en:
This dataset contains several useful components for **Swiss Electricity system modeling**:
1. **High-voltage Swiss grid**: 2019 snapshot of the high-voltage (-150kV) grid composed of :
- Nodes: names, voltage, position.
- Lines: ends nodes, resistance, power capacity.
- Transformers: ends nodes, power capacity, resistance, tap ratio.
2. **Hydropower topology** : Representative description of Swiss reservoirs and plants (2019) composed of:
- Plants: Lower reservoir, Upper reservoir, pump/turbine, debit, power capacity.
- Reservoirs: Volume, altitude, position, canton.
3. **Inflows** into all the reservoirs: hourly time series post-processed from PREVAH model outputs from 2009 to 2019.
4. **Wind production per node**: COSMO-1 data processed and scaled to match SFOE annual production.
5. **Solar irradiance maps projected onto tilted surfaces**: hourly time series for 35° and 65° tilts, azimuth 180°. (same method as [Frischholz, Y. (2025)](https://www.doi.org/10.16904/envidat.632))
6. **Processed ERA5 (historical), ECMWF SEAS5 (seasonal forecast) and ECMWF TIGGE (short-term forecast)**:
- ERA5 Land: For inflow forecast model: historical runoff, snow depth, temperature and total precipitation per catchment (hourly, 2009-2019). For residual demand forecast model: historical temperature, u-v wind, ssrd per country (CH, AT, DE, FR, IT, hourly 2015-2019)
- ECMWF SEAS5: For inflow forecast model: same variables as ERA5 (yearly forecast starting from every 1st day of every month in 2019). For residual demand forecast model: same variables as ERA5 (yearly forecast starting from every 1st day of every month in 2019).
- ECMWF TIGGE: For inflow forecast model: same variables as ERA5 (two weeks forecast starting from every 1st day of every week in 2019). For residual demand forecast model: same variables as ERA5 (two weeks forecast starting from every 1st day of every week in 2019).
7. **Run-of-river production per electricity node**: 15-min resolution run-of-river production time-series (15min, 2009-2019). Raw data and documentation can be found on [https://data.sccer-jasm.ch/runofriver_production/2017-10-16/].
\
More details can be found on *README.txt*.

en: reservoir-inflow solar-irradiance meteorological-data renewable-energy electricity-grid hydropower forecast-models

en: Swiss electricity system modeling -- HV grid - hydropower topology and inflows - renewable productions - past and forecast meteorological data

en:
Resource Title: node_RunOfRiver_15min.ftr
    Size: 527832187 bytes
    Format: application/octet-stream
    URL: https://www.envidat.ch/dataset/97e11e0b-8146-422d-8b04-33c9337eaba6/resource/9923c621-7238-4b16-b20d-6736da165a5a/download/node_runofriver_15min.ftr
    Description: Run-of-river production on 15min resolution from 2009 to 2019 in Switzerland, aggregated by electrical nodes.

en:
Resource Title: data_IFM_RDFM.zip
    Size: 1191853425 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/97e11e0b-8146-422d-8b04-33c9337eaba6/resource/965d0b4b-a87f-4023-8bb8-a33dd2d86c5a/download/data_ifm_rdfm.zip
    Description:

en:
Resource Title: README.txt
    Size: 6216 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/97e11e0b-8146-422d-8b04-33c9337eaba6/resource/0dc23d95-7563-4f21-a416-ca46643d9b69/download/readme.txt
    Description: Data structure and description.

en:
Resource Title: PV_data.zip
    Size: 2072321720 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/97e11e0b-8146-422d-8b04-33c9337eaba6/resource/e0e501b9-1041-4ff9-a3d9-485cce4aadac/download/pv_data.zip
    Description: Solar irradiance maps projected onto tilted surfaces: hourly time series for 35° and 65° tilts, azimuth 180°. (same method as [Frischholz, Y. (2025)](https://www.doi.org/10.16904/envidat.632))

en:
Resource Title: data_IFM_RDFM.zip
    Size: 1202590843 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/97e11e0b-8146-422d-8b04-33c9337eaba6/resource/7f514513-cb54-44a9-8ea4-8f8087048247/download/data_ifm_rdfm.zip
    Description: ERA5 Land, Seasonal forecast and short-term forecast meteorological data to train inflow and residual demand forecast models.

en:
Resource Title: SwissGrid_data.zip
    Size: 17664 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/97e11e0b-8146-422d-8b04-33c9337eaba6/resource/a1224789-8bb8-46cd-a36d-4cb81d6d47ec/download/swissgrid_data.zip
    Description: Description of Swissgrid high-voltage (>150kV) grid, including lines, transformers and nodes (snapshot of the grid in 2019) .

en:
Resource Title: hydropower.zip
    Size: 21349007 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/97e11e0b-8146-422d-8b04-33c9337eaba6/resource/66f009b8-0cef-4f4e-bc12-c3a7d684f229/download/hydropower.zip
    Description: Plants and reservoirs description, with associated hourly inflows (2009 - 2019).

electricity-grid

display_name: electricity-grid

forecast-models

display_name: forecast-models

hydropower

display_name: hydropower

meteorological-data

display_name: meteorological-data

renewable-energy

display_name: renewable-energy

reservoir-inflow

display_name: reservoir-inflow

solar-irradiance

display_name: solar-irradiance


$oid: OBSOLETE

en: This dataset contains code and data to reproduce the figures and analyses in the article 'Environmental DNA metabarcoding reveals biodiversity recovery in tropical forest restoration across multiple landscapes' in Ecosphere journal. In this study, we analysed environmental DNA data from water and soil samples collected across gradients of forest regrowth at six sites in Colombia to assess the recovery of mammal and soil biodiversity associated with forest restoration.

en: mammals forest-restoration environmental-dna colombia soil-biodiversity biodiversity-assessment

envidat

approval_status: approved

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

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

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

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

de: EnviDat: das Umwelt-Datenportal

en: EnviDat: the Environmental Data Portal

fr: EnviDat: le portail de données environnementales

it: EnviDat: il portale dei dati ambientali

political_level: other

state: active

type: organization

wsl

capacity: public

de: EnviDat

en: Data and code underlying 'Environmental DNA metabarcoding reveals biodiversity recovery in tropical forest restoration across multiple landscapes'

type: dataset

key: guid

key: uri

value: Envidat Harvester

envi

de: Umwelt

en: Environment

fr: Environnement

it: Ambiente

en:
Resource Title: Analysis Data and Code.zip
    Size: 15005123 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/18ce28d1-0fa3-4f97-9690-78697dd39683/resource/275e7eac-1898-48ed-8c91-e3d2ee840782/download/analysis-data-and-code.zip
    Description: A zipped folder containing the scripts and data necessary to reproduce the analyses described in the study. Further instructions are provided in scripts/ReadMe.txt

format: ZIP

en:
Resource Title: Raw Data.zip
    Size: 1610612736 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/18ce28d1-0fa3-4f97-9690-78697dd39683/resource/b97d2608-f0d8-4544-a9a6-024f43b1d55d/download/raw-data.zip
    Description: Paired-end reads (specified by the R1 and R2 suffixes) for each individual sample. The reads have been demultiplexed using cutadapt but primers remain present in the sequences.

media_type: application/zip

biodiversity-assessment

display_name: biodiversity-assessment

colombia

display_name: colombia

environmental-dna

display_name: environmental-dna

forest-restoration

display_name: forest-restoration

mammals

display_name: mammals

soil-biodiversity

display_name: soil-biodiversity


en: In the context of landslide early warning research, soil moisture (e.g. volumetric soil water content and soil water potential) has been measured at six locations in the Napf-region (Emmental, central Switzerland) since April 2019. Here, we provide the hourly mean values of all sensors from all 6 locations after a comprehensive data control, filtering and aggregation (from 10-min to 1-hour values). A sub-set of these data (for the locations Wasen i.E.) has previously been published in envidat.ch at https://www.doi.org/10.16904/envidat.369 applying the same data post-processing method. The dataset is complemented with meteorological data (locally measured air temperature and precipitation) as well as soil temperature. A detailed description of the sites and measurement installations can be found in a separate report (attached with the data).

en: soil-moisture soil-water-content landslide-early-warning soil-temperature soil-water-matrix-potential

en: In-situ soil moisture measurements Napf-region

en:
Resource Title: In-situ soil moisture measurements, Ranflüh, 2021-2023
    Size: 6994002 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/60d27b8c-1004-40fa-ab26-da593cd90e74/resource/6526d0fe-255b-47ba-ae37-c5614500e6ba/download/soil_moisture_data_ranflueh_napf_2.csv
    Description: Volumetric soil water content (m3 m-3), soil water potential (mbar) and soil temperatures (oC) measured in two profiles and four depths each, as well as air temperature (oC) and precipitation (mm). Time intervall: 1 hour. Measurement period: April 2021-Dec 2023.
Location: hillslope, meadow
For a detailed description of site, soil and vegetation: see attached document.

format: XLS

en:
Resource Title: In-situ soil moisture measurements, Langnau i E, since 2021
    Size: 9919529 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/60d27b8c-1004-40fa-ab26-da593cd90e74/resource/4df60c67-a0b9-4d1e-952d-11913104c1cb/download/soil_moisture_data_langnau_i.e._napf_3.csv
    Description: Volumetric soil water content (m3 m-3), soil water potential (mbar) and soil temperatures (oC) measured in two profiles and four depths each. Meteorological variables, such as air temperature or precipitation can be received from MeteoSwiss.
Time interval: 1 hour. Measurement period: since June 2021.
Location: flat terrain, meadow (measurement site of MeteoSwiss)
For a detailed description of site, soil and vegetation: see attached document.

en:
Resource Title: Detailed description of soil moisture measurment sites, soil properties and sensor installations (in German)
    Size: 5211423 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/60d27b8c-1004-40fa-ab26-da593cd90e74/resource/f9981d88-aaaa-4e89-8abf-6a6357194cf6/download/detaillierte-beschreibung-standorte-und-bodeneigenschaften-pilotstudie-napf.pdf
    Description:

format: PDF

media_type: application/pdf

en:
Resource Title: In-situ soil moisture measurements, Ranflüh, since 2021
    Size: 9751757 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/60d27b8c-1004-40fa-ab26-da593cd90e74/resource/ae6122ba-cbd3-4269-a140-f9d196d6046c/download/soil_moisture_data_ranflueh_napf_2.csv
    Description: Volumetric soil water content (m3 m-3), soil water potential (mbar) and soil temperatures (oC) measured in two profiles and four depths each, as well as air temperature (oC) and precipitation (mm). Time intervall: 1 hour. Measurement period: since April 2021.
Location: hillslope, meadow
For a detailed description of site, soil and vegetation: see attached document.
Update 2025:
The “precipitation” column was set to not available (NA) for periods when the pluviometer was identified as clogged. These periods were assigned (i) based on regular maintenance of the measurement station and (ii) irregular behavior of the measurement series compared to the precipitation signal from the other nearby measurement stations.

