en:
Compilation of normalized crack-propagation speeds (expressed as a fraction of the slab shear-wave speed).
The dataset contains crack-propagation speeds from DEM simulations (79 flat and 6 tilted; Bobillier et al., 2024), MPM simulations (48 flat and 191 tilted; Trottet et al., 2022), and field measurements: PSTs (222 data points, including 192 from low-angle terrain - 30°; van Herwijnen et al., 2016) and avalanche-video analyses (6 cross-slope and 5 down-slope speeds; Trottet et al., 2022).
The dataset also includes Python scripts that generate the relative-frequency distribution of the compiled, normalized crack-propagation speeds.
Bobillier, G., Bergfeld, B., Dual, J., Gaume, J., van Herwijnen, A., 55 and Schweizer, J.: Numerical investigation of crack propagation regimes in snow fracture experiments, https://doi.org/10.1007/s10035-024-01423-5 2024
Trottet, B., Simenhois, R., Bobillier, G., Bergfeld, B., van Herwijnen, A., Jiang, C. F. F., and Gaume, J.: Transi- 55 tion from sub-Rayleigh anticrack to supershear crack propagation in snow avalanches, Nat. Phys., 18, 1094–1098, https://doi.org/10.1038/s41567-022-01662-4, 2022.
van Herwijnen, A., Gaume, J., Bair, E. H., Reuter, B., Birkeland, K. W., and Schweizer, J.: Estimating the effective elastic modulus and specific fracture energy of snowpack layers from field experiments, J. Glaciol., 62, 997–1007, https://doi.org/10.1017/jog.2016.90, 2016a.

en: weak-layer dry-snow-avalanche crack-propagation field-data crack-speed numerical-simulations

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: Compilation of normalized  crack propagation speeds

envi

en: Environment

en:
Resource Title: DEM_dataNormalizedByc_flat_data.txt
    Size: 2055 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/8a7f5d94-91af-463e-aee0-acbfada0b3ec/resource/458d8261-9b42-4f10-9c30-3979046a0e3a/download/dem_datanormalizedbyc_flat_data.txt
    Description: DEM data flat terrain

en:
Resource Title: PST_dataNormalizedByc_slopeHigher30deg_data.txt
    Size: 754 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/8a7f5d94-91af-463e-aee0-acbfada0b3ec/resource/997b18ab-9e57-469a-b72e-8da079e2bc4f/download/pst_datanormalizedbyc_slopehigher30deg_data.txt
    Description: Field data PST >30deg

en:
Resource Title: MPM_dataNormalizedByc_slope_data.txt
    Size: 4966 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/8a7f5d94-91af-463e-aee0-acbfada0b3ec/resource/5f43f7ec-28d5-4b0d-b308-78ed4c3084e7/download/mpm_datanormalizedbyc_slope_data.txt
    Description: MPM data slope terrain

en:
Resource Title: NHESS_Fig2.py
    Size: 5481 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/8a7f5d94-91af-463e-aee0-acbfada0b3ec/resource/270844a2-5218-43a6-95f4-7b81eccd6e3f/download/nhess_fig2.py
    Description: Python scripts that generate the relative-frequency distribution of the compiled, normalized crack-propagation speeds.

en:
Resource Title: PST_dataNormalizedByc_slopeLess30deg_data.txt
    Size: 4992 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/8a7f5d94-91af-463e-aee0-acbfada0b3ec/resource/9c7c9f4f-74c1-458e-a01d-c0cdc361fe0b/download/pst_datanormalizedbyc_slopeless30deg_data.txt
    Description: Field data PST <30deg

en:
Resource Title: Video_dataNormalizedByc_flat_data.txt
    Size: 156 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/8a7f5d94-91af-463e-aee0-acbfada0b3ec/resource/abf2a891-3382-4ca2-82cd-90c30ffb898d/download/video_datanormalizedbyc_flat_data.txt
    Description: Video analyze data cross slope

en:
Resource Title: Video_dataNormalizedByc_slope_data.txt
    Size: 130 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/8a7f5d94-91af-463e-aee0-acbfada0b3ec/resource/5aff5cf6-1c1f-4186-bf56-f1e71348016b/download/video_datanormalizedbyc_slope_data.txt
    Description: Video analyze data up-slope

en:
Resource Title: MPM_dataNormalizedByc_flat_data.txt
    Size: 1248 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/8a7f5d94-91af-463e-aee0-acbfada0b3ec/resource/9331f966-5264-425d-9e37-155b0b69fceb/download/mpm_datanormalizedbyc_flat_data.txt
    Description: MPM data flat terrain

en:
Resource Title: DEM_dataNormalizedByc_slope_data.txt
    Size: 156 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/8a7f5d94-91af-463e-aee0-acbfada0b3ec/resource/78b26ac4-e690-4371-acc1-42611d937d78/download/dem_datanormalizedbyc_slope_data.txt
    Description: DAM data slope terrain

en:
Resource Title: NHESS_Fig2.py
    Size: 5481 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/8a7f5d94-91af-463e-aee0-acbfada0b3ec/resource/6821e603-5e6c-43b4-ab07-b435fd406321/download/nhess_fig2.py
    Description:

crack-propagation

display_name: crack-propagation

crack-speed

display_name: crack-speed

dry-snow-avalanche

display_name: dry-snow-avalanche

numerical-simulations

display_name: numerical-simulations

weak-layer

display_name: weak-layer


$oid: OBSOLETE

en:
Monitoring of vertebrates of the lower Magdalena river through eDNA metabarcoding
The Magdalena River basin harbors a large biodiversity of vertebrates, with numerous endemic species, many of which are threatened. Here, we used environmental DNA (eDNA) metabarcoding, with two primer sets targeting different regions of the mitochondrial DNA 12S ribosomal RNA gene, to detect vertebrate diversity in the Magdalena River. We detected a total of 159 vertebrate taxa, not only aquatic but also terrestrial, arboreal, and aerial. The diversity of these vertebrates increases in relation to the proximity to the river mouth with a change in the composition of the assemblage of aquatic vertebrates detected. We conclude that eDNA metabarcoding allows characterizing vertebrate assemblages in large rivers, assessing conservation status, and elucidating biodiversity patterns with minimal ecosystem disturbance. Samples were taken at the sides of the river or in the center using a boat. At each station, we performed two filtration replicates using a peristaltic pump to conduct environmental DNA (eDNA) sampling. Each filtration targeted a maximum duration of 1 hours, during which a maximum of 30 liters of water were filtered through each capsule. After filtration, the water inside the capsules was removed, and the capsules were filled with 50 ml of conservation buffer for preservation at room temperature. We followed strict contamination control protocols throughout both the fieldwork and laboratory processes, adhering to the guidelines of Valentini et al. (2016). To prevent contamination, each sample was processed using disposable gloves and single-use filtration equipment. The MiSeq Reagent Kit v3 (2x75 bp) (Illumina, San Diego, CA, USA) was used for paired-end sequencing at a theoretical sequencing depth of 200,000 reads per sample.
Data content:
	* rawdata/: contains the raw reads for each individual sample. One archive contains the paired-end reads specified by the _R1 or _R2 suffix as well as individually tagged PCR replicates (if available) together with an archive containing all extraction and PCR blank samples of the library. Reads have been demultiplexed using cutadapt but not trimmed, individual demultiplexing tags and primers remain present in the sequences.
	* taxadata/: contains the table with all detected taxonomy for each sample after bioinformatic processing (see Polanco et al. 2020 for details; https://doi.org/10.1002/edn3.140) and associated field metadata.
	* metadata/: contains two metadata files, one related to the data collected in the field for each filter, and the second related to the sequencing process in the lab (including the tag sequence, library name, and marker information for each sample)

en: magdalena fish edna vert01 teleo metabarcoding colombia

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.

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

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

en: Environmental DNA Freshwater Colombia Magdalena 2022

type: dataset

key: guid

key: uri

value: Envidat Harvester

envi

de: Umwelt

fr: Environnement

it: Ambiente

colombia

display_name: colombia

edna

display_name: edna

fish

display_name: fish

magdalena

display_name: magdalena

metabarcoding

display_name: metabarcoding

teleo

display_name: teleo


en:
These datasets and script document the analyses and the plot generation for the article **“Trends in background mortality in unmanaged forests across Europe over the last century”**.
We used a comprehensive network of permanent plots with repeated censuses spanning from 1936 to 2020 in 299 unmanaged forest reserves across Europe. The database includes 1.5 million tree records over successive censuses covering a total sampled area of 853.7 ha.
It consists of the following files:
- **Mortality_script.Rmd**: R markdown document to reproduce the analysis and the plot generation.
- **plot_level.RDS**: This dataset contains annual mortality rate values for each permanent plot at each census, of plots with at least three censuses. This dataset is used to calculate the weighted mean annual background mortality rates by forest types, and the series of models to study the trends of annual mortality rates, and then to create Figure 1 and Figure 2.
- **tree_level.RDS**: This dataset contains tree census data for each permanent plot at each census, of plots with at least two censuses. This dataset is used to model species-specific size-dependent mortality probabilities of the studied tree species, and then to create Figure 3.

en: forest-inventory forest temperate-forests mortality-rate ecological-niche forest-dynamics tree-mortality

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:
Resource Title: tree_level.RDS
    Size: 2222669 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/9e684bf2-daf1-4662-8425-1196c5dedfbc/resource/4081e017-d05d-47dd-89a4-68a2cd22b4c6/download/tree_level.rds
    Description: This dataset contains tree census data for each permanent plot at each census, of plots with at least two censuses. This dataset is used to model species-specific size-dependent mortality probabilities of the studied tree species, and then to create Figure 3.

format: OCTET

en:
Resource Title: plot_level.RDS
    Size: 41149 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/9e684bf2-daf1-4662-8425-1196c5dedfbc/resource/15a70c68-bb5b-4741-b8f1-49e54c0bbfea/download/plot_level.rds
    Description: This dataset contains annual mortality rate values for each permanent plot at each census, of plots with at least three censuses. This dataset is used to calculate the weighted mean annual background mortality rates by forest types, and the series of models to study the trends of annual mortality rates, and then to create Figure 1 and Figure 2.

en:
Resource Title: Mortality_script.Rmd
    Size: 23700 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/9e684bf2-daf1-4662-8425-1196c5dedfbc/resource/d8382129-4275-456c-b062-de2098d676f6/download/mortality_script.rmd
    Description: R markdown document to reproduce the analysis and the plot generation.

