maintainer: Tobias Wechsler

en: decision-making integral-water-management hydropower ecosystem-protection gis

format: SHP

en: Indicators

en: The indicators capture supporting ecosystem functions.

en:
 A spatial dataset and tool to simultaneously assess hydropower potential and ecological potential of the Swiss river network (Version 2016)

 Introduction
The steadily growing demand for energy and the simultaneous pursuit of decarbonisation are increasing interest in the expansion of renewable energies worldwide. In Switzerland, various funding projects have been launched to promote technologies in the field of renewable energies and their application as quickly as possible. With the introduction of a funding instrument in 2009, the number of projects submitted to produce renewable energies increased rapidly. The applications for small hydropower plants (≤ 10 MW) were correspondingly numerous. However, the assessment of the environmental impact and its comparison with hydropower importance is still not standardized.
To provide a basis for decision-making, a methodology was developed to determine the overall hydropower potential of a region. A detailed assessment of each river reach, and the systematic and holistic assessment of small hydropower projects at a regional scale are combined here. The assessment of a river reach is conducted at the river space (i.e., the river and adjacent areas) and at the surrounding landscape level. The HYDROpot_integral methodology was developed as part of Carol Hemund's dissertation (2012) at the University of Bern. It allows the evaluation of river reaches holistically, regarding ecological, social, economic and cultural criteria. As a second part of the overall project, the theoretical hydropower (or hydraulic) potential was calculated for the entire river network, which complemnets the spatial assessment. In particular, it is possible to classify river reaches into those that are more suitable for hydropower production (=”use”) and those that are more suitable for protection.

 Material and method
The HYDROpot_Integral method was developed and tested on the basis of cantonal and national data (Hirschi et al. 2013). The method relies on 73 geodata sets. This holistic assessment is the key element of the entire assessment procedure. Its aim is to quantify the importance of the ecosystem functions in terms of services. The river network (GWN07) is divided into reaches of about 450m and for each reach two study units are defined. The river space (RS) records the ecosystem functions of the water body and the nearby riparian area. The length of the RS is 315 m on average in Switzerland and a maximum of 450 m, whereas the width is based on the FOEN definition (BWG 2001: 18f) and varies between 7-107 m. The surrounding landscape (SLS) is the second survey unit that records the ecosystem functions of the surrounding area over a range of 21 m to 321 m. The SLS is calculated over three times the RS width. The length of the SLS is identical to the length of the RS. The ecosystem functions are divided into three types: regulating (service A), cultural (service B) and provisioning (service C) functions. Accordingly, the assessment of the functions is divided into three parts and three values are assigned to each river reach. The more functions there are and the greater their performance, the higher these values are and the more important the corresponding functions are. Hence, these values quantify the importance of the ecosystem functions and the ecological, cultural and economic ecosystem services of each river reach. The concatenation of ecosystem services results in a value (ABC) that can occur in 125 different versions due to the chosen five-level value scale; i.e. each digit of the three-digit number sequence can be assigned a value between 1 and 5. Each of the 125 combinations, and thus each river reach, has its own characteristics determined by the assessments of the three function types. To record the suitability, the combinations are ranked according to their ecological, cultural and economic ecosystem services. These rules mean that the combination that is most suitable for hydropower production at minimum cost in terms of ecological and cultural ecosystem services and has a high economic potential is ranked first; rank 125 indicates the highest ecological and cultural ecosystem services and the lowest economic services and is therefore most suitable for protection. A river reach that is excluded from hydropower use due to legislation, a so-called priority reach, is given rank 126 from the outset and specially marked. A more detailed description of the methods can be found in Hirschi et al. 2013 [Link]. The dataset presented here presents the latest state of the HYDROpot_integral methodology applied at the national level. Only national data that is easily accessible was used in the preparation of the dataset. The cantonal data, such as renaturation and revitalization, would have to be requested by each canton individually and was excluded here. The nationwide value synthesis was made with R.
A list of data sources can be found here [link to text file]
A list of all parameters can be downloaded here [link to PDF and text files]

 Dataset description
Data is presented as a single shapefile. It contains the river network and all assessment results obtained with HYDROpot_Integral.

 Changes in the methodology compared to the original method (Hirschi et. al 2013)

 * RS_A11 Ecomorphology: recorded for the whole of Switzerland and zero values equated with NA;
individual cantons such as Zug and St. Gallen have no mapped values according to the modular
concept of the federal government, Valais and Graubünden only the main valleys, Ticino and Fribourg not
completely (BAFU 2009).
 * RS_A14 Renaturation and revitalization data: not centrally available at the time of data collection.
centrally available, therefore values in GR were equated with NA.
 * RS_A15 Dilution ratio at wastewater treatment plants (WWTPs) for discharges: Zero values
equal to NA.
 * RS_A20 Water flow: use WASTA (2013) with hydroelectric power plants (> 300 kW) under
Federal control and dams serving hydroelectricity (Dam, as of 2013).
 * RS_C05 Synoptic hazard maps: are cantonally managed at the time of data collection,
Values in GR are marked with a 5 so that the systematics in the decision tree is not affected.
is affected.
 * Water quality (RS_A15, RS_A16, RS_A17, RS_A18, RS_A19): for the evaluation of the function type.
A Nature, it is important whether the median of the five values is less than or equal to 3 in total. This
evaluation is based on the decision tree for evaluating GR (Hirschi et al. 2013:22).
Therefore, an evaluation of the station data is made where critical and possible river segments
with poor quality (median less than 3) exist. Only two longer and one short
sections in Switzerland receive a lower median than 3 for water quality.
 * SLS_B06 Visibility: For 99 percent of the river segments (30,733 of 31,062) in the canton of
Bern (2015 reduced version), the landscape area is considered to be visible. Due to this high number
of sections, a large number of viewpoints in the layer of Swisstopo and
the computation time and computability in ArcGIS, the landscape area is classified as generally viewable
(equal to 1).
16 Method
Additional indicators were added (see Appendix B.2):
 * SLS_A21 Dissection
 * SLS_A22 Forest areas
 * SLS_B03 Hiking trails
 * SLS_B10 Residential and vacation homes
 * SLS_B11 Tourist infrastructure
 * SLS_C01 Landfill
 * SLS_C03 Infrastructure
 * SLS_C05 Industry
 * SLS_C06 Agricultural land
Not to be added, although present to some extent:
 * SLS_B06 Cultural assets of national importance: here, too, the calculability of the visibility analysis is
for the whole of Switzerland is limited
 * SLS_A15 Legally binding protection and land use planning: the individual river sections are not
clearly designated, i.e. no geodata exist
The following data are also not supplemented, as they are cantonal data:
 * SLS_A10 Cantonal nature reserves
 * SLS_A16 Forest reserves
 * SLS_A17 Cantonal inventories and contractually protected areas

decision-making

display_name: decision-making

ecosystem-protection

display_name: ecosystem-protection

gis

display_name: gis

hydropower

display_name: hydropower

integral-water-management

display_name: integral-water-management

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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.


wind-crust-formation-snowmicropen-data

maintainer: EnviDat Support

title_for_slug: wind-crust-formation-snowmicropen-data

en: smp snowmicropen snow wind-crust wind-packing

state: active

type: dataset

en: SMP data

en: Links to the dataset

format: SERVICE

en: README

media_type: text/plain

en: Describes the dataset in detail

format: TXT

mimetype: text/plain

en: Processing scripts

media_type: application/zip

en: Contains the R-scripts used to process the SMPs

format: ZIP

mimetype: application/zip

en:
This dataset contains the SnowMicroPen (SMP) data from 38 wind tunnel experiments on wind-packing / wind crust formation. These experiments were performed in the winters 2015/16 and 2016/17 and include more than 1000 SMP measurements.

The SMPs are organized per experiment. Each experiment subfolder contains the processed SMP profiles and some additional files.

Please refer to the README for more details on the data. The processing scripts are available for download as well. The scripts are mainly provided as documentation and would need to be adjusted to be used.

