en:
This dataset contains all data on which the following publication below is based.
Paper Citation:
 - Risch AC, Ochoa-Hueso R, van der Putten WH, Bump JK, Busse MD, Frey B, Gwiazdowicz DJ, Page-Dumroese DS, Vandegehuchte ML, Zimmermann S, Schütz M. Size-dependent loss of aboveground animals differentially affects grassland ecosystem coupling and functions. 2018. Nature Communications 9: 3684.  [doi: 10.1038/s41467-018-06105-4](https://doi.org/10.1038/s41467-018-06105-4).
Please cite this paper together with the citation for the datafile.
Methods
Study sites
The experimental exclosure setups were installed within the SNP (IUCN category Ia preserve; Dudley 2008), in south-eastern Switzerland. The park covers 172 km2 of forests and subalpine and alpine grasslands along with scattered rock outcrops and scree slopes. The entire area has been protected from human impact (no hunting, fishing, camping or off-trail hiking) since 1914. Large, fairly homogenous patches of short- and tall-grass vegetation, which originate from different historical management and grazing regimes, cover the park’s subalpine grasslands entirely. Short-grass vegetation developed in areas where cattle used to rest (nutrient input) prior to the park’s foundation (14th century to 1914) (Schütz and others 2003, 2006) and is dominated by lawn grass species such as Festuca rubra L., Briza media L. and Agrostis capillaris L. (Schütz and others 2003, 2006). Today, this vegetation type is intensively grazed by diverse vertebrate and invertebrate communities that inhabit the park and consume up to 60% of the available biomass (Risch and others 2013). Tall-grass vegetation developed where cattle formerly grazed, but did not rest, and is dominated by rather nutrient-poor tussocks of Carex sempervirens Vill. and Nardus stricta L. (Schütz and others 2003, 2006). This vegetation type receives considerably less grazing, with only roughly 20% of the biomass consumed (Risch and others 2013). Consequently, the two vegetation types together represent a long-term trajectory of changes in grazing regimes. Underlying bedrock of all grasslands is dolomite, which renders these grasslands rather poor in nutrients regardless of former and current land-use regimes.
Experimental design
To progressively exclude aboveground vertebrate and invertebrate animals, we established 18 size-selective exclosure setups (nine in short-grass, nine in tall-grass vegetation) distributed over six subalpine grasslands across the SNP (Risch and others 2013, 2015). Elevation differences of exclosure locations did not exceed 350 m (between 1975 and 2300 m a.s.l.). The exclosures were established immediately after snowmelt in spring 2009 and were left in place for five consecutive growing seasons (until end of 2013). They were, however, temporarily dismantled every fall (late October after first snowfall) to protect them from avalanches. They were re-established in the same location every spring immediately after snowmelt. Each size-selective exclosure setup consisted of five plots (2 x 3 m) that progressively excluded aboveground vertebrates and invertebrates from large to small. The plots are labelled according to the guilds that had access to them “L/M/S/I”, “M/S/I”, “S/I”, “I”, “None”; L = large mammals, M = medium mammals, S = small mammals, I = invertebrates, None = no animals had access. As we only had permission to have the experimental setup in place for five consecutive growing seasons, the experiment had to be completely dismantled in the late fall of 2013 and all material removed from the SNP.
Our exclosure design was aimed at excluding mammalian herbivores, but naturally also excluded the few medium and small mammalian predators, as well as the entire aboveground invertebrate food web. A total of 26 large to small mammal species can be found in the SNP, but large apex predators are missing (wolf, bear, lynx) . Reptiles, amphibians and birds are scarce to absent in the subalpine grasslands under study. Only two reptile species occur in the park and they are confined to rocky areas that warm up enough for them to survive. One frog species spawns in an isolated pond far from our grasslands. Only three bird species occasionally feed on the subalpine grasslands. Using game cameras (Moultrie 6MP Game Spy I-60 Infrared Digital Game Camera, Moultrie Feeders, Alabaster, AL, USA), we did observe that the medium- and small-sized mammals (marmot/hares and mice) were not afraid to enter the fences and feed on their designated plots. We never spotted reptiles, amphibians or birds on camera. We distinguished between 59 higher aboveground-dwelling invertebrate taxa that our size-selective exclosures excluded (see also methods for aboveground-dwelling invertebrates below).
The “L/M/S/I” plot (not fenced) was located at least 5 m from the 2.1 m tall and 7 x 9 m large main electrical fence that enclosed the other four plots. The bottom wire of this fence was mounted at 0.5 m height and was not electrified to enable safe access for medium and small mammals, while fencing out the large ones. Within each main fence, we randomly established four 2 x 3 m plots separated by 1-m wide walkways from one another and from the main fence line: 1) the “M/S/I” plots were unfenced, allowing access to all but the large mammals; 2) the “S/I” plots (10 x 10 cm electrical mesh fence) excluded all medium-sized mammals. Note that the bottom 10 cm of this fence remained non-electrified to enable safe access for small mammals; 3) the “I” plots (2 x 2 cm metal mesh fence) excluded all mammals. We double-folded the mesh at the bottom 50 cm to reduce the mesh size to smaller than 1 x 1 cm openings; and 4) the “None” plots were surrounded by a 1 m tall mosquito net (1.5 x 2 mm) to exclude all animals. The top of the plot was covered with a mosquito-meshed wooden frame mounted to the corner posts (roof). We treated these plots a few times with biocompatible insecticide (Clean kill original, Eco Belle GmbH, Waldshut-Tiengen, Germany) to remove insects that might have entered during data collection or that hatched from the soil, but amounts were negligible and did not impact soil moisture conditions within these plots.
To assess whether the design of the “None” exclosure (mesh and roof) affected the response variables within the plots and, therefore, influenced the results, we established an additional six “micro-climate control” exclosures (one in each of the six grasslands) (Risch and others 2013, 2015). These exclosures were built as the “None” exclosures but were open at the bottom (20 cm) of the 3-m side of the fence facing away from the prevailing wind direction to allow invertebrates to enter. A 20-cm high and 3-m long strip of metal mesh was used to block access to small mammals. Thus, this construction allowed a comparable micro-climate to the “None” plots, but also a comparable feeding pressure by invertebrates to the “I” plots. We compared various properties within these exclosures against one another to assess if our construction altered the conditions in the “None” plots. We showed that differences in plant (e.g., vegetation height, aboveground biomass) and soil properties (e.g., soil temperature, moisture) found between the “I” and the “None” treatments were not due to the construction of the “None” exclosure, but a function of animal exclusions, although the amount of UV light reaching the plant canopy was significantly reduced (Risch and others 2013).
Aboveground invertebrate sampling
Aboveground invertebrates were sampled with two different methods to capture both ground- and plant-dwelling organisms: 1) we randomly placed two pitfall traps (67 mm in diameter, covered with a roof) filled with 20% propylene glycol in one 1 x 1 m subplot of the 2 x 3 m treatment plots in spring 2013 (May) and emptied them every two weeks until late September 2013 (Vandegehuchte and others 2017b, 2018). A pitfall trap consisted of a plastic cylinder (13 cm depth, 6.75 cm diameter). Within each cylinder we placed a 100 ml plastic vial with outer diameter 6.70 cm and on top of the cylinder we placed a plastic funnel to guide the invertebrates into the vials. Each trap was cover with a cone-shaped and transparent plastic roof to protect the trap from rain (Vandegehuchte and others 2017b, 2018). Note that in the “None” plots only one trap was placed as control to check for effectiveness of the exclosure. 2) We vacuumed all invertebrates from a 60 x 60 cm area on another 1 x 1 m subplot with a suction sampler (Vortis, Burkhard manufacturing CO, Ltd., Rickmansworth, Hertfordshire, UK) every month from June to September 2013 (Vandegehuchte and others 2017b, 2018). For this purpose, we quickly placed a square plastic frame (60 x 60 x 40 cm) with a closable mosquito mesh sleeve attached to the top edge into the plot from the outside. The suction sample was then inserted into through the sleeve and operated for 45 s to collect the invertebrates (Vandegehuchte and others 2017b, 2018).
We sorted the ≈100 000 individuals collected with both methods by hand and identified each individual morphologically to the lowest taxonomic level feasible (59 taxa, including orders, suborders, subfamilies, families; phylum for Mollusca). These taxa belonged to the following feeding types: 19 herbivores, 16 detritivores, 9 predators, 8 mixed feeders, 5 omnivores and 2 non-classified feeders (or not feeding as adults) (Vandegehuchte and others 2017b). We summed the numbers from the two pitfall traps and the suction sampling over the course of the 2013 season to represent the aboveground invertebrate abundance and community composition of a plot. Note: we did not specifically attempt to catch flying invertebrates with e.g., sticky traps, thus a few flying insects may have been missed with our vacuum sampling approach.
Sampling of plant properties
The vascular plant species composition was assessed at peak biomass every summer (July) by estimating the frequency of occurrence of each species with the pin count method in each plot (Frank and McNaughton 1990). A total of 172 taxa occurred within our 90 plots and we calculated plant species richness for each plot separately. We used the 2013 data in this study. Plant quality was assessed every year in July and September; here we use plant quality at the end of the experiment (September 2013). Two 10 x 100 cm wide strips of vegetation per plot were clipped, combined, dried at 65°C, and ground (Pulverisette 16, Fritsch, Idar-Oberstein, Germany) to pass through a 0.5 mm sieve. Twenty randomly selected samples across all treatments were analysed for N (Leco TruSpec Analyser, Leco, St. Joseph, Michigan, USA) (Vandegehuchte and others 2015). Nitrogen concentrations of the other samples were then estimated from models established for the experiment and the entire SNP relating Fourier transform-near infrared reflectance (FT-NIR) spectra to the measured values of N using a multi-purpose FT-NIR spectrometer (Bruker Optics, Fällanden, Switzerland) (Vandegehuchte and others 2015). Root biomass was sampled every fall by collecting five 2.2 cm diameter x 10 cm deep soil samples (Giddings Machine Company, Windsor, CO, USA) per plot (450 samples year-1). The samples were dried at 30 °C and roots were sorted from the sample by hand. We sorted each sample for 1 h which allowed to retrieve over 90% of all roots present in the samples (Risch and others 2013). The roots were then dried at 65 °C for 48 and weighed to the nearest mg. We averaged the values per plot and used the 2013 data only in this study.
Sampling of edaphic communities
In 2009, 2010, and 2011 we collected three composited soil samples (5 cm diameter x 10 cm depth; AMS Samplers, American Falls, ID, USA) and assessed bacterial community structure using T-RFLP profiling (Liu and others 1997; Blackwood and others 2003; Hodel and others 2014). We detected a total of 89 operational taxonomic units (OTUs). These values are in accordance with other studies reporting OTU richness (Wirthner and others 2011; Zumsteg and others 2012; Meola and others 2014) using T-RFLP profiling, a method that detects the most abundant, and thus likely, the most relevant, taxa. We averaged the data over the three years of collections for our calculations. Microbial biomass carbon (MBC) was determined with the substrate-induced method (Anderson and Domsch 1978) every fall (September) between 2009 and 2013 by collecting three mineral soil samples (5 cm diameter × 10 cm mineral soil core, AMS Samplers, American Falls, ID, USA). The three samples were combined (90 samples for each sampling year), immediately put on ice, taken to the laboratory, passed through a 2-mm sieve and stored at 4°C. Again, we only used the 2013 data in this study.
Soil samples (5 cm diameter x 10 cm depth) to extract soil arthropods were collected in June, July, and August 2011 with a soil corer lined with a plastic sleeve to ensure an undisturbed sample (total of 270 samples). The plastic line core was immediately sealed on both ends using cling film and put into a cooler. All plots were sampled within three days and the extraction of arthropods started the evening of the sampling day using a high-gradient Tullgren funnel apparatus (Crossley and Blair 1991; Vandegehuchte and others 2015). Samples were kept in the extractor for four days and the soil arthropods were collected in 95% ethanol. All individuals were counted and each individual was identified morphologically to the lowest level feasible [76 taxa, including orders, suborders, subfamilies, families (Protura, Thysanoptera, Aphidina, Psylina, Coleoptera, Brachycera, Nematocera, Auchenorryncha, Heteroptera, Formicidae); sub-phylum for Myriapoda, for Acari and Collembola also including morpho-species). Note that we also included larval stages (nine of the 76 taxa) (Vandegehuchte and others 2015). All data were summed over the season. A detailed species list for mites and collembolans is published (Vandegehuchte and others 2017a) [https://doi.org/10.1371/journal.pone.0118679.s001]. Earthworms are rare in the SNP and therefore were not included. We collected eight random 2.2 cm diameter x 10 cm deep soil cores from each plot in September 2013 to determine the soil nematode community composition. The samples were mixed and the nematodes were extracted from 100 ml of fresh soil using Oostenbrink elutriators (Oostenbrink 1960). All nematodes in a 1 ml of the 10 ml extract were counted, a minimum of 150 individuals sample-1 were identified to genus or family level using (Bongers 1988), the numbers of all nematodes were extrapolated to the entire sample and expressed for a 100 g dry sample. In total we identified 63 genus or family levels (Vandegehuchte and others 2015). The list of all the nematodes found is published (Vandegehuchte and others 2015) [http://www.oikosjournal.org/appendix/oik-03341] or DOI: [doi: 10.1111/oik.03341].
We are aware that sampling soil microbes from 2009 to 2011 and soil arthropods in 2011 was not ideal, but we are positive that this does not bias the results. Most of the parameters measured in our experiment either already showed a treatment response after the first growing season (e.g., plant biomass) or did not respond over the entire time experiment (e.g., microbial biomass C). The microbial community composition (2009 – 2011) was highly influenced by inter-annual differences in temperature and precipitation, but did not differ between treatments or vegetation types (Hodel and others 2014). We therefore felt comfortable using the 2009 through 2011 data for describing the soil microbial community in our experimental treatments. Similarly, we are positive that our soil arthropod data are representative. We did assess soil arthropods in August 2012 and found no differences to the August 2011 data. However, we did not feel comfortable combining the 2011 June, July, August data with only August data for 2012 for our analyses.
Sampling of soil properties
We collected three soil samples (5 cm diameter x 10 cm depth) in each plot in September 2013 after removing the vegetation. First, we collected the top layer of mineral soil rich in organic matter, the surface organic layer or rhizosphere, typically 1 to 3 cm in depth with a soil corer (AMS Samples, American Falls, Idaho, USA). Second, we collected a 10 cm mineral soil core beneath this surface layer. The cores for each layer were composited, dried at 65 °C for 48 h and fine-ground to pass a 0.5 mm screen. We then analysed all samples for total C using a Leco TruSpec Analyser (Leco, St. Joseph, Michigan, USA). Mineral soil pH was measured potentiometrically in 1:2 soil:CaCl2 solution with an equilibration time of 30 min.
Soil net N mineralisation was assessed during the 2013 growing season (Risch and others 2015). For this purpose, we randomly collected a 5 cm diameter x10 cm deep soil sample with a soil corer (AMS Samples, American Falls, Idaho, USA) after clipping the vegetation in June 2013. After weighing and sieving (4 mm mesh) the soil, we extracted a 20 g subsample in 1 mol l-1 KCl for 1.5 h on an end-over-end shaker and thereafter filtered it through ashless folded filter paper (DF 5895 150, ALBET LabScience, Hahnenmühle FineArt GmbH, Dassel, Germany). From these filtrates NO3- concentrations were measured colorimetrically (Norman and Stucki 1981) and NH4+with flow injection analysis (FIAS 300, Perkin Elmer, Waltham Massachusetts, USA) (Risch and others 2015). We dried the rest of the sample 105 °C to constant mass to determine fine,fraction bulk density. A second soil sample was collected within each plot in June 2013 with a corer lined with a 5 x 13 cm aluminium cylinder. The corer was driven 11.5 cm deep into the soil so that the top 1.5 cm of the cylinder remained empty. Into this space we placed a polyester bag (250 µm) filled an ion-exchanger resin to capture the incoming N. The bag was filled with a 1:1 mixture of acidic and alkaline exchanger resin (ion-exchanger I KA/ion exchanger IIIAA, Merck AG, Darmstadt, Germany). We then removed 1.5 cm soil at the bottom of the cylinder and placed a second resin exchanger bag into this space to capture the N leached from the soil column. To assure that the exchange resin was saturated with H+ and Cl- prior to filling the bags, the mixture was stirred with 1.2 ml l-1 HCl for 1 h and then rinsed with demineralized water until the electrical conductivity of the water reached 5 µm cm-1. The cylinder with the resin bags in place was reinserted into the soil with the top flush to the soil surface and incubated for three months. We recollected the cylinders in September 2013. Each resin bag and 20 g of sieved soil (4 mm mesh) from each cylinder were then separately extracted with KCl and NO3- and NH4+ concentrations were measured. Nitrate and NH4+ concentrations of all samples were then converted to a content basis by multiplying their values with fine fraction bulk density. Net N mineralisation was thereafter calculated as the difference between the N content of the samples collected at the end of the three-month incubation (including the N extracted from the bottom resin bag) and the N content at the beginning of the incubation (Risch and others 2015).
Soil CO2 emissions were measured every two weeks between 0900 and 1700 hrs from early May through late September 2013 with a PP-Systems SRC-1 soil respiration chamber (15 cm high, 10 cm diameter; closed circuit) attached to a PP-Systems EGM-4 infrared gas analyser (PP-Systems, Amesbury, MA, USA) on two locations per plot (Risch and others 2013). The chamber was placed on randomly placed, permanently installed PVC collars (10 cm diameter) driven 5 cm into the soil at the beginning of the study (Risch and others 2013). Freshly germinated plants growing within the collars were removed prior to each measurement to avoid measuring plant respiration or photosynthesis. The two measurements collected per plot and sampling date were averaged.
Soil moisture (with time domain reflectometry; Field-Scout TDR-100, Spectrum Technologies, Plainfield, Illionois, USA) and temperature (with a waterproof digital pocket thermometer; Barnstead International, Dubuque, Iowa, USA) were measured at five random locations per plot every two weeks during the growing seasons during the experiment for the 0 to 10 cm depth (Risch and others 2013, 2015). As soil moisture and soil temperature were highly negatively correlated (Risch and others 2013), we only used soil moisture for this study. We used plot-level averages of all values available to capture soil moisture variability during the five years of the experiment. The results remained unchanged when we only used soil moisture from the 2013 growing season.
Numeral calculations and statistical analyses
Ecosystem coupling. We conducted principal component analyses (PCAs; unscaled) at the complete dataset level using the abundances of each taxonomical entity to describe each of the five different communities used in this study: aboveground-dwelling invertebrates, vascular plants, soil microorganisms, soil arthropods and soil nematodes. We retained the first two components (PCA axis 1 and PCA axis 2) of each analysis as we found them to adequately represent the temporal and spatial variability of our 90 treatment plots in previous studies55,67. Together they explained a total of 71.70% of the variation for aboveground invertebrates, 44.36% for plants, 44.85% for soil microorganisms, 61.85% for soil arthropods and 77.19% for soil nematodes. In addition, we used soil pH and soil organic C content as a proxy for soil chemical properties, soil bulk density as a proxy for soil physical properties and soil moisture (negatively correlated with soil temperature) as a proxy for soil micro-climatic conditions for an overall total of fourteen constituents.
We calculated ecosystem coupling9 for each exclosure treatment within each vegetation type (i.e., 2  5 treatment combinations in total) as an integrated measure of pairwise ecological interactions between ecosystem constituents representing ecological communities and the soil abiotic environment. These ecological interactions are defined by non-parametric Spearman rank correlation analyses between two constituents, excluding interactions involving two abiotic constituents (e.g., soil pH vs. soil moisture) and interactions between the first (PC1) and second (PC2) component of each community type, as these are orthogonal by definition. Interactions between abiotic constituents were excluded from the analyses because the focus of our study was on communities and how they interact with one another and their surrounding environment; therefore, including abiotic-abiotic interactions was not of interest here. Given that the effectiveness of our experimental design resulted in that no community composition data of aboveground-dwelling invertebrates was available for the “None” plots (all animals excluded), only thirteen instead of fourteen constituents were included in the ecosystem coupling calculations for this treatment. The complete absence of aboveground invertebrates represents the most extreme case of disturbance between aboveground animal communities and the rest of the ecosystem constituents. This may have resulted in a slight overestimation of ecosystem coupling for these plots.
	Average ecosystem coupling was calculated as follows:
Ecosystem coupling=
where Xi is the absolute Coupling was calculated value of the Spearman’s rho coefficient of the ith correlation for each treatment within each vegetation type (i.e., based on nine replicates each), considering and n is the number of pairwise comparisons considered (n = a total of 80;  interactions (56 in the case of the “None” treatment). We considered a total of 40 biotic-biotic interactions (i.e., concerning two community-level principal components such as plants and microbes; 24 in the case of the “None” treatment) and 40 abiotic-biotic (i.e., concerning one community-level principal component and one abiotic factor, e.g., plant community and soil properties; 32 in the case of the “None” treatment).	Coupling was calculated for each treatment within each vegetation type (i.e., based on nine replicates each), considering a total of 80 interactions (56 in the case of the “None” treatment). We considered a total of 40 biotic-biotic interactions (i.e., concerning two community-level principal components such as plants and microbes; 24 in the case of the “None” treatment) and 40 abiotic-biotic (i.e., concerning one community-level principal component and one abiotic factor, e.g., plant community and soil properties; 32 in the case of the “None” treatment).
To establish whether constituents were significantly and positively coupled within treatments (i.e., the average of their correlation coefficients were greater than in a null model where correlation only happens by chance), we calculated one-tailed p-values based on permutation tests with 999 permutations.