format: CSV

media_type: text/csv

en:
Resource Title: In-situ soil moisture measurements, Wasen i.E., steep slope, since 2019
    Size: 13820232 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/60d27b8c-1004-40fa-ab26-da593cd90e74/resource/526d9589-dbbd-4e7c-99f5-3f399c139840/download/soil_moisture_data_wasen_i.e._hillslope_emm_1.csv
    Description: Volumetric soil water content (m3 m-3), soil water potential (mbar) and soil temperatures (oC) measured in two profiles and four depths each, and two additional soil temperature measurements (oC), air temperature (oC) and precipitation (mm). Time intervall: 1 hour. Measurement period: since April 2019.
Location: steep hillslope, meadow
For a detailed description of site, soil and vegetation: see attached document.

en:
Resource Title: In-situ soil moisture measurements, Napf, since 2021
    Size: 9982444 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/60d27b8c-1004-40fa-ab26-da593cd90e74/resource/ded05973-051e-438f-a123-0bf18a65eab6/download/soil_moisture_data_napf_napf_1.csv
    Description: Volumetric soil water content (m3 m-3), soil water potential (mbar) and soil temperatures (oC) measured in two profiles and four depths each. Meteorological variables such as air temperature or precipitation can be received from MeteoSwiss.
Time interval: 1 hour.
Measurement period: since June 2021
Location: flat terrain, meadow (official MeteoSwiss station)

en:
Resource Title: In-situ soil moisture measurements, Trub, since 2021
    Size: 8975811 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/60d27b8c-1004-40fa-ab26-da593cd90e74/resource/00b3d08d-369e-421e-8b0a-09a874211b1b/download/soil_moisture_data_trub_napf_4.csv
    Description: Volumetric soil water content (m3 m-3), soil water potential (mbar) and soil temperatures (oC) measured in two profiles and four depths each, as well as air temperature (oC) and precipitation (mm). Time intervall: 1 hour. Measurement period: since April 2021.
Location: slope, meadow
For a detailed description of site, soil and vegetation: see attached document.

en:
Resource Title: In-situ soil moisture measurements, Wasen i.E., flat location, since 2019
    Size: 13662945 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/60d27b8c-1004-40fa-ab26-da593cd90e74/resource/49ea6359-5735-42fd-adea-2db3ce46328d/download/soil_moisture_data_wasen_i.e._flat_terrain_emm_2.csv
    Description: Volumetric soil water content (m3 m-3), soil water potential (mbar) and soil temperatures (oC) measured in two profiles and four depths each, and two additional soil temperature measurements (oC), air temperature (oC) and precipitation (mm). Time intervall: 1 hour. Measurement period: since April 2019.
Location: flat terrain, meadow
For a detailed description of site, soil and vegetation: see attached document.
Updates 2025:
The “precipitation” column was set to not available (NA) for periods when the pluviometer was identified as clogged. These periods were assigned (i) based on regular maintenance of the measurement station and (ii) irregular behavior of the measurement series compared to the precipitation signal from the other nearby measurement stations.
Column “VWC_0.7m_right” and “ST_5TE_0.7m_right” were set to not available (NA) for the period after the 2023-06-19T14:00:00Z due to irregular behavior of the ECH2O - 5TE sensor.

en:
Resource Title: In-situ soil moisture measurements, Wasen i.E., flat location, 2019-2023
    Size: 11901338 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/60d27b8c-1004-40fa-ab26-da593cd90e74/resource/668b78c4-9473-47f5-8d58-721c4be5e30d/download/soil_moisture_data_wasen_i.e._flat_terrain_emm_2.csv
    Description: Volumetric soil water content (m3 m-3), soil water potential (mbar) and soil temperatures (oC) measured in two profiles and four depths each, and two additional soil temperature measurements (oC), air temperature (oC) and precipitation (mm). Time intervall: 1 hour. Measurement period: April 2019-Dec 2023.
Location: flat terrain, meadow
For a detailed description of site, soil and vegetation: see attached document.

landslide-early-warning

display_name: landslide-early-warning

soil-moisture

display_name: soil-moisture

soil-temperature

display_name: soil-temperature

soil-water-content

display_name: soil-water-content

soil-water-matrix-potential

display_name: soil-water-matrix-potential


en: This dataset contains number concentrations of ice-nucleating particles active at -15 °C observed at Weissfluhjoch during February and March 2019, as well as complementary data (measured aerosol number concentrations and modelled total precipitation along air mass trajectories). This data formed the basis of our paper with the title “Towards parameterising atmospheric concentrations of ice-nucleating particles active at moderate supercooling”.

en: clouds aerosol raclets backward-trajectories ice-nucleation

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: Ice nucleating particle concentrations active at -15 °C at Weissfluhjoch

en:
Resource Title: INP15_WFJ_version2.csv
    Size: 12704 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/abf0b918-c606-4d3b-99cb-e503e99435f6/resource/3fd9cf7f-1b00-4e70-be8d-eb3b70c4ad03/download/inp15_wfj_version2.csv
    Description: This dataset version includes revised formatting for the start and end time fields.

en:
Resource Title: INP15_WFJ_version1
    Size: 11030 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/abf0b918-c606-4d3b-99cb-e503e99435f6/resource/28c08311-01f4-4245-a139-f867cfe69677/download/inp15_wfj.csv
    Description:

aerosol

display_name: aerosol

backward-trajectories

display_name: backward-trajectories

clouds

display_name: clouds

ice-nucleation

display_name: ice-nucleation

raclets

display_name: raclets


restwasser-datenbank

en:
(in English below)
Der erweiterte Ausbau der Wasserkraftproduktion steht im Spannungsfeld mit der Sicherstellung ökologischer Funktionen von Fliessgewässern. Die neu entwickelte Restwasser-Datenbank bietet eine öffentlich zugängliche Grundlage zu den Restwasserbestimmungen der Schweizer Wasserkraftanlagen (WKA). Sie umfasst 252 WKA mit einer installierten Leistung von mindestens 3 MW, darunter 160 Laufwasserkraftwerke, 75 Speicherkraftwerke, 16 Pumpspeicherkraftwerke und ein Umwälzkraftwerk. Die erwartete jährliche Stromproduktion dieser Anlagen (ohne Umwälzbetrieb) beträgt 31’540 GWh, was rund 76 % der gesamten schweizerischen Wasserkraftproduktion entspricht. Die Datenbank umfasst rechtliche, hydrologische und technische Attribute und erlaubt dank ihrer kraftwerksspezifischen Struktur eine einfache Verknüpfung mit der schweizerischen Wasserkraftstatistik (WASTA). Dadurch wird die effiziente Bearbeitung hydro-energetischer Fragestellungen ermöglicht.
Eine öffentlich zugängliche Datengrundlage ist insbesondere vor dem Hintergrund des Klimawandels relevant, da dieser die hydrologischen Verhältnisse verändert und Nutzungskonflikte um Wasserressourcen verschärft. Gleichzeitig steigt der Druck auf aquatische Lebensräume, unter anderem infolge steigender Wassertemperaturen. Die Restwasser-Thematik betrifft nicht nur das Spannungsfeld zwischen Energieproduktion und Gewässerökologie, sondern auch Aspekte der Wasserqualität sowie weitere Nutzungen wie Trinkwasserversorgung, landwirtschaftliche Bewässerung, Kühlung und den Betrieb von Abwasserreinigungsanlagen (ARAs). Für eine nachhaltige Wasserwirtschaft ist die Etablierung öffentlicher und belastbarer Datengrundlagen unerlässlich, da sie eine Quantifizierung und Abwägung divergierender Interessen ermöglicht. Nur auf dieser Basis lässt sich die bislang emotional geführte Debatte versachlichen und können Entscheidungsprozesse evidenzbasiert unterstützt werden, die eine zukunftsfähige und nachhaltige Wasserwirtschaft fördern.
The planned expansion of hydropower in Switzerland conflicts with the need to preserve the ecological functions of rivers. To support informed decision-making, a publicly accessible database on environmental flows has been developed. It documents the environmental flow requirements for 252 hydropower plants with an installed capacity of ≥ 3 MW, including 160 run-of-river plants, 75 storage plants, 16 pumped-storage plants, and one closed-loop pumped-storage plant. Together, these plants have an expected annual electricity production of 31’540 GWh—around 76% of Switzerland’s total hydropower generation.
The database contains legal, hydrological, and technical attributes and can be easily linked to the national hydropower statistics (WASTA), enabling efficient analysis of hydroelectric issues. In the context of climate change, such an open database is crucial, as shifting hydrological conditions intensify competing water uses and increase pressure on aquatic ecosystems. Environmental flow requirements involve not only the trade-off between energy production and river ecology but also water quality and other uses such as drinking water supply, irrigation, cooling, and wastewater treatment. Robust, publicly available data are essential for quantifying and balancing these competing interests and for supporting evidence-based decisions in sustainable water resources management.

en: konzessionen wasserkraft restwasser wasserwirtschaft dotierwasser

en: Restwasser-Datenbank

title_for_slug: restwasser-datenbank

envi

en: Environment

en:
Resource Title: Restwasserstrecken - Restwasser-Datenbank 2025.zip
    Size: 1604321 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/58c9e08b-4163-4a0f-a90f-babca8444ae9/resource/594bbc94-7b31-43d0-b11e-aded84961656/download/restwasserstrecken-restwasser-datenbank-2025.zip
    Description: Shapefile mit Restwasserstrecken - ein Produkt das in der Erarbeitung der Restwasser-Datenbank mitentstanden ist.

en:
Resource Title: Dokumentation_Restwasser_Datenbank.pdf
    Size: 1954979 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/58c9e08b-4163-4a0f-a90f-babca8444ae9/resource/9aad39fc-71b3-47e8-a48e-7b7a77294c85/download/dokumentation_restwasser_datenbank_jan26.pdf
    Description:

en:
Resource Title: Einzugsgebiete - Restwasser-Datenbank 2025.zip
    Size: 6280235 bytes
    Format: application/x-zip-compressed
    URL: https://www.envidat.ch/dataset/58c9e08b-4163-4a0f-a90f-babca8444ae9/resource/96aafd27-de12-4e91-818a-972d8e4e465d/download/einzugsgebiete-restwasser-datenbank-2025.zip
    Description:

en:
Resource Title: Hydrologische Abflusszeitreihen - Restwasser-Datenbank 2025.xlsx
    Size: 12247368 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/58c9e08b-4163-4a0f-a90f-babca8444ae9/resource/82bdfb38-0d6b-4b32-8538-83d6820730de/download/hydrologische-abflusszeitreihen-restwasser-datenbank-2025.xlsx
    Description: Hydrologische Abflusszeitreihen von 1991-2020 für Anwendungen mit der Restwasser-Datenbank

en:
Resource Title: Restwasserdatenbank_2025.xlsx
    Size: 169021 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/58c9e08b-4163-4a0f-a90f-babca8444ae9/resource/592a4142-73f8-4b06-8683-6bc93368a015/download/restwasserdatenbank_2025.xlsx
    Description: Restwasser-Datenbank mit rechtlichen, hydrologischen und technischen Attributen

dotierwasser

display_name: dotierwasser

konzessionen

display_name: konzessionen

restwasser

display_name: restwasser

wasserkraft

display_name: wasserkraft

wasserwirtschaft

display_name: wasserwirtschaft


en:
This repository contains the data necessary to reproduce Fig. 5 of the publication: L. Mewes, H. Löwe, M. Schneebeli & B. Walter, *Optical determination of snow density via sub-surface scattering*, Commun Phys, doi: [10.1038/s42005-026-02490-1](https://doi.org/10.1038/s42005-026-02490-1).
The source code generating Fig. 5 for the above mentioned publication is available at [10.16904/envidat.726](https://doi.org/10.16904/envidat.726).
 Files
`SI01_Reflectance_Coldlab.h5`: Reflectance and partial reflectance data of a snow profile using the [SnowImager](https://www.snowimager.ch/).
`uCT_reference_data.csv`: Reference data extracted from a micro-computed tomography measurement.
Please refer to the `README` of the analysis code at [10.16904/envidat.726](https://doi.org/10.16904/envidat.726) for further information.