ecological-niche

display_name: ecological-niche

forest

display_name: forest

forest-dynamics

display_name: forest-dynamics

forest-inventory

display_name: forest-inventory

mortality-rate

display_name: mortality-rate

temperate-forests

display_name: temperate-forests

tree-mortality

display_name: tree-mortality


en:
Environmental DNA complements scientific trawling in surveys of marine fish biodiversity (Dataset 2021)
At the end of October and the beginning of November 2021, we selected 18 sites from the 2021 EVHOE survey for eDNA sampling. The French international EVHOE bottom trawl survey is conducted annually in autumn in the Bay of Biscay (BoB) to monitor demersal fish resources. All selected sites were located on the continental shelf at depths ranging from 30 to 230 m. At each site, we sampled seawater using an underwater pump equipped with two peristaltic heads (subspace), mounted on Ifremer’s Pagure sledge. We collected approximately 30 liters of water directly from the seabed at a flow rate of 1.0 L min⁻¹. For filtration, we used VigiDNA 0.20 μm filtration capsules (SPYGEN, Le Bourget-du-Lac, France) along with disposable sterile tubing. Each filtration device processed water along a transect, representing two replicates per sampling site. To prevent contamination during fieldwork, we adhered to strict protocols, including the use of disposable gloves and single-use filtration equipment. At the end of each filtration, we emptied the remaining water from the capsule and replaced it with 80 mL of CL1 conservation buffer before storing the samples at room temperature. We processed the eDNA capsules at SPYGEN, following the protocol outlined by Polanco-Fernández et al. (2020). Library preparation and sequencing were performed at Fasteris (Geneva, Switzerland). Specifically, we prepared four libraries using the MetaFast protocol (a ligation-based method) and sequenced them separately. Paired-end sequencing was conducted using a MiSeq sequencer (2 × 125 bp, Illumina, San Diego, CA, USA) on two MiSeq Flow Cell Kits (v3; Illumina), following the manufacturer’s instructions. We analyzed the sequence reads using the OBITools package (http://metabarcoding.org/obitools; Boyer et al., 2016), following the protocol described by Valentini et al. (2016).
Data content:
	* rawdata/: contains the raw reads for each individual sample. One archive contains the paired-end reads specified by the _R1 or _R2 suffix as well as individually tagged PCR replicates (if available) together with an archive containing all extraction and PCR blank samples of the library. Reads have been demultiplexed using cutadapt but not trimmed, individual demultiplexing tags and primers remain present in the sequences.
	* taxadata/: contains the table with all detected taxonomy for each sample after bioinformatic processing (see Polanco et al. 2020 for details; https://doi.org/10.1002/edn3.140) and associated field metadata.
	* metadata/: contains two metadata files, one related to the data collected in the field for each filter, and the second related to the sequencing process in the lab (including the tag sequence, library name, and marker information for each sample)

en: bay-biscay atlantic-region actinopterygii metabarcoding fish-composition edna teleo chondrichthyes

envidat

en: EnviDat: the Environmental Data Portal

en: Environmental DNA Marine France Evhoe 2021

envi

en: Environment

actinopterygii

display_name: actinopterygii

atlantic-region

display_name: atlantic-region

bay-biscay

display_name: bay-biscay

chondrichthyes

display_name: chondrichthyes

fish-composition

display_name: fish-composition


en:
Monitoring fish diversity through eDNA metabarcoding along the Casamance river
In 2018, water samples were collected in 13 locations along the Casamance in Senegal. Samples were taken either from a boat or by filtering from the side of the river. At each station, two filtration replicates were performed using a peristaltic pump to conduct environmental DNA (eDNA) sampling. Each filtration targeted a maximum duration of 30 min, during which approximately 30 liters of water were filtered through each filtration capsule. After filtration, the water inside the capsules was removed, and the capsules were filled with 50 ml of conservation buffer for preservation at room temperature. We followed strict contamination control protocols throughout both the fieldwork and laboratory processes, adhering to the guidelines of Valentini et al. (2016). To prevent contamination, each sample was processed using disposable gloves and single-use filtration equipment. We use primers for eukaryote and fish. The MiSeq Reagent Kit v3 (2x75 bp) (Illumina, San Diego, CA, USA) was used for paired-end sequencing at a theoretical sequencing depth of 200,000 reads per sample.
Data content:
	* rawdata/: contains the raw reads for each individual sample. One archive contains the paired-end reads specified by the _R1 or _R2 suffix as well as individually tagged PCR replicates (if available) together with an archive containing all extraction and PCR blank samples of the library. Reads have been demultiplexed using cutadapt but not trimmed, individual demultiplexing tags and primers remain present in the sequences.
	* taxadata/: contains the table with all detected taxonomy for each sample after bioinformatic processing (see Polanco et al. 2020 for details; https://doi.org/10.1002/edn3.140) and associated field metadata.
	* metadata/: contains two metadata files, one related to the data collected in the field for each filter, and the second related to the sequencing process in the lab (including the tag sequence, library name, and marker information for each sample)

en: senegal metabarcoding fish edna teleo

en: Environmental DNA Freshwater Senegal Casamance 2018

edna

display_name: edna

senegal

display_name: senegal


en: By using hazard scenarios based on CH2018 climate projections and the RAMMS avalanche model, we generated large-scale hazard indication maps for future avalanche hazards. By employing the open-source probabilistic risk assessment platform CLIMADA, along with building data and vulnerability functions, we estimated risks for the present time and two future time frames: mid-century (2060) and the end of the century (2085). An uncertainty and sensitivity analysis complemented the study to account for potential fluctuations in model assumptions. The data contains the hazard information and data used for the Climada risk analysis.

en: ramms climada climate-change avalanche risk snow-avalanche

en: Assessing the impacts of climate change on snow avalanche-induced risk in alpine regions

format: ZIP

avalanche

display_name: avalanche

climada

display_name: climada

climate-change

display_name: climate-change

ramms

display_name: ramms

risk

display_name: risk

snow-avalanche

display_name: snow-avalanche


en:
To assess the possible consequences of potential changes in snow accumulation and temperature and their impact on avalanche hazard, we introduce a comprehensive multi-step framework. It includes the analysis of climate change scenarios as well as the modeling of future snow covers and the simulation of avalanches in a case study region in central Switzerland.
Using a downscaling and a quantile mapping approach, we considered the high emission RCP8.5 from the CH2018 Swiss climate change scenarios and simulated a potential snow cover of more than 100 future winters with the snow cover model SNOWPACK. Changing snow accumulation and snow cover temperature was taken into account for two future time frames. The changed parameters were used in the RAMMS::EXTENDED avalanche simulation software on large scale.

en: ramms climate-change hazard avalanche new-snow avalanche-mapping

en: A novel approach for bridging the gap between climate change scenarios and avalanche hazard indication mapping

avalanche-mapping

display_name: avalanche-mapping

hazard

display_name: hazard

new-snow

display_name: new-snow


en: This dataset provides data on the occurrence of 672 European bryophyte species in European countries or territories. All species which are considered threatened or near threatened according to the European Red List (Hodgetts et al. 2019) are included (553 species). Further, all species evaluated in the European Red List assessed as LC, DD, NE and EX, which at the same time are either endemic, near endemic or globally rare, are included (119 species). Therefore, the list contains not only all European bryophyte species that are threatened or near threatened, but also all species endemic or near endemic to Europe as well as all globally rare species occurring in Europe. For each of the 553 threatened or near threatened species, we provide a conservation a priority score which was calculated based the Red List status and the proportion of the European population of the global population or the global rarity of the species. For details on the prioritisation approach see Bisang et al. (2025).

en: endemic europe range-size red-list conservation-priority rarity bryophytes

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: Priority ranking for the conservation of all European bryophyte species - dataset

format: XLS

bryophytes

display_name: bryophytes

conservation-priority

display_name: conservation-priority

endemic

display_name: endemic

europe

display_name: europe

range-size

display_name: range-size

rarity

display_name: rarity

red-list

display_name: red-list


en:
Monitoring terrestrial mammals through eDNA in rivers of northern Namibia
In 2022, we collected 20 water samples from 10 stations two rivers of Namibia. Samples were taken from the side of the river. At each station, we performed two filtration replicates using a peristaltic pump to conduct environmental DNA (eDNA) sampling. Each filtration targeted a maximum duration of 30 minutes, during which approximately 30 liters of water were filtered through each capsule. After filtration, the water inside the capsules was removed, and the capsules were filled with 50 ml of conservation buffer for preservation at room temperature. We followed strict contamination control protocols throughout both the fieldwork and laboratory processes, adhering to the guidelines of Valentini et al. (2016). We used eDNA primers targeting bacteria, bivalves, fish, vertebrates (V05) and all Eukaryotes (Euka03). To prevent contamination, each sample was processed using disposable gloves and single-use filtration equipment. The MiSeq Reagent Kit v3 (2x75 bp) (Illumina, San Diego, CA, USA) was used for paired-end sequencing at a theoretical sequencing depth of 200,000 reads per sample.
Data content:
	* rawdata/: contains the raw reads for each individual sample. One archive contains the paired-end reads specified by the _R1 or _R2 suffix as well as individually tagged PCR replicates (if available) together with an archive containing all extraction and PCR blank samples of the library. Reads have been demultiplexed using cutadapt but not trimmed, individual demultiplexing tags and primers remain present in the sequences.
	* taxadata/: contains the table with all detected taxonomy for each sample after bioinformatic processing (see Polanco et al. 2020 for details; https://doi.org/10.1002/edn3.140) and associated field metadata.
	* metadata/: contains two metadata files, one related to the data collected in the field for each filter, and the second related to the sequencing process in the lab (including the tag sequence, library name, and marker information for each sample)

en: bivalves namibia eukaryotes metabarcoding edna

en: Environmental DNA Freshwater Namibia Namibia 2022

bivalves

display_name: bivalves

edna

display_name: edna

eukaryotes

display_name: eukaryotes

metabarcoding

display_name: metabarcoding

namibia

display_name: namibia


en:
Description:
This dataset comprises the time series of overland flow (OF) and topsoil interflow (TIF) discharge, and tracer concentrations during artificial rainfall simulation experiments at two large (-80 m2) trenched runoff plots in the Studibach catchment in the Alptal, a typical pre-Alpine headwater catchment in Switzerland.
One plot is located in a natural clearing in an open mixed forest and the other in a grassland. Together, they represent the dominant land cover types in the region.
We applied streamwater to the surface of the plots using sprinklers and added tracers after OF and TIF had reached steady state. Deuterium enriched water was applied to the surface of the plots via the sprinklers, while Uranine and NaCl were applied as a line tracer at multiple distances from the trench. NaBr was injected into the topsoil at ~20 cm depth. Samples of overland flow and topsoil interflow were collected for several hours after tracer application, while the sprinklers continued to apply water to the surface. The runoff was collected into self-made "Upwelling Bernoulli Tubes" and the water level inside these tubes was measured using pressure sensors (DCX-22-CTD, Keller Druck, Switzerland) at a 1-min resolution during the day and 5-min resolution during the night. Uranine concentrations and electrical conductivity (EC) were recorded at a 1-minute interval. Samples for deuterium and Bromide were analysed in the lab.
The celerity of overland flow and topsoil interflow was determined during another experiment by temporarily adding more water to the surface of the plots at different distances from the trench after steady state conditions had been reached. The overland flow and topsoil interflow discharge were again measured using the Upwelling Bernoulli Tubes and pressure transducers.