We considered six ecosystem functions and process rates commonly used to assess ecosystem functioning (Meyer and others 2015; Manning and others 2018). Plant N content represents a measure of forage quality, while plant richness has been shown to stabilise biomass production, thus allowing the system to respond to changes in herbivory. Soil net N mineralisation, soil respiration, root biomass, and microbial biomass represent fluxes or stocks of energy. For all functions and processes higher values represent higher functioning (Manning and others 2018). All these variables were measured in the last year of the experiment (2013). We then quantified ecosystem multifunctionality using the multiple threshold approach (Byrnes and others 2014; Manning and others 2018), which considers the number of functions that are above a certain threshold, over a series of threshold values (typically 10-99%) that are defined based on the maximum value of each function. We weighted all our functions equally for these calculations (Manning and others 2018). The number of functions in a plot with values higher than a given threshold value for the respective function is summed up. The sum represents ecosystem multifunctionality for that plot. Given that choosing any particular threshold as a measure of ecosystem multifunctionality is arbitrary, we calculated the average of thresholds from 10-90% (in 10% intervals) as a more integrated representation of ecosystem multifunctionality.
We used Pearson correlations to explore the relationships between ecosystem coupling (all interactions, biotic-biotic interactions, abiotic-biotic interactions involving above- and belowground constituents, and all interactions, biotic-biotic interactions, abiotic-biotic interactions involving belowground constituents only) and ecosystem multifunctionality by calculating the slopes of all relationships between ecosystem coupling and multifunctionality for all thresholds between 10 and 99%. We also related ecosystem coupling with the average of multifunctionality at thresholds between 30-80% as explained before and considered this correlation as a robust indication of the type of association between these two variables. In addition, we explored the relationships between ecosystem coupling (all interactions, biotic-biotic interactions, abiotic-biotic interactions involving above- and belowground constituents, and all interactions, biotic-biotic interactions, abiotic-biotic interactions involving belowground constituents only) and individual ecosystem functions. The effects of exclosures and vegetation type on individual functions and multifunctionality were evaluated using linear mixed effects models ('lme' function of the nlme package), with exclosure and vegetation type as fixed effects and fence as a random factor. All statistical analyses and numerical calculations were done in R version 3.4.0 (R Core Team 2016).
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en: Ecosystem coupling and multifunctionality - exclosure experiment