en: laboratory-study snow-profile snowimager snow-microstructure snow-stratigraphy snow-density reflection

en: Data for the publication Optical determination of snow density via sub-surface scattering

laboratory-study

display_name: laboratory-study

reflection

display_name: reflection

snow-density

display_name: snow-density

snow-microstructure

display_name: snow-microstructure

snow-profile

display_name: snow-profile

snow-stratigraphy

display_name: snow-stratigraphy

snowimager

display_name: snowimager


en:
This is the source code for modeling preferential snowfall deposition and snowfall downscaling as described in:
Helbig N., Mott R., Bühler Y., Le Toumelin L., Lehning M. (2024) Snowfall deposition in mountainous terrain: a statistical downscaling scheme from high-resolution model data on simulated topographies. Front. Earth Sci. 11, 1308269 (19 pp.). https://doi.org/10.3389/feart.2023.1308269
The code reads wind speed, wind direction, and snowfall values for each time step from the example file meteo.txt, as well as terrain elevations (DEM) from dem.txt. The snowfall value is then downscaled to the fine grid defined by the DEM and written to pref_dep.txt.
The current version can be found in the WSL/SLF Gitlab repository:
https://gitlabext.wsl.ch/snow-models/statistical-preferential-deposition-model

en: preferential-deposition statistical-model snowfall mountains downscaling

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: Source code for a preferential snowfall deposition model

downscaling

display_name: downscaling

mountains

display_name: mountains

preferential-deposition

display_name: preferential-deposition

snowfall

display_name: snowfall

statistical-model

display_name: statistical-model


en:
The repository contains the source code necessary to reproduce Figs. 2-5 of the publication: L. Mewes, H. Löwe, M. Schneebeli & B. Walter, *Optical determination of snow density via sub-surface scattering*, Commun Phys, doi: [10.1038/s42005-026-02490-1](https://doi.org/10.1038/s42005-026-02490-1).
The data for Fig. 5 of the above mentioned publication is available at [10.16904/envidat.724](https://doi.org/10.16904/envidat.724).
Please refer to the `README` in this repository for additional information.
- **License:** The scripts in this repository are licensed under the MIT License; see LICENSE.txt for the full text.
 Files
`generate_figures.py`: Main script to generate the figures of the publication.
`snow_optics.py`: Core radiative-transfer functions.
`snow_image.py`: Utilities for loading and processing SnowImager ([www.snowimager.ch](https://www.snowimager.ch)) HDF5 data.
`helper.py`: Miscellaneous helper functions.
`lambertw.py`: Lambert W function implementation (John Burkardt, 2023, MIT license, -https://people.sc.fsu.edu/~jburkardt/py_src/lambert_w/lambert_w.py-).
 Third party resources
- Refractive indices of ice are taken from 'Warren, S. G., and R. E. Brandt (2008), Optical constants of ice from the ultraviolet to the microwave: A revised compilation, J. Geophys. Res., 113, D14220, doi:[10.1029/2007JD009744](https://doi.org/10.1029/2007JD009744).' available at: https://refractiveindex.info/database/data/main/H2O/nk/Warren-2008.yml
- The Lambert *W* function is implemented using the code of John Burkardt, modified 20 June 2023 and distributed under the MIT license (-https://people.sc.fsu.edu/~jburkardt/py_src/lambert_w/lambert_w.py-).
- The source code in this repository is part of a larger project for post-processing [SnowImager](https://www.snowimager.ch) data hosted at [https://code.wsl.ch/snow-physics/snowimagerpro](https://code.wsl.ch/snow-physics/snowimagerpro).

en: snow-microstructure snow-density snow-stratigraphy reflection laboratory-study snow-profile snowimager

envidat

en: EnviDat: the Environmental Data Portal

en: Source code for the publication Optical determination of snow density via sub-surface scattering

en:
Resource Title: Source code
    Size: 22825 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/5ef9984d-7fd8-4b95-87c4-f479b2e5ac13/resource/9af1ca7b-8780-46ec-abbc-e4b6890eead6/download/src.zip
    Description: Source code to generate the figures for Mewes et al., Commun Phys, 2026.

The scripts in this repository are licensed under the MIT License; see LICENSE.txt for the full text.

en:
Resource Title: README.md
    Size: 5181 bytes
    Format: text/markdown
    URL: https://www.envidat.ch/dataset/5ef9984d-7fd8-4b95-87c4-f479b2e5ac13/resource/97d46f1d-9321-4b1a-9a72-d79978da633f/download/readme.md
    Description: Instructions to generate figures for Mewes et al., Commun Phys, 2026.

format: markdown


en: This is the metadata collected in the Blue-Green Biodiversity Beavers project running from 2021 till 2025 about how beavers affect the biodiversity and ecosystem. See the linked datasets for studies and methods.

en: metadata freshwater soil beaver bats deadwood

en: Blue-Green Biodiversity Beavers affecting Ecosystems

envi

en: Environment

bats

display_name: bats

beaver

display_name: beaver

deadwood

display_name: deadwood

freshwater

display_name: freshwater

metadata

display_name: metadata

soil

display_name: soil


en:
This data set includes 57 years of hydrometeorological measurements from small (first-order) catchments in the pre-alpine valley Alptal. Here we provide daily mean values; values in hourly or 10-min resolution can be provided on demand.
Runoff has been measured at the outlet of three small (first-order) catchments of approximately 1 km2 area: Erlenbach (two independent runoff measurements), Vogelbach and Lümpenenbach. The catchments are similar with regard to geology (Flysch) and soil conditions (clay soils), but differ in forest coverage (20 to 60%). A detailed description of the catchments can be found at https://www.wsl.ch/alptal  .
Runoff in these small catchments is typically very dynamic and can temporally carry large amounts of sediment and large wood. Thus, the accuracy of the measurements at very large flow is limited.
Meteorological variables have been measured on a meadow (Erlenhöhe) located in the Erlenbach catchment at 1220 m a.s.l. using a standard meteorological station (incl. ventilated air temperature and heated rain gauges). In addition, precipitation has also been recorded at two other locations (in the Vogelbach and Lümpenenbach catchments).
Snow measurements have been conducted weekly to monthly since 1968 at more than 15 locations (30-m transects) representing different altitudes, aspects and land uses (meadow, forest). In addition, snow depth has been recorded continuously since 2003 at Erlenhöhe, and for this location we also include a simulation of snow depth and SWE (using the numerical models COUP and DeltaSnow) that assimilates the manual weekly snow-course measurements. Details on these snow measurements can be found in Stähli, M. and Gustafsson, D. 2006. Hydrol. Proc., 20, 411-428. doi: 10.1002/hyp.6058.
Further information on the methods and sensors can be found at https://www.wsl.ch/alptal  .
A first version of this data set (for the period 1968-2017) was uploaded in June 2018 at the occasion of the 50-year anniversary. This original data set was updated in February 2021 (with data from 2018 and 2019), and this data set was used for a longterm trend analysis, submitted for publication in a special issue of Hydrological Processes. Further updates of the data set (with data from 2020 to 2022) were uploaded in March 2023, February 2024, March 2025 and January 2026.

en: snow alptal meteorological-data subalpine runoff first-order-catchment

en: Longterm hydrological observatory Alptal (central Switzerland)

en:
Resource Title: Runoff daily mean Alptal 1968-2025 EnviDat updated
    Size: 2474639 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/4de5d4cd-f265-48b9-98a1-290d6f78fb23/resource/bb1f67fd-4bd6-46fe-8b0a-e2ba2c076842/download/runoff_daily-mean_alptal_1968-2025_envidat_updated.xlsx
    Description: Runoff, water temperature and electrical conductivity have been measured since 1968 at the outlet of three torrential catchments (with an area of approximately 1 km2 each) located in the Alptal valley: Erlenbach, Lümpenenbach and Vogelbach. This data set provides daily mean values; data at 10-min resolution can be provided on request for the period 1984-2025 (contact: alptal@wsl.ch).

en:
Resource Title: Manual snow measurements Alptal (1968-2022)
    Size: 1040241 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/4de5d4cd-f265-48b9-98a1-290d6f78fb23/resource/3fd1e126-25cc-490b-bb90-5fca04dc4ee9/download/snow-measurements-alptal-1969-2022_envidat_updated.xlsx
    Description: Snow depth, snow density and snow water equivalent have been measured since winter 1968/69 along more than 15 transects distributed across the Alptal valley representing different altitudes, aspects and land use (closed forest and open meadows). Length of the snow courses: 20 to 30 m. The measurement interval has been weekly to monthly.
More details about the locations and methods can be found in Stähli, M.; Gustafsson, D., (2006). Long-term investigations of the snow cover in a subalpine semi-forested catchment. Hydrological Processes, 20, 411-428. doi: 10.1002/hyp.6058.

en:
Resource Title: Snow measurements Alptal 1969-2025 EnviDat updated
    Size: 1059062 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/4de5d4cd-f265-48b9-98a1-290d6f78fb23/resource/81eb8552-6178-4071-97f5-905416ed9972/download/snow-measurements-alptal-1969-2025_envidat_updated.xlsx
    Description: Snow depth, snow density and snow water equivalent have been measured since winter 1968/69 along more than 15 transects distributed across the Alptal valley representing different altitudes, aspects and land use (closed forest and open meadows). Length of the snow courses: 20 to 30 m. The measurement interval has been weekly to monthly. More details about the locations and methods can be found in Stähli, M.; Gustafsson, D., (2006). Long-term investigations of the snow cover in a subalpine semi-forested catchment. Hydrological Processes, 20, 411-428. doi: 10.1002/hyp.6058.

en:
Resource Title: Daily runoff data from three steep torrents in the Alptal (1968-2022)
    Size: 2380268 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/4de5d4cd-f265-48b9-98a1-290d6f78fb23/resource/aae85e10-27fc-48bd-9f4d-f30a65f06b17/download/runoff_daily-mean_alptal_1968-2022_envidat_updated.xlsx
    Description: Runoff, water temperature and electrical conductivity have been measured since 1968 at the outlet of three torrential catchments (with an area of approximately 1 km2 each) located in the Alptal valley: Erlenbach, Lümpenenbach and Vogelbach. This data set provides daily mean values; data at 10-min resolution can be provided on request for the period 1984-2022 (contact: alptal@wsl.ch).