en: runoff-plot topsoil-interflow celerity overland-flow studibach rainfall-simulation alptal preferential-flow velocity tracers

envidat

en: EnviDat: the Environmental Data Portal

en: Flow and tracer data for overland flow and topsoil interflow during rainfall simulation experiments in the Studibach catchment - Alptal - Switzerland

envi

en: Environment

en:
Resource Title: plots_runoff_responses_rainfall_experiment.csv
    Size: 67679 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/66059067-b7b3-494c-b356-01f922afd554/resource/863aef5c-80d7-4e5b-acbd-a8fe538eda3a/download/plots_runoff_responses_rainfall_experiment.csv
    Description:

en:
Resource Title: grassland_tracer_experiment_studibach.csv
    Size: 12060 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/66059067-b7b3-494c-b356-01f922afd554/resource/4e41685f-5a74-45d6-a044-26ca59df33ad/download/grassland_tracer_experiment_studibach.csv
    Description:

en:
Resource Title: clearing_tracer_experiment_studibach.csv
    Size: 64438 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/66059067-b7b3-494c-b356-01f922afd554/resource/01a9c6b2-5159-4e8c-a49a-15bb6416b6cb/download/clearing_tracer_experiment_studibach.csv
    Description:

alptal

display_name: alptal

celerity

display_name: celerity

overland-flow

display_name: overland-flow

preferential-flow

display_name: preferential-flow

rainfall-simulation

display_name: rainfall-simulation

runoff-plot

display_name: runoff-plot

studibach

display_name: studibach

topsoil-interflow

display_name: topsoil-interflow

tracers

display_name: tracers

velocity

display_name: velocity


chelsacanaryclim-climatologies

en:
CHELSACanaryClim is a high-resolution, terrain-informed downscaling model developed specifically for the Canary Islands. It builds on the CHELSA v1.2 framework and integrates extensive local meteorological station data to refine temperature and precipitation estimates. The model incorporates high-resolution elevation data (down to 5 m), planetary boundary layer height, and ERA-Interim reanalysis inputs to simulate fine-scale climatic variation in mountainous island terrain.
CHELSACanaryClim-climatologies is a very-high resolution climate dataset generated with the CHELSACanaryClim downscaling model. It consists of monthly climatologies of air-temperatures and precipitation.

en: climatologies air-temperature climate precipitation canaries

en: CHELSACanaryClim-climatologies

title_for_slug: chelsacanaryclim-climatologies

en:
Resource Title: CHELSACanaryClim-climatologies: Daily Minimum Near-Surface Air Temperature
    Size: 104857600 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fchelsa01%2F&prefix=chelsa_canaryclim%2Fcanaries%2Fclimatologies%2Ftasmin%2F
    Description: Daily Minimum Near-Surface Air Temperature

Files are provided as Cloud-Optimized GeoTIFFs (COGs) with standardized metadata.

Each COG encodes scale and offset parameters in its metadata. Standards-compliant software will apply these fields automatically and return values in the correct units; however, legacy or non-compliant applications may not. If there is any uncertainty regarding units, please consult the file metadata to verify the applied scale/offset and units.

en:
Resource Title: CHELSACanaryClim-climatologies: Daily Maximum Near-Surface Air Temperature
    Size: 104857600 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fchelsa01%2F&prefix=chelsa_canaryclim%2Fcanaries%2Fclimatologies%2Ftasmax%2F
    Description: Daily Maximum Near-Surface Air Temperature

Files are provided as Cloud-Optimized GeoTIFFs (COGs) with standardized metadata.

Each COG encodes scale and offset parameters in its metadata. Standards-compliant software will apply these fields automatically and return values in the correct units; however, legacy or non-compliant applications may not. If there is any uncertainty regarding units, please consult the file metadata to verify the applied scale/offset and units.

en:
Resource Title: CHELSACanaryClim-climatologies: Daily Mean Near-Surface Air Temperature
    Size: 83886080 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fchelsa01%2F&prefix=chelsa_canaryclim%2Fcanaries%2Fclimatologies%2Ftas%2F
    Description: Daily Mean Near-Surface Air Temperature

Files are provided as Cloud-Optimized GeoTIFFs (COGs) with standardized metadata.

Each COG encodes scale and offset parameters in its metadata. Standards-compliant software will apply these fields automatically and return values in the correct units; however, legacy or non-compliant applications may not. If there is any uncertainty regarding units, please consult the file metadata to verify the applied scale/offset and units.

en:
Resource Title: CHELSACanaryClim-climatologies: Precipitation
    Size: 83886080 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fchelsa01%2F&prefix=chelsa_canaryclim%2Fcanaries%2Fclimatologies%2Fpr%2F
    Description: Precipitation

Files are provided as Cloud-Optimized GeoTIFFs (COGs) with standardized metadata.

Each COG encodes scale and offset parameters in its metadata. Standards-compliant software will apply these fields automatically and return values in the correct units; however, legacy or non-compliant applications may not. If there is any uncertainty regarding units, please consult the file metadata to verify the applied scale/offset and units.

air-temperature

display_name: air-temperature

canaries

display_name: canaries

climate

display_name: climate

climatologies

display_name: climatologies

precipitation

display_name: precipitation


en: This repository presents the basis data of both the Energyscape 1 (2018) and the Energyscape 2 (2022) survey about renewable energy infrastructure related landscape preferences in Switzerland. Both  datasets are based on Swiss-national representatative online panel surveys (BILENDI). Information about the choice design and landscape visualizations can be derived from https://www.sciencedirect.com/science/article/pii/S2352340921003097fig0001

en: energy-transition discrete-choice survey landscape-perception renewable-energy

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: Energyscape 2 - Comparing stated preferences of renewable energy landscapes in Switzerland in 2018 and 2022

en:
Resource Title: Energyscape2 Covariates
    Size: 12192 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/e3451afd-f9d8-41ce-a7dc-d3f9fad95e67/resource/9d6902f1-784f-4a0a-be6a-aa800b430beb/download/energyscape2_n1006_basis_cov_items_recoded.csv
    Description: This data includes the recoded covariates used in the publication (Cov_1, Cov_2, Cov_3). They can be merged with the column "sys_RespNum" to the basis dataset of the Energyscape 2 survey.

format: CSV

media_type: text/csv

en:
Resource Title: Energyscape2 basis data with original Respondent ID
    Size: 70331 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/e3451afd-f9d8-41ce-a7dc-d3f9fad95e67/resource/4ad511f8-f29a-4b71-bd2c-8b2e9e541ee6/download/energyscape2_n1006_basis_ce1_swth_sel.csv
    Description: This is solely the Energyscape 2 basis data including the original respondents ID "sys_RespNum" to be merged with the covariated data set.

en:
Resource Title: Energyscape1 & Energyscape2 basis data
    Size: 136853 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/e3451afd-f9d8-41ce-a7dc-d3f9fad95e67/resource/9081e5b8-6f16-4873-84f3-f8ab6d030cf2/download/energyscape12_basis_ce1_swth_sel.csv
    Description: This is the already cleaned and ready to use basis dataset for the comparison of stated choice preferences across the 2018 (Energyscape 1, n=844) and the 2022 (Energyscape 2, n=1006) surveys. The first four numbers in the first column "sys_RespNum" of the dataset refer to the year of the surveys, followed by the original Respondent ID. The date can be uploaded as is to analysis software (like Sawtooth) and can be filtered by survey with the help of the very last column "surveytime".

discrete-choice

display_name: discrete-choice

energy-transition

display_name: energy-transition

landscape-perception

display_name: landscape-perception

renewable-energy

display_name: renewable-energy

survey

display_name: survey


en:
CHELSA is a mechanistic downscaling model that links large-scale atmospheric conditions with local topographic factors to produce very high-resolution climate data. It includes commonly used climate variables for impact modeling, such as air temperature, precipitation, humidity, solar radiation, wind speed, and derived variables.
CHELSAch-highres-climatologies is a high resolution climate dataset generated with the CHELSA downscaling model. It consists of long term - 30 year mean aggregated surface variables.
Climatological summaries are provided for: Near-Surface Wind Speed, Daily Mean Near-Surface Air Temperature, Daily Maximum Near-Surface Air Temperature, Daily Minimum Near-Surface Air Temperature. Air Temperature Lapse Rate, Total Cloud Cover Percentage, Precipitation, Surface Downwelling Shortwave Flux in Air
Files are provided in NetCDF format with standardized metadata.

en: air-pressure solar-radiation humidity wind-speed air-temperature climate precipitation

envidat

en: EnviDat: the Environmental Data Portal

en: CHELSAch-highres-climatologies at high resolution

envi

en: Environment

en:
Resource Title: CHELSAch-highres-climatologies: Daily Mean Near-Surface Air Temperature
    Size: 129184563 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Fch%2Fclimatologies%2Ftas%2F
    Description: Climatologies of Daily Mean Near-Surface Air Temperature

Files are provided in NetCDF format with standardized metadata.

Each file encodes scale and offset parameters in its metadata. Standards-compliant software will apply these fields automatically and return values in the correct units; however, legacy or non-compliant applications may not. If there is any uncertainty regarding units, please consult the file metadata to verify the applied scale/offset and units.

en:
Resource Title: CHELSAch-highres-climatologies: Daily Minimum Near-Surface Air Temperature
    Size: 129184563 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Fch%2Fclimatologies%2Ftasmin%2F
    Description: Climatologies of Daily Minimum Near-Surface Air Temperature

Files are provided in NetCDF format with standardized metadata.

Each file encodes scale and offset parameters in its metadata. Standards-compliant software will apply these fields automatically and return values in the correct units; however, legacy or non-compliant applications may not. If there is any uncertainty regarding units, please consult the file metadata to verify the applied scale/offset and units.

en:
Resource Title: CHELSAch-highres-climatologies: Daily Maximum Near-Surface Air Temperature
    Size: 129184563 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Fch%2Fclimatologies%2Ftasmax%2F
    Description: Climatologies of Daily Maximum Near-Surface Air Temperature

Files are provided in NetCDF format with standardized metadata.