en: ecosystem-coupling ecosystem-multifunctionality grazing subalpine invertebrates swiss-national-park vertebrates exclusion grassland ecosystem-functions

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ecosystem-functions

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ecosystem-multifunctionality

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exclusion

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invertebrates

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swiss-national-park

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vertebrates

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en:
Dataset of an experimental campaign of induced rockfall in Tschamut, Grisons, Switzerland.
The data archive contains site specific geographical data such as DEM and orthophoto as well as the deposition points of manually induced rockfall by releasing differently shaped boulders with 30–80 kg of mass. Additionally available are all the StoneNode data streams for rocks equipped with a sensor. The data set consists of
* Deposition points from two series (wet (27/10/2016) and frozen (08/12/2016) ground)
* Digital Elevation Model (grid resolution 2 m) obtained via UAV
* Orthophoto (5 cm resolution) obtained via UAV
* Digitized rock point clouds (.pts input files for RAMMS::ROCKFALL)
* StoneNode v1.0 raw data stream for equipped rocks.
Further information is found in
* A. Caviezel et al., _Design and Evaluation of a Low-Power Sensor Device for Induced Rockfall Experiments_, IEEE Transactions on Instrumentation and Measurement, 2018, 67, 767-779, http://ieeexplore.ieee.org/document/8122020/
*  P. Niklaus et al., _StoneNode: A low-power sensor device for induced rockfall experiments_, 2017 IEEE Sensors Applications Symposium (SAS), 2017, 1-6, http://ieeexplore.ieee.org/document/7894081/

en: Induced Rockfall Dataset (Small Rock Experimental Campaign), Tschamut, Grisons, Switzerland

en: induced-rockfall stonenode stonenodedata rockfall natural-hazards rockfall-experiments deposition-points rockfall-runout sensor-stream dem

envidat

approval_status: approved

fr: EnviDat est le portail de données du WSL; il offre un accès uniformisé et réglementé aux données de surveillance et de recherche en matière d’environnement. Ce portail est capable d’héberger et de publier des ensembles de données précieuses et uniques, qui sont partagées aux quatre coins de la planète. Ce faisant, EnviDat favorise la recherche et contribue à l’avancement des sciences environnementales.

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

de: EnviDat ist das Datenportal der WSL für einen einheitlichen und verwalteten Zugang zu Umweltdaten aus Monitoring- und Forschungsprojekten. Auf dem Portal können Datensätze gehostet und veröffentlicht werden. Durch die weltweite Bereitstellung einzigartiger und wertvoller Datensätze leistet EnviDat einen Beitrag zur Forschung im Bereich der Umweltwissenschaften.

it: EnviDat è il portale dati del WSL che fornisce un accesso unificato e gestito ai dati di monitoraggio ambientale e di ricerca. Il portale ha la capacità di ospitare e pubblicare serie di dati preziosi e unici che vengono condivisi in tutto il mondo. Così facendo, EnviDat promuove la ricerca e contribuisce al progresso della scienza ambientale.

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

fr: EnviDat: le portail de données environnementales

it: EnviDat: il portale dei dati ambientali

political_level: other

state: active

type: organization

wsl

capacity: public

de: EnviDat

type: dataset

key: guid

key: uri

value: Envidat Harvester

envi

de: Umwelt

en: Environment

fr: Environnement

it: Ambiente

en:
Resource Title: Induced Rockfall Data, Tschamut, GR
    Size: 83833546 bytes
    Format: application/x-7z-compressed
    URL: https://www.envidat.ch/dataset/5b7a47bf-cbea-42a0-879f-ea2ccd17e82f/resource/3be3d9f6-cf12-4dbc-bdf1-80e101fb47f7/download/2018_rf_tschamut.7z
    Description: __ Induced Rockfall Experimental Data, Tschamut, GR, Switzerland__

The archive contains site specific geographical data as well as the deposition points of manually induced rockfall by releasing differently shaped boulders with 30–80 kg of mass. Additionally availabe are the StoneNode v1.0 sensor streams for the equipped rocks.

The _OverviewFigures_ file serves as quick representation of the included data. It also contains the overview table for the rock masses in order to set the dimensions accordingly in RAMMS::ROCKFALL.

The archive contains the following folders:
<\ul>
* DEM: ArcGIS compatible DEM Tschamut_DEM_2m (grid resolution of  2 m) as well as the .asc grid used in RAMMS::ROCKFALL simulations
* _DepositionPoints_: containing two folders _RF Tschamut Frozen_ and _RF Tschamut WET_ containing each a shapefile with the complete deposition data of each series as well as deposition shapfiles for each rock shape.
* _DigitizedRocks_: Digitized point clouds of the used rocks as used for RAMMS::ROCKFALL simulations (.pts files) (dimensions have to be checked).
* _Orthofoto_: Orthophoto of the experimental site obtained via UAV with 5 cm resolution.

en:
Resource Title: StoneNode v1.0 Data for equipped experimental Runs.
    Size: 6899716 bytes
    Format: application/x-7z-compressed
    URL: https://www.envidat.ch/dataset/5b7a47bf-cbea-42a0-879f-ea2ccd17e82f/resource/c80b0561-d5f8-4bd6-97e7-ec5a15bfd84e/download/experimentalruns_sensorstreams.7z
    Description: Corresponding StoneNode v1.0 data streams belonging to the deposition points.

dem

display_name: dem

deposition-points

display_name: deposition-points

induced-rockfall

display_name: induced-rockfall

natural-hazards

display_name: natural-hazards

rockfall

display_name: rockfall

rockfall-experiments

display_name: rockfall-experiments

rockfall-runout

display_name: rockfall-runout

sensor-stream

display_name: sensor-stream

stonenode

display_name: stonenode

stonenodedata

display_name: stonenodedata


lwf-tea-bag-sites

en:
Decomposition of plant litter is a key process for the transfer of carbon and nutrients in ecosystems. Carbon contained in the decaying biomass is released to the atmosphere as respired CO2, and may contribute to global warming. Litterbag studies have been used to improve our knowledge of the drivers of litter decomposition, but they lack comparability because litter quality is plant species-specific. The use of commercial tea bags as a standard substrate was suggested in order to harmonize studies, where green tea and rooibos represent more labile and more recalcitrant C compounds as surrogates of local litter.
The tea bag approach was implemented on eight sites of the Swiss long-term Forest Ecosystem Research (LWF) network (https://www.wsl.ch/LWF). This allowed us to take advantage from the existing infrastructure and data from a previous litterbag study with local litter. In Beatenberg and Schaenis, additional elevation transects were established (1200-1800 m and 540-1150 m, respectively) to examine particularly the effect of temperature on decomposition. In Pfynwald (https://www.wsl.ch/de/ueber-die-wsl/versuchsanlagen-und-labors/flaechen-im-wald/pfynwald.html) and Salgesch, infrastructure of running projects was used to examine the effect of drought and understory removal, respectively. In Novaggio, tea bags were incubated in summer and winter to study the effect of seasonality particularly precipitation. Tea bags are collected after 3, 12, 24, and 36 months; for the two time-shifted experiments additionally after 6 and 9 months.
The study has two primary objectives. Firstly, it contributes to TeaComposition initiative (http://teacomposition.org/) which aims at investigating long-term litter decomposition and its key drivers at present as well as under different future climate scenarios using a common protocol and standard litter (tea) across nine terrestrial biomes. Secondly, the data are used to further develop decomposition models such as Yasso (http://en.ilmatieteenlaitos.fi/yasso) which is used by several countries, including Switzerland to estimate the annual carbon fluxes in dead wood, litter, and soil for reporting in National Greenhouse Gas Inventories under the United Nations Framework Convention on Climate Change and the Kyoto Protocol.