en:
Resource Title: Daily meteorological and snow data (1968-2022) Alptal
    Size: 2296381 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/4de5d4cd-f265-48b9-98a1-290d6f78fb23/resource/1207f33e-6efd-467f-8bf0-9e3303d529a7/download/meteorological-data_alptal_1968-2022_envidat_updated.xlsx
    Description: Air temperature, dew point temperature, relative humidity, wind speed, precipitation and global radiation have been measured (since 1981) on a meadow (Erlenhöhe) in the Erlenbach catchment. It is located at 1'220 m a.s.l. with an exposure towards west. In order to assess the spatial variability of precipiation, two additional rain gauges have been running in the Vogelbach and Lümpenenbach catchment, respectively.
For the period before 1981, meteorological variables have been extrapolated from the nearby MeteoSwiss station Einsiedeln (ca. 15 km north) to the WSL station Erlenhöhe using a linear correction factor for air temperature, wind speed and precipitation.
Snow depth has been recorded automatically since 2003. Snow water equivalent has been calculated using two numerical models: COUP model (Jansson, 2012) and DeltaSnow model (Winkler et al., 2021)

Jansson, P.-E. (2012). COUP model: model use, calibration, and validation.Transactions of the ASABE, 55(4), 1335–1344.
Winkler, M., et al. (2021): Snow water equivalents exclusively from snow depths and their temporal changes: the Δsnow model, Hydrol. Earth Syst. Sci., 25, 1165-1187, 10.5194/hess-25-1165-861 2021.

en:
Resource Title: Meteorological data Alptal 1968-2025 EnviDat updated
    Size: 2527068 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/4de5d4cd-f265-48b9-98a1-290d6f78fb23/resource/92245b92-5f2b-48a0-920d-4406cddc7d15/download/meteorological-data_alptal_1968-2025_envidat_updated.xlsx
    Description: Air temperature, dew point temperature, relative humidity, wind speed, precipitation and global radiation have been measured (since 1981) on a meadow (Erlenhöhe) in the Erlenbach catchment. It is located at 1'220 m a.s.l. with an exposure towards west. In order to assess the spatial variability of precipitation, two additional rain gauges have been running in the Vogelbach and Lümpenenbach catchment, respectively. For the period before 1981, meteorological variables have been extrapolated from the nearby MeteoSwiss station Einsiedeln (ca. 15 km north) to the WSL station Erlenhöhe using a linear correction factor for air temperature, wind speed and precipitation. Snow depth has been recorded automatically since 2003. Snow water equivalent has been calculated using two numerical models: COUP model (Jansson, 2012) and DeltaSnow model (Winkler et al., 2021)

Jansson, P.-E. (2012). COUP model: model use, calibration, and validation.Transactions of the ASABE, 55(4), 1335–1344. Winkler, M., et al. (2021): Snow water equivalents exclusively from snow depths and their temporal changes: the Δsnow model, Hydrol. Earth Syst. Sci., 25, 1165-1187, 10.5194/hess-25-1165-861 2021.

alptal

display_name: alptal

first-order-catchment

display_name: first-order-catchment

meteorological-data

display_name: meteorological-data

runoff

display_name: runoff

snow

display_name: snow

subalpine

display_name: subalpine


en:
High-resolution information on climatic conditions is essential to many applications in environmental and ecological sciences. Here we present the CHELSA (Climatologies at high resolution for the earth’s land surface areas) data of downscaled temperature and precipitation to a high resolution of 30 arc sec. The temperature algorithm is based on statistical downscaling of atmospheric temperatures. The precipitation algorithm incorporates orographic predictors including wind fields, valley exposition, and boundary layer height, with a subsequent bias correction.

CHELSA data published in EnviDat includes the deprecated version 1.2 (originally published under 10.5061/dryad.kd1d4). Please use the current 2.1 version.
Paper Citation:
 - _Karger DN. et al. Climatologies at high resolution for the earth’s land surface areas, Scientific Data, 4, 170122 (2017)  [doi: 10.1038/sdata.2017.122](https://doi.org/10.1038/sdata.2017.122)._

en: climatology free-climate-data climate climate-layers climate-change temperature precipitation bioclim

envidat

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

en: EnviDat: the Environmental Data Portal

en:
Resource Title: CHELSA Technical Documentation
    Size: 285413 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/2adb0c83-4653-4337-af28-f75c63ab7c74/resource/61fff0a7-6abb-45f7-a5f6-48f6e2c24851/download/chelsa_file_specification.pdf
    Description: Technical documentation document including the variable names, units, scaling, offset, and background.

en:
Resource Title: CHELSA V2.1 (current)
    Size: 2308974418330 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.unil.cloud.switch.ch%2Fchelsa02%2F&prefix=chelsa%2Fglobal%2Fclimatologies%2F
    Description: CHELSA Version 2.1 based on ERA5 forcings and CMIP6

en:
Resource Title: CHELSA V1.2 (deprecated)
    Size: 1319413953331 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fchelsav1%2F
    Description: CHELSA Version 1.2 based on ERA-Interim forcings and CMIP5

bioclim

display_name: bioclim

climate

display_name: climate

climate-change

display_name: climate-change

climate-layers

display_name: climate-layers

climatology

display_name: climatology

free-climate-data

display_name: free-climate-data

precipitation

display_name: precipitation

temperature

display_name: temperature


en: This is an R script written to calculate the relative terrain aspect parameter, which is utilized in the preferential snowfall downscaling scheme for mountainous terrain. The code reads a terrain aspect angle grid from file 'terrain_aspect_grid.txt' and  writes the computed relative terrain aspect angle grid to file 'delta_psi_grid.txt'.

en: downscaling complex-topography preferential-deposition r-script snowfall

en: Snowfall  downscaling Source code to calculate the relative terrain aspect parameter

envi

en: Environment

complex-topography

display_name: complex-topography

downscaling

display_name: downscaling

preferential-deposition

display_name: preferential-deposition

r-script

display_name: r-script

snowfall

display_name: snowfall


en:
This is the source code for computing the seasonal fractional snow-covered area. It is written in Fortran 90. The code reads snow depth (HS) and snow water equivalent (SWE) data from the provided example file HS_SWE.txt and writes the computed fractional snow-covered area (fSCA) to a file fSCA.txt.
The current version can be found in the WSL/SLF Gitlab repository:
https://gitlabext.wsl.ch/snow-models/fractional-snow-covered-area

en: snow-water-equivalent hysteresis snow-depth snow-cover-modeling subgrid-topography source-code

en: Seasonal fractional snow-covered area algorithm

hysteresis

display_name: hysteresis

snow-cover-modeling

display_name: snow-cover-modeling

snow-depth

display_name: snow-depth

snow-water-equivalent

display_name: snow-water-equivalent

source-code

display_name: source-code

subgrid-topography

display_name: subgrid-topography


en:
Carabid beetle and wild bee occurrences in the city of Zurich, Switzerland.
Dataset available upon request (An agreement between the data provider and the data recipient is necessary).

en: bettergarden gardens niche-breadth ecology species functional-traits urban-ecology community-assembly environmental-heterogeneity ground-beetle ground-beetles trait wild-bee functional-diversity garden allotments allotment wild-bees diversity composition niche urbanization functional bettergardens species-composition

en: The origin of urban communities: from the regional species pool to community assemblages in city

en:
Resource Title: Arthropod-databank query used to access data.
    Size: 7751 bytes
    Format: application/sql
    URL: https://www.envidat.ch/dataset/33eb0e1a-fa8b-4b57-8db9-7a929feda811/resource/040d9b89-6455-4af9-8092-47e4fdd487d8/download/fido_global_extract-2019-10-30_13-31-00-urban-carabidae-apidae.sql
    Description:

format: sql

en:
Resource Title: Urban carabid and bee species city of Zurich Switzerland
    Size: 12151612 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/33eb0e1a-fa8b-4b57-8db9-7a929feda811/resource/0d32e239-6d49-4d69-a1fd-81a3cd854591/download/fido_global_extract-2019-10-30_13-31-00-urban-carabidae-apidae.txt
    Description: Carabid beetle and wild bee occurrences in the city of Zurich, Switzerland, from the years (project) 2009 (BiodiverCity), 2011 (ENHANCE) and 2016 (BetterGardens).

format: TXT

media_type: text/plain

allotment

display_name: allotment

allotments

display_name: allotments

bettergarden

display_name: bettergarden

bettergardens

display_name: bettergardens

community-assembly

display_name: community-assembly

composition

display_name: composition

diversity

display_name: diversity

ecology

display_name: ecology

environmental-heterogeneity

display_name: environmental-heterogeneity

functional

display_name: functional

functional-diversity

display_name: functional-diversity

functional-traits

display_name: functional-traits

garden

display_name: garden

gardens

display_name: gardens

ground-beetle

display_name: ground-beetle

ground-beetles

display_name: ground-beetles

niche

display_name: niche

niche-breadth

display_name: niche-breadth

species

display_name: species

species-composition

display_name: species-composition

trait

display_name: trait

urban-ecology

display_name: urban-ecology

urbanization

display_name: urbanization

wild-bee

display_name: wild-bee

wild-bees

display_name: wild-bees


en:
Base data which were used for the methodology projecting future regional snow depths based on temperature scenarios. This study was supported by Seilbahnen Schweiz, Schweiz Tourismus, Seco and Speed2Zero.
The data is split in three folders:
- Literature-Fit dataset
- Literature-Validation dataset
- Projections
The Literature-Fit dataset is the data which was used to retrieve the fit parameters a, Delta b and Delta c, for different elevations and temperature scenarios, which can be found in data/literature_fit/fitfactor.csv. Those fit factors were used to project future snow depths from climatological snow depths. Futhermore, this dataset was used to link decreases in mean snow depths for different seasonal periods to the NDJFMA period (November until April, in total six months), those differences in reduction values can be found in data/literature_fit/difference_decrease_4differentperiods.csv.  The raw reference and future snow depths of different studies and different elevation and temperature scenarios (dt) can be found in data/literature_fit/literature_data/* where each file is named by data_author_station_dt.csv.
The Literature-Validation dataset can be found in data/literature_validation/literature_data.csv contains the reference, RCP scenario, reference period, projected period and corresponding temperature scenarios. Furthermore, it contains region, elevation and relative decreases with corresponding seasonal periods, and the number of days with a certain amount of snow during the reference period and the projected period, if literature reported these values.
The folder projections contains mean snow depths, 5th and 95th percentile snow depth for each day of the year for the reference period and a temperature scenario of +2°C for all four stations Engelberg, Maloja, Saanenmöser and Weissfluhjoch.