This dataset is the basis of the following publication:

Sommer C.G., Lehning M., & Fierz C. (2017). Wind tunnel experiments: Saltation is necessary for wind-packing. Journal of Glaciology, 63(242), 950-958. doi:10.1017/jog.2017.53

smp

display_name: smp

snow

display_name: snow

snowmicropen

display_name: snowmicropen

wind-crust

display_name: wind-crust

wind-packing

display_name: wind-packing

educ

fr: Éducation, culture et sport

de: Bildung, Kultur und Sport

it: Istruzione, cultura e sport

fr: EnviDat: le portail de données environnementales

de: EnviDat: das Umwelt-Datenportal

it: EnviDat: il portale dei dati ambientali

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

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

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

political_level: other

wsl

capacity: public

type: organization

approval_status: approved

key: guid

key: uri

value: Envidat Harvester

en: Wind crust formation: SnowMicroPen data


maintainer: Amelie Fees

en: avalanche-activity time-lapse-photography avalanche glide-snow-avalanche snowpack-simulation

en: SNOWPACK simulations

en: SNOWPACK simulations (.pro and .smet) covering season 2008/09 to 2021/22 at 10 virtual locations on Dorfberg. The locations correspond to the most common glide-snow avalanche paths.

en: README.txt explaining the dataset and columns of tables in more detail.

en: Glide-snow avalanche activity

en: Table that contains all glide-snow avalanche events that were detected in time-lapse photographs (season 2008/09 to 2021/22). The columns are explained in the README.txt

en: Glide distances for opening glide-cracks

en: This folder contains all glide-cracks where glide-distances were extracted from time-lapse photographs. Glide-distances were calculated in x-direction (width) and y-direction (downslope, length) by georeferencing the images.

en:
This dataset includes the processed data of the glide-snow avalanche activity and dynamics on Dorfberg (Davos, Switzerland) covering seasons 2008/09 to 2021/22. This dataset was described in the research article:

Fees, A., van Herwijnen A., Altenbach, M., Lombardo, M., Schweizer, J.: Glide-snow avalanche characteristics at different time-scales extracted from time-lapse photography, Annals of Glaciology, 91

We extracted the dynamics of opening glide-cracks and the glide-snow avalanche activity from time-lapse photographs. Glide-snow avalanches were separated into surface and interface events using the liquid water content which was simulated with SNOWPACK at 10 virtual stations on Dorfberg.

avalanche

display_name: avalanche

avalanche-activity

display_name: avalanche-activity

glide-snow-avalanche

display_name: glide-snow-avalanche

snowpack-simulation

display_name: snowpack-simulation

time-lapse-photography

display_name: time-lapse-photography

en: Glide-snow avalanche activity on Dorfberg, Davos, Switzerland


en: geology flora landscape-evolution madagascar endemism

en: Escarpment evolution drives the diversification of the Madagascar flora

en: This upload contains the data (species checklist, species range maps, time-calibrated phylogenies, topographic change, etc.) generated, analyzed, and presented in the paper .

en: Data v1.o

en: used for paper submission only

en: Although much of the endemic biodiversity of Madagascar can be attributed to its isolation as an island in the Indian Ocean, the high rates of speciation throughout its geologic history suggest an influence of local-scale landscape dynamics. The topographic evolution of Madagascar is dominated by the formation of high-relief continental rift escarpment and we argue that the erosion and landward retreat of this topography creates habitat heterogeneity that has served as a speciation pump for the island. The highest plant richness is found along the escarpment and is characterized by steady diversification rates over the last 45 Ma. Modeled landscape evolution by escarpment retreat demonstrates opportunities for allopatric speciation by transient habitat fragmentation through multiple mechanisms, including catchment expansion, isolation of highland remnants and formation of topographic and river barriers The segregation of floral phylogenetic turnover parallel to the escarpment is consistent with these mechanisms and indicates the importance of erosion-driven landscape dynamics on speciation.

endemism

display_name: endemism

flora

display_name: flora

geology

display_name: geology

landscape-evolution

display_name: landscape-evolution

madagascar

display_name: madagascar

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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.


radiosondes

maintainer: Jörg Wieder

title_for_slug: radiosondes

en: raclets pressure wind temperature wind-direction radiosonde relative-humidity holoballoon

en: Radiosond Sounding Files

en:
The "soundings" radiosond data contains information on ambient pressure (mbar), temperature (C), relative humidity (%), wind speed (m s‾ ¹) and wind direction (true deg), and are ordered with respect to the height above ground (m AGL) with a step size of 20 m. The first line of each file idicates the geographic location and the start time (in UTC) of the ascent. If the wind speed was zero, no wind direction is given.
The zip files contain ascents on the following days:
February 10 (morning and afternoon),
February 11 (morning),
February 16 (afternoon),
February 22 (morning),
March 1 (morning),
March 5 (morning),
March 11 (morning),
March 12 (morning),
March 13 (morning),
March 14 (morning),
March 17 (afternoon), and
March 18.
The data was managed with Windsond Receiver Application Demo Version 2.92, (C) Sparv Embedded AB 2016.

en: Radiosond Template Files

en:
The "template" files contain standard parameters, i.e. ambient pressure (mbar and Pa), temperature (°C), relative humidity (%), wind speed (m s‾ ¹) and wind direction (true deg), as well as additional information, e.g. time (UTC and local time), dew point (°C), mixing ration (g/kg), density (kg m³), altitude (m MSL), height above ground (ft and m AGL), and geographic coordinates (longitude, latitude). If the wind speed was zero, no wind direction is given.
The zip files contain ascents on the following days:
February 10 (morning and afternoon),
February 11 (morning),
February 16 (afternoon),
February 22 (morning),
March 1 (morning),
March 5 (morning),
March 11 (morning),
March 12 (morning),
March 13 (morning),
March 14 (morning),
March 17 (afternoon), and
March 18.
The data was managed with Windsond Receiver Application Demo Version 2.92, (C) Sparv Embedded AB 2016.

en: Radiosondes (Windsond, Sparv Embedded AB) were started in Davos Wolfgang (LON: 9.853594, LAT: 46.835577) to report height profiles of pressure, relative humidity and temperature at specific days. In addition to regular launches of radiosondes, sondes were attached to [HoloBalloon](https://www.envidat.ch/group/clouds-in-situ-raclets) to report the ambient conditions of the in-situ measurements. Further profiles of meteorological measures were recorded at [HoloGondel](https://www.envidat.ch/group/clouds-in-situ-raclets) which was installed at the gondola moving between Gotschnaboden and Gotschnagrat at 2285 m a.s.l.

holoballoon

display_name: holoballoon

pressure

display_name: pressure

raclets

display_name: raclets

radiosonde

display_name: radiosonde

relative-humidity

display_name: relative-humidity

temperature

display_name: temperature

wind

display_name: wind

wind-direction

display_name: wind-direction

en: Radiosondes


maintainer: Matthias Haeni

en: meteo long-term wind-speed climate-change meteorology swiss-forest-lab relative-humidity par precipitation temperature

en: Data plot of the field station (JUF)

media_type: application/pdf

en: Data overview for air temperature, relative humidity, precipitation, PAR, wind speed.

format: PDF

mimetype: application/pdf

en: Site photo of the forest station (JUB)

en: Site photo of the forest station from the side.

mimetype: image/jpeg

en: Site aerial photo (Jussy)

en: Site aerial photo from both Jussy stations. Source: Google. 2016. Site aerial photo from both Jussy stations. Retrieved November 11, 2016, from https://www.google.ch/maps

en: Data plot of the forest station (JUB)

en: Forest station data (JUB)

media_type: text/csv

en: Data file.

format: CSV

mimetype: text/csv

en: Site photo of the field station (JUF)

en: Site photo of the field station from the side.

en: High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for two meteorological stations in Jussy in Switzerland where one station is located within a natural broad-leaved forest stand (JUB) with sessile oak (_Quercus petrea_; 90 yrs), aspen (_Populus tremula_; 60 yrs) and European hornbeam (_Carpinus betulus_; 60 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, JUF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Jussy is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

climate-change

display_name: climate-change

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

precipitation

display_name: precipitation

swiss-forest-lab

display_name: swiss-forest-lab

wind-speed

display_name: wind-speed

en: Jussy, Switzerland: Long-term forest meteorological data from the Long-term Forest Ecosystem Research Programme (LWF), from 1997 onwards


maintainer: Jürg Schweizer

en: avalanche-size snow-avalanche avalanche-forcasting avalanche-activity danger-level

en: Readme

en: The Readme file contains the description of the two data files.

en: Snow avalanche data

en: This data file includes data on the avalanches mapped in the region of Davos.

en: Avalanche activity data

en: This data file includes data on the avalanche activity per day aggregated from the avalanche data.

en:
These data include all avalanches that were mapped in the region of Davos, Switzerland during the winters 1998-1999 to 2018-2019 (21 years), in total 13,918 avalanches, and the corresponding forecast danger level valid on the day of avalanche occurrence, 3533 days and danger ratings in total.