en: LWF-Tea bag sites

en: carbon decomposition litter verification roiboos tea-bag forest modeling green-tea

title_for_slug: lwf-tea-bag-sites

format: CSV

carbon

display_name: carbon

decomposition

display_name: decomposition

forest

display_name: forest

green-tea

display_name: green-tea

litter

display_name: litter

modeling

display_name: modeling

roiboos

display_name: roiboos

tea-bag

display_name: tea-bag

verification

display_name: verification


en:
In summer 2014, 6 rock blocks between 20 and 80kg have been thrown in total 111 times down a slope at the Swiss Oberalppass close to the village Tschamut. The slope was mainly covered by grass and its lower part was flat and large enough to provide natural runouts of the single trajectories.
An extensive measurement program has been set up to measure the block trajectories: With surveyor's instruments the slope and the six used rock blocks were scanned and the start and end positions of each test were recorded. During the single events two cameras filmed the trajectories. A special sensor device located within the blocks recorded the acting accelerations and rotational speeds over time. Further, the device emitted a Wifi signal that got detected from eight receivers around the slope. Based on this signal the block position has been recorded over time.
The dataset contains all data that were gathered through above field campaign.

en: Repetitive trajectory testing in Tschamut 2014

en: trajectory field-tests experiments experiment field-data field-test rockfall natural-hazards mass-movements

en:
Resource Title: Block trajectories recorded from local positioning system
    Size: 6430962 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/6a7664a6-77a9-49c9-9498-4b63c018fa09/resource/b6dc0f14-5b86-4353-a2a6-ef06c0ddf0ad/download/trajectoriesfromlps.zip
    Description: This file contains more than 80 rockfall trajectories projected onto the terrain, i.e. the positions of the single blocks over time during the single tests that were recorded by the local positioning system with about 10Hz. It contains the detected positions as well as a smoothened path (see Volkwein et al., Geosciences, 2018). The table also contains the derived velocities and accelerations along the slope (attention: these accelerations are the once that occur during an impact).

format: ZIP

media_type: application/zip

en:
Resource Title: Overview of all tests
    Size: 44962 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/6a7664a6-77a9-49c9-9498-4b63c018fa09/resource/467dc8f8-9069-4c87-8856-3d12817633be/download/overviewalltests.zip
    Description: This table gives an overview on all tests performed including
- block used
- start & end position
- number of jumps
- etc.
-

en:
Resource Title: Jumps and impacts
    Size: 1051503 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/6a7664a6-77a9-49c9-9498-4b63c018fa09/resource/e2f0958e-2b51-49ce-ba25-40c4ffd331a7/download/jumpsandimpacts.zip
    Description: This table contains data of more than 2200 of each jumps and impacts of the test blocks on a grassy slope. It gives there durations in combination with acting accerlartions and the rotational speed of the blocks. The data were retrieved using the block internal accelerometer and rotation sensors. The combination of these data with the measurement from the local positioning system allows the deduction of jump lengths, slope gradient etc.

en:
Resource Title: Tschamut2014_Slope+BlockScans
    Size: 1779331 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/6a7664a6-77a9-49c9-9498-4b63c018fa09/resource/8cf275ca-06d0-47cf-b67f-48780b019ae6/download/geosciences-08-00088-s001.zip
    Description: These data contain the point clouds obtained from laser scanning the test slope and the six test blocks used for the experiments. The coordinates of the slope are given in CH-1903 format. The coordinates of the block point clouds are kept in a lokal x/y/z coordinate system.

experiment

display_name: experiment

experiments

display_name: experiments

field-data

display_name: field-data

field-test

display_name: field-test

field-tests

display_name: field-tests

mass-movements

display_name: mass-movements

trajectory

display_name: trajectory


en: We recorded snow ablation maps with a terrestrial laser scanner (TLS, Riegl-VZ6000) at the Gletschboden area. The TLS position is located approximately 30 vertical meters above the Gletschboden area at a northerly exposed slope. In total 44 TLS measurement sets have been conducted in three consecutive years 2014-2016 (2014: 13 measurements; 2015: 17 measurements; 2016: 14 measurements). The TLS system has a single-point measurement frequency of 300 kHz and a beam divergence of 0.007°. This set-up allows a horizontal resolution of approximately 0.01 m in 100 m distance to the TLS position. One scan of the Gletschboden area lasts approximately 15 minutes. The travel time from the laser scanner towards the surface is recorded and afterwards converted into a point cloud of distances. 5 reflectors located at the Gletschboden area and in the closer surroundings were additionally scanned during each measurement to transform the point cloud from the scanner own coordinate system into Swiss coordinates. Additionally, orthophotos have been created by using pictures recorded from the TLS in order to provide snow mask maps. Snow and bare ground can be distinguished by the RGB color information of the orthophoto. Cells with blue band information greater than 175 were categorized as snow and all cells with values smaller or equal 175 were categorized as bare ground.

en: DISCHMEX - High-resolution daily snow ablation rates in an Alpine environment

en: terrestrial-laser-scanning riegl-vz6000 tls patchy-snow-covers snow-ablation-rates

en:
Resource Title: Gletschboden test site
    Size: 352578 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/6b961ebc-1c86-45ec-8b6d-8efdd2e8babe/resource/645e45ec-fc90-432c-a29e-d1d79781d5b2/download/dischma_neu.pdf
    Description:

format: PDF

media_type: application/pdf

en:
Resource Title: Snowmask 2014
    Size: 2069460 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/6b961ebc-1c86-45ec-8b6d-8efdd2e8babe/resource/5a5b22eb-a0ae-4552-a7b3-34631c3ae998/download/2014snowmask.zip
    Description:

en:
Resource Title: Snowmask 2015
    Size: 6736562 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/6b961ebc-1c86-45ec-8b6d-8efdd2e8babe/resource/89c08602-142c-4fdb-9c76-3993a9d0dbfc/download/2015snowmask.zip
    Description:

en:
Resource Title: DEM 2015
    Size: 85474333 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/6b961ebc-1c86-45ec-8b6d-8efdd2e8babe/resource/9d19c582-76ca-45df-b032-46d8346f45be/download/2015dem.zip
    Description: Digital Elevation Modell 2015

en:
Resource Title: DEM 2014
    Size: 76297946 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/6b961ebc-1c86-45ec-8b6d-8efdd2e8babe/resource/299a98ef-94e5-4bdd-912f-24b347d20da6/download/2014dem.zip
    Description: Digital Elevation Modell 2014

en:
Resource Title: Snowmask 2016
    Size: 1979860 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/6b961ebc-1c86-45ec-8b6d-8efdd2e8babe/resource/2b54670d-74e9-4ea5-8fcd-4ea98ad26ed6/download/2016snowmask.zip
    Description:

en:
Resource Title: DEM 2016
    Size: 73447711 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/6b961ebc-1c86-45ec-8b6d-8efdd2e8babe/resource/787f969b-71db-4ec9-967b-7e0198dd9d71/download/2016dem.zip
    Description: Digital Elevation Modell 2016

patchy-snow-covers

display_name: patchy-snow-covers

snow-ablation-rates

display_name: snow-ablation-rates

terrestrial-laser-scanning

display_name: terrestrial-laser-scanning

tls

display_name: tls


weissfluhjoch-dataset-for-esm-snowmip

en: This Weissfluhjoch dataset is a processed version  of the Weissfluhjoch dataset version 6 from https://doi.org/10.16904/6. This dataset was specially created for the ESM-SnowMIP project. Here it is documented how this dataset has been created.

en: Weissfluhjoch dataset for ESM-SnowMIP

en: snow-depth snow snow-models esm-snowmip weissfluhjoch

envidat

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

en: EnviDat: the Environmental Data Portal

title_for_slug: weissfluhjoch-dataset-for-esm-snowmip

envi

en: Environment

en:
Resource Title: WFJ_AirPressure_Data.zip
    Size: 4688961 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/a9264e9f-ea9b-4c89-b471-464efb891826/resource/b834a645-c5e0-4bf1-bceb-17a2eb62b61a/download/wfjairpressuredata.zip
    Description: WFJ_AirPressure_Data.zip

en:
Resource Title: Conversion script
    Size: 900 bytes
    Format: text/x-sh
    URL: https://www.envidat.ch/dataset/a9264e9f-ea9b-4c89-b471-464efb891826/resource/aa8942dc-5fe5-4792-bf4b-1b950d9c6204/download/createwfjdataset.sh
    Description: Use this script to convert WFJ_optimaldataset_v6.smet to wfj.smet, the file that is used for the ESM-SnowMIP project. It also requires the file: WFJ_AirPressure_Data.zip