en: snow-climatology future snow-depth alps climate-change

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: Literature based approach to estimate future snow

alps

display_name: alps

climate-change

display_name: climate-change

future

display_name: future

snow-climatology

display_name: snow-climatology

snow-depth

display_name: snow-depth


en:
This dataset forms the base of the paper 'Contrasting canopy air temperatures across complex terrain during the snow season' submitted to JGR Atmospheres. It aims to ensure full reproducibility of the figures by providing all relevant scripts (MATLAB R2024a), functions, processed data, and primary data. The primary data consists of three January-April periods in two Alpine valleys (Flüela, 2023; Monstein; 2024, 2025) of:
i) Ventilated canopy air temperatures and humidity (60s intervals) measured at 2.5 m above ground by automatic weather stations (AWS) at opposing north- and south-facing slopes.
ii) Concurrent AWS observations (15s intervals) at a non-forested site in the Monstein valley (2024, 2025) of incoming LW, SW at approximately 0.5 m above ground. At approximately 2.5 m above ground, RH (ventilated), air temperature (ventilated), wind speed, and wind direction were measured.
iii) Passive-ventilated HOBO loggers measuring air temperature at 0.5 m, 1.0 m, 2.5 m, 4.5 m above ground along vertical profiles installed on stems at 30-minute (2023, 2024) or 15-minute (2025) intervals at multiple sites across at opposing north- and south-facing slopes.
iv) In addition, information on when snowfall occurred and when snow cover was present below the canopy or within the canopy is available for the 2023 and 2024 observation periods.
Full details are available in the corresponding publication (citation reference to be found under 'Related Research' once accepted).

en: subalpine forest-canopy snow forest-snow canopy-cover

envidat

en: EnviDat: the Environmental Data Portal

en: Canopy air temperatures in subalpine forests during three snow seasons

canopy-cover

display_name: canopy-cover

forest-canopy

display_name: forest-canopy

forest-snow

display_name: forest-snow

snow

display_name: snow

subalpine

display_name: subalpine


en:
This repository contains all WRF model outputs and observational data sets used for the paper:
Georgakaki, P., Sotiropoulou, G., Vignon, É., Billault-Roux, A.-C., Berne, A., and Nenes, A.: Secondary ice production processes in wintertime alpine mixed-phase clouds, Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-760, in review, 2021.

en: secondary-ice-production ice-water-content jungfraujoch ice-crystal-number-concentration blowing-snow liquid-water-content wrf swiss-alps

en: Data for the publication "Secondary ice production processes in wintertime alpine mixed-phase clouds"

envi

en: Environment

en:
Resource Title: Observational data
    Size: 4448 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/a014f39f-34c3-499f-9627-0efde504d2e1/resource/4ea9d0c6-106e-424a-9d61-9fc1dc99f576/download/observations.zip
    Description: The .zip file contains 6 .csv files including all microphysical measurements taken at the Jungfraujoch station during the two periods of interest:

* 25-28 January 2014 : northwesterly-winds (NW)
* 29 January - 1 February 2014 : southeasterly-winds (SE)

The total Ice Crystal Number Concentration (ICNC; reported in L⁻¹) is measured by the two-dimensional stereo hydrometeor spectrometer (2D-S; Lawson et al., 2006) over the size range 10-1280 μm. The total ice water content (IWC; reported in gm⁻³) is also derived by the 2D-S data using the Brown and Francis (1995) mass-diameter relationship. Finally, the quantification of the liquid water content (LWC; reported in gm⁻³) is based on the liquid droplet size distribution data derived from a DMT cloud droplet probe (CDP; Lance et al., 2010) over the size range 2-50 μm. The frequency of the measurements in the .csv files is 30 min, to match the output frequency of the model. Datetime is also reported in the files (DD/MM/YYYY h:mm) in UTC.

__Acknowledgment__: Collection and pre-processing of the microphysical measurements has been performed by Gary Lloyd (gary.lloyd@manchester.ac.uk). More details about the instrumentation during the CLACE2014 campaign can be found in Lloyd et al. (2015).

en:
Resource Title: WRF outputs
    Size: 741751014 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/a014f39f-34c3-499f-9627-0efde504d2e1/resource/45b96d72-d1ef-4208-8b22-6c6ab546208b/download/wrf-outputs.zip
    Description: The .zip file contains all the NetCDF outputs produced by the mesoscale Weather Research and Forecasting (WRF) model (version: 4.0.1). Two case studies were simulated in this study, between 25-28 January 2014 (00:00 UTC) and 29 January - 1 February 2014 (00:00 UTC), respectively. The former is denoted as "NW" and the latter as "SE", owing to the prevailing wind conditions at the Jungfraujoch (JFJ) station.

The outputs come from the innermost domain of the simulations with a spatial resolution of 1 km and are extracted from the nearest to JFJ model grid point (46.55°N 7.98°E). The dimensions of each model variable is [145,100], which corresponds to time and height, respectively. The frequency of the outputs is 30 min. Note that the first 24 hours of each simulation (i.e., the first 48 outputs) were considered spin up time.

The following sets of sensitivity simulations were presented in this study:

* CNTRL_NW.nc, CNTRL_SE.nc : Sensitivity simulations performed with the default version of WRF
* DS_PHILL_NW.nc, DS_PHILL_SE.nc : Sensitivity simulations including a description of the droplet shattering process following Phillips et al. (2018)
* DS_SULL_NW.nc, DS_SULL_SE.nc : Sensitivity simulations including a description of the droplet shattering process following Sullivan et al. (2018)
* PHILL_NW.nc, PHILL_SE.nc : Sensitivity simulations including a description of the ice-ice collisional break-up process following Phillips et al. (2017)
* TAKAH_NW.nc, TAKAH_SE.nc : Sensitivity simulations including a description of the ice-ice collisional break-up process following Sullivan et al. (2018) based on Takahashi et al. (1995)
* TAKAHrim_NW.nc, TAKAHrim_SE.nc : Same set-up as before but applied only to collisions between rimed ice particles
* BIPS_Xk0_DY_NW.nc, BIPS_Xk0_DY_SE.nc : Sensitivity simulations including a source of Xk0 (either 10.0 or 100.0 L⁻¹) ice crystals with sizes of DY (either 10 or 100 μm) in the first atmospheric level of the model
* BIPS100_PHILL_NW.nc, BIPS100_PHILL_SE.nc : Sensitivity simulations where the combined effect of blowing snow and ice-ice collisional break-up is examined

blowing-snow

display_name: blowing-snow

ice-crystal-number-concentration

display_name: ice-crystal-number-concentration

ice-water-content

display_name: ice-water-content

jungfraujoch

display_name: jungfraujoch

liquid-water-content

display_name: liquid-water-content

secondary-ice-production

display_name: secondary-ice-production

swiss-alps

display_name: swiss-alps

wrf

display_name: wrf


en:
Data associated to the publication "Environmental DNA sequences from aquatic insects indicate freshwater ecosystem state"
 Authors:
Flurin Leugger, Martina Lüthi, Meret Jucker, Virginie Marques, Sarah Thurnheer, Zacharias Kontarakis and Loïc Pellissier
 Contact:
flurinleugger@gmail.com
loic.pellissier@usys.ethz.ch
 Project description:
In this project, we aimed to compare kick-sampling-derived taxa lists and ecosystem state classifications (IBCH: Indece biologique Suisse) with eDNA metabarcoding and CRISPR-Dx. Additionally, we calculated the association with environmental variables and ecosystem state.
We retrieved the kick-sampling-derived data from Haberthür et al. (2021) and Keck et al. (2023). We collected eDNA samples in 36 sites in the Rhine catchment in Switzerland (lowland) which are used for the national monitoring of freshwater in Summer 2024. We extracted the samples in the clean lab at ETH using the protocol described in Leugger et al. (2025). We used the 16S Ins primer (Elbrecht et al. 2016) for metabarcoding and for CRISPR analysis. To select indicator eDNA metabarcoding sequences, we applied a machine learning approach combining LASSO and rpart decision trees. For CRISPR-Dx, we used the rules of Leski et al. (2023) to in silicon predict detections based on the metabarcoding sequences and used the same machine learning approach as for the indicator metabarcoding eDNA sequences (see publication for more details). The data for the environmental variables is from the SWECO25 database (https://zenodo.org/communities/sweco25/records?q=&l=list&p=1&s=10&sort=newest; Külling et al. 2024).
 Folders:
 catchments\:
Catchments in Switzerland, downloaded from https://data.geo.admin.ch/browser/index.html/collections/ch.bafu.wasser-einzugsgebietsgliederung/items/wasser-einzugsgebietsgliederung?.language=en&.asset=asset-wasser-einzugsgebietsgliederung_2056-gpkg-zip
The subfolder upstream_catchments includes the catchment for each buffer size tested.
comparison_classification_methods\:
File with the ecosystem state classification based on kick-sampling, indicator eDNA metabarcoding sequences (using the rpart decision tree) and CRISPR-Dx (using predicted, lab and retrained rpart trees).
 eDNA\:
 Folder metabarcoding\:
Raw and cleaned metabarcoding data (ASVs) per environmental extract (EVE), including taxa information from Ecotag reference data base. Additionally, the rpart trees for indicator sequences only from Ephemeroptera and all EPT are provided.
Columns which might not be self explanatory
taxon: identified taxon
rank: rank of identified taxon
nb_reads: read numbers
EVS and metabarcoding: key columns to link with metadata files
ASV_cleaned_by_site.csv: Read count by site (after cleaning)
ASV_raw_by_site.csv: Read count by site (before cleaning), column 'NC' is for the negative controls
sequence_count_per_site.csv: Comparison of reads per site before and after cleaning/filtering. 'NC' refers again to Negative Controls.
 Folder CRISPR\:
crispr_by_site.csv: Lab-based detection of the guide per site. Maximum number of detections is 6, as each site had two environmental extracts (EVE), and the PCR replicates were combined in 3 pools each. GRN refers to lab internal numbering of CRISPR-Dx assays.
detection_matrix_Ephemeroptera_28_site.csv: Predicted detection based on eDNA metabarcoding sequences and the model of Leski et al 2023 per site.
rpart_model_Ephemeroptera.rds: best performing rpart model for ecosystem state classification using the predicted CRISPR-Dx detections
rpart_model_retrained.rds: best performing rpart model for ecosystem state classification using the actual lab-based CRISPR-Dx detections (thus "retrained" based on actual detections).
 IBCH\:
IBCH_classification_filtered_and_extended.csv: includes IBCH_cat (ecosystem category from kick-sampling with IBCH 2019 categorization).
IBCH_taxa_kick-sampling.csv: contains taxa detect per site (site_code as column name to link with metadata or eDNA data)
kicknet_Trend_IBCH_sites.csv: taxa detected by site, raw data
 metadata\:
Folder containing files with overview of site names, extract number and coordinates. Columns named "metabarcoding" (and "EVS") are keys to link rows from the different tables.
 SWECO25\:
Folder containing raster stack from SWECO25 data (Külling et al. 2024) used in the article and a table with the extracted variable value per site/catchment with the different upstream buffer sizes tested.
site_code: Code for the sampling site, see also metadata to link to EVS
Temperature_avg: annual mean temperature in upstream catchment [°C]
Precip_annual: annual precipitation [mm]
Population_density: mean population density in 25m cells
Traffic_noise: noise levels
EVI, NDVI and LAI: each standard deviation (sd) and average (avg) value per upstream catchment
Natural rivers: proportion of upstream river length which is classified as natural
Little-disturbed_rivers: proportion of upstream river length which is classified as little disturbed
Heavily-disturbed_rivers: proportion of upstream river length which is classified as heavily disturbed
unnatural_rivers: proportion of upstream river length which is classified as unnatural
culverted_rivers: proportion of upstream river length which is culverted
Forest_edges: proportion of forest edges in upstream catchment
Forest: proportion of forest in upstream catchment
Crops: proportion of crops in upstream catchment
Built_environment: proportion of built environment in upstream catchment
buffer: buffer width for upstream catchment area [m]
catchment_area_m2: upstream catchment area in square meters
 References:
Elbrecht, V., Taberlet, P., Dejean, T., Valentini, A., Usseglio-Polatera, P., Beisel, J. N., Coissac, E., Boyer, F., & Leese, F. (2016). Testing the potential of a ribosomal 16S marker for DNA metabarcoding of insects. PeerJ, 2016(4). https://doi.org/10.7717/peerj.1966
Haberthür, M. (2021). Ergebnisse der 3. Erhebung NAWA-Trend Los 2, Makrozoobenthos. https://www.google.com/url?sa=t&source=web&rct=j&opi=89978449&url=https://www.bafu.admin.ch/dam/bafu/de/dokumente/wasser/externe-studien-berichte/nawa_trend_biologie_2019-teil_makrozoobenthos.pdf.download.pdf/nawa_trend_biologie_2019-teil_makrozoobenthos.pdf&ved=2ahUKEwjI5crG-IaPAxUF_gIHHQisBZEQFnoECBgQAQ&usg=AOvVaw1QL3GRZdTllPsHLQ6hQtlP
Külling, N., Adde, A., Fopp, F., Schweiger, A. K., Broennimann, O., Rey, P. L., Giuliani, G., Goicolea, T., Petitpierre, B., Zimmermann, N. E., Pellissier, L., Altermatt, F., Lehmann, A., & Guisan, A. (2024). SWECO25: a cross-thematic raster database for ecological research in Switzerland. Scientific Data, 11(1). https://doi.org/10.1038/s41597-023-02899-1
Leski, T. A., Spangler, J. R., Wang, Z., Schultzhaus, Z., Taitt, C. R., Dean, S. N., & Stenger, D. A. (2023). Machine learning for design of degenerate Cas13a crRNAs using lassa virus as a model of highly variable RNA target. Scientific Reports, 13(1), 6506. https://doi.org/10.1038/s41598-023-33494-4
Leugger, F., Lüthi, M., Schmidlin, M., Kontarakis, Z., & Pellissier, L. (2025). Rapid field-based detection of a threatened and elusive species with environmental DNA and CRISPR-Dx. Global Ecology and Conservation, 59, e03518. https://doi.org/10.1016/j.gecco.2025.e03518