Each file encodes scale and offset parameters in its metadata. Standards-compliant software will apply these fields automatically and return values in the correct units; however, legacy or non-compliant applications may not. If there is any uncertainty regarding units, please consult the file metadata to verify the applied scale/offset and units.

en:
Resource Title: CHELSAch-highres-climatologies: Precipitation
    Size: 129184563 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Fch%2Fclimatologies%2Fpr%2F
    Description: Climatologies of Precipitation

Files are provided in NetCDF format with standardized metadata.

Each file encodes scale and offset parameters in its metadata. Standards-compliant software will apply these fields automatically and return values in the correct units; however, legacy or non-compliant applications may not. If there is any uncertainty regarding units, please consult the file metadata to verify the applied scale/offset and units.

air-pressure

display_name: air-pressure

humidity

display_name: humidity

solar-radiation

display_name: solar-radiation

wind-speed

display_name: wind-speed


en: This work presents the numerical study of the thermal stabilisation methods to slow this permafrost thawing, protecting from landscapes and infrastructure damaging at an alpine site. We investigate different methods based on passive and active cooling system. The best approach mixes both methods and manages heat flow, potentially allowing excess energy to be used locally. This dataset allows one to test and check the different thermal stabilisation methods.

en: barrier-layer permafrost swiss-alps thermal-insulation thermal-stabilisation permafrost-degradation solar-energy heat-pump cooling-pipes climate-change

en: Assessment of thermal stabilisation measures based on numerical simulations at a Swiss Alpine permafrost site

barrier-layer

display_name: barrier-layer

climate-change

display_name: climate-change

cooling-pipes

display_name: cooling-pipes

heat-pump

display_name: heat-pump

permafrost

display_name: permafrost

permafrost-degradation

display_name: permafrost-degradation

solar-energy

display_name: solar-energy

swiss-alps

display_name: swiss-alps

thermal-insulation

display_name: thermal-insulation

thermal-stabilisation

display_name: thermal-stabilisation


en:
Background information
The availability of nitrogen (N) and phosphorus (P) is considered to be a major factor limiting growth and productivity in terrestrial ecosystems globally. This project aimed to determine whether the growth stimulation documented in previous short‐term fertilisation trials persisted in a longer‐term study (12 years) in the treeline ecotone, and whether possible negative effects of nutrient addition offset the benefits of any growth stimulation.
Over the course of the 12 study years, NPK fertiliser corresponding to 15 or 30 kg N ha−1 a−1 was added annually to plots containing 30‐year‐old *Larix decidua* or 32‐year-old *Pinus uncinata* individuals with an understorey of mainly ericaceous dwarf shrubs. To quantify growth, annual shoot increments of trees and dwarf shrubs as well as radial growth increments of trees were measured. Nutrient concentrations in the soil were also measured and the foliar nutritional status of trees and dwarf shrubs was assessed.
 Experimental design
Over an elevation gradient of 140 m across the treeline afforestation site Stillberg, 22 locations were chosen that covered the whole range of microenvironmental conditions (*see* Nutrient addition experimental design.png). Half of the blocks included European larch (*L. decidua*) and the other half included mountain pine (*P. uncinata*). Within each block, three plantation quadrats were randomly selected as experimental plots and each plot was assigned to a control (no fertilisation) or to one of two fertiliser dose treatments (15 kg and 30 kg N ha−1 a−1). Treatments were assigned randomly but confined so that the location of fertilised plots within a block was not directly above control plots to avoid nutrient input from drainage. For details about the experiment, *see* Möhl et al (2019).
 Data description
The available datasets contain climate variables (2004-2016), nutrient isotope measurements (2010 & 2016), shrub growth measurements (2004-2016), soil parameter measurements and annual ring and shoot measurements (2004-2016). All data can be found here:
-https://figshare.com/articles/dataset/Twelve_years_of_low_nutrient_input_stimulates_growth_of_trees_and_dwarf_shrubs_in_the_treeline_ecotone/7025858-

en: dwarf-shrubs fertilization stillberg tree-rings nitrogen-isotope treeline

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: Nutrient addition experiment at the Alpine treeline site Stillberg, Switzerland

en:
Resource Title: Data Nutrient Addition Stillberg
    Size: 339539 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/3bc7cad9-38af-453a-8f1e-3afb23000c62/resource/1eb39a79-2953-4aee-b7f0-b63744fef1e0/download/7025858.zip
    Description: This link leads to the figshare repository, which contains all nutrient addition data.

media_type: application/zip

en:
Resource Title: Metadata Nutrient Addition Stillberg Experimental Design
    Size: 1327266 bytes
    Format: image/png
    URL: https://www.envidat.ch/dataset/3bc7cad9-38af-453a-8f1e-3afb23000c62/resource/3874f6f4-be83-403a-b2f8-ab1a0dd465d3/download/nutrient_addition_experimental_design.png
    Description: Nutrient addition map of the study area with the investigated plots. Each circle (study block) contains one control plot and two plots that received NPK fertilizer corresponding to 15 (NPK15) or 30 (NPK30) kg N ha-1 a-1. Contour lines specify the elevation (m a.s.l.) in steps of 10 m.

format: PNG

media_type: image/png

dwarf-shrubs

display_name: dwarf-shrubs

fertilization

display_name: fertilization

nitrogen-isotope

display_name: nitrogen-isotope

stillberg

display_name: stillberg

tree-rings

display_name: tree-rings

treeline

display_name: treeline


en:
This dataset contains the results of a case study analysing the potential impacts of a compound meteorological extreme event on the protective forest in the Val Mesolcina. These impacts were assessed in an experts survey. 29 Experts from practice, administration and science estimated the probabilities for a loss of the protective function due to a drought-related compound extreme event based on different hazard scenarios. The experts not only assessed these probabilities but also provided estimates about the reliability of the scenarios, other socio-economic consequences and options for adaptation.
This dataset contains the following information:
- Table with all (anonymised) answers from the survey
- Factsheets summarising the results and methods in German, French and Italian
- A detailed description of the study site and survey instructions
- Link to the project website wit illustrations for each individual question of the survey

en: protective-effect compound-events natural-hazards extreme-events forest-fire drought protection-forest bark-beetles

en: Experts survey protective forest and combined extremes in Val Mesolcina

en:
Resource Title: MisoxFactsheet_IT.pdf
    Size: 1839616 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/cfb5ccf9-deb0-4c5c-871e-d9988a75db62/resource/b044052a-c8d1-4120-ac92-b3a9be8faac4/download/misoxfactsheet_it.pdf
    Description: Factsheet summarising the key results of the study (in Italian).

format: PDF

media_type: application/pdf

en:
Resource Title: Misox_Survey_Answers_anonymous.xlsx
    Size: 108567 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/cfb5ccf9-deb0-4c5c-871e-d9988a75db62/resource/47c3701d-749c-497b-9982-2a20cf8b101b/download/misox_survey_answers_anonymous.xlsx
    Description: This file contains the anonymous answers to the survey for the case study in the protective forest, Val Mesolcina, GR, Switzerland within the BAFU Project "Wenn Risiken kumulieren - Analyse und Umgang mit unerwarteten Ereignissen und kombinierten Risiken".
The survey consists of two parts, based on different concepts: "top-down" and "bottom-up". Answers for both concepts are available in two different worksheets within the Excel file.

en:
Resource Title: Schlussfolgerungen und Empfehlungen_BAFU_Wildcard.pdf
    Size: 310388 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/cfb5ccf9-deb0-4c5c-871e-d9988a75db62/resource/bfd5af20-8102-4872-b742-abe70176c031/download/schlussfolgerungen-und-empfehlungen_bafu_wildcard.pdf
    Description: Conclusions and recommendations of the project (in German).

en:
Resource Title: Methodenbericht_BAFU.pdf
    Size: 1786555 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/cfb5ccf9-deb0-4c5c-871e-d9988a75db62/resource/df678b13-0df1-4dd4-bc80-c0008403c7c3/download/methodenbericht_bafu.pdf
    Description: Factsheet summarising the methods used in this project (in German).

en:
Resource Title: MisoxFactsheet_FR.pdf
    Size: 1848388 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/cfb5ccf9-deb0-4c5c-871e-d9988a75db62/resource/be732b0e-182f-4007-9f20-dc11cc01baa6/download/misoxfactsheet_fr.pdf
    Description: Factsheet summarising the key results of the study (in French).

en:
Resource Title: Erlaeuterungen_zum_Fragebogen_Misox.pdf
    Size: 484195 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/cfb5ccf9-deb0-4c5c-871e-d9988a75db62/resource/9e5169e1-7933-40de-a27e-82050cf55437/download/erlaeuterungen_zum_fragebogen_misox.pdf
    Description: Description of the study site, extreme event (trigger event) and informations about the survey.

en:
Resource Title: MisoxFactsheet.pdf
    Size: 1784390 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/cfb5ccf9-deb0-4c5c-871e-d9988a75db62/resource/95f4a266-6930-4b22-8de7-190894f81db7/download/misoxfactsheet.pdf
    Description: Factsheet summarising the key results of the study (in German).

bark-beetles

display_name: bark-beetles

compound-events

display_name: compound-events

drought

display_name: drought

extreme-events

display_name: extreme-events

forest-fire

display_name: forest-fire

natural-hazards

display_name: natural-hazards

protection-forest

display_name: protection-forest

protective-effect

display_name: protective-effect


en:
Background information
High elevation ecosystems are important in research about environmental change because shifts in climate associated with anthropogenic greenhouse gas emissions are predicted to be more pronounced in these areas compared to most other regions of the world. This project involved a Free Air CO2 Enrichment (FACE) and soil warming experiment located in a natural treeline environment near Davos, Switzerland (Stillberg, 2200 m a.s.l.). Elevated atmospheric CO2 concentrations (+200 ppm) were applied from 2001 until 2009, and a soil warming treatment (+4 °C) was applied from 2007 until 2012. The combined CO2 enrichment and warming treatment reflects conditions expected to occur in this region in approximately 2050. A broad range of ecological and biogeochemical research was carried out as part of this environmental change project.
 Experimental design
The experiment consisted of 40 hexagonal 1.1 m² plots, 20 with a *Pinus mugo* ssp. *uncinata* (mountain pine, evergreen) individual in the centre and 20 with a *Larix decidua* (European larch, deciduous) individual in the centre. A dense cover of understorey vegetation surrounded the tree in each plot, including the dominant dwarf shrub species *Vaccinium myrtillus* (bilberry), *Vaccinium gaultherioides* (group *V. uliginosum agg.*, northern bilberry) and *Empetrum nigrum* ssp. *hermaphroditum* (crowberry) plus several herbaceous and non-vascular species.
At the beginning of the experimental period, the 40 plots were assigned to ten groups of four neighbouring plots (two larch and two pine trees per group) in order to facilitate the logistics of CO2 distribution and regulation. Half of these groups were randomly assigned to an elevated CO2 treatment, while the remaining groups served as controls and received no additional CO2. In spring 2007, one plot of each tree species identity was randomly selected from each of the 10 CO2 treatment groups and assigned a soil warming treatment, yielding a balanced design with a replication of five individual plots for each combination of CO2 level, warming treatment and tree species.
 Data description
Soil and air conditions have been monitored closely throughout the study period, with most measurements made during the combined CO2 x warming experiment (2007-2009). The data comprise of air temperature, soil temperature, soil moisture, sapflow, tree diameter and CO2 measurements.