Use: bash create_wfj_dataset.sh > input/wfj.smet

en:
Resource Title: Dataset Weissfluhjoch for ESM-SnowMIP
    Size: 11596605 bytes
    Format: application/x-smet
    URL: https://www.envidat.ch/dataset/a9264e9f-ea9b-4c89-b471-464efb891826/resource/a5918c50-6716-4dcf-b462-e1970ae1e072/download/wfj.smet
    Description: Dataset Weissfluhjoch for ESM-SnowMIP

en:
Resource Title: ini file
    Size: 1410 bytes
    Format: text/x-ini
    URL: https://www.envidat.ch/dataset/a9264e9f-ea9b-4c89-b471-464efb891826/resource/c7f7533e-03f2-42c2-ad82-36d3c6ab8fd2/download/io.ini
    Description: This ini file is required by data-converter from MeteoIO version 1887 (http://models.slf.ch/p/meteoio/)

esm-snowmip

display_name: esm-snowmip

snow

display_name: snow

snow-depth

display_name: snow-depth

snow-models

display_name: snow-models

weissfluhjoch

display_name: weissfluhjoch


en:
The dataset comprises - 90 000 records from inventories in 54 strict forest reserves in [Switzerland](https://www.wsl.ch/de/wald/biodiversitaet-naturschutz-urwald/naturwaldreservate.html) and [Lower Saxony / Germany](http://naturwaelder.de/) along a considerable environmental gradient. It was used to develop parsimonious, species-specific mortality models for 18 European tree species based on tree size and growth as well as additional covariates on stand structure and climate.
 Inventory data
Measurements had been conducted repeatedly on up to 14 permanent plots per reserve for up to 60 years with re-measurement intervals of 4 - 27 years. The permanent plots vary in size between 0.03 and 3.47 ha. The inventories provide diameter measurements at breast height (DBH) and information on the species and status (alive or dead) of trees with DBH ≥ 4 cm for Switzerland and ≥ 7 cm for Germany.
 Data selection
We excluded three permanent plots where at least 80 % of the trees died during an interval of 10 years, and mortality could be clearly assigned to a disturbance agent. Mortality in the remaining stands was rather low, with a mean annual mortality rate of 1.5 % and strong variation between plots from 0 to 6.5 % (assessed for trees of all species with DBH ≥ 7 cm).
We only used data from permanent plots with at least 20 trees per species to obtain reliable plot-level mortality rates even for species with low mortality rates (about 5 % during 10 years), and selected tree species occurring on at least 10 plots to cover sufficient ecological gradients. This led to a dataset of 197 permanent plots and 18 tree or shrub species: _Abies alba_ Mill., _Acer campestre_ L., _Acer pseudoplatanus_ L., _Alnus incana_ Moench., _Betula pendula_ Roth, _Carpinus betulus_ L., _Cornus mas_ L., _Corylus avellana_ L., _Fagus sylvatica_ L., _Fraxinus excelsior_ L., _Picea abies_ (L.) Karst, _Pinus mugo_ Turra, _Pinus sylvestris_ L., _Quercus pubescens_ Willd., _Quercus_ spp. (_Q. petraea_ Liebl. and _Q. robur_ L.; not properly differentiated in the Swiss inventories), _Sorbus aria_ Crantz, _Tilia cordata_ Mill. and _Ulmus glabra_ Huds..
 Predictors of tree mortality
We considered tree size and growth as key indicators for mortality risk. Radial stem growth between the first and second inventory and DBH at the second inventory were used to predict tree status (alive or dead) at the third inventory. To this end, the annual relative basal area increment (relBAI) was calculated as the compound annual growth rate of the trees basal area. Additional covariates on stand structure and climate comprise mean annual precipitation sum (P), mean annual air temperature (mT), the mean and the interquartile range of DBH (mDBH, iqrDBH), basal area (BA) and the number of trees (N) per hectare.
 Further information
For further information, refer to Hülsmann _et al_. (in press) How to kill a tree – Empirical mortality models for eighteen species and their performance in a dynamic forest model. _Ecological Applications_.

en: Calibration data for empirical mortality models of 18 European tree species

en: tree-growth empirical-mortality-models inventory-data forest-reserves tree-mortality

empirical-mortality-models

display_name: empirical-mortality-models

forest-reserves

display_name: forest-reserves

inventory-data

display_name: inventory-data

tree-growth

display_name: tree-growth

tree-mortality

display_name: tree-mortality


en:
Stable water isotopes (δ18O) obtained from snow and ice samples of polar regions are used to reconstruct past climate variability, but heat and mass transport processes can affect the isotopic composition. Here we present an experimental study on the effect on the snow isotopic composition by airflow through a snow pack in controlled laboratory conditions. The influence of isothermal and controlled temperature gradient conditions on the δ18O content in the snow and interstitial water vapor is elucidated. The observed disequilibrium between snow and vapor isotopes led to exchange of isotopes between snow and vapor under non-equilibrium processes, significantly changing the δ18O content of the snow. The type of metamorphism of the snow had a significant influence on this process.
Ebner, P. P., Steen-Larsen, H. C., Stenni, B., Schneebeli, M., and Steinfeld, A.: Experimental observation of transient δ18O interaction between snow and advective airflow under various temperature gradient conditions, The Cryosphere Discuss., https://doi.org/10.5194/tc-2017-16, accepted, 2017.

en: Experiments on stable water isotopes,  snow metamorphism, and advection

en: 18o snow stable-water-isotope metamorphism advection

en:
Resource Title: Data files and read-me
    Size: 8226023 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/f87efc01-9914-4a75-998f-7dfc1fcef563/resource/e133ed87-de41-4595-87c9-b07f696c5cce/download/archive.zip
    Description: raw data and micro-CT data available from contacts

en:
Resource Title: Read-me
    Size: 974 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/f87efc01-9914-4a75-998f-7dfc1fcef563/resource/92a315fd-1e17-4b9e-bce3-e69a3fac0d0a/download/readme.txt
    Description: A short description of the data contained in the zipped-file. Recommended for reading before downloading the dataset.

format: TXT

media_type: text/plain

advection

display_name: advection

metamorphism

display_name: metamorphism

stable-water-isotope

display_name: stable-water-isotope


en:
This dataset contains eddy-covariance measurements in the ablation period of 2014-2016. Measurements were taken from two turbulence towers over a long-lasting snow patch, which are 5 m apart from each other (2014 and 2015). The turbulence towers were equipped with two YOUNG ultrasonic anemometers mounted 0.7 m (in 2014) and 3.3 m (in 2015) above snow-free ground, two ultrasonic anemometers (CSAT3, Campbell Scientific, Inc.) mounted at 2.6 m (in 2014) and 2.2 m (in 2015) above snow-free ground and one anemometer (DA-600, Kaijo Denki) mounted at 0.3 m above snow surface.
The measurement setup changed in 2016 and includes a measurement above the snow-free ground in upwind direction (Swiss coordinates: 790191/176689). The measurement tower is equipped with one ultrasonic anemometer (CSAT3, Campbell Scientific, Inc.) in 3.3 m above the snow-free ground. Additionally, one measurement tower is installed above the long-Lasting snow patch and equipped with the same setup as 2015.
Turbulence data were sampled at a frequency of 20 Hz. The processing of the data to quality controlled fluxes has been done with the Biomicrometeorology flux software (Thomas et al., 2009). The program applies plausibility tests and a despiking test after Vickers and Mahrt (1997) on the measured data. The routine further applies a time-lag correction and considers the deployment (e.g.  the sonic azimuth). A frequency response correction (Moore, 1986) is done and a three-dimensional rotation is performed. Finally, quality assurance/quality control (QA/QC) flags after Foken et al., (2004) are issued and fast Fourier transform power and co-spectra are calculated.  The change in snow height is considered in the post-processing for every measurement day. The turbulence data were averaged to 30 minute intervals.

en: DISCHMEX - Impact of extreme land-surface heterogeneity on micrometeorology over spring snow-cover

en: eddy-covariance-measurements patchy-snow-covers dischmex turbulent-sensible-heat-fluxes snow-patch

en:
Resource Title: S3 2014
    Size: 717361 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/7e8c6dac-80cf-49d7-bd85-2a61d3336e6f/resource/96640b5b-18e4-4de4-b19b-d8be3fabe9a6/download/s3-2014.zip
    Description: Eddy-covariance measurement with an ultrasonic anemometer (R.M. Young Company) in 0.7 m.

en:
Resource Title: S2 2014
    Size: 726971 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/7e8c6dac-80cf-49d7-bd85-2a61d3336e6f/resource/25ce04fb-452c-439e-b1fe-8ef2ccb1ea4e/download/s2-2014.zip
    Description: Eddy-covariance measurement with an ultrasonic anemometer (CSAT3, Campbell Scientific, Inc.) in 2.6 m.

en:
Resource Title: S2 2016
    Size: 571682 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/7e8c6dac-80cf-49d7-bd85-2a61d3336e6f/resource/e78a7861-5a9d-458f-b66d-d180292f6840/download/s2-2016.zip
    Description: Eddy-covariance measurement with an ultrasonic anemometer (CSAT3, Campbell Scientific Inc.) in 3.2 m on a daily basis.

en:
Resource Title: S1 2014
    Size: 725025 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/7e8c6dac-80cf-49d7-bd85-2a61d3336e6f/resource/486e31a9-78e2-4736-9cad-a40c0958662c/download/s1-2014.zip
    Description: Eddy-covariance measurement with an ultrasonic anemometer (CSAT3, Campbell Scientific, Inc.) in 2.6 m.

en:
Resource Title: S3 2015
    Size: 765677 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/7e8c6dac-80cf-49d7-bd85-2a61d3336e6f/resource/9e551281-5120-4041-860e-8d2fc911c9dd/download/s3-2015.zip
    Description: Eddy-covariance measurement with an ultrasonic anemometer (CSAT3, Campbell Scientific, Inc.) in 2.2 m.

en:
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    Size: 764023 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/7e8c6dac-80cf-49d7-bd85-2a61d3336e6f/resource/3e7cd0af-60cb-4026-8e8f-7c0736c45f5b/download/s4-2015.zip
    Description: Eddy-covariance measurement with an ultrasonic anemometer (CSAT3, Campbell Scientific, Inc.) in 2.2 m.

en:
Resource Title: S5 2014
    Size: 212111 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/7e8c6dac-80cf-49d7-bd85-2a61d3336e6f/resource/fb937402-fc94-4121-9d55-809664005628/download/s5-2014.zip
    Description: Eddy-covariance measurement with an ultrasonic anemometer (DA-600, Kaijo-Denki) in 0.3 m on a daily basis.

en:
Resource Title: S1 2015
    Size: 737846 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/7e8c6dac-80cf-49d7-bd85-2a61d3336e6f/resource/68c609d2-beb3-45b7-bbd4-cdf33de5f6e1/download/s1-2015.zip
    Description: Eddy-covariance measurement with an ultrasonic anemometer (R.M. Young Company) in 3.3 m.

en:
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    Format: application/zip
    URL: https://www.envidat.ch/dataset/7e8c6dac-80cf-49d7-bd85-2a61d3336e6f/resource/43081c3a-5d6c-4f7c-9259-b221e82f9b61/download/s5-2016.zip
    Description: Eddy-covariance measurement with an ultrasonic anemometer (DA-600, Kaijo-Denki) in 0.3 m on a daily basis.