en: river-restoration dna-metabarcoding biomonitoring crispr-dx edna aquatic-invertebrates landuse biodiversity-monitoring conservation

en: Assessing ecosystem state with environmental DNA of aquatic insects

en:
Resource Title: eDNA.zip
    Size: 885782 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/3c77b20b-7b1f-4ccc-9ece-aca9b4d680b8/resource/d1e0c8df-b744-44f4-9721-e95e144bd7cc/download/edna.zip
    Description:

en:
Resource Title: comparison_classification_methods.zip
    Size: 1165 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/3c77b20b-7b1f-4ccc-9ece-aca9b4d680b8/resource/a64df406-4654-423e-b5d5-a3835fb1ddc1/download/comparison_classification_methods.zip
    Description:

en:
Resource Title: catchments.zip
    Size: 244292996 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/3c77b20b-7b1f-4ccc-9ece-aca9b4d680b8/resource/352b1914-eab0-44eb-af50-1629b7c59060/download/catchments.zip
    Description:

en:
Resource Title: Readme.txt
    Size: 6898 bytes
    Format: text/plain
    URL: https://www.envidat.ch/dataset/3c77b20b-7b1f-4ccc-9ece-aca9b4d680b8/resource/f477b2e4-59f5-495d-b7fa-7a611161fb36/download/readme.txt
    Description:

en:
Resource Title: IBCH.zip
    Size: 13178 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/3c77b20b-7b1f-4ccc-9ece-aca9b4d680b8/resource/02849ade-2de9-43ce-b2bb-c99b0749f52f/download/ibch.zip
    Description:

en:
Resource Title: metadata.zip
    Size: 18080 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/3c77b20b-7b1f-4ccc-9ece-aca9b4d680b8/resource/2596f08b-959e-45d1-9aaa-6694b81e43c2/download/metadata.zip
    Description:

aquatic-invertebrates

display_name: aquatic-invertebrates

biodiversity-monitoring

display_name: biodiversity-monitoring

biomonitoring

display_name: biomonitoring

conservation

display_name: conservation

crispr-dx

display_name: crispr-dx

dna-metabarcoding

display_name: dna-metabarcoding

edna

display_name: edna

landuse

display_name: landuse

river-restoration

display_name: river-restoration


en:
Raw data of paper: A recent ash dieback infection neither affects emerald ash borer
performance nor triggers a substantial systemic phytochemical
defense response in European ash (https://doi.org/10.1007/s10340-025-01981-4)
Raw data on emerald ash borer (EAB) weight gain, mortality, development and longevity. Raw data of ash phloem and leaf chemistry. Raw data of ash dieback (ADB) lesion length.

en: ash-dieback fraxinus-excelsior pest-invasion metabolomics agrilus-palnipennis

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: Raw data-A recent ash dieback infection neither affects emerald ash borer performance nor triggers a substantial systemic phytochemical defense response in European ash

agrilus-palnipennis

display_name: agrilus-palnipennis

ash-dieback

display_name: ash-dieback

fraxinus-excelsior

display_name: fraxinus-excelsior

metabolomics

display_name: metabolomics

pest-invasion

display_name: pest-invasion


functional-invertebrate-groups-dataset

en: Collected Invertebrate data using pitfall traps at streetlights with different characteristics at three different sites in Switzerland (Birmensdorf, Lägern & Alpthal). LED characteristics are LED color temperature, light level and luminaire shape (K, L_level, Diff). Additionally, we had two pitfall trap positions: Center (C; 100% light intensity)) and  Periphery (P; 10% light intensity). The traps were emptied weekly over a period of two summers (2021 & 2022). The samples were sorted into 40 different taxonomic invertebrate groups. We included weeks where we turned of the light for a different experiement, these weeks were excluded from this dataset.

en: led invertebrates artificial-lighting light-pollution alan community-composition functional-groups

en: Functional Invertebrate Groups - Dataset

title_for_slug: functional-invertebrate-groups-dataset

envi

en: Environment

alan

display_name: alan

artificial-lighting

display_name: artificial-lighting

community-composition

display_name: community-composition

functional-groups

display_name: functional-groups

invertebrates

display_name: invertebrates

led

display_name: led

light-pollution

display_name: light-pollution


en:
The SwissRad10 dataset contains light availability maps at 10 m and hourly resolution across an entire annual cycle with wall-to-wall coverage across the whole of Switzerland.
Areas below and within 25 m of forests include light availability calculated for both leaf-on and leaf-off canopy structure, and terrain only data is available across the full domain.
The variables sky-view factor and direct-beam transmissivity are both included, allowing estimation of both direct and diffuse light at the ground surface.
The dataset was calculated using the detailed synthetic hemispheric image-based ray-tracing Canopy Radiation Model (CanRad) with the latest airborne lidar and terrain surface data from the swissSURFACE3D dataset.

en: solar-energy terrain solar-irradiance shortwave-radiation radiation-transfer forests lidar light-availability transmissivity sky-view-fraction

en: SwissRad10 Hourly light availability maps at 10 m resolution over Switzerland

forests

display_name: forests

lidar

display_name: lidar

light-availability

display_name: light-availability

radiation-transfer

display_name: radiation-transfer

shortwave-radiation

display_name: shortwave-radiation

sky-view-fraction

display_name: sky-view-fraction

solar-energy

display_name: solar-energy

solar-irradiance

display_name: solar-irradiance

terrain

display_name: terrain

transmissivity

display_name: transmissivity


en:
This repository contains data related to an interdisciplinary study on playgrounds, looking at both playground vegetation and the well-being of pre-school children using those playgrounds. This project was funded by and initiated at the Institute for Landscape Planning and Ecology (ILPÖ) of the University of Stuttgart, Germany. Data was collected by ILPÖ. The project was finalised in collaboration with the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL). The aim of the study was to (1) describe playground vegetation (species richness and diversity at the ground, shrub and tree layers; habitat structure); (2) describe preschool children’s well-being and nature-connectedness; and (3) investigate whether there is a relationship between plant diversity and well-being while exploring potential other predictors of well-being, including children’s and parents’ or carer’s nature-connectedness, greenspace exposure, seasonality, and socio-demographic background.
We sampled ground (-1m height), shrub (1-2m height) and tree (-2m hieght) vegetation of 29 playgrounds of Stuttgart's inner city. Sampling took place between May 25 and July 01, 2021. Ground layer vegetation was sampled in ten one-by-one m2 quadrats per playground, within which we recorded the cover of each species based on the Braun-Blanquet scale. Woody vegetation was exhaustively sampled within the playgrounds and in a surrounding two meters buffer, recording each individual plant. Vegetation cover was visually estimated as a percentage for each vegetation layer, namely the ground, shrub and tree (canopy) layers.
In parallel, we distributed questionnaires to parents and carers to assess the well-being and connectedness-to-nature of preschool children (aged 6 or younger) across the seasons. The questionnaire covered children's (1) use of greenspaces, (2) nature-connectedness, (3) well-being, and (4) socio-demographic variables. Questionnaires were distributed accross all seasons: sampling seasons included autumn (Oct-Nov 2021), winter (Jan-Feb 2022), spring (April-May 2022) and summer (June-July 2022). Ethical approval was granted by the University of Stuttgart Commission on Responsibility in Research (Az. 21-033).

en: well-being biodiversity green-spaces seasons urban

en: Playground biodiversity and preschool children well-being

en:
Resource Title: Spielplatz Fragebogen_Rumänisch.pdf
    Size: 349716 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/0ac43c39-4a0d-40c2-a544-e2a4e6109213/download/spielplatz-fragebogen_rumanisch.pdf
    Description: This document includes the Romanian version of the questionnaire administered to carers of pre-school children.

en:
Resource Title: Spielplatz Fragebogen_Spanisch.pdf
    Size: 345221 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/c57948ab-c230-45c0-a9b2-b60eb3460cfd/download/spielplatz-fragebogen_spanisch.pdf
    Description: This document includes the Spanish of the questionnaire administered to carers of pre-school children.

en:
Resource Title: Spielplatz Fragebogen_Russisch.pdf
    Size: 357530 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/53481be4-b668-48c6-98df-c58961caf97b/download/spielplatz-fragebogen_russisch.pdf
    Description: This document includes the Russian version of the questionnaire administered to carers of pre-school children.

en:
Resource Title: Spielplatz Fragebogen_Englisch.pdf
    Size: 340244 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/b87bc6b7-9aaa-4c86-adfc-52dcf47bcfb4/download/spielplatz-fragebogen_englisch.pdf
    Description: This document includes the English version of the questionnaire administered to carers of pre-school children. This was the original questionnaire, later translated in the 10 most spoken languages in Baden-Württemberg (DE).

en:
Resource Title: Spielplatz Fragebogen_Türkisch.pdf
    Size: 346481 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/f49040c1-0140-4b98-8b3a-b8b6be4fd565/download/spielplatz-fragebogen_turkisch.pdf
    Description: This document includes the Turkish version of the questionnaire administered to carers of pre-school children.

