bulk density with a mean error of 4.3% compared to manual measurements. Radar-derived snow water equivalent deviated from manual measurements by 5%. Furthermore, we tracked the location of the dry-to-wet transition in the snowpack until water percolated to the ground. Based on the transition and an independent snow height measurement it was possible to estimate the volumetric liquid water content and its temporal evolution. Even though we need additional information to derive some of the snow properties, our results show that it is possible to quantitatively derive snow properties with upGPR.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , NonPeerReviewed
    Format: application/pdf
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 9
    Publication Date: 2019-07-17
    Repository Name: EPIC Alfred Wegener Institut
    Type: Conference , NonPeerReviewed
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 10
    Publication Date: 2019-07-17
    Description: Previous snowpack monitoring systems deployed for the entire winter season are either limited to the information of the snow height or weight at a specific point or are inadequate in monitoring the temporal evolution of the snowpack as the method is destructive. Due to an expected spatial variability in the snowpack stratigraphy, only non-destructive sensor systems are suited to observe the temporal evolution of the snowpack, e.g. strain rates of specific layers after recent snow loading or the observation of the penetration of wetting fronts until liquid water percolated all the way down to the ground. For this study, two different upward-looking radar systems buried into the ground provid an extensive data set of the temporal changes in snowpack stratigraphy and characteristics. The radars recorded data for almost five months every three hours in dry-snow conditions and down to every 30 minutes, while moisture occurred in the snowpack. In comparison to a previously employed and tested upward-looking impulse radar system (upGPR), a distinctive less cost-intensive self-made frequency modulated continuous wave system (upFMCW) in a similar frequency range was tested on its applicability. The scope of this paper is to compare the radar signals gathered with two different frequencies (600, 1600 MHz) by the upGPR with signals recorded by the upFMCW in the frequency range of 1-2 GHz. In combination with conventional snowpack measurements, both radar data demonstrate applicability to validating and improving snowpack models The method seems to provide an unique possibility to determine the differential volumetric liquid-water content (\theta_{W}) in the snowpack and monitor sub-daily to monthly changes thereof. The occurrence of strong multiple reflections as well as the diurnal increase in two-way travel time of reflection horizons effected by moisture allow to determine the absolute amount of \theta_{W}, the depth of moisture percolation, the timing of the diurnal peak and the monitoring of the decrease in \theta_{W} due to nocturnal refreezing.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Conference , NonPeerReviewed
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...