en:
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    URL: https://www.envidat.ch/dataset/7e8c6dac-80cf-49d7-bd85-2a61d3336e6f/resource/60ca7742-4ab9-49f6-9318-3dac0c4ae4bd/download/s4-2014.zip
    Description: Eddy-covariance measurement with an ultrasonic anemometer (R.M. Young Company) in 0.7 m.

en:
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    Format: application/zip
    URL: https://www.envidat.ch/dataset/7e8c6dac-80cf-49d7-bd85-2a61d3336e6f/resource/0425d29f-b2cd-4092-afe6-00ca6fbd2303/download/s3-2016.zip
    Description: Eddy-covariance measurement with an ultrasonic anemometer (CSAT3, Campbell Scientific Inc.) in 1.7 m on a daily basis.

en:
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    Format: application/zip
    URL: https://www.envidat.ch/dataset/7e8c6dac-80cf-49d7-bd85-2a61d3336e6f/resource/b5c85840-bf9f-4605-b4c7-9d05b00f2cdc/download/s1-2016.zip
    Description: Eddy-covariance measurement with an ultrasonic anemometer (R.M. Young Company) in 3.5 m.

en:
Resource Title: Output explanation
    Size: 17405 bytes
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format: XLS

en:
Resource Title: S2 2015
    Size: 735270 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/7e8c6dac-80cf-49d7-bd85-2a61d3336e6f/resource/81cb8412-b9bf-4ac8-a65b-7fdd0c597087/download/s2-2015.zip
    Description: Eddy-covariance measurement with an ultrasonic anemometer (R.M. Young Company) in 3.3 m.

en:
Resource Title: Gletschboden setup
    Size: 1723556 bytes
    Format: image/png
    URL: https://www.envidat.ch/dataset/7e8c6dac-80cf-49d7-bd85-2a61d3336e6f/resource/622ba326-7828-4f83-868c-94ad784c1841/download/gletschboden.png
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format: PNG

media_type: image/png

en:
Resource Title: S5 2015
    Size: 271399 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/7e8c6dac-80cf-49d7-bd85-2a61d3336e6f/resource/d9037751-fbdf-438c-a1b0-03aa3301c065/download/s5-2015.zip
    Description: Eddy-covariance measurement with an ultrasonic anemometer (DA-600, Kaijo-Denki) in 0.3 m on a daily basis.

dischmex

display_name: dischmex

eddy-covariance-measurements

display_name: eddy-covariance-measurements

patchy-snow-covers

display_name: patchy-snow-covers

snow-patch

display_name: snow-patch

turbulent-sensible-heat-fluxes

display_name: turbulent-sensible-heat-fluxes


en:
Dataset of meteorological and snowpack measurements from the automatic weather station at Weissfluhjoch, Davos, Switzerland, suitable for driving snowpack models. The dataset contains standard meteorological measurements, and additionally snowpack runoff data from a snow lysimeter. Where possible, data is quality checked and missing data are replaced from backup sensors from the measurement site itself, or (in only a few cases) from the MeteoSwiss weather station at 470 m distance and 150 m above the measurement site.
Publication
Wever, N., Schmid, L., Heilig, A., Eisen, O., Fierz, C., and Lehning, M. Verification of the multi-layer SNOWPACK model with different water transport schemes. 2015. The Cryosphere. Volume 9. 2271-2293. http://dx.doi.org/10.5194/tc-9-2271-2015.

en: WFJ_MOD: Meteorological and snowpack measurements from Weissfluhjoch, Davos, Switzerland

en: wind-direction precipitation-amount humidity snow-ice-temperature shortwave-radiation longwave-radiation air-temperature snow-depth wind-speed

envidat

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

en: EnviDat: the Environmental Data Portal

envi

en: Environment

en:
Resource Title: Version 6
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    URL: https://os.zhdk.cloud.switch.ch/envicloud/slf/snow_and_permafrost/wfj_mod/WFJ_optimaldataset_v6.smet
    Description: Deprecated version.

Release notes:

- Missing ISWR for 2009-09-30 and 2010-04-30 has been replaced by data from WFJ Gipfel

This dataset is the basis for the Weissfluhjoch dataset in ESM-SnowMIP (doi: http://dx.doi.org/10.16904/16).

en:
Resource Title: Version 3
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    Description: Deprecated version. Release notes:

Bug fix: in version 2, the undercatch correction was not applied correctly

Bug fix: in version 2, snow lysimeter data was missing for extended periods of time

Update: dataset extended to 2016-01-02T00:30

Update: refreshing data originating from MeteoSwiss (particularly precipitation)

en:
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    URL: https://os.zhdk.cloud.switch.ch/envicloud/slf/snow_and_permafrost/wfj_mod/WFJ_optimaldataset_v4.smet
    Description: Deprecated version. Release notes:

Update: dataset extended to 2016-09-02T00:30

Update: refreshing data originating from MeteoSwiss (particularly precipitation)

en:
Resource Title: SNOWPACK ini file (old syntax)
    Size: 2223 bytes
    Format: text/x-ini
    URL: https://www.envidat.ch/dataset/38112bee-f865-4b29-ba19-47a99ba78833/resource/e51b83ae-99a6-42f0-add4-8da9590c6573/download/iowfjref.ini
    Description: This ini-file can be used to run SNOWPACK simulations with the WFJ data set, using version 3.4.0 or higher.

en:
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    URL: https://os.zhdk.cloud.switch.ch/envicloud/slf/snow_and_permafrost/wfj_mod/WFJ_optimaldataset_v5.smet
    Description: Deprecated version. Release notes:

Update: using the incoming and outgoing short- and longwave radiation data from the new processing chain from 2010 onwards, filling also data gaps in pre-2010 data.

Update: dataset extended to 2016-10-04T00:30

Update: refreshing data originating from MeteoSwiss (particularly precipitation)

en:
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    URL: https://os.zhdk.cloud.switch.ch/envicloud/slf/snow_and_permafrost/wfj_mod/WFJ_optimaldataset.smet
    Description: Deprecated version. Release notes:

First release of dataset.

en:
Resource Title: All versions
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    Format: No Info
    URL: https://envicloud.wsl.ch/#/?prefix=slf/snow_and_permafrost/wfj_mod/
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en:
Resource Title: Version 7 (current)
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    URL: https://www.envidat.ch/dataset/38112bee-f865-4b29-ba19-47a99ba78833/resource/3074d1dc-6083-4025-9ac4-484cfa88658b/download/wfj_optimaldataset_v7.smet
    Description: Release notes:

Bug fix: in previous versions, snow lysimeter data from September 2010 onwards was erroneously reported for UTC+2, instead of UTC+1 (i.e., reported one hour later than should have been).

Update: dataset extended to 2017-07-11T00:30.

en:
Resource Title: SNOWPACK ini file (new syntax)
    Size: 2490 bytes
    Format: text/x-ini
    URL: https://www.envidat.ch/dataset/38112bee-f865-4b29-ba19-47a99ba78833/resource/8d201858-fba9-449c-b41b-4e49624fa6cc/download/iowfjref.ini
    Description: This ini-file can be used to run SNOWPACK simulations with the WFJ data set, using the new MeteoIO Filter, Generator and Interpolation syntax.

en:
Resource Title: SNOWPACK sno file
    Size: 1095 bytes
    Format: .sno
    URL: https://www.envidat.ch/dataset/38112bee-f865-4b29-ba19-47a99ba78833/resource/ec0609f1-42fa-4a20-945e-6809bb15a8a0/download/wfj2.sno
    Description: This sno-file can be used to run SNOWPACK simulations with the WFJ data set, using version 3.4.0 or higher.

en:
Resource Title: Version 2
    Size: 0
    Format: application/x-smet
    URL: https://os.zhdk.cloud.switch.ch/envicloud/slf/snow_and_permafrost/wfj_mod/WFJ_optimaldataset_v2.smet
    Description: Deprecated version. Release notes:

Bug fix: in v1, incoming radiation components were taken from WFJ_Gipfel station, instead of WFJ Versuchsfeld.

en:
Resource Title: Undercatch correction
    Size: 59121 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/38112bee-f865-4b29-ba19-47a99ba78833/resource/022a5232-e9a6-4972-a59a-f1aedc2697d3/download/undercatch.pdf
    Description: This document describes how the undercatch correction for the Weissfluhjoch measurement site was determined.

air-temperature

display_name: air-temperature

humidity

display_name: humidity

longwave-radiation

display_name: longwave-radiation

precipitation-amount

display_name: precipitation-amount

shortwave-radiation

display_name: shortwave-radiation

snow-ice-temperature

display_name: snow-ice-temperature

wind-direction

display_name: wind-direction

wind-speed

display_name: wind-speed


en:
The data correspond to the experiments presented and discussed in a paper regarding the interaction between turbulent wind fluctuations and snow saltation mass-fluxes (Paterna, 2016). Each of the nine data files corresponds to a different experiment presented in the paper and conducted in the winter 2014/2015 in the WSL/SLF cold wind tunnel in Davos. For each file the five columns indicate the time from the beginning of the experiment, the streamwise (u’) and the vertical (w’) wind velocity fluctuations, the streamwise (qx) and the vertical (qz) snow mass-flux components. From these time-series the scales of the snow saltation and of the turbulent flow are obtained with respect to the eddy-cycles and snow saltation cycles. From spectral analysis of the time-series a decoupling of the snow saltation from the turbulence forcing reveals two regimes of interaction: a turbulence-dependent regime occurring with weak saltation, and a turbulence-independent regime with strong saltation. Further details can be found at the link below.
Publication http://onlinelibrary.wiley.com/doi/10.1002/2016GL068171/abstract

en: Wind tunnel measurement data of drifting snow and turbulent wind fluctuations

en: boundary-layer-winds vertical-wind-motion snow-cover snow-depth saltation

boundary-layer-winds

display_name: boundary-layer-winds

saltation

display_name: saltation

snow-cover

display_name: snow-cover

snow-depth

display_name: snow-depth

vertical-wind-motion

display_name: vertical-wind-motion


en: To study the performance of mature Scots pine (_Pinus sylvestris_ L.) under chronic drought conditions in comparison to their immediate physiological response to drought release, a controlled long-term and large-scale irrigation experiment has been set up in 2003. The experiment is located in a xeric mature Scots pine forest in the Pfynwald (46° 18' N, 7° 36' E, 615 m a.s.l.) in one of the driest inner-Alpine valleys of the European Alps, the Valais (mean annual temperature: 9.2°C, annual precipitation sum: 657 mm, both 1961-1990). Tree age is on average 100 years, the top height is 10.8 m and the stand density is 730 stems ha-1 with a basal area of 27.3 m2 ha-1. The forest is described as _Erico Pinetum sylvestris_ and the soil is a shallow pararendzina characterized by low water retention. The experimental site (1.2 ha; 800 trees) is split up into eight plots of 1'000 m2 each. During April-October, irrigation is applied on four randomly selected plots with sprinklers of 1 m height at night using water from an adjacent water channel. The amount of irrigation corresponds to a supplementary rainfall of 700 mm year-1. Trees in the other four plots grow under naturally dry conditions. Soil moisture has been monitored since the beginning of the project at 3 soil depths (10, 20 and 60 cm). The crown condition of each tree is being assessed each year since 2003. Tree measurement data such as diameter at breast height, tree height, and social status were assessed in 2002, 2009 and 2014. The duration of the irrigation experiment is planned for 20 years.