en:
Resource Title: Plant and playground data.xlsx
    Size: 97321 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/eb12671e-2a17-4acf-b181-a68e40fd1fe5/download/plant-and-playground-data.xlsx
    Description: This file contains the playground and plant diversity data for the manuscript "Playground tree diversity: a driver of well-being in preschool children".
The file is separated in five tabs containing:
(1) the overview of the playgrounds,
(2) the overview of all plant species, with their life-history traits and the diversity indexes per layer,
(3) the tree (canoy) layer abundance of each plant species, measured exhaustively in each playground,
(4) the shrub layer abundance of each plant species, measured exhaustively in each playground, and
(5) the ground layer abundance of each plant species, estimated with the Braun-Blanquet scale in 10 quadrats per playground.

en:
Resource Title: Spielplatz Fragebogen_Arabisch.pdf
    Size: 397855 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/56c767f8-0b3d-45c3-9209-2bce6dac682f/download/spielplatz-fragebogen_arabisch.pdf
    Description: This document includes the Arabic version of the questionnaire administered to carers of pre-school children.

en:
Resource Title: Spielplatz Fragebogen_Italienisch.pdf
    Size: 322529 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/6971a33d-2b7d-40d4-8d99-d583aed944d2/download/spielplatz-fragebogen_italienisch.pdf
    Description: This document includes the Italian version of the questionnaire administered to carers of pre-school children.

en:
Resource Title: Spielplatz Fragebogen_Deutsch.pdf
    Size: 364554 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/deca6461-d9a1-4cf4-8739-480e13432408/download/spielplatz-fragebogen_deutsch.pdf
    Description: This document includes the German version of the questionnaire administered to carers of pre-school children.

en:
Resource Title: Spielplatz Fragebogen_Polnisch.pdf
    Size: 361073 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/024bbf41-00b5-4c84-ba75-28e136050d41/download/spielplatz-fragebogen_polnisch.pdf
    Description: This document includes the Polish version of the questionnaire administered to carers of pre-school children.

en:
Resource Title: Spielplatz Fragebogen_Französisch.pdf
    Size: 353495 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/872f9d84-d7a4-498d-9f3e-5851bd9bddfd/download/spielplatz-fragebogen_franzosisch.pdf
    Description: This document includes the French version of the questionnaire administered to carers of pre-school children.

en:
Resource Title: Spielplatz Fragebogen_Ukrainian.pdf
    Size: 1015736 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/1ae17430-7011-40f1-87d5-48f642e997ea/download/spielplatz-fragebogen_ukrainian.pdf
    Description: This document includes the Ukrainian version of the questionnaire administered to carers of pre-school children.

en:
Resource Title: Well-being.xlsx
    Size: 184576 bytes
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/517c3b45-c944-41fd-8f3e-bc37ec321e88/resource/8b624832-b01e-4728-95cc-22644320da26/download/well-being.xlsx
    Description: This file contains the anonymised well-being and nature-connectedness data for the manuscript "Playground tree diversity: a driver of well-being in preschool children".

biodiversity

display_name: biodiversity

green-spaces

display_name: green-spaces

seasons

display_name: seasons

urban

display_name: urban

well-being

display_name: well-being


en:
This repository contains data related to the field experiment of the WP3 (social impacts) of the ALANeX project. This project is a collaboration between the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL) and Elektrizitätswerk des Kantons Zürich (EKZ). It has received funding from the WSL programme EXtremes. The overall objective of the ALANeX project was to assess the ecological and social impact of anthropogenic light at night.
We conducted a randomized field experiment to compare the well-being benefits of exposure to streetlights of different correlated colour temperatures (CCT) during a 20-min stay in the centre of Richterswil, Swizerland, to explore:
 - the impact of exposure to streetlamps of different CCT on affect, self-reported stress and cortisol levels
- the differences in impression of artificial light and of the feeling of safety provided by streetlamps based on its CCT.

en: well-being field-data artificial-lighting urban-landscape stress

envidat

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

en: EnviDat: the Environmental Data Portal

envi

en: Environment

en:
Resource Title: 03_Questionnaire_t1.pdf
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    Format: application/pdf
    URL: https://www.envidat.ch/dataset/e0e1abb0-c6ff-4bf9-ae3e-d7fa56e50c11/resource/94abc98c-0c0b-482c-bf2d-9981f191ef4e/download/02_questionnaire_t1.pdf
    Description: This document includes the questionnaire administered at the first measurement time point (before exposure).

en:
Resource Title: 01_Information sheet.pdf
    Size: 90044 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/e0e1abb0-c6ff-4bf9-ae3e-d7fa56e50c11/resource/9dd17102-a6b3-4a71-b3d3-89b1f198c3f9/download/01_information-sheet.pdf
    Description: This file includes the information sheet provided to participants before they consented to take part in the study.

en:
Resource Title: 05_Anonymised dataset.xlsx
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    URL: https://www.envidat.ch/dataset/e0e1abb0-c6ff-4bf9-ae3e-d7fa56e50c11/resource/fb8c2b1b-d969-4087-9606-f0944391938f/download/05_anonymised-dataset.xlsx
    Description: This file contains data for the manuscript "Randomised trial reveals a mismatch between preferences for and hormonal responses to anthropogenic light colour temperatures".

en:
Resource Title: 04_Questionnaire_t2.pdf
    Size: 486850 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/e0e1abb0-c6ff-4bf9-ae3e-d7fa56e50c11/resource/ca5b4cb0-bc6e-46c0-b177-a92505aedd1e/download/04_questionnaire_t2.pdf
    Description: This document includes the questionnaire administered at the second measurement time point (after exposure).

en:
Resource Title: 02_Particiants consent form.pdf
    Size: 121509 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/e0e1abb0-c6ff-4bf9-ae3e-d7fa56e50c11/resource/5817334b-fad2-47ce-972c-0ac3fb6758d9/download/02_informed-consent.pdf
    Description: This file contains the informed consent document that participants signed to participate in the study.

artificial-lighting

display_name: artificial-lighting

field-data

display_name: field-data

stress

display_name: stress

urban-landscape

display_name: urban-landscape


wasserschloss-europas

en:
*english description below
Die Schweiz als „Wasserschloss Europas“ ist eine etablierte Bezeichnung im öffentlichen Diskurs, die sich im Laufe der Zeit zu einer identitätsstiftenden Metapher entwickelt hat. Die Zeitungsanalyse der letzten 100 Jahre zeigt, wie sich die Verwendung dieser Metapher unter dem Einfluss äusserer Faktoren gewandelt hat. Das Jahr mit den meisten Zeitungsartikeln, in denen die Metapher verwendet wurde, war der Hitzesommer 2003. Weitere Jahre mit häufigem Vorkommen der Metapher fallen mit internationalen Ausstellungen (Expos) zusammen, bei denen sich die Schweiz als „Wasserschloss Europas“ präsentierte oder entsprechende Bezüge herstellte. Dabei diente die Metapher einerseits als Symbol für den Wasserreichtum des Landes, andererseits unterstrich sie die Rolle der Schweiz im Umweltschutz, deren Verantwortung gegenüber den Unterliegern; zudem diente sie der touristischen Vermarktung der Naturlandschaft. Lange Zeit galt der Wasserreichtum in der Schweiz als selbstverständlich, angesichts der rasanten Klimaerwärmung und des damit einhergehenden steigenden Nutzungsdrucks auf die Ressource Wasser und die aquatischen Lebensräume erscheint die Verwendung dieser beschaulichen Metapher als überholt.
Switzerland, as the “Wasserschloss Europas”, is an established term in public discourse that has evolved over time into an identity-shaping metaphor. A newspaper analysis spanning the last 100 years shows how the use of this metaphor has changed in response to external factors. The year with the highest number of newspaper articles employing the metaphor was the heatwave summer of 2003. Other years with high numbers of occurrences coincide with international exhibitions (Expos), where Switzerland presented itself as the “Wasserschloss Europas” or made related references. The metaphor served as a symbol of the country’s abundance of water and, highlighted Switzerland’s role in environmental protection and its responsibility towards downstream countries; it also supported the tourist marketing of its natural landscapes. For a long time, Switzerland’s water wealth was taken for granted. In view of rapid climate warming and the resulting increasing pressure on water resources and aquatic habitats, the use of this idyllic metaphor now seems outdated.

en: zeitungsartikelanalyse metapher wasserressourcen wasserwirtschaft wasserschloss

en: Wasserschloss Europas

title_for_slug: wasserschloss-europas

en:
Resource Title: Wasserschloss_Europas.xlsx
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    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet
    URL: https://www.envidat.ch/dataset/83825ceb-c5ca-4c11-882e-235fd121734b/resource/a2ec7e2b-4c6e-4787-94be-2ee0f3a78455/download/wasserschloss_europas.xlsx
    Description: Sammlung der 226 verwendeten Zeitungsartikel.

en:
Resource Title: Wasserschloss_Europas.csv
    Size: 128150 bytes
    Format: application/vnd.ms-excel
    URL: https://www.envidat.ch/dataset/83825ceb-c5ca-4c11-882e-235fd121734b/resource/73611293-12d3-496b-a721-85b5d0eba126/download/wasserschloss_europas.csv
    Description:

en:
Resource Title: Kodierungsschema_Wasserschloss_Europas.pdf
    Size: 56023 bytes
    Format: application/pdf
    URL: https://www.envidat.ch/dataset/83825ceb-c5ca-4c11-882e-235fd121734b/resource/1ff678b7-aa77-47ae-8fa7-7f78fbc5af34/download/kodierungsschema_wasserschloss_europas.pdf
    Description: Kodierungsschema für die Zeitungsartikelanalyse.

metapher

display_name: metapher

wasserressourcen

display_name: wasserressourcen

wasserschloss

display_name: wasserschloss

wasserwirtschaft

display_name: wasserwirtschaft

zeitungsartikelanalyse

display_name: zeitungsartikelanalyse


en: Countrywide vegetation height models (VHM) were generated for Armenia based on Copernicus Sentinel-2 imagery within the framework of the FORACCA project. “The Forest Restoration and Climate Change in Armenia” (FORACCA) project is funded by the Swiss Agency for Development and Cooperation (SDC). The project is implemented by the Swiss Federal Institute for Forest, Snow, and Landscape Research (WSL) in collaboration with Zoï Environment Network as well as the Forest Alliance of Armenia. A Convolutional Neural Network (CNN) model was trained in Switzerland to estimate the maximum vegetation height at the spatial resolution of the Sentinel-2 pixel of 10 m. Vegetation heights from the spatially higher-resolved VHM Lidar NFI were used as reference data for the CNN training. Then, the model was spatially transferred and VHMs for Armenia were generated annually based on available Sentinel-2 imagery from May – September of the respective year. Further details on the dataset and model to create the Sentinel-2 VHMs can be found in the paper Jiang et al. (2023, https://doi.org/10.1016/j.srs.2023.100099). Contains modified Copernicus Sentinel data.