This avalanche activity data set was analysed and results published by Schweizer et al. (2020). They found that the
number of avalanches per day strongly increased with increasing danger level, but avalanche size was poorly related to avalanche danger level.

The data are provided in two files: the first includes the avalanche data (13,918 records); the second includes the avalanche activity per day (3533 records).
Please refer to the Read-me file for further details on the data.

These data are the basis of the following publication:
Schweizer, J., Mitterer, C., Techel, F., Stoffel, A. and Reuter, B., 2020. On the relation between avalanche occurrence and avalanche danger level. The Cryosphere, 14, 737-750, https://doi.org/10.5194/tc-14-737-2020.

avalanche-activity

display_name: avalanche-activity

avalanche-forcasting

display_name: avalanche-forcasting

avalanche-size

display_name: avalanche-size

danger-level

display_name: danger-level

snow-avalanche

display_name: snow-avalanche

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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: Snow avalanche data Davos, Switzerland, 1999-2019


en: climate-change snowmelt precipitation discharge hydrology soil-moisture

en: Daily simulated data for the future period

en: Daily simulated discharge, precipitation, snowmelt, and soil moisture for the period 1981-2100 in mm for the 307 catchments.

en: Daily simulated data for the reference period

en: Daily simulated discharge, precipitation, snowmelt, and soil moisture for the reference period 1981-2017 in mm.

en: Shapefile of 307 catchments in Switzerland

en: Shapefile of the 307 medium-sized catchments in Switzerland. The "gridcode" provides the ID of the catchment used in the datafiles.

en:
Daily discharge and the related hydro-meteorological variables precipitation, snowmelt, and soil moisture are provided for current (1981-2017) and for future climate conditions (1981-2100) for 307 medium-sized catchments in Switzerland. The catchments have a median catchment area of 117 km². The 307 catchments together form a set representative of the climatological conditions and runoff characteristics in Switzerland. The four variables were simulated at a daily resolution using the hydrological model PREVAH. PREVAH is a conceptual process-based model that was run in this study in its fully distributed version on a 500 m grid (Viviroli et al. 2009a). For the calibration, runoff time series from 140 mesoscale catchments covering the different runoff regimes were used. The model calibration was conducted over the period 1993-1997. Verification was performed on the period 1983-2005 using (i) volumetric deviation (Viviroli et al. 2007) and (ii) benchmark efficiency (Schäfli et al 2007) as objective functions. The calibration and validation procedures are described in detail in Köplin et al. (2010). The parameters for each model grid cell were derived by regionalizing the parameters obtained for the 140 catchments with a procedure based on ordinary kriging (Viviroli et al. 2009b, Köplin et al. 2010).
The calibrated and validated model was then driven with transient meteorological data (precipitation, temperature, radiation, and wind) representing both reference (1981-2017) and future climate conditions (2018-2099). The data were derived from the CH2018 climate scenarios (NCCS 2018) provided by the Swiss National Centre for Climate Services (NCCS). They were obtained from climate experiments produced with different climate modeling chains, consisting of a global and a regional circulation model each, within EUROCORDEX for three representative concentration pathways (RCP) emission scenarios. Downscaled output of ten climate model chains derived by quantile mapping were considered. The focus was on the chains of the EUR-11 domain with a horizontal resolution of 0.11 degrees (roughly 12.5 km). The climate model chains (GCM, RCM, RCP, and grid resolution) used are listed below:

- ICHEC-EC-EARTH	DMI-HIRHAM5	2.6	EUR-11
- ICHEC-EC-EARTH	DMI-HIRHAM5	4.5	EUR-11
- ICHEC-EC-EARTH	DMI-HIRHAM5	8.5	EUR-11
- ICHEC-EC-EARTH	SMHI-RCA4	2.6	EUR-11
- ICHEC-EC-EARTH	SMHI-RCA4	4.5	EUR-11
- ICHEC-EC-EARTH	SMHI-RCA4	8.5	EUR-11
- MOHC-HadGEM2-ES	SMHI-RCA4	4.5	EUR-11
- MOHC-HadGEM2-ES	SMHI-RCA4	8.5	EUR-11
- MPI-M-MPI-ESM-LR	SMHI-RCA4	4.5	EUR-11
- MPI-M-MPI-ESM-LR	SMHI-RCA4	8.5	EUR-11

*References*:

-	Köplin, N., D. Viviroli, B. Schädler, and R. Weingartner (2010), _How does climate change affect mesoscale catchments in Switzerland? - A framework for a comprehensive assessment_, Advances in Geosciences, 27, 111-119, doi:10.5194/adgeo-27-111-2010.
-	National Centre for Climate Services (2018), CH2018 - _Climate Scenarios for Switzerland_, Tech. rep., NCCS, Zurich.
-	Schäfli, B., and H. V. Gupta (2007), _Do Nash values have value?_, Hydrological Processes, 21, 2075-2080, doi:10.1002/hyp.6825.
-	Viviroli, D., J. Gurtz, and M. Zappa (2007), _The hydrological modelling system PREVAH. Part II - Physical model description_, Geographica Bernensia, 40, 1-89.
-	Viviroli, D., M. Zappa, J. Gurtz, and R. Weingartner (2009a), _An introduction to the hydrological modelling system PREVAH and its pre- and post-processing-tools_, Environmental Modelling & Software, 24, 1209-1222, doi:10.1016/j.envsoft.2009.04.001.
-	Viviroli, D., H. Mittelbach, J. Gurtz, and R. Weingartner (2009b), _Continuous simulation for flood estimation in ungauged mesoscale catchments of Switzerland-Part II: Parameter regionalisation and flood estimation results_, Journal of Hydrology, 377 (1), 208-225, doi:10.1016/j.jhydrol.2009.08.022.

discharge

display_name: discharge

hydrology

display_name: hydrology

snowmelt

display_name: snowmelt

soil-moisture

display_name: soil-moisture

en: Simulated future discharge and climatological variables for medium-sized catchments in Switzerland


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

en: Daily runoff data from three steep torrents in the Alptal (1968-2022)

en: 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).

format: XLS

en: Manual snow measurements Alptal (1968-2022)

en:
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: Daily meteorological and snow data (1968-2022) Alptal

en:
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:
This data set includes 54 years of hydrometeorological measurements from small (first-order) catchments in the pre-alpine valley Alptal. Here we provide daily mean values; values in sub-daily 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. A second update of the data set (with data from 2020 to 2022) was uploaded in March 2023.