en: Tree measurements 2002-2016 from the long-term irrigation experiment Pfynwald, Switzerland

en: swiss-forest-lab crown-condition tree-species lwf irrigation drought tree forest dbh scots-pine diameter-at-breast-height

envidat

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

en: EnviDat: the Environmental Data Portal

en:
Resource Title: Site photo 2
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    Description:

format: jpeg

en:
Resource Title: Shapefile	of measurement location
    Size: 0
    Format: No Info
    URL: https://map.geo.admin.ch/?topic=swisstopo&X=127951&Y=613350&zoom=11&lang=de&bgLay er=ch.swisstopo.pixelkarte-farbe&crosshair=marker
    Description:

en:
Resource Title: Swiss Forest Health Inventory
    Size: 1 bytes
    Format: text/html
    URL: https://www.wsl.ch/en/forest/forest-development-and-monitoring/sanasilva-forest-health-inventory.html
    Description:

format: HTML

media_type: text/html

en:
Resource Title: Site photo 1
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    Description:

en:
Resource Title: Long-term Irrigation	Experiment Pfynwald homepage
    Size: 1 bytes
    Format: text/html
    URL: https://www.wsl.ch/en/about-wsl/instrumented-field-sites-and-laboratories/experimental-sites-in-forests/pfynwald.html
    Description:

en:
Resource Title: Site photo 3
    Size: 8186031 bytes
    Format: image/jpeg
    URL: https://www.envidat.ch/dataset/0e18a914-f2e4-47df-a86c-a44a1b0055e4/resource/e3c46133-0b7c-4d9c-a3d0-ba0e91e663b5/download/20150709pfyn218.jpg
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en:
Resource Title: Dataset
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    Description:

crown-condition

display_name: crown-condition

dbh

display_name: dbh

diameter-at-breast-height

display_name: diameter-at-breast-height

drought

display_name: drought

forest

display_name: forest

irrigation

display_name: irrigation

lwf

display_name: lwf

scots-pine

display_name: scots-pine

swiss-forest-lab

display_name: swiss-forest-lab

tree

display_name: tree

tree-species

display_name: tree-species


en:
Important
This EnviDat entry is outdated. The most recent, usable version of the data can be found under the new EnviDat entry "Long-term afforestation experiment at the Alpine treeline site Stillberg, Switzerland." The entry can be found under this link -https://www.envidat.ch/dataset/afforestation-stillberg-  and with this DOI 10.16904/envidat.397.

en: Long-term treeline research dataset at Stillberg, Davos

en: mountain-forest stillberg long-term-experiment afforestation treeline

envi

en: Environment

en:
Resource Title: Site photo
    Size: 32941 bytes
    Format: image/jpeg
    URL: https://www.envidat.ch/dataset/b72cc62e-cf31-4f4c-b89e-eba90f27ac50/resource/ca3ffbc8-b692-4f9c-ab49-f1c09fdb4e69/download/stillpic.jpeg
    Description: This site photo is outdated and has been replaced with an updated version (see description).

en:
Resource Title: Dataset V1
    Size: 18459904 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/b72cc62e-cf31-4f4c-b89e-eba90f27ac50/resource/f488643a-8f64-4427-8b08-a947c47a1302/download/stillberggis.zip
    Description: This dataset is outdated and has been replaced with an updated version (see description).

en:
Resource Title: Documentation
    Size: 57344 bytes
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    URL: https://www.envidat.ch/dataset/b72cc62e-cf31-4f4c-b89e-eba90f27ac50/resource/545c2ff6-8fdb-4ea0-85a8-49f49d877022/download/documentationstillberg1520160325.doc
    Description: This data documentation is outdated and has been replaced with an updated version (see description).

format: msword

afforestation

display_name: afforestation

long-term-experiment

display_name: long-term-experiment

mountain-forest

display_name: mountain-forest

stillberg

display_name: stillberg

treeline

display_name: treeline


en:
During the last 45 years, about 100 people lost their lives in avalanches in the European Alps each year. Avalanche fatalities in settlements and on transportation corridors have considerably decreased since the 1970s. In contrast, the number of avalanche fatalities during recreational activities away from avalanche-secured terrain doubled between the 1960s and 1980s and has remained relatively stable since, despite a continuing strong increase in winter backcountry recreational activities.
Data complementing Figure 2 in:
_"Avalanche fatalities in the European Alps: long-term trends and statistics"_, by Techel, F., Jarry, F., Kronthaler, G., Mitterer, S., Nairz, P., Pavšek, M., Valt, M., and Darms, G.
Data description:
please refer to section 2 (Data and Methods) in the mentioned publication

en: Avalanche fatalities in the European Alps (1969/1970 - 2014/2015)

en: avalanche-fatalities avalanche-statistics avalanche-accident-statistics avalanche-accident long-term-trends

avalanche-accident

display_name: avalanche-accident

avalanche-accident-statistics

display_name: avalanche-accident-statistics

avalanche-fatalities

display_name: avalanche-fatalities

avalanche-statistics

display_name: avalanche-statistics

long-term-trends

display_name: long-term-trends


en:
This snow depth map was generated 14 January 2015, close to peak of winter accumulation, applying Unmanned Aerial System digital surface models with a spatial resolution of 10 cm. The covered area is 285'000 m2 at the top of Brämabüel, 2490 m a.s.l. covering all expositions. Coordinate system: CH1903LV03.
A detailed description is given here:
Bühler, Y., Adams, M. S., Bösch, R., and Stoffel, A.: Mapping snow depth in alpine terrain with unmanned aerial systems (UASs): potential and limitations, The Cryosphere, 10, 1075-1088, 10.5194/tc-10-1075-2016, 2016.
Abstract:
Detailed information on the spatial and temporal distribution, and variability of snow depth (HS) is a crucial input for numerous applications in hydrology, climatology, ecology and avalanche research. Nowadays, snow depth distribution is usually estimated by combining point measurements from weather stations or observers in the field with spatial interpolation algorithms. However, even a dense measurement network is not able to capture the large spatial variability of snow depth in alpine terrain.
Remote sensing methods, such as laser scanning or digital photogrammetry, have recently been successfully applied to map snow depth variability at local and regional scales. However, such data acquisition is costly, if manned airplanes are involved. The effectiveness of ground-based measurements on the other hand, is often hindered by occlusions, due to the complex terrain or acute viewing angles. In this paper, we investigate the application of unmanned aerial systems (UAS), in combination with structure-from-motion photogrammetry, to map snow depth distribution. Such systems have the advantage that they are comparatively cost-effective and can be applied very flexibly to cover also otherwise inaccessible terrain. In this study we map snow depth at two different locations: a) a sheltered location at the bottom of the Flüela valley (1900 m a.s.l.) and b) an exposed location (2500 m a.s.l.) on a peak in the ski resort Jakobshorn, both in the vicinity of Davos, Switzerland. At the first test site, we monitor the ablation on three different dates. We validate the photogrammetric snow depth maps using simultaneously acquired manual snow depth measurements. The resulting snow depth values have a root mean square error (RMSE) better than 0.07 to 0.15 m on meadows and rocks and a RMSE better than 0.30 m on sections covered by bushes or tall grass. This new measurement technology opens the door for efficient, flexible, repeatable and cost effective snow depth monitoring for various applications, investigating the worlds cryosphere.

en: UAS based snow depth maps Brämabüel, Davos, CH

en: swe remote-sensing snow-depth snow uas

envidat

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

en: EnviDat: the Environmental Data Portal

en:
Resource Title: HS map Brämabül, 14. April 2015
    Size: 163529181 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/84db9938-9af5-4ae1-8e30-cb45c61fc274/resource/22d008e7-8312-4676-8792-81ed927e4951/download/snowdepth_20150414_10cm_reffromsummer_setnull_final.tif
    Description: 10 cm resolution
15 cm accuracy

format: TIFF

media_type: image/tiff

en:
Resource Title: .tfw file
    Size: 89 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/84db9938-9af5-4ae1-8e30-cb45c61fc274/resource/95509c9f-8a0a-4f7f-a46e-9db9a9c795fa/download/snowdepth_20150414_10cm_reffromsummer_setnull_final.tfw
    Description: coordinates for the .tif raster

remote-sensing

display_name: remote-sensing

snow

display_name: snow

snow-depth

display_name: snow-depth

swe

display_name: swe

uas

display_name: uas


en: Dataset of manual bi-weekly snow profiles from Weissfluhjoch, Davos, Switzerland. Typical snow profile measurements and observations are included (temperature, density, grain size, grain type, hardness, wetness), following the guidelines of the The International Classification for Seasonal Snow on the Ground (ICSSG) [Fierz, C., Armstrong, R.L., Durand, Y., Etchevers, P., Greene, E., McClung, D.M., Nishimura, K., Satyawali, P.K. and Sokratov, S.A. 2009. The International Classification for Seasonal Snow on the Ground. IHP-VII Technical Documents in Hydrology N°83, IACS Contribution N°1, UNESCO-IHP, Paris].

en: Manual bi-weekly snow profiles from Weissfluhjoch, Davos, Switzerland

en: weisfluhjoch snow-density snow-stratigraphy snow-ice-temperature snow-water-equivalent

en:
Resource Title: README
    Size: 5514 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/0b294122-015c-46bf-b5c5-cc6d0a6f67c1/resource/8b7b0710-a781-41c4-9345-b31a5e93982b/download/readme.txt
    Description: README file giving use metadata.