en: armenia vegetation-height cnn remote-sensing forest sentinel-2 foracca

en: Sentinel-2 Vegetation Height Model Armenia

en:
Resource Title: S2-VHM_2021_max.tif
    Size: 2834678415 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/d5dd3a3d-093e-4206-9e0b-76c6f21c9be1/resource/5b72d532-7a61-45a2-a09a-d83dfa61f9f2/download/s2-vhm_2021_max.tif
    Description:

format: TIFF

media_type: image/tiff

en:
Resource Title: S2-VHM_2025_max.tif
    Size: 3167538381 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/d5dd3a3d-093e-4206-9e0b-76c6f21c9be1/resource/f1b1e699-6f6c-4bb0-89f6-89d8c455c5a2/download/s2-vhm_2025_max.tif
    Description:

en:
Resource Title: S2-VHM_2018_max.tif
    Size: 3167538381 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/d5dd3a3d-093e-4206-9e0b-76c6f21c9be1/resource/cf0e2bc7-a73a-477a-86bc-6ed8e7cd8e8d/download/s2-vhm_2018_max.tif
    Description:

en:
Resource Title: S2-VHM_2024_max.tif
    Size: 3189013217 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/d5dd3a3d-093e-4206-9e0b-76c6f21c9be1/resource/98667a97-fe5d-4d46-a0a0-93a0e951c7e4/download/s2-vhm_2024_max.tif
    Description:

en:
Resource Title: S2-VHM_2022_max.tif
    Size: 3178275799 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/d5dd3a3d-093e-4206-9e0b-76c6f21c9be1/resource/f0b468d3-1f4b-454d-93dc-d01a72902001/download/s2-vhm_2022_max.tif
    Description:

en:
Resource Title: S2-VHM_2023_max.tif
    Size: 3189013217 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/d5dd3a3d-093e-4206-9e0b-76c6f21c9be1/resource/692904ba-e575-4e69-8950-288ffe11a952/download/s2-vhm_2023_max.tif
    Description:

en:
Resource Title: S2-VHM_2020_max.tif
    Size: 3178275799 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/d5dd3a3d-093e-4206-9e0b-76c6f21c9be1/resource/1ccbef32-82b2-463e-a109-80f4f40037cd/download/s2-vhm_2020_max.tif
    Description:

en:
Resource Title: S2-VHM_2019_max.tif
    Size: 3178275799 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/d5dd3a3d-093e-4206-9e0b-76c6f21c9be1/resource/7bde832d-dcba-4df3-b2ff-e01941712029/download/s2-vhm_2019_max.tif
    Description:

en:
Resource Title: S2-VHM_2017_max.tif
    Size: 3178275799 bytes
    Format: image/tiff
    URL: https://www.envidat.ch/dataset/d5dd3a3d-093e-4206-9e0b-76c6f21c9be1/resource/511abee2-19eb-45e9-b28c-23a3f8cada46/download/s2-vhm_2017_max.tif
    Description:

armenia

display_name: armenia

cnn

display_name: cnn

foracca

display_name: foracca

forest

display_name: forest

remote-sensing

display_name: remote-sensing

vegetation-height

display_name: vegetation-height


en:
This repository hosts the experimental data accompanying our publication "The influence of snow microstructure on the compressive mechanical properties of weak snowpack layers" feautured in Acta Materialia.
- Experimental Data and microstructural descriptors:
Full dataset used for the main analysis of the paper. Contains the measured mechanical properties, µCT parameters, further analysis, etc. The column "ID" (e.g. 363)  links this data with the 3D µCT dataset  (e.g. e0000363).
- 3D Data of the segmented µCT scans:
Full dataset containing the raw segmented µCT scans in the MetaIO format. They can be opened using the SimpleITK package (`pip install SimpleITK`).
Note: the Files can be idenfied by their scan number in the filename, (e.g, e0000363)
 `import SimpleITK as sitk `
 `img = sitk.ReadImage("e0000363_crop_seg.mhd") `
 `array = sitk.GetArrayFromImage(img) `  shape: [z, y, x]
`array_xyz = np.transpose(array, (2, 1, 0))`  (Optional) for array axes in [x, y, z]
 `spacing = img.GetSpacing() `                  voxel size (x,y,z)

en: lab-experiment snow-avalanche snow snow-mechanics snow-microstructure

envidat

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

en: EnviDat: the Environmental Data Portal

envi

en: Environment

en:
Resource Title: Dataset_v1.csv
    Size: 64099 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/e3ac64e4-3204-4edb-8b10-b458373d9e1f/resource/5b516f93-a87b-4315-9a02-325e2400ee81/download/dataset_v1.csv
    Description: Dataset containing both the experimental results and microstructural parameters.

en:
Resource Title: 3D_CT_files
    Size: 6442450944 bytes
    Format: No Info
    URL: https://envicloud.wsl.ch/#/?bucket=https%3A%2F%2Fos.zhdk.cloud.switch.ch%2Fenvicloud%2F&prefix=doi%2Fenvidat.648%2F
    Description: MetaIO_files

lab-experiment

display_name: lab-experiment

snow

display_name: snow

snow-avalanche

display_name: snow-avalanche

snow-mechanics

display_name: snow-mechanics

snow-microstructure

display_name: snow-microstructure


en:
This repository hosts the experimental data accompanying our publication, “On the compressive strength of weak snow layers of depth hoar,” featured in the Journal of Glaciology.
-Compressive Strength Data:
Measurements of the compressive strength for 92 artificially grown weak snow samples.
-Microstructural CT Data:
CT-derived microstructural information for each sample, including:
Density
Specific surface area
Connectivity density
Correlation lengths
Anisotropy
-Additional CT Data:
Parent Sample Variability: CT data used to assess the variability of the parent samples.
Temporal Evolution: CT data capturing the evolution within the artificial weak layers.
Reference Data: Information on the reference CT data sourced from the RHOSSA and MOSAiC campaigns.

en: depth-hoar microstructure strength snow snow-mechanics slab-avalanche

en:
Resource Title: ExperimentalData.csv
    Size: 5928 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/f428c8e6-191b-45d4-8b92-239b5f056338/resource/adb3a453-f03a-44cc-b74b-ff9cb12878ec/download/experimentaldata.csv
    Description: Experimental Data: Contains results of the compression experiments and microstructural parameters.

en:
Resource Title: ParentSampleVariability.csv
    Size: 1406 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/f428c8e6-191b-45d4-8b92-239b5f056338/resource/83b74fbf-3d28-4a2e-b856-92573f39977c/download/parent_sample_variability.csv
    Description: Parent sample variability: Contains the CT data used to estimate the parent sample variability.

en:
Resource Title: TimeSeriesData.csv
    Size: 4202 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/f428c8e6-191b-45d4-8b92-239b5f056338/resource/f100da36-5f10-49ba-a38d-140aed84c664/download/timeseriesdata.csv
    Description: Time series data: Contains the CT data of upper slab, weak layer and lower slab used to evaluate the temporal evolution within the artificial samples.

en:
Resource Title: ReferenceDataCT.csv
    Size: 8841 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/f428c8e6-191b-45d4-8b92-239b5f056338/resource/e8f6bc95-aff3-437e-a5a2-b04cb020f330/download/ct_references.csv
    Description: CT Reference Data: Contains sample names, positions, evaluated regions and microstructural parameters based on data from the RHOSSA and MOSAiC campaigns.

MOSAiC:
https://mosaic-portal.org/data/open-mcs/vessel/polarstern/sn_microct/sn_microct/exdata/
https://doi.org/10.1594/PANGAEA.952794

RHOSSA:
https://doi.org/10.16904/envidat.151

depth-hoar

display_name: depth-hoar

microstructure

display_name: microstructure

slab-avalanche

display_name: slab-avalanche

strength

display_name: strength


en: This research data is used to re includes 1 km resolution seed plant species range maps for the Hengduan mountain region (southwest China), elevation information for each species, family-level plant richness data, and habitat heterogeneity data at both Eurasia and Hengduan mountain regions. This research data includes 1 km resolution seed plant species range maps for the Hengduan mountain region (southwest China), elevation information for each species, family-level plant richness data, and habitat heterogeneity data at both Eurasia and Hengduan mountain regions.

en: model-residuals phytodiversity hypervolume habitat-heterogeneity hengduan-mountains

en: Phytodiversity is associated with habitat heterogeneity from Eurasia to Hengduan

en:
Resource Title: Plant range map at Hengduan scale
    Size: 635180593 bytes
    Format: application/x-7z-compressed
    URL: https://www.envidat.ch/dataset/736a30b8-2b01-40b0-b97f-aba77c2272e6/resource/95b657e6-4f16-4d44-aea1-6014d6560b54/download/three_models.7z
    Description: This is the plant range map at the Hengduan mountain scale based on species distribution model, elevation, and county level distribution information

en:
Resource Title: Hengduan plant family richness map
    Size: 159254007 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/736a30b8-2b01-40b0-b97f-aba77c2272e6/resource/fd56e712-502c-4c52-9ec4-fe7f0b461393/download/hengduan-plant-richness.zip
    Description: This is the family level plant richness map in the Hengduan mountain scale at 1km resoution

en:
Resource Title: Eurasia SR and heteorgeneity
    Size: 33861 bytes
    Format: text/csv
    URL: https://www.envidat.ch/dataset/736a30b8-2b01-40b0-b97f-aba77c2272e6/resource/f80b00d6-7381-4789-873c-c2bb4d2aa932/download/sr_eurasia_revision.csv
    Description: This table is used for the Eurasia scale analyses, including both family level species richness map and different heterogeneity predictors

en:
Resource Title: HDM heterogeneity scales
    Size: 210551963 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/736a30b8-2b01-40b0-b97f-aba77c2272e6/resource/092b3ec7-afab-4692-9547-1aacba54f89e/download/hdm_heterogeneity_scales.zip
    Description: The Heterogeneity matrics in the Hengduan mountain scale

en:
Resource Title: Eurasia plant family richness map
    Size: 1149466779 bytes
    Format: application/zip
    URL: https://www.envidat.ch/dataset/736a30b8-2b01-40b0-b97f-aba77c2272e6/resource/8b94b856-31b3-42e3-bfb3-e77d7a54e209/download/eurasia_fam.zip
    Description: This is the plant family level richness map at the Eurasia scale calculated from https://www.nature.com/articles/s41597-021-00997-6

habitat-heterogeneity

display_name: habitat-heterogeneity

hengduan-mountains

display_name: hengduan-mountains

hypervolume

display_name: hypervolume

model-residuals

display_name: model-residuals

phytodiversity

display_name: phytodiversity


en: Data of 13C-pulselabeling experiments in a young beech model ecosystem and a mature pine forest exposed to drought and rewetting. Data include microclimate during the experiment, total PLFA contents, d13C signatures in PLFA , microbial biomass, soil-respired CO2 measure during 30 days following 3-4 hour long pulse labeling with highly 13C-enriched CO2.

en: microbial-biomass drought c13-labeling forest biogeochemical-cycling plfa

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: Gao_Drought resistance and resilience of rhizosphere communities_13C-PLFA

envi

en: Environment

biogeochemical-cycling

display_name: biogeochemical-cycling

drought

display_name: drought

forest

display_name: forest

microbial-biomass

display_name: microbial-biomass

plfa

display_name: plfa