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: Longterm hydrological observatory Alptal (central Switzerland)


maintainer: Giulia Mazzotti

en: forest-structure snow-energy-balance snow-modelling forest-snow snow-distribution

en: Snow depth data open sites

en: Contains all snow detph data accquired at open sites nearby the forest stands during the same period.

en: Grid point nomenclature

en: The grid structure of each forest site and the respective nomenclature applied to label individual points within each grid are outlined here.  Each point marks the location of snow depth measurements and co-located canopy structure parameters.

en: Canopy data

en: Includes all canopy structure metrics computed at all surveyed locations

en: Coordinates data

en: Includes coordinate information of each surveyed point (7 x 276 = 1932 forest points, 2 open areas)

en: Meteo data to drive FSM2 model

en: Includes meteorological driving data used to run the forest snow model FSM2, processed and parsed in text files that match the format required by FSM2. Separate files are available for each field area (Laret, Drusatscha and Ischlag) and season (2012/13, 2013/14, 2014/15). Each file includes data for the period from October 1st to May 31st at hourly resolution.

en: Snow depth data forest sites

en: Contains all snow depth data acquired at all forest sites during winters 2012/13, 2013714 and 2014/15.

en:
This dataset contains all snow, canopy and meteorological data presented and used in the publication: Mazzotti, G., Essery, R., Moeser, D. & Jonas T. (2020) 'Resolving spatial variability of forest snow using an energy-balance model with a 1-layer canopy'. Water Resources Research, https://doi.org/10.1029/2019WR026129.
This publication must be cited when using this dataset.

forest-snow

display_name: forest-snow

forest-structure

display_name: forest-structure

snow-distribution

display_name: snow-distribution

snow-energy-balance

display_name: snow-energy-balance

snow-modelling

display_name: snow-modelling

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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: Snow depth, canopy structure and meterorological datasets from the Davos area, Switzerland, Winters 2012/13-2014/15, used for high-resolution forest snow modelling


en: precipitation meteorology swiss-forest-lab wind-speed long-term par relative-humidity meteo climate-change temperature

en: Data plot of the field station (SCF)

en: Data overview for air temperature, relative humidity, precipitation, PAR, wind speed.

en: Site photo of the forest station (SCB)

en: Site photo of the forest station from below (viewing upwards the slope).

en: Further details on the data repository

en: Meta data documentation.

en: Forest station data (SCB)

en: Data file.

en: Site aerial photo (Schänis)

en: Site aerial photo from both Schänis stations. Source: Google. 2016. Site aerial photo from both Schänis stations. Retrieved November 11, 2016, from https://www.google.ch/maps

en: Field station data (SCF)

en: Data plot of the forest station (SCB)

en: Site photo of the field station (SCF)

en: Site photo of the field station from above (viewing downwards the slope).

en: High quality meteorological data are needed for long-term forest ecosystem research, particularly in the light of global change. The long-term data series published here comprises almost 20 years of measurements for two meteorological stations in Schänis in Switzerland where one station is located within a natural mixed forest stand (SCB) with European beech (_Fagus sylvatica_; 130-150 yrs), European silver fir (_Abies alba_; 130-150 yrs) and European ash (_Fraxinus excelsior_; 130-150 yrs) as dominant tree species. A second station is situated in the very vicinity outside of the forest (field station, SCF). The meteorological time series are presented in hourly time resolution of air temperature, relative humidity, precipitation, photosynthetically active radiation (PAR) and wind speed. Schänis is part of the Long-term Forest Ecosystem Research Programme (LWF) established and maintained by the Swiss Federal Research Institute WSL.

climate-change

display_name: climate-change

long-term

display_name: long-term

meteo

display_name: meteo

meteorology

display_name: meteorology

par

display_name: par

precipitation

display_name: precipitation

relative-humidity

display_name: relative-humidity

swiss-forest-lab

display_name: swiss-forest-lab

temperature

display_name: temperature

wind-speed

display_name: wind-speed

en: Schänis, Switzerland: Long-term forest meteorological data from the Long-term Forest Ecosystem Research Programme (LWF), from 1998 onwards


en: meteo-station longwave-radiation gemstock snow-height shortwave-radiation

en: DATA ACCESS

en:
Meteo data at Gemsstock [Level 2 dataset](http://models.slf.ch/p/dataset-processing/).

fields      = timestamp TSS HS VW DW VW_MAX OSWR ISWR ILWR RECORD AUX_VOLTAGE LOGGER_VOLTAGE LW_SENSOR_TEMP VENTILATION_FLAG OLWR

en: Meteorological station at Gemstock (3021 m asl) in Canton Uri. The station includes in/out LW/SW and a snow height sensor.

gemstock

display_name: gemstock

longwave-radiation

display_name: longwave-radiation

meteo-station

display_name: meteo-station

shortwave-radiation

display_name: shortwave-radiation

snow-height

display_name: snow-height

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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: GEM2: Meteorological and snow station at Gemsstock (3021 m asl), Canton Uri, Switzerland


maintainer: Avalanche Warning Service SLF

en: Avalanche fatalities per year in Switzerland since 1936/1937

en:
Attention: this data is not updated after 2022 anymore.
This dataset contains the statistics on the number of avalanche fatalities per hydrological year in Switzerland. The data set commences with the beginning of the hydrological year 1936/37 on 01/10/1936. After the completion of a hydrological year, the new data is appended to the existing dataset.
The following information is contained (by column and column title):
 - hydrological year
 - number of fatalities in the backcountry (=tour)
 - number of fatalities in terrain close to ski areas (=offpiste)
 - number of fatalities on transportation corridors including ski runs, roads, railway lines (=transportation.corridors)
 - number of fatalities in or around buildings or in settlements (= buildings)
 - sum (of all four categories)
The definition for these four categories as described in the guidelines to the avalanche accident database:
**tour**:
activities include back-country ski, snowboard or snow-shoe touring
**offpiste**:
access from ski area, generally from the top of a skilift with short hiking distances
**transportation.corridors** ([Techel et al., 2016](http://www.geogr-helv.net/71/147/2016/ )):
people travelling or recreating on open or temporarily closed
transportation corridors (e.g. a road user or a skier on a ski run) and people working on open or closed transportation corridors (e.g. maintenance crews on roads, professional rescue teams)
**buildings** ([Techel et al., 2016](http://www.geogr-helv.net/71/147/2016/ )):
people inside or just outside buildings, and workers on high alpine building
sites

avalanche-accident-statistics

display_name: avalanche-accident-statistics

avalanche-accidents

display_name: avalanche-accidents

avalanche-fatalities

display_name: avalanche-fatalities

fatalities-in-or-around-buildings

display_name: fatalities-in-or-around-buildings

fatalities-in-settlements

display_name: fatalities-in-settlements

fatalities-in-the-backcountry

display_name: fatalities-in-the-backcountry

fatalities-on-transportation-corridors

display_name: fatalities-on-transportation-corridors

en: Number of avalanche fatalities per hydrological year in Switzerland since 1936-1937


lidar-davos-wolfgang

maintainer: Patric Seifert

title_for_slug: lidar-davos-wolfgang

en: tropos raclets lidar clouds polly

en: Raman Lidar Davos

en: A portable Raman lidar system (Polly) from Leibnitz Institute for Tropospheric Research (Tropos) was deployed at Davos Wolfgang (LON: 9.853594, LAT: 46.835577). Please use this [link](http://polly.tropos.de/?p=lidarzeit&Ort=39), to be directly forwarded to the Davos location and select the date of interest from the calendar (bold numbers). The data can be requested directly at the Polly team.

clouds

display_name: clouds

lidar

display_name: lidar

polly

display_name: polly

raclets

display_name: raclets

tropos

display_name: tropos

en: LIDAR Davos Wolfgang


maintainer: Esther Frei

en: mountain-ecology literature-review stillberg long-term-experiment treeline-ecosystems

en: The Stillberg bibliography (Stillberg_bibliography_v1.zip) comprises a comprehensive list of 276 scientific publications, 91 of them published in peer-reviewed ISI journals (Stillberg_bibliography_data_v1.csv) along with the metadata file (Stillberg_bibliography_metadata_v1.csv). Currently the bibliography comprises literature about the main afforestation experiment, the FACE × warming experiment, the nutrient addition experiment, and the G-TREE experiment, as well as further publications related to the Stillberg research site that have been published until August 2023. The bibliography can be filtered for different categories, e.g., experiment, peer-review, source repository or database, and source title.

en:
 Background information

The Stillberg ecological treeline research site in the Swiss Alps was established in 1975, with the aim to develop ecologically, technically, and economically sustainable reforestation techniques at the treeline to reduce the risk of snow avalanches. In the course of time, additional research aspects gained importance, such as the ecology of the treeline ecotone under global change. Over almost fifty years, research at the Stillberg site combined long-term monitoring of the large-scale high-elevation afforestation with experimental manipulations simulating global change impacts. Besides providing a scientific basis and practical guidelines for high-elevation afforestation, this research has contributed to a comprehensive understanding of ecological processes in the treeline ecotone across different compartments and scales, from individual trees, non-tree vegetation and soils to whole ecosystems, in the context of global change resulting in more than 150 publications.