en:
Resource Title: WFJ Snow Profiles 1999-2014
    Size: 237845 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/0b294122-015c-46bf-b5c5-cc6d0a6f67c1/resource/f64d8a9f-36ea-40f6-9874-bc9071050d0a/download/wfjsnowprofiles19992014.zip
    Description: Biweekly manual snow profiles from Weissfluhjoch, Davos, Switzerland.
Version: 2015-09-14T16:25

snow-density

display_name: snow-density

snow-ice-temperature

display_name: snow-ice-temperature

snow-stratigraphy

display_name: snow-stratigraphy

snow-water-equivalent

display_name: snow-water-equivalent

weisfluhjoch

display_name: weisfluhjoch


en:
A landslide testsite dataset related to pore water pressure perturbations on the stability of unsaturated silty sand slopes leading to the initiation and propagation of the shear deformations and eventual rapid mass movements. This project was initiated and led by the Institute of Geotechnical Engineering (IGT) of the Swiss Federal Institute of Technology (ETH Zurich) and was incorporated in a Swiss national (TRAMM) and a European Union (SafeLand) multidisciplinary research project. Field site: The experimental slope is 7.5 m wide by 35 m long, located in the Swiss lowlands on an east facing slope over-looking the river Rhine, at an altitude of ~ 350 masl. Originally there were forestry covertures of circa 80%, heights of 5-20 m. Shrubs up to 1-5 m high and a free herb layer covered ~ 50% of the surface. The average gradient was determined to be from 38° to 43° with a slightly concave surface. The underlying rock consists mainly of Molasse, which is formed by alternate layers of sea deposits under the Tethys Sea (Seawater Molasse) and land deposits (Freshwater Molasse). Several augured samples, as well as an outcrop of the bedrock about 20 m above the selected field, revealed horizontal layering of fine grained sand- and marlstone at the test site. The sandstone was later proven to be highly permeable and fissured. Grain-size distributions were determined and the soil was classified as medium-low plasticity silty sand. Site instrumentation:Measurements of soil suction, groundwater level, soil volumetric water content, rain intensity and soil temperature were taken and combined with geophysical monitoring using Electrical Resistance Tomography (ERT) and investigations into subsurface flow by means of tracer experiments. Deformations were monitored during the experiment, both on the surface via photogrammetrical methods and within the soil mass, using a flexible probe equipped with strain gauges at different points and two axis inclinometers on the top and acoustic sensors. Instruments were installed mainly in three clusters at depths of 15, 30, 60, 90, 120, and 150 cm below the ground surface over the slope, including jet-fill tensiometers, TDRs, Decagon TDRs, piezometers, soil temperature sensors, deformation probes, earth pressure cells, acoustic sensors and rain gauges. A ring-net barrier (provided by Geobrugg AG) was set up at the foot of the slope to protect the road. Experiments: A sprinkling experiment was carried out in September 2008 to investigate the hydrological and mechanical response of the slope (Experiment 1), followed by a second one to trigger a landslide in March 2009 (Experiment 2).
Publications
1. Lehmann, P., F. Gambazzi, B. Suski, L. Baron, A. Askarinejad, S. M. Springman, K. Holliger, and D. Or (2013), Evolution of soil wetting patterns preceding a hydrologically induced landslide inferred from electrical resistivity survey and point measurements of volumetric water content and pore water pressure, Water Resour. Res., 49, 7992–8004, doi:[10.1002/2013WR014560](http://dx.doi.org/10.1002/2013WR014560).
2. Springman, S. M., Kienzler, P., Casini, F., & Askarinejad, A. (2009). Landslide triggering experiment in a steep forested slope in Switzerland. In 17th International Conference of Soil Mechanics and Geotechnical Engineering, Alexandria, Egypt (pp. 1698-1701). doi: [10.3233/978-1-60750-031-5-1698](http://dx.doi.org/10.3233/978-1-60750-031-5-1698)

en: TRAMM project Ruedlingen experimental landslide dataset, Switzerland

en: pressure-perturbations cces pore-water landslide-testsite tramm landslides

envi

en: Environment

cces

display_name: cces

landslide-testsite

display_name: landslide-testsite

landslides

display_name: landslides

pore-water

display_name: pore-water

pressure-perturbations

display_name: pressure-perturbations

tramm

display_name: tramm


en:
Rufiberg is a pre-alpine meadow site in Switzerland where shallow landslides have been observed after past intense rain storms. In order to assess the triggering mechanisms of these landslides, a comprehensive investigation was conducted within the project TRAMM from Nov 2009 to Oct 2012. It included meteorological observations, soil moisture measurements, bedrock groundwater measurements. The Rufiberg is located at the NW side of the Gnipen to the north of the village Arth-Goldau in the Canton of Schwyz. In the summer months, the site is used for pasturing. Usually, from December to March a snow cover is present at the Rufiberg. The site is at an altitude between 1080 – 1180 m asl, is ENE oriented, and has an average slope of 30 -35°. The Subalpine Molasse in the region is inclined with 30 - 35° to SE. In the area of the field site, beds of conglomerate with several m of thickness alter with beds of sandstone and marlstone. A ca. 2 – 5 m thick eluvium/colluvium layer composed of silty and sandy clay covers the bedrock. This site has been chosen because on one hand, during heavy rainfall events, e.g. autumn 2005, numerous landslides occur in the region of the Gnipen and the Rufiberg. On the other hand, the Rufiberg is very appropriate for experiments due its location away from infrastructures and due to its accessibility. The goal of the investigation was to understand the hydrology and hydrogeology of the slope with regard to shallow landslides.
More information: Brönnimann, C., Stähli, M., Schneider, P., Seward, L. and Springman, S.M. 2013. Bedrock exfiltration as a triggering mechanism for shallow landslides. Water Resources Research, 49 (9): 5155–5167. DOI: 10.1002/wrcr.20386.

en: TRAMM project - experimental hydrological and hydrogeological dataset of a landslide prone hillslope. Rufiberg, Switzerland

en: meadow soil-moisture-water-content hydrology landslides water-table

en:
Resource Title: Data Soil water content TDR.xlsm
    Size: 7866407 bytes
    Format: application/vnd.ms-excel.sheet.macroEnabled.12
    URL: https://www.envidat.ch/dataset/5333838f-5da6-4574-8d28-ce1794c19631/resource/fd31a45e-e5d0-476e-9a45-611f4d572d93/download/data-soil-water-content-tdr.xlsm
    Description: Four test pits were excavated in summer 2010 along the slope to install vertical profiles of Time Domain Reflectometry sensors [Topp et al., 1980] to measure soil water content at depths of 0.25 m, 0.7 m, 1.1 m and 1.5 m. The 15 cm long TDR rods were inserted horizontally into the vertical walls of the pits, and the four pits were carefully refilled with the excavated soil. The water content was recorded from summer 2010 to fall 2011 at 10-minute time intervals using a Campbell TDR 100 system.

en:
Resource Title: Data Groundwater level in Bedrock.xlsx
    Size: 939397 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/5333838f-5da6-4574-8d28-ce1794c19631/resource/0e09242b-0222-4b90-b247-4fa2c34bb8ca/download/data-groundwater-level-in-bedrock.xlsx
    Description: We drilled six boreholes in two clusters. The boreholes reached a depth between 2 and 9 m below the ground surface. The lower half of boreholes BH1 and BH6 were cored with a 9 cm-diameter rotational diamond drilling head. The other boreholes were drilled destructively with an 11 cm-diameter Mitsubishi hammer system. Boreholes BH1, BH2 and BH5 were equipped with open standpipe piezometers, whereas BH3, BH4 and BH6 were equipped with a special piezometer system composed of an enclosed measuring cell at the bottom of a 1 inch-PVC tube. The free groundwater level in the PVC tube is measured in the standpipe piezometer, but it doesn’t necessarily represent the water table in the soil layer because the pressure sensor is located in the sealed lower part of the piezometer in the enclosed measuring cell and thus is not in contact with the air. This system allows the hydraulic pressure of lithologies with low permeability to be measured directly. Two piezometers were installed in BH6 at different depths. The PVC tubes were slotted at the bottom for 0.5, 1 or 2 meters and the boreholes were sealed carefully with clay pellets above this filter section to avoid by-pass and infiltration from the surface. DCX-22 pressure sensors from Keller AG Winterthur, with integrated data loggers, were installed in each piezometer to measure the relative hydraulic pressure at a 30 minute-intervals from November 2010 to November 2011. The data were corrected for in-situ air-pressure fluctuations.

en:
Resource Title: Data Groundwater level in Soil.xlsx
    Size: 5593516 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/5333838f-5da6-4574-8d28-ce1794c19631/resource/720b044d-3ee5-4104-ba45-4b5b8ee7bf3e/download/data-groundwater-level-in-soil.xlsx
    Description:

en:
Resource Title: Data Lateral subsurface water flow.xlsm
    Size: 2033894 bytes
    Format: application/vnd.ms-excel.sheet.macroEnabled.12
    URL: https://www.envidat.ch/dataset/5333838f-5da6-4574-8d28-ce1794c19631/resource/251578d0-3df2-44ed-9090-613a678bdbf8/download/data-lateral-subsurface-water-flow.xlsm
    Description:

hydrology

display_name: hydrology

meadow

display_name: meadow

soil-moisture-water-content

display_name: soil-moisture-water-content

water-table

display_name: water-table


envidat-supports-open-science

en:
The article "EnviDat Supports Open Science" originally appeared in WSLintern No. 3 (2020), page 14-15 and it is republished here with permission from the WSLintern editorial team. It contains guidelines for WSL scientists about the main issues behind Open Science and how to pragmatically approach the complexities of doing Open Science with EnviDat’s support.
License: This article is released by WSL and the EnviDat team to the public domain under a Creative Commons 4.0 CC0 "No Rights Reserved" international license. You can reuse the information contained herein in any way you want, for any purposes and without restrictions.

en: EnviDat Supports Open Science

en: juypter-notebooks wsl research-data-management envidat open-science

envidat

en: EnviDat is the WSL data portal providing unified and managed access to environmental monitoring and research data. The portal has the capability to host and publish data sets. Through the sharing of unique and high-value data sets worldwide, EnviDat fosters research and contributes to advancing environmental science.

en: EnviDat: the Environmental Data Portal

title_for_slug: envidat-supports-open-science

display_name: envidat

juypter-notebooks

display_name: juypter-notebooks

open-science

display_name: open-science

research-data-management

display_name: research-data-management

wsl

display_name: wsl