en: stillberg experiment vegetation soil-temperature climate-change carbon-dioxide

envidat

en: EnviDat: the Environmental Data Portal

en: FACE: Stillberg CO2 enrichment and soil warming study

envi

en: Environment

en:
Resource Title: Metadata FACE Stillberg Experimental Design
    Size: 533823 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/0d88fc12-285e-4a64-b2d6-d8a7bf0603f8/resource/0ba721cc-8433-4047-8e3a-24fd69e5a933/download/metadata_face_stillberg_experimental-design.pdf
    Description: Schematic illustration and tabular listing of the FACE experimental design.

en:
Resource Title: Metadata FACE Stillberg Data File Description
    Size: 9011 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/0d88fc12-285e-4a64-b2d6-d8a7bf0603f8/resource/eb14b5cf-974f-402a-9cf6-1cc95bd0a7dd/download/metadata_face_stillberg_data-file_description.csv
    Description: List of descriptions for each of the .csv FACE data files.

en:
Resource Title: Data FACE Stillberg
    Size: 54418509 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/0d88fc12-285e-4a64-b2d6-d8a7bf0603f8/resource/666184ed-e140-483c-8362-fcdca851b368/download/data_face_stillberg.zip
    Description: Folder in .zip format containing the FACE datasets.

carbon-dioxide

display_name: carbon-dioxide

climate-change

display_name: climate-change

experiment

display_name: experiment

soil-temperature

display_name: soil-temperature

vegetation

display_name: vegetation


en:
Alpine3D (A3D) runs between 1950 and 2022 in hourly resolution. Simulations are run for every year separately (year n = Sept. n-1 to Aug. n), starting again with no snow every 1st of September (i.e. there is no snow accumulation from year to year).
Meteorological conditions over the past 70 years were obtained from several datasets: ERA5 providing the hourly data over the full 1950-2022 period, IMIS and MeteoSuisse allowing to validate and correct the downscaled ERA5 data. ERA5 data were downscaled to a 50m grid using Toposcale (Fiddes et al., 2015) (see also https://github.com/joelfiddes/toposcale). This downscaling tool allowed us to obtain a 50 m grid from the ERA5 data including the effect of the local topography. The meteorological input data was further sued to run the 3-dimensional snow model Alpine 3D.
Temperature correction is based on an additive delta change correction following the procedure using harmonic functions filtering described by Michel et al. (2021). Given the hourly timestep provided by ERA5 and Toposcale, we defined an hourly delta change. In practice, this was done by repeating 24 times the delta-change derivation from Michel et al.  (2021) to obtain a day-of-the-year delta for each of the 24 hours of the day.
The simulation covers the slope at Spitze Stei region with  precipitation scaled using snow height measured by a drone flight. One of the 70 years runs was computed with a precipitation redistribution with the idea to mimic snow transport and preferential deposition. The precipitation redistribution grid was based on a single snow height measurement: one snow-free drone flight on 01.10.2021 and one peak snow season flight on 27.03.2022. The precipitation on each pixel is computed as i) multiplying the disaggregated KAS precipitation by the average slope elevation. ii) multiplying that value on each pixel with the weight obtain from the snow height as HS pixel/HS mean.

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: Alpine3D Climate Data

snow-climatology

display_name: snow-climatology

snow-cover

display_name: snow-cover

snow-depth

display_name: snow-depth


ensemble-hydrograph-separation-scripts

en:
Calculation scripts that perform ensemble hydrograph separation.  Identical scripts in R and MATLAB are provided, along with demonstration input time series and the corresponding outputs.  These scripts were tested on R version 3.6.2 (2019-12-12) and on MATLAB versions 2018b and 2109b.
These scripts are made publicly available under GNU General Public License 3; for details see https://www.gnu.org/licenses/.
ETH Zurich, WSL, James Kirchner, and Julia Knapp make ABSOLUTELY NO WARRANTIES OF ANY KIND, including NO WARRANTIES, expressed or implied, that this software is free of errors or is suitable for any particular purpose.  Users are solely responsible for determining the suitability and reliability of this software for their own purposes.

en: hydrograph-separation streamflow isotopes runoff catchment tracers

en: Ensemble hydrograph separation scripts

title_for_slug: ensemble-hydrograph-separation-scripts

en:
Resource Title: *deprecated* MATLAB scripts and demonstration files (*deprecated version* - build 20200718 - do not use!)
    Size: 227403 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/ddc39d77-c0a3-4a8c-858a-efda8b6dffd9/resource/bd43b9fb-7fda-4c26-a38c-31016f035429/download/ehs-v1.4-matlab-scripts.zip
    Description: The ensemble hydrograph separation functions themselves are in EHS_Fnew.m, EHS_profile.m, and EHS_TTD.m.

EHS_demo_RUN_THIS.m is a demonstration script that calls the EHS functions to analyze the demo input files. The resulting output files are in the "demo output files" folder.  These were generated by the R versions of the scripts but have been verified to be numerically equal to the MATLAB outputs, within machine precision.

en:
Resource Title: R scripts and demonstration files
    Size: 235119 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/ddc39d77-c0a3-4a8c-858a-efda8b6dffd9/resource/212f3a19-0530-4cd9-b10d-cd387ac98018/download/ehs-v1.4-r-scripts-and-demo-files.zip
    Description: The ensemble hydrograph separation functions themselves are in EHS_v1.4.R.

EHS_demo_v1.4.R is a demonstration script that calls EHS_v1.4.R to analyze the demo input files.  The resulting output files are in the "demo output files" folder.

en:
Resource Title: MATLAB scripts and demonstration files (current version - build 20201119)
    Size: 178465 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/ddc39d77-c0a3-4a8c-858a-efda8b6dffd9/resource/27da91e3-24b1-4d76-883e-37619652d785/download/ehs-v1.4-matlab-scripts-build-20201119.zip
    Description: The ensemble hydrograph separation functions themselves are in EHS_Fnew.m, EHS_profile.m, and EHS_TTD.m.

Build 20201119 has improved commenting, naming, and structuring, and also minor bug fixes in EHS_Fnew, EHS_TTD, and EHS_profile.  Build 20200718 has been deprecated.  Use build 20201119 instead.

EHS_demo_RUN_THIS.m is a demonstration script that calls the EHS functions to analyze the demo input files. The resulting output files are in the "demo output files" folder.  These were generated by the R versions of the scripts but have been verified to be numerically equal to the MATLAB outputs, within machine precision.

catchment

display_name: catchment

hydrograph-separation

display_name: hydrograph-separation

isotopes

display_name: isotopes

runoff

display_name: runoff

streamflow

display_name: streamflow

tracers

display_name: tracers


en:
In this experiment, we investigated the inoculation-effects of two ectomycorrhizal fungi (EMF) species with contrasting evolutionary histories, ecological properties, host-preferences, and habitat-ranges on phenotypic responses and growth dynamics of pedunculate oak (*Quercus robur*), an ecologically and economically important temperate forest tree species.
We set up the mycorrhization experiment using 96 plants of a genetically uniform *Q. robur* clone (DF159) and applied four treatments: A control treatment; an inoculation-treatment with the cosmopolitan Ascomycete *Cenococcum geophilum*, which is commonly found in oak forests; an inoculation-treatment with the Basidiomycete *Piloderma croceum*, which has not yet been found in natural oak forests but has been shown in previous experiments to support oak growth; and a co-inoculation treatment. We then assessed growth stage development of the trees over eight experimental weeks and measured various phenotypic traits during a destructive sampling.

en: quercus-robur oak cenococcum-geophilum piloderma-croceum ectomycorrhiza rhythmic-growth

en: Phenotypic and Growth Stage Development Data of a Quercus robur Mycorrhization Experiment

en:
Resource Title: pheno_data.csv
    Size: 24577 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9d0661cc-cbbc-452e-8bd9-574161c73cd1/resource/e0197cc6-6279-4f22-8e6a-3cc51a8973e1/download/pheno_data.csv
    Description: Contains phenotypic data assessed during the destructive sampling step of the experiment.

Columns:
- ID = Tree identifier.
- Treatment = Experimental treatment.
- nSF = Number of completed shoot flushes.
- Max_Stages_Reached = Total number of growth stages reached during the experiment.
- n_L_SF1 = Number of leaves of the second newest shoot flush at time of sampling.
- n_L_SF2 = Number of leaves of the newest shoot flush at time of sampling.
- Alive = Plant alive or not.
- Contamination = Plant contaminated or not.
- Exclude = Exclude plant or not.
- Shoot_Length_Init = Shoot length at start of the experiment.
- Shoot_Length = Shoot length at sampling.
- Delta_Length = Shoot length increase during experiment.
- FW_Plant = Fresh weight total plant.
- DW_Plant = Dry weight total plant.
- FW_Shoot = Fresh weight shoot.
- DW_Shoot = Dry weight shoot.
- FW_Stem = Fresh weight stem.
- DW_Stem = Dry weight stem.
- FW_L_SF1 = Fresh weight leaves second newest shoot flush.
- DW_L_SF1 = Dry weight leaves second newest shoot flush.
- FW_L_SF2 = Fresh weight leaves newest shoot flush.
- DW_L_SF2 = Dry weight leaves newest shoot flush.
- FW_L_Rest = Fresh weight remaining leaves.
- DW_L_Rest = Dry weight remaining leaves.
- FW_Bud = Fresh weight bud.
- DW_Bud = Dry weight bud.
- FW_Roots_Total = Fresh weight total roots.
- DW_Roots_Total = Dry weight total roots.
- FW_PR = Fresh weight principal roots.
- DW_PR = Dry weight principal roots.
- FW_LR = Fresh weight lateral roots.
- DW_LR = Dry weight lateral roots.
- A_L_SF1 = Leave area second newest shoot flush.
- A_L_SF2 = Leave area newest shoot flush.
- N_Ceno = Number of root tips mycorrhized by *Cenococcum geophilum*.
- N_Pilo = Number of root tips mycorrhized by *Piloderma croceum*.
- N_Other = Number of root tips mycorrhized by other species.
- N_No = Number of not mycorrhized root tips.
- Length_Tot = Total root length.
- Area_Tot = Total root surface area.
- Diameter_Avg = Average root diameter.
- Root_Vol = Total root volume.
- Tips = Total number root tips.
- Forks = Total number root forks.
- Crossings = Total number root crossings.
- Length_Fine = Root length fine roots (diameter < 1mm).
- SA_Fine = Surface area fine roots (diameter < 1mm).
- Vol_Fine = Volume fine roots (diameter < 1mm).

en:
Resource Title: time_series.csv
    Size: 83281 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/9d0661cc-cbbc-452e-8bd9-574161c73cd1/resource/2664abc3-ba85-4000-bb9d-162677eb47b7/download/time_series.csv
    Description: Contains growth stage data assessed over the experimental period.