 Dataset generation

We compiled a comprehensive list of scientific publications covering research at the Stillberg research site by conducting searches in the literature databases Web of Science and Google Scholar, as well as in the Digital Object Repository of the Swiss Federal Institute for Forest, Snow and Landscape Research WSL (DORA). We compiled all publications about the afforestation experiment, the FACE × warming experiment, the nutrient addition experiment, the G-TREE experiment, as well as other studies related to the Stillberg research site.

 Data description

The Stillberg bibliography (Stillberg_bibliography_data_v1.csv) comprises a comprehensive list of 276 scientific publications, 91 of them published in peer-reviewed ISI journals. Currently the bibliography comprises literature about the main afforestation experiment, the FACE × warming experiment, the nutrient addition experiment, and the G-TREE experiment, as well as further publications related to the Stillberg research site that have been published until August 2023. The bibliography can be filtered for different categories, e.g., experiment, peer-review, source repository or database, and source title. The bibliography is described in a metadata file (Stillberg_bibliography_metadata_v1.csv). The bibliography along with the metadata file are provided in a ZIP-folder (Stillberg_bibliography_v1.zip).

literature-review

display_name: literature-review

long-term-experiment

display_name: long-term-experiment

mountain-ecology

display_name: mountain-ecology

stillberg

display_name: stillberg

treeline-ecosystems

display_name: treeline-ecosystems

en: Bibliography of the long-term treeline research site Stillberg, Switzerland


maintainer: Christoph Marty

en: CH2014 REPORT

en:
CH2014-Impacts: Toward Quantitative Scenarios of Climate Change Impacts in Switzerland

The CH2014-Impacts report presents the results of a concerted effort of 15 Swiss research institutions to describe impacts of climate change in Switzerland quantitatively. This dataset contributes to the Crosphere/Snowcover section.

en: Dataset

en: Datasets are grouped under experiment "Aare" and "Graubunden".Data is also made available in netCDF format. A range of tools are available to [read netCDF](http://www.unidata.ucar.edu/software/netcdf/software.html).

en: Graubunden input

en: Grid input data for the 'Graubunden' CH2014 simulation.

mimetype: application/x-tar

en: Aare input

en: Grid input data for the 'Aare' CH2014 simulation.

en:
 Overview

The CH2014-Impacts initiative is a concerted national effort to describe impacts of climate change in Switzerland quantitatively, drawing on the scientific resources available in Switzerland today. The initiative links the recently developed Swiss Climate Change Scenarios CH2011 with an evolving base of quantitative impact models. The use of a common climate data set across disciplines and research groups sets a high standard of consistency and comparability of results. Impact studies explore the wide range of climatic changes in temperature and precipitation projected in CH2011 for the 21st century, which vary with the assumed global level of greenhouse gases, the time horizon, the underlying climate model, and the geographical region within Switzerland. The differences among climate projections are considered using three greenhouse gas scenarios, three future time periods in the 21st century, and three climate uncertainty levels (Figure 1). Impacts are shown with respect to the reference period 1980-2009 of CH2011, and add to any impacts that have already emerged as a result of earlier climate change.

 Experimental Setup

Future snow cover changes are simulated with the physics-based model Alpine3D (Lehning et al., 2006). It is applied to two regions: The canton of Graubünden and the Aare catchment. These domains are modeled with a Digital Elevation Model (DEM) with a resolution of 200 m × 200 m. This defines the simulation grid that has to be filled with land cover data and downscaled meteorological input data for each cell for the time period of interest at hourly resolution. The reference data set consists of automatic weather station data. All meteorological input parameters are spatially interpolated to the simulation grid. The reference period comprises only thirteen years (1999–2012), because the number of available high elevation weather stations for earlier times is not sufficient to achieve unbiased distribution of the observations with elevation. The model uses projected temperature and precipitation changes for all greenhouse gas scenarios (A1B, A2, and RCP3PD) and CH2011 time periods (2035, 2060, and 2085).

 Data

Snow cover changes are projected to be relatively small in the near term (2035) (Figure 5.1 top), in particular at higher elevations above 2000 m asl. As shown by Bavay et al. (2013) the spread in projected snow cover for this period is greater between different climate model chains (Chapter 3) than between the reference period and the model chain exhibiting the most moderate change. In the 2085 period much larger changes with the potential to fundamentally transform the snow dominated alpine area become apparent (Figure 5.1 bottom). These changes include a shortening of the snow season by 5–9 weeks for the A1B scenario. This is roughly equivalent to an elevation shift of 400–800 m. The slight increase of winter precipitation and therefore snow fall projected in the CH2011 scenarios (with high associated uncertainty) can no longer compensate for the effect of increasing winter temperatures even at high elevations. In terms of Snow Water Equivalents (SWE), the projected reduction is up to two thirds toward the end of the century (2085). A continuous snow cover will be restricted to a shorter time period and/or to regions at increasingly high elevation. In Bern, for example, the number of days per year with at least 5 cm snow depth will decrease by 90% from now 20 days to only 2 days on average.

climate-change

display_name: climate-change

snow-depth

display_name: snow-depth

snow-water-equivalent

display_name: snow-water-equivalent

en: Alpine3D simulations of future climate scenarios CH2014


data-set-on-snow-instability

title_for_slug: data-set-on-snow-instability

en: crack-propagation slab-tensile-support snow-stability-evaluation failure-initiation rutschblock propgatoin-saw-test weak-layer slab avalanche-forcasting snow-avalanche

en: Read-me file on snow instability data

en: data set on snow instability

en:
These data on snow instability include three data subsets that were analyzed and the results published by Reuter and Schweizer (2018) who suggest a novel framework on how to describe snow instability by failure initiation, crack propagation and slab tensile support.

Please refer to the Read-me file for further details on the data.

These data are the basis of the following publication:
Reuter, B. and Schweizer, J., 2018. Describing snow instability by failure initiation, crack propagation and slab tensile support. Geophys. Res. Lett., 45, doi: 10.1029/2018GL078069.

avalanche-forcasting

display_name: avalanche-forcasting

crack-propagation

display_name: crack-propagation

failure-initiation

display_name: failure-initiation

propgatoin-saw-test

display_name: propgatoin-saw-test

rutschblock

display_name: rutschblock

slab

display_name: slab

slab-tensile-support

display_name: slab-tensile-support

snow-avalanche

display_name: snow-avalanche

snow-stability-evaluation

display_name: snow-stability-evaluation

weak-layer

display_name: weak-layer

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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: Data set on snow instability


maintainer: Marcia Phillips

en: temperature permos permafrost gemsstock borehole

en: PERMOS DATA POLICY

en: Map of PERMOS borehole network

en: DATASET & PLOTS

en: Data visualiser and download service provided by PERMOS.

en:
Processed ground temperature measurements at the Gemsstock permafrost borehole in canton Uri, Switzerland. The borehole is located at 2940 m asl on a steep (50°) North-West slope (315°). The surface material is bedrock and borehole depth is 40 m. Thermistors used YSI 44008. Year of drilling 2006. This borehole is part of the Swiss Permafrost network, PERMOS (www.permos.ch). Contact phillips@slf.ch for details of processing applied.

Publications

1. A. Haberkorn, M. Phillips, R. Kenner, H. Rhyner, M. Bavay, S.P. Galos, M. Hoelzle. Thermal regime of rock and its relation to snow cover in steep Alpine rock walls: Gemsstock, central Swiss Alps. 2015. Geografiska Annaler: Series A, Physical Geography. Volume 97. Issue 3. 579–597. http://dx.doi.org/10.1111/geoa.12101. 10.1111/geoa.12101.

2. R. Kenner, M. Phillips, C. Danioth, C. Denier, P. Thee, A. Zgraggen. Investigation of rock and ice loss in a recently deglaciated mountain rock wall using terrestrial laser scanning: Gemsstock, Swiss Alps. 2011. Cold Regions Science and Technology. Volume 67. Issue 3. 157–164. http://dx.doi.org/10.1016/j.coldregions.2011.04.006. 10.1016/j.coldregions.2011.04.006.

borehole

display_name: borehole

gemsstock

display_name: gemsstock

permafrost

display_name: permafrost

permos

display_name: permos

temperature

display_name: temperature

en: Processed permafrost borehole data (2940 m asl), Gemsstock, Switzerland


en: perialpine-lakes switzerland climate-change hydrologic-and-hydrodynamic-modelling lake-level-regulation

en: Lake outflow scenarios CH2018

en: Lake outflow scenarios for Lake Walen, Lake Zurich, Lake Brienz and Lake Thun.

en: Lake characteristics

en: Lake characteristics: stage-area relation for Lake Walen, Lake Zurich, Lake Brienz and Lake Thun, stage-discharge relations for the unregulated Lake Walen and semi-regulated Lake Brienz and, lake level management rules for the two regulated lakes Zurich and Thun.

en: Lake water level scenarios CH2018

en: Lake water level scenarios for Lake Walen, Lake Zurich, Lake Brienz and Lake Thun.

en:
The dataset "Lake_climate_change_scenarios_CH2018" provides simulation-based climate change impact scenarios for perialpine lakes in Switzerland. These transient future scenarios were produced by combining the hydrologic model PREVAH with the hydrodynamic model MIKE11 to simulate daily lake water level (Lake_water_level_scenarios_CH2018.xls) and outflow scenarios (Lake_outflow_scenarios_CH2018.xls) from 1981 to 2099, using the Swiss Climate Change Scenarios CH2018. The future scenarios contain a total of 39 model members for three Representative Concentration Pathways, RCP2.6 (concerted mitigation efforts), RCP4.5 (limited climate mitigation) and RCP8.5 (no climate mitigation measures). These scenarios result from the study titled "Lower summer lake levels in regulated perialpine lakes, caused by climate change," authored by Wechsler et al. in 2023.

The dataset emphasizes four specific Swiss lakes, each subject to different degrees of lake level management: an unregulated lake (Lake Walen), a semi-regulated lake (Lake Brienz), and two regulated lakes (Lake Zurich and Lake Thun).

In addition, the file (Lake_characteristics.xlsx) includes data used in the modeling process, encompassing the stage-area relation for the four lakes, stage-discharge relations for the unregulated and semi-regulated lakes, and lake level management rules for the two regulated lakes.

climate-change

display_name: climate-change

hydrologic-and-hydrodynamic-modelling

display_name: hydrologic-and-hydrodynamic-modelling

lake-level-regulation

display_name: lake-level-regulation

perialpine-lakes

display_name: perialpine-lakes

switzerland

display_name: switzerland


maintainer: Mountain Hydrology and Mass Movements

en: debris-flow-fatalities earthquake-fatalities lightning-fatalities windstorm-fatalities flood-fatalities rockfall-fatalities landslide-fatalities natural-hazard-fatalities ice-avalanche-fatalities

en: Natural hazard fatalities per year in Swizterland since 1946.

en:
This dataset contains the number of fatalities due to flood, debris flow, landslide, rockfall, windstorm, lightning, ice avalanche, earthquake and other processes like roof avalanche or lacustrine tsunami for each year since 1946.
The following information is contained (by column and column title):

* year
* total number of hazard fatalities
* number of fatalities by flood (German: Hochwasser, Überschwemmung). Flood includes people drowned in flooded or inundated areas or carried away in streams under high-water conditions.
* number of fatalities by debris flow (German: Murgang).
* number of fatalities by landslide (German: Erdrutsch). Landslide includes people killed by landslides and hillslope debris flows (German: Hangmure).
* number of fatalities by rockfall (German: Steinschlag, Fels- und Bergsturz).
* number of fatalities by windstorm (German: Sturm). Windstorm includes people killed by falling objects or trees during very strong wind conditions and people who drowned in lakes because their boat capsized during such conditions.
* number of fatalities by lightning (German: Blitz).
* number of fatalities by ice avalanche (German: Eislawine).
* number of fatalities by earthquake (German: Erdbeben).
* number of fatalities by other processes like roof avalanche, lacustrine tsunami (German: andere Prozesse wie Dachlawine, Tsunami im See).

The data was collected based on newspaper research. For more information please refer to

_Badoux, A., Andres, N., Techel, F., and Hegg, C.: Natural hazard fatalities in Switzerland from 1946 to 2015, Nat. Hazards Earth Syst. Sci., 16, 2747-2768, https://doi.org/10.5194/nhess-16-2747-2016, 2016._

The data collection is financed by the FOEN (with exception of the collection of the avalanche fatalities). The data contains the official statistics of the FOEN on fatalities due to flood, debris flow, landslide, rock fall and avalanche.

Restrictions: The data set is not complete. Only fatalities in or around settlements and on open transportation routes are included. More precisely, fatalities were not collected, when persons exposed themselves to a great danger on purpose. Or fatalities during leisure activities which are connected to a higher risk were not included (this includes e.g. canoeing or river surfing during flood, canyoning, mountaineering, climbing, walking or driving on a closed road).

Fatalities by avalanches are collected at the WSL Institute for Snow and Avalanche Research SLF. You can download the avalanche fatalities per hydrological year [here](https://www.envidat.ch/dataset/avalanche-fatalities-switzerland-1936) and per calendar year [here](https://www.envidat.ch/dataset/avalanche-fatalities-per-calendar-year-since-1936). For a direct comparison with the fatalities presented here, please download the data set with the calendar years and do not consider fatalities in the backcountry (tour) or in terrain close to ski areas (offpiste).

debris-flow-fatalities

display_name: debris-flow-fatalities

earthquake-fatalities

display_name: earthquake-fatalities

flood-fatalities

display_name: flood-fatalities

ice-avalanche-fatalities

display_name: ice-avalanche-fatalities

landslide-fatalities

display_name: landslide-fatalities

lightning-fatalities

display_name: lightning-fatalities

natural-hazard-fatalities

display_name: natural-hazard-fatalities

rockfall-fatalities

display_name: rockfall-fatalities

windstorm-fatalities

display_name: windstorm-fatalities

educ

en: Education, culture and sport

envidat

en: EnviDat: the Environmental Data Portal

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: Number of natural hazard fatalities per year in Switzerland since 1946


rorcc

title_for_slug: rorcc

en: design-discharge environmental-flow run-of-river-power-plants hydropower climate-change

en: RoRCC

en:
The dataset “RoRCC” consists of simulation-based results on climate change impacts on Alpine RoR power production; it is based on 21 Swiss RoR power plants, with a total production of 5.9 TWh a-1. The dataset contains the following information:
-	metadata on the RoR power plants under consideration
-	annual and seasonal production scenarios differentiated into three emission scenarios (RCP2.6, RCP4.5, RCP8.5) and three future periods (T1: 2020–2049, T2: 2045–2074, T3: 2070–2099)
-	annual and seasonal production loss due to environmental flow requirements
-	annual and seasonal the technical increase potential (via design discharge optimisation)
-	annual and seasonal changes in the hydrological cycle for the three emission scenarios (RCP2.6, RCP4.5, RCP8.5) and three future periods (T1: 2020–2049, T2: 2045–2074, T3: 2070–2099)

en:
The dataset "RoRCC" consists of simulation-based results on climate change impacts on Alpine RoR power production; it is based on 21 Swiss RoR power plants, with a total production of 5.9 TWh a-1. The dataset contains the following information:
1) metadata on the RoR power plants under consideration, 2) annual and seasonal production potential scenarios under into three emission scenarios (RCP2.6, RCP4.5, RCP8.5) and three future periods (T1: 2020–2049, T2: 2045–2074, T3: 2070–2099), 3) annual and seasonal streamflow scenarios, 4) annual and seasonal production loss due to environmental flow requirements, 5) annual and seasonal the technical increase potential (via design discharge optimisation) and 6) annual and seasonal changes in the hydrological cycle.