Columns:
- ID = Tree identifier.
- Set = Date of plant preparation.
- Treatment = Experimental treatment.
- Date = Date of growth stage assessment,
- Days = Number of past days since start of experiment.
- Stage = Growth stage (XY = Groth cycle & development stage).
- Week = Experimental week.

cenococcum-geophilum

display_name: cenococcum-geophilum

ectomycorrhiza

display_name: ectomycorrhiza

oak

display_name: oak

piloderma-croceum

display_name: piloderma-croceum

quercus-robur

display_name: quercus-robur

rhythmic-growth

display_name: rhythmic-growth


en:
The data consists of a collection of environmental data, tree-ring width and intra-annual δ13C measurements of tree rings of three conifer species (Pinus sylvestris, Picea abies, Abies alba), and the R scripts that were used to analyse the data. Data was collected at two pairs of north and south exposed sites in Switzerland, in the Eastern Grisons (Surava North and Surava South) and Central Valais (Buthan and Lens).
Intra-annual δ13C measurements were obtained using the laser ablation technique, which involved 10 sequential shots per ring. Shot 1 represents the δ13C value at the start of the ring, while Shot 10 corresponds to the δ13C value at the end of the ring's formation. Overall, the datasets consist of 400 profiles and 4000 isotope measurements.
Environmental data was collected at each site over decade, from 2012 to 2023. Key environmental variables include temperature, vapour pressure deficit (VPD), and soil water potential (SWP). Precipitation data was obtained from the EOBS v29.0e dataset (https://www.ecad.eu/download/ensembles/download.php) from the closest grid point. All data was aggregated on an hourly to daily scale.
In addition to environmental data, dendrometer data was used to derive the onset days, beginning of growth for each site (Onset_days.Rds). The data captures the dynamic relationship between environmental factors, such as soil and air moisture, and tree physiological responses, as reflected in δ13C variation. This dataset provides insights into the intra-seasonal interactions between environmental conditions and tree physiology. We provide the scripts for the main analyses performed in the Vitali, V. et al. 2025 article listed below, including the correlation of the isotope intra-annual time series with environmental variables.
This dataset contains all data on which the publication listed below is based.
Please cite this paper together with the citation for the datafile.

en: picea-abies soil-water abies-alba drought tree-ring pinus-sylvestris stable-isotopes vpd dendrochronology

envidat

en: EnviDat: the Environmental Data Portal

en: 10 years of intra-annual carbon isotopes in tree rings from 3 conifer species

envi

en: Environment

abies-alba

display_name: abies-alba

dendrochronology

display_name: dendrochronology

drought

display_name: drought

picea-abies

display_name: picea-abies

pinus-sylvestris

display_name: pinus-sylvestris

soil-water

display_name: soil-water

stable-isotopes

display_name: stable-isotopes

tree-ring

display_name: tree-ring

vpd

display_name: vpd


en: Here, we present a comprehensive isotope dataset of soil and stem xylem water collected during two pan-European sampling campaigns in spring and summer 2023. The dataset includes samples from 40 forest sites featuring beech (Fagus sylvatica), spruce (Picea abies), or mixed beech-spruce forests, and is supplemented with detailed site-specific, soil-specific, and tree-specific metadata. Samples and metadata were collected by various researchers across Europe following a standardized protocol. Soil samples were taken at up to five depths (ranging from 0 to 90 cm), and stem xylem samples were collected from three beech and/or spruce trees at each site. All samples were sent to a single laboratory for analysis, where water was extracted using cryogenic vacuum distillation and analyzed with an isotope laser spectrometer. Additionally, a subset of the samples underwent analysis with an isotope ratio mass spectrometer. The complete description of the data can be found in a publication in Earth System Science Data (in review).

en: cryogenic-extraction forest isotopes soil-water xylem-water critical-zone hydrogen-isotopes water-isotopes hydrology europe picea-abies oxygen-isotopes spruce ecohydrology beech fagus-sylvatica

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: Soil and stem xylem water isotope data from two pan-European sampling campaigns

en:
Resource Title: WATSON_Canopydata.csv
    Size: 40574 bytes
    Format: text/csv
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.542/WATSON_Canopydata.csv
    Description: Dataset containing the information on the canopy cover.

en:
Resource Title: WATSON_Isotopedata.csv
    Size: 104798 bytes
    Format: text/csv
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.542/WATSON_Isotopedata.csv
    Description: Dataset containing information about sample weights, cryogenic water extraction and the actual hydrogen and oxygen isotope data of the study.

en:
Resource Title: WATSON_Canopy_Pictures.zip
    Size: 3221225472 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.542/WATSON_Canopy_Pictures.zip
    Description: All canopy pictures in one ZIP file.

en:
Resource Title: WATSON_Metadata.csv
    Size: 8948 bytes
    Format: text/csv
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.542/WATSON_Metadata.csv
    Description: Dataset containing the metadata of the sampling sites, including site-, soil-, tree-specific information.

en:
Resource Title: deprecated_csv_data_2024.zip
    Size: 41321 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/75d32500-127e-4f8d-b5de-02ded379e9d9/resource/6c3020bb-795a-49db-ad12-7db15bee2a19/download/deprecated_csv_data_2024.zip
    Description:

en:
Resource Title: WATSON_Canopy_Pictures (individual JPG files)
    Size: 3221225472 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.542%2FWATSON_Canopy_Pictures%2F
    Description: All canopy pictures as individual files.

beech

display_name: beech

critical-zone

display_name: critical-zone

cryogenic-extraction

display_name: cryogenic-extraction

ecohydrology

display_name: ecohydrology

europe

display_name: europe

fagus-sylvatica

display_name: fagus-sylvatica

forest

display_name: forest

hydrogen-isotopes

display_name: hydrogen-isotopes

hydrology

display_name: hydrology

isotopes

display_name: isotopes

oxygen-isotopes

display_name: oxygen-isotopes

spruce

display_name: spruce

water-isotopes

display_name: water-isotopes

xylem-water

display_name: xylem-water


en:
This dataset accompanies the article Factors influencing public support for forest restoration in Europe: Evidence from Sweden and Spain, published in the journal Ecosystems and People. It presents results from a multi-country survey exploring public perceptions of forests and support for forest restoration in Västerbotten County (Sweden) and the Castilla y León autonomous community (Spain).
Between March and September 2024, structured questionnaires were distributed to 3,000 randomly selected households, yielding 241 valid responses after data cleaning (171 from Sweden and 70 from Spain). The dataset includes anonymised survey responses measured on 5-point Likert scales, covering composite indicators for support for forest restoration, perceived forest benefits, and perceived impacts of restoration activities. It also contains socio-demographic information such as age, education level, and years of residence.
Sampling adhered to the EU General Data Protection Regulation (GDPR) and the Swiss Federal Act on Data Protection. Principal Components Analysis (PCA) was used to construct composite indicators, and Generalised Linear Modelling (GLM) was applied to assess how socio-demographic and perceptual factors influence support for restoration.
The dataset provides insights into behavioural, perceptual, and demographic factors that shape public support for forest restoration, contributing to policy discussions, such as the EU Nature Restoration Regulation (2023). A full codebook is included to facilitate reuse.

en: socio-demographic-factors household-surveys forest-restoration spain sweden public-perceptions

en:
Resource Title: Forest_Restoration_Survey_Data_Sweden_Spain_2024.xlsx
    Size: 48735 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/bd1818e7-deef-4ecb-95bf-6d7fb26239e4/resource/a5233576-1b32-495d-a2da-0b7743100d92/download/dataset_sweden_spain.xlsx
    Description: This file contains anonymised survey responses from 241 individuals in Västerbotten County (Sweden) and Castilla y León (Spain), collected between March and September 2024. It includes variables on forest visitation, restoration awareness, perceptions of forest benefits and impacts, and socio-demographic characteristics. The responses are coded numerically and correspond to categories defined in the metadata file. The dataset supports analysis of public support for forest restoration as presented in the associated article.

en:
Resource Title: Forest_Restoration_Survey_Metadata_Sweden_Spain_2024.xlsx
    Size: 15572 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/bd1818e7-deef-4ecb-95bf-6d7fb26239e4/resource/90046645-5c1e-482b-9da2-931fc5da1866/download/metadata_sweden_spain.xlsx
    Description: This metadata file provides detailed documentation for the survey dataset titled "Survey data on public support for forest restoration in Europe based on evidence from Sweden and Spain." It includes:

Variable Map (Variable names and descriptions): Each survey item is listed alongside a clear explanation of its content and purpose.
Labels Map: For categorical variables, response options are defined numerically and labelled (e.g., Likert scale options, age groups, gender).
Derived variables: Several composite indicators have been created from survey responses, including support for restoration, perceived forest benefits, and perceived restoration impacts.
The metadata enables accurate interpretation, reuse, and analysis of the dataset and is formatted in two Excel sheets:

Variable Map – detailing survey question codes and content.
Labels Map – providing categorical response scales for select questions.

forest-restoration

display_name: forest-restoration

household-surveys

display_name: household-surveys

public-perceptions

display_name: public-perceptions

socio-demographic-factors

display_name: socio-demographic-factors

spain

display_name: spain

sweden

display_name: sweden


en: Meteorological data used to run SNOWPACK for 58 catchments in the Swiss Alps. The data consists of a 2 km grid of "virtual meteorological stations" for each catchment. It was used to simulate snow cover processes during rain-on-snow events, therefore meteorological data of each catchment contains at least one rain-on-snow event. Further information can be found in the attached readme.txt and in Würzer & Jonas et al. (2017), currently under review in Hydrological Processes.