design-discharge

display_name: design-discharge

environmental-flow

display_name: environmental-flow

hydropower

display_name: hydropower

run-of-river-power-plants

display_name: run-of-river-power-plants


global-cryosphere-watch-data-survey

maintainer: Mathias Bavay

title_for_slug: global-cryosphere-watch-data-survey

en: data-exchange gcw data-portal automatic-publication data-usage

en: Data interoperability survey

en: Third party data usage

en: Two surveys on the topic of data usage where conducted for the Global Cryosphere Watch data portal. The first one focused on the data provider point of view while the second one focused on the data user point of view. 37 data providers (ie institutions) worldwide provided their answers for the first survey (from fall 2017 until summer 2018) while 54 users (contacted through various mailing list such as the Cryolist) answered the questions on their third party data usage (fall 2019 until January 2020).

automatic-publication

display_name: automatic-publication

data-exchange

display_name: data-exchange

data-portal

display_name: data-portal

data-usage

display_name: data-usage

gcw

display_name: gcw

en: Global Cryosphere Watch data survey


disdrometer-data-gotschnagrat

title_for_slug: disdrometer-data-gotschnagrat

en: disdrometer hydrometeors raclets visibility precipitation

en: Disdrometer Data Gotschnagrat

en: The zip folder contains one netCDF file per day for Gotschnagrat from February 11 to March 27 2019 with a temporal resolution of 30 seconds (time in UTC). The naming convention for the files is Gotschna_YYYYMMDD.nc and the files include the following: characteristics of hydrometeors (e.g. diameter, fall velocity, amount per diameter class,...), precipitation rate, radar reflectivity, visibility range, weather codes and instrument performance.

en: A laser optical disdrometer (Parsivel² , OTT Hydromet) was deployed at Gotschnagrat (LON: 9.849, LAT: 46.859) to measure hydrometeors by extinction when passing a laser beam. The instrument can classify eight different kinds of precipitation, including rain, hail, snow, drizzle, and hybrid forms. The dataset contains information on precipitation amount and type for the period of February 11 to March 27 2019 at Gotschnagrat.

disdrometer

display_name: disdrometer

hydrometeors

display_name: hydrometeors

precipitation

display_name: precipitation

raclets

display_name: raclets

visibility

display_name: visibility


mountain-permafrost-hydrology

maintainer: Jeannette Noetzli

title_for_slug: mountain-permafrost-hydrology

en: monitoring-techniques climate-change-impacts ice-rich-permafrost mountain-permafrost-hydrology permafrost-degradation mass-movements

en: DORA Persistent URL

en: Synthesis report chapter of the Hydro-CH2018 project of the Federal Office for the Environment (FOEN)

en: This report was prepared as one of the synthesis report chapters of the Hydro-CH2018 project of the Federal Office for the Environment (FOEN). In earlier reports such as the CH2014-IMPACTS report (CH-Impacts 2014), the topic of mountain permafrost hydrology was not addressed. Here, we provide a baseline of the available knowledge of mountain permafrost in the Swiss Alps for future reference. We compile an overview of the current understanding of mountain permafrost in the Swiss Alps, its distribution and characteristics, observed and projected changes, and expected impacts on slope stability, infrastructure and hydrological aspects. We also briefly describe the measurement techniques and modelling approaches applied. The chapter closes with a summary of the most important open research questions. The literature cited mainly includes studies on mountain permafrost published in scientific journals and assessments of long-term observation data. We focus on permafrost hydrology interactions wherever information is available. However, systematic studies on permafrost hydrology in mountain areas are still limited.

climate-change-impacts

display_name: climate-change-impacts

ice-rich-permafrost

display_name: ice-rich-permafrost

mass-movements

display_name: mass-movements

monitoring-techniques

display_name: monitoring-techniques

mountain-permafrost-hydrology

display_name: mountain-permafrost-hydrology

permafrost-degradation

display_name: permafrost-degradation

educ

en: Education, culture and sport

en: Mountain Permafrost Hydrology


maintainer: Marco Moretti

en: sustainability urbanization pollination honeybees urban-biodiversity remote-sensing

en: Dataset 1

en: Dataset 1: Processed data for urban beekeeping 2012-2018

en: Dataset 2

en: Dataset 2: Processed data for modelling balance urban greenspace

en: Dataset 3

en: Aggregated data on number hives, beekeeping locations and ratios

en: Data on: (1) spatial distribution of urban beekeeping (number of hives and number of beekeeping locations) in 14 Swiss cities (Geneva, Lausanne, Biel, Neuchatel, Basel, Zurich, Chur, Luzern, St. Gallen, Winterthur, Bern, Lugano, Bellinzona, Thun) for the period 2012-2018; (2) aggregated data to model the sustainability of urban beekeeping.

honeybees

display_name: honeybees

pollination

display_name: pollination

remote-sensing

display_name: remote-sensing

sustainability

display_name: sustainability

urban-biodiversity

display_name: urban-biodiversity

urbanization

display_name: urbanization

envidat

en: EnviDat: the Environmental Data Portal

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: Challenging the sustainability of urban beekeeping: evidence from Swiss cities


maintainer: Frank Techel

en: snowpack-model avalanche avalanche-size natural-avalanches machine-learning

en: Data set AV3 was used for validation of the avalanche-day classifier (Sections 2.1.3 and 3.3(1) in Mayer et al.).

en: Data set AV1 was used for training the avalanche-day classifier (Sections 2.1.1, 2.2, and 3.1 in Mayer et al.).

en: Data set DL was used for validation of the avalanche-day classifier and the avalanche-size estimator. The data set contains the quality-checked danger levels merged with the respective SNOWPACK simulations (Sections 2.3 and 3.3(2) in Mayer et al.).

en: Data set AV2 used for training the avalanche-size estimator (Sections 2.1.2 and 3.2 in Mayer et al.)

en:
The data set contained in this repository was used in the analysis by Mayer et al. (2023):
Mayer, S. I., Techel, F., Schweizer, J., and van Herwijnen, A.: Prediction of natural dry-snow avalanche activity using physics-based snowpack simulations, EGUsphere, https://doi.org/10.5194/egusphere-2023-646, 2023.

avalanche

display_name: avalanche

avalanche-size

display_name: avalanche-size

machine-learning

display_name: machine-learning

natural-avalanches

display_name: natural-avalanches

snowpack-model

display_name: snowpack-model

en: Data-set for prediction of natural dry-snow avalanche activity and avalanche size using physics-based snowpack simulations


maintainer: Sofia Pagliarin

en: barcelona urban-atlas milan imperviousness copernicus soil-sealing

en: Shareable project in Esri ArcGIS format including the HRL IMD data in raster format for each of the territorial boundaries as specified in letter a)-h), see Dataset description

en: Information on data sources

en:
Dataset description

This dataset is a recalculation of the Copernicus 2015 high resolution layer (HRL) of imperviousness density data (IMD) at different spatial/territorial scales for the case studies of Barcelona and Milan. The selected spatial/territorial scales are the following:

 * a)	Barcelona city boundaries
 * b)	Barcelona metropolitan area, Àrea Metropolitana de Barcelona (AMB)
 * c)	Barcelona greater city (Urban Atlas)
 * d)	Barcelona functional urban area (Urban Atlas)
 * e)	Milan city boundaries
 * f)	Milan metropolitan area, Piano Intercomunale Milanese (PIM)
 * g)	Milan greater city (Urban Atlas)
 * h)	Milan functional urban area (Urban Atlas)

In each of the spatial/territorial scales listed above, the number of 20x20mt cells corresponding to each of the 101 values of imperviousness (0-100% soil sealing: 0% means fully non-sealed area; 100% means fully sealed area) is provided, as well as the converted measure into squared kilometres (km2).