en: meteorological-data snow-hydrology catchment-data rain-on-snow snowpack

envidat

en: EnviDat: the Environmental Data Portal

en: Meteorological data for investigation of rain-on-snow events in 58 catchments in Switzerland

en:
Resource Title:
    Size: 768 bytes
    Format: text/plain
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.305/ros_data/readme.txt
    Description: Readme.txt

format: TXT

media_type: text/plain

en:
Resource Title:
    Size: 1534677078 bytes
    Format: application/zip
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.305/ros_data/ros_data.zip
    Description: The file contains all data needed to run simulations with the snow cover model SNOWPACK.

catchment-data

display_name: catchment-data

meteorological-data

display_name: meteorological-data

rain-on-snow

display_name: rain-on-snow

snow-hydrology

display_name: snow-hydrology

snowpack

display_name: snowpack


en: orography paleo-climate air-temperature precipitation last-glacial-maximum glaciers

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: CHELSA-TraCE21k: Downscaled transient temperature and precipitation data since the last glacial maximum

envi

en: Environment

en:
Resource Title: Technical documentation
    Size: 478853 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/c88baa58-dbae-452c-8c2c-343e4c9fb885/resource/613fcb27-3649-4b5f-8880-984403cccd62/download/chelsa-trace21k_technical_documentation.pdf
    Description: Technical documentation containing file metadata and variable descriptions.

en:
Resource Title: Data Access
    Size: 3848290697216 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fchelsav1%2F&prefix=chelsa_trace%2F
    Description: High resolution, downscaled climate model data are used in a wide variety of applications in environmental sciences. Here we present the CHELSA-TraCE21k downscaling algorithm to create global monthly climatologies for temperature and precipitation at 30 arcsec spatial resolution in 100 year time steps for the last 21,000 years. Paleo orography at high spatial resolution and at each timestep is created by combining high resolution information on glacial cover from current and Last Glacial Maximum (LGM) glacier databases with the interpolation of a dynamic ice sheet model (ICE6G) and a coupling to mean annual temperatures from CCSM3-TraCE21k. Based on the reconstructed paleo orography, mean annual temperature and precipitation was downscaled using the CHELSA V1.2 algorithm.

The data is published under a Creative Commons Attribution 2.0 Generic (CC BY 2.0) license.

air-temperature

display_name: air-temperature

glaciers

display_name: glaciers

last-glacial-maximum

display_name: last-glacial-maximum

orography

display_name: orography

paleo-climate

display_name: paleo-climate

precipitation

display_name: precipitation


en:
Outlines of 18'737 avalanches mapped from SPOT6 satellite data over the Swiss Alps on 24 January 2018. The outlines have different attributes described in the data example key (ExampleKey_AvalMapping.pdf)
The generation of the data is described in:
Bühler, Y., E. D. Hafner, B. Zweifel, M. Zesiger, and H. Heisig (2019), Where are the avalanches? Rapid SPOT6 satellite data acquisition to map an extreme avalanche period over the Swiss Alps, The Cryosphere, 13(12), 3225-3238, doi:10.5194/tc-13-3225-2019.
Abstract.
Accurate and timely information on avalanche occurrence are key for avalanche warning, crisis management and avalanche documentation. Today such information is mainly available at isolated locations provided by observers in the field. The achieved reliability considering accuracy, completeness and reliability of the reported avalanche events is limited. In this study we present the spatial continuous mapping of a large avalanche period in January 2018 covering the majority of the Swiss Alps (12’500 km2).
We tested different satellite sensors available for rapid mapping during a first avalanche period. Based on these experiences, we tasked SPOT6/7 data for data acquisition to cover the second, much larger avalanche period. We manually mapped the outlines of 18’737 individual avalanche events, applying image enhancement techniques to analyze regions in cast shadow as well as brightly illuminated ones. The resulting dataset of mapped avalanche outlines, having a unique completeness and reliability, is evaluated to produce maps of avalanche occurrence and avalanche size. We validated the mapping of the avalanche outlines using photographs acquired from helicopters just after the avalanche period.
This study demonstrates the applicability of optical, very high spatial resolution satellite data to map an exceptional avalanche period with very high completeness, accuracy and reliability over a large region. The generated avalanche data is of great value to validate avalanche bulletins, complete existing avalanche databases and for research applications by enabling meaningful statistics on important avalanche parameters.
Koordinate System: CH1903+ LV95 LN02

en: snow natural-hazard satellite avalanche hazard-mapping

en: SPOT6 Avalanche outlines 24 January 2018

avalanche

display_name: avalanche

hazard-mapping

display_name: hazard-mapping

natural-hazard

display_name: natural-hazard

satellite

display_name: satellite

snow

display_name: snow


en:
**for English see below**
*******************************************************************************
-br/- -/br-
 Datenbeschrieb
-br/- -/br-
Dieser Datensatz enthält die **Umrisse der 11'120 Lawinen** die aus schwarzweiss Luftbildern, welche zwischen dem 25.2.1999 und dem 1.3.1999 aufgenommen wurden, kartiert wurden. Die Lawinenumrisse haben verschiedene Attribute welche im **beigelegten Beispielschlüssel** beschrieben sind (Beispielschluessel_1999_d.pdf).
Es gibt drei Shapefiles:
* **avalanches1999_endversion1.shp**: die kartierten Lawinen (für Attribute siehe Beispielschlüssel!)
* **area_images_1999.shp**: Fläche die durch die Luftbilder abgedeckt wurde
* **clouds_1999.shp**: grobe Umrisse der Wolken in den Bildern
 Bildverfügbarkeit:
Die entzerrten Luftbilder können von der [Swisstopo](https://s.geo.admin.ch/rpq3hufnb588) einzeln über den Downloadlink heruntergeladen werden (herzlichen Dank an Holger Heisig für die Prozessierung und ans BAFU für die Finanzierung der Prozessierung!!). Über "Erweiterte Werkzeuge"/ "Datei importieren" können die Bilder nach hereinziehen des Orthofotolinks direkt im map.geo.admin.ch angezeigt werden.
 Weiterführende Litertaur:
Details zu den Luftbildern und zur Kartierung, sowie eine kleine Analyse und Empfehlungen zur Verwendung der Daten finden sich unter
- Hafner, E., Margreth, S., and Bühler, Y.: Die grossflächigen Lawinenkartierungen 1999, 2018 und 2019: ein Überblick für die Praxis, FAN Agenda, 1/2025, 15 - 21, 2025.
- Dal, F. J., Hafner, E. D., Peters, T., Narnhofer, D., Caye Daudt, R., Heisig, H., & Bühler, Y. (2024). Automated snow avalanche mapping with deep learning in aerial imagery from the extreme avalanche winter of 1999. In K. Gisnås, P. Gauer, H. Dahle, M. Eckerstorfer, A. Mannberg, & K. Müller (Eds.), Proceedings of the international Snow Science Workshop 2024 (pp. 1264-1271). Norwegian Geotechnical Institute.
- Hafner, E. D., Techel, F., Heisig, H., Dal, J. F., & Bühler, Y. (2024). Remotely sensed avalanche activity during three extreme avalanche periods in Switzerland. In K. Gisnås, P. Gauer, H. Dahle, M. Eckerstorfer, A. Mannberg, & K. Müller (Eds.), Proceedings of the international Snow Science Workshop 2024 (pp. 1222-1229). Norwegian Geotechnical Institute.
*******************************************************************************
-br/- -/br-
 Data description
-br/- -/br-
This dataset contains the **outlines of 11'120 avalanches** mapped from panchromatic aerial imagery taken between February 25, 1999 and March 1, 1999. The avalanche outlines have various attributes which are described in the **attached example key** (ExampleKey_AvalMapping_1999_e.pdf).
There are three shapefiles:
* **avalanches1999_endversion1.shp**: the mapped avalanches (for attributes see example key!)
**area_images_1999.shp**: Area covered by the aerial images
**clouds_1999.shp**: rough outlines of the clouds in the images
 Image availability:
The rectified aerial images can be downloaded individually from [Swisstopo](https://s.geo.admin.ch/bg6beetinfdc) via the download link (many thanks to Holger Heisig for processing and to BAFU for financing the processing!!). The images can be displayed directly in map.geo.admin.ch via “Advanced tools”/“Import file” after dragging in the orthophoto link.
 Further Reading:
Details on the aerial images and mapping, as well as a brief analysis and tips on using the data can be found at
- Hafner, E., Margreth, S., and Bühler, Y.: Die grossflächigen Lawinenkartierungen 1999, 2018 und 2019: ein Überblick für die Praxis, FAN Agenda, 1/2025, 15 - 21, 2025.
- Dal, F. J., Hafner, E. D., Peters, T., Narnhofer, D., Caye Daudt, R., Heisig, H., & Bühler, Y. (2024). Automated snow avalanche mapping with deep learning in aerial imagery from the extreme avalanche winter of 1999. In K. Gisnås, P. Gauer, H. Dahle, M. Eckerstorfer, A. Mannberg, & K. Müller (Eds.), Proceedings of the international Snow Science Workshop 2024 (pp. 1264-1271). Norwegian Geotechnical Institute.
- Hafner, E. D., Techel, F., Heisig, H., Dal, J. F., & Bühler, Y. (2024). Remotely sensed avalanche activity during three extreme avalanche periods in Switzerland. In K. Gisnås, P. Gauer, H. Dahle, M. Eckerstorfer, A. Mannberg, & K. Müller (Eds.), Proceedings of the international Snow Science Workshop 2024 (pp. 1222-1229). Norwegian Geotechnical Institute.

en: avalanche-mapping avalanche-activity avalanche aerial-imagery remote-sensing

en: Avalanche outlines February and March 1999 from aerial imagery

aerial-imagery

display_name: aerial-imagery

avalanche-activity

display_name: avalanche-activity

avalanche-mapping

display_name: avalanche-mapping

remote-sensing

display_name: remote-sensing


en:
This dataset contains measurements from two debris flows recorded in 2024 at the Illgraben debris-flow observatory in Switzerland. The first debris flow was recorded on 15 June 2024 and the second debris flow was recorden on 21 June 2024.
This dataset contains the following reseach data for both:
a) Cummulative rainfall measured at CD1 in the catchment.
b) Radar-based flow height of debris flows measured at CD28.
Abstract
In recent years, the destructive impact of debris flows in alpine regions has become increasingly evident. Surge waves within debris flows increase peak discharge and magnify the hazard potential. Hence, understanding the dynamic complexity of debris flows is crucial to mitigate their risk. In order to capture the dynamic processes involved in the formation and interaction of surge waves, it is necessary to obtain distributed observations in the spatiotemporal domain. In this study, we present near-torrent distributed seismic measurements to monitor the Illgraben channel located in the Swiss Alps. With 33 nodal sensors, we detected and tracked surge waves along a 2-kilometer torrent section across the Illgraben fan, which allowed us to gain valuable new insights into the spatial scales relevant for surge wave formation and their long-distance propagation characteristics. We observed erosion-deposition waves that emerged out of the muddy flow tail and propagated with constant velocity along the torrent, reaching meter-scale flow heights within only 100s of meters of flow distance which significantly impact the hazard potential of debris flows. Our results provide valuable observations of surge waves from their formation to their annihilation. We can differentiate flow regimes based on their seismic signature and track them along the torrent, thus mapping the debris-flow evolution in time and space. The observations elucidate large-scale debris flow dynamics thus improving our understanding of hazard potential and the effectiveness of structural countermeasures.

en: rainfall debris-flow radar illgraben surge-waves

en: Debris flow observation at Illgraben 2024: Event Data 15 June / 21 June

en:
Resource Title: Radar_Illgraben_CD28_2025-06-21
    Size: 86229 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/052465cb-5c81-4ba5-88be-115a96c27dd1/resource/be56122c-15cb-40e0-8df3-ae54a02861f0/download/radar_illgraben_cd28_2025-06-21.csv
    Description: Radar-based flow height measurement of debris flow at CD28 at Illgraben. Flow height is derived relative to pre-event channel-bed elevation. Sensor location: 46.309677N, 7.633304E

en:
Resource Title: Rainfall_Illgraben_CD1_2025-06-15
    Size: 34923 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/052465cb-5c81-4ba5-88be-115a96c27dd1/resource/26a8197f-a18d-48b7-84fd-ad7453b09781/download/rainfall_illgraben_cd1_2025-06-15.csv
    Description: Cumulative rainfall measured at CD1 in the Illgraben catchment. Sensor location:  46.283287N / 7.619689E

en:
Resource Title: Rainfall_Illgraben_CD1_2025-06-21
    Size: 34812 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/052465cb-5c81-4ba5-88be-115a96c27dd1/resource/f8e3ff62-bdf1-4043-9956-7937c47f2191/download/rainfall_illgraben_cd1_2025-06-21.csv
    Description: Cumulative rainfall measured at CD1 in the Illgraben catchment. Sensor location:  46.283287N / 7.619689E

en:
Resource Title: Radar_Illgraben_CD28_2025-06-15
    Size: 73728 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/052465cb-5c81-4ba5-88be-115a96c27dd1/resource/fb160833-ebd4-4374-96ff-378473c4cebc/download/radar_illgraben_cd28_2025-06-15.csv
    Description: Radar-based flow height measurement of debris flow at CD28 at Illgraben. Flow height is derived relative to pre-event channel-bed elevation. Sensor location: 46.309677N, 7.633304E

debris-flow

display_name: debris-flow

illgraben

display_name: illgraben

radar

display_name: radar

rainfall

display_name: rainfall

surge-waves

display_name: surge-waves


en:
This dataset comprises of a post-processed set of terrestrial laser scans (TLS’s) of Antarctic sea ice obtained during the Sea Ice Physics and Ecosystem Experiment-2 (SIPEX-2, http://seaice.acecrc.org.au/sipex2012/) in September-November 2012. The post-processing steps include the registration of the individual scans into a single 3-dimensional point cloud, the removal of unwanted noise caused by particles in the air (i.e., snow crystals), and the final generation of surface grids based on the cleaned individual point returns. The final product includes the ‘xyz’ coordinates of the individual point measurements, and gridded surfaces covering study areas of 100m x 100 m, and at resolutions of 0.01 m, 0.1 m, 0.25 m, 0.5 m and 1 m for each of the survey dates. Additionally, subgrid statistics that include the mean elevation, standard deviation, minimum and maximum elevations, range, and number of point returns in each gridcell are generated. The final product is provided in space-delimited text files, with the surface grids provided in Digital Terrain Model (DTM) format ready for visualization in any GIS software.
How to cite:
Please also cite the original publication when using this data set.: Trujillo, E., K. Leonard, T. Maksym, and M. Lehning (2016), Changes in snow distribution and surface topography following a snowstorm on Antarctic sea ice, J. Geophys. Res. Earth Surf., 121, doi:[10.1002/2016JF003893](https://dx.doi.org/10.1002/2016JF003893).

en: sea-ice sea-ice-elevation tls terrestrial-laser-scans polar

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: High resolution sea ice surface topography from the SIPEX-2 expedition, East Antarctica, 2012

en:
Resource Title: Data processing documentation
    Size: 848896 bytes
    Format: application/msword
    URL: https://www.envidat.ch/dataset/c88b82ed-d54e-43e6-b4e4-7ae1ee06a014/resource/bb51210c-6738-41d4-b4a4-31dd08f4725e/download/tlssipex-2metadata.doc
    Description:

format: msword

en:
Resource Title: Post Processed TLS's
    Size: 932144467 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/c88b82ed-d54e-43e6-b4e4-7ae1ee06a014/resource/2557ecb5-e65d-4d60-97ce-fd6696ee2d00/download/10-16904-9sipex2dat.zip
    Description: Compressed dat files

polar

display_name: polar

sea-ice

display_name: sea-ice

sea-ice-elevation

display_name: sea-ice-elevation

terrestrial-laser-scans

display_name: terrestrial-laser-scans

tls

display_name: tls


en:
The attached data are some large GIS raster files (GeoTIFFs) made with Natural Earth data. Natural Earth is a free vector and raster map data @ naturalearthdata.com. The data used for creating these large files was the "Cross Blended Hypso with Shaded Relief and Water". Data was concatenated to achieve larger and larger files. Internal pyramids were created, in order that the files can be opened easily in a GIS software such as QGIS or by a (future) GIS data visualisation module integrated in EnviDat.
Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com

en: Large GIS raster data derived from Natural Earth Data (Cross Blended Hypso with Shaded Relief and Water)

envi

en: Environment

en:
Resource Title: map preview 0.5MB
    Size: 482223 bytes
    Format: image/jpeg
    URL: https://os.zhdk.cloud.switch.ch/envicloud/doi/envidat.68/gisdata/tiny_map_preview.jpg
    Description:

format: jpeg

en:
Resource Title: Bulk Data Access
    Size: 111669149696 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.68%2F
    Description: Link to the S3 bucket where all the data resources can be downloaded in bulk

gis

display_name: gis

large-files

display_name: large-files

natural-earth

display_name: natural-earth

qgis

display_name: qgis


en:
The following repository contains the data and code to reproduce the figures analyses of the paper "Examining honeybee (Apis mellifera) dominance patterns within urban bee communities worldwide". It contains three datasets and one .R file
---
The data results from a literature review on abundance distribution of urban bee communities worldwide, aiming at obtaining studies reporting total abundances of honeybees and wildbees in a given city, and species abundances of wildbees and honeybees in a given city.
---
1. **Data**:
- *20240308_cities_coords.csv*: the data contains the latitude and longitude of the included cities in the study. It is used for making the world map with the cities.
- *20241201_proportion_HB_WB.csv*: the data contains the total wild bee and honeybee abundances per city/urban aggregation, and the proportions.
- *20241201_rad_bees.csv*: the data contains the species abundances per city/urban aggregation
2. **Script**:
- *HoneybeeDominance_Analyses_Figures.R*: the script to run the analyses and make the plots. Analyses were done in R version 4.2.1, using the packages ggplot2, glmmTMB, multcomp, wesanderson, terra.

en: dominance honeybees sads urban-beekeeping cities wildbees urban-ecosystems anthophila

en: Data supporting ‘Examining honeybee (Apis mellifera) dominance patterns within urban bee communities worldwide’

en:
Resource Title: Dataset proportion honeybees and wild bees
    Size: 14245 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/683ed266-c67f-40db-84cd-e8599f075126/resource/90c4bffd-bfc1-4100-99f5-a2ad3e9503a8/download/20241201_proportion_hb_wb.csv
    Description: The dataset provide the main features for each included dataset from published and unpublished research works.  Each row represents a dataset, which provides bee community data in one city / urban aggregation. Overall, it contains 68 datasets from 46 cities in 15 countries and five continents. The data is organised in the following columns:
- Article_ID: id used in the study
- DOI: doi of the publication, when available
- Authors
- Year: of publication
- Duration sampling (years)
- Start_sampling: month of the year
- End_sampling: month of the year
- Continent
- Country
- N. cities: number of cities included in the publication
- City
- Sampling type: active, passive or both
- Sampling methodology: within each sampling type.
- Habitats: list of sampling habitats
- N_habitats: number of sampling habitats
- Parks_similar: binnary (1 = yes; 0 = no)
- Agriculture: binnary (1 = yes; 0 = no)
- Private_gardens: binnary (1 = yes; 0 = no)
- Green_roofs: binnary (1 = yes; 0 = no)
- seminatural_natural_wasteland: binnary (1 = yes; 0 = no)
- other_unspecified: binnary (1 = yes; 0 = no)
- Number sites
- Abundance honeybees
- Abundance wild bees
- Total bees
- Proportion honeybees
- Proportion wildbees
- Area:. of the studied city/urban aggregation

en:
Resource Title: Dataset coordinates study cities
    Size: 2196 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/683ed266-c67f-40db-84cd-e8599f075126/resource/9a73209e-98c0-4fee-a208-c726bf957efa/download/20240308_cities_coords.csv
    Description: The data contains the latitude and longitude of the studied cities / urban aggregations. It contains the following columns:
- Continent
-Country
- City
- Lat: Latitude
- Lon: Longitude

en:
Resource Title: Dataset species abundance
    Size: 598032 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/683ed266-c67f-40db-84cd-e8599f075126/resource/a4e637d3-911b-4806-b0ba-cbbd17a34309/download/20241201_rad_bees.csv
    Description: This data resource provides the individual species abundance per city / urban aggregation. It contains data from 41 datasets from 37 studies collected in 33 cities / urban aggregations. It contains the following columns:
 - Article_ID
- DOI
- Authors
- Year
- Continent
- Country
- City
- Bee genus
- Bee species
- Bee merged
- Bee full
- Abundance
- Bee_ID_per_study: ID for the study

en:
Resource Title: R script for analyses and plots
    Size: 17744 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/683ed266-c67f-40db-84cd-e8599f075126/resource/2f39336d-f343-4325-8207-38372826ecf4/download/honeybeedominance_analyses_figures.r
    Description:

anthophila

display_name: anthophila

cities

display_name: cities

dominance

display_name: dominance

honeybees

display_name: honeybees

sads

display_name: sads

urban-beekeeping

display_name: urban-beekeeping

urban-ecosystems

display_name: urban-ecosystems

wildbees

display_name: wildbees