 Dataset composition

The dataset is provided in .csv format and is composed of:

_IMD15_BCN_MI_Sources.csv_: Information on data sources

 _IMD15_BCN.csv_: This file refers to the 2015 high resolution layer of imperviousness density (IMD) for the selected territorial/spatial scales in Barcelona:
 * a)	Barcelona city boundaries (label: bcn_city)
 * b)	Barcelona metropolitan area, Àrea metropolitana de Barcelona (AMB) (label: bcn_amb)
 * c)	Barcelona greater city (Urban Atlas) (label: bcn_grc)
 * d)	Barcelona functional urban area (Urban Atlas) (label: bcn_fua)

 _IMD15_MI.csv_: This file refers to the 2015 high resolution layer of imperviousness density (IMD) for the selected territorial/spatial scales in Milan:
 * e)	Milan city boundaries (label: mi_city)
 * f)	Milan metropolitan area, Piano intercomunale milanese (PIM) (label: mi_pim)
 * g)	Milan greater city (Urban Atlas) (label: mi_grc)
 * h)	Milan functional urban area (Urban Atlas) (label: mi_fua)

_IMD15_BCN_MI.mpk_: the shareable project in Esri ArcGIS format including the HRL IMD data in raster format for each of the territorial boundaries as specified in letter a)-h).

Regarding the territorial scale as per letter f), the list of municipalities included in the Milan metropolitan area in 2016 was provided to me in 2016 from a person working at the PIM.

In the IMD15_BCN.csv and IMD15_MI.csv, the following columns are included:

 * Level: the territorial level as defined above (a)-d) for Barcelona and e)-h) for Milan);
 * Value: the 101 values of imperviousness density expressed as a percentage of soil sealing (0-100%: 0% means fully non-sealed area; 100% means fully sealed area);
 * Count: the number of 20x20mt cells corresponding to a certain percentage of soil sealing or imperviousness;
 * Km2: the conversion of the 20x20mt cells into squared kilometres (km2) to facilitate the use of the dataset.

 Further information on the Dataset

This dataset is the result of a combination between different databases of different types and that have been downloaded from different sources. Below, I describe the main steps in data management that resulted in the production of the dataset in an Esri ArcGIS (ArcMap, Version 10.7) project.

 1. The high resolution layer (HRL) of the imperviousness density data (IMD) for 2015 has been downloaded from the official website of Copernicus. At the time of producing the dataset (April/May 2021), the 2018 version of the IMD HRL database was not yet validated, so the 2015 version was chosen instead. The type of this dataset is raster.

 2. For both Barcelona and Milan, shapefiles of their administrative boundaries have been downloaded from official sources, i.e. the ISTAT (Italian National Statistical Institute) and the ICGC (Catalan Institute for Cartography and Geology). These files have been reprojected to match the IMD HRL projection, i.e. ETRS 1989 LAEA.

 3. Urban Atlas (UA) boundaries for the Greater Cities (GRC) and Functional Urban Areas (FUA) of Barcelona and Milan have been checked and reconstructed in Esri ArcGIS from the administrative boundaries files by using a Eurostat correspondence table. This is because at the time of the dataset creation (April/May 2021), the 2018 Urban Atlas shapefiles for these two cities were not fully updated or validated on the Copernicus Urban Atlas website. Therefore, I had to re-create the GRC and FUA boundaries by using the Eurostat correspondence table as an alternative (but still official) data source. The use of the Eurostat correspondence table with the codes and names of municipalities was also useful to detect discrepancies, basically stemming from changes in municipality names and codes and that created inconsistent spatial features. When detected, these discrepancies have been checked with the ISTAT and ICGC offices in charge of producing Urban Atlas data before the final GRC and FUA boundaries were defined.

Steps 2) and 3) were the most time consuming, because they required other tools to be used in Esri ArcGIS, like spatial joins and geoprocessing tools for shapefiles (in particular dissolve and area re-calculator in editing sessions) for each of the spatial/territorial scales as indicated in letters a)-h).

Once the databases for both Barcelona and Milan as described in points 2) and 3) were ready (uploaded in Esri ArcGIS, reprojected and their correctness checked), they have been ‘crossed’ (i.e. clipped) with the IMD HRL as described in point 1) and a specific raster for each territorial level has been calculated. The procedure in Esri ArcGIS was the following:

 * Clipping: Arctoolbox > Data management tools > Raster > Raster Processing > Clip. The ‘input’ file is the HRL IMD raster file as described in point 1) and the ‘output’ file is each of the spatial/territorial files. The option "Use Input Features for Clipping Geometry (optional)” was selected for each of the clipping.
 * Delete and create raster attribute table: Once the clipping has been done, the raster has to be recalculated first through Arctoolbox > Data management tools > Raster > Raster properties > Delete Raster Attribute Table and then through Arctoolbox > Data management tools > Raster > Raster properties > Build Raster Attribute Table; the "overwrite" option has been selected.

 Other tools used for the raster files in Esri ArcGIS have been the spatial analyst tools (in particular, Zonal > Zonal Statistics). As an additional check, the colour scheme of each of the newly created raster for each of the spatial/territorial attributes as per letters a)-h) above has been changed to check the consistency of its overlay with the original HRL IMD file. However, a perfect match between the shapefiles as per letters a)-h) and the raster files could not be achieved since the raster files are composed of 20x20mt cells.

The newly created attribute tables of each of the raster files have been exported and saved as .txt files. These .txt files have then been copied in the excel corresponding to the final published dataset.

barcelona

display_name: barcelona

copernicus

display_name: copernicus

imperviousness

display_name: imperviousness

milan

display_name: milan

soil-sealing

display_name: soil-sealing

urban-atlas

display_name: urban-atlas

educ

en: Education, culture and sport

en: Soil sealing Barcelona and Milan different territorial levels


maintainer: EnviDat Support

en: soil-mapping ecological-indicator-values soil-ph ecological-maps plants landolt switzerland soil-moisture

en: Predictors

en: Predictors generated and used in Descombes et al. (2020)

en: Description

en: Description of the predictors provided in this dataset

en:
Ecologically meaningful predictors are often neglected in plant distribution studies, resulting in incomplete niche quantification and low predictive power of species distribution models (SDMs). Because environmental data are rare and expensive to collect, and because their relationship with local climatic and topographic conditions are complex, mapping them over large geographic extents and at high spatial resolution remains a major challenge. Here, we derived environmental data layers by mapping ecological indicator values (EIVs) in space by using a large set of environmental predictors in Switzerland.

This dataset contains the predictors (raster layers) generated and used in the following publication (Descombes et al. 2020). Only predictors for which we have the rights to share them are provided. Other datasets and predictors can be accessed via the original data provider. Details on the predictors and sources are fully described in the publication. The predictors are provided as GeoTIFF files, at 93 m spatial resolution and Mercator projection ("+proj=merc +lon_0=0 +k=1 +x_0=0 +y_0=0 +ellps=WGS84 +towgs84=0,0,0,0,0,0,0 +units=m +no_defs"). The excel file (xlsx) provides a short description of the raster layers.

Paper Citation:

Descombes, P. et al. (2020). Spatial modelling of ecological indicator values improves predictions of plant distributions in complex landscapes. Ecography. (accepted)

ecological-indicator-values

display_name: ecological-indicator-values

ecological-maps

display_name: ecological-maps

landolt

display_name: landolt

plants

display_name: plants

soil-mapping

display_name: soil-mapping

soil-moisture

display_name: soil-moisture

soil-ph

display_name: soil-ph

switzerland

display_name: switzerland


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

en:
This file contains the anonymous answers to the survey for the case study in the protective forest, Val Mesolcina, GR, Switzerland within the BAFU Project "Wenn Risiken kumulieren - Analyse und Umgang mit unerwarteten Ereignissen und kombinierten Risiken".
The survey consists of two parts, based on different concepts: "top-down" and "bottom-up". Answers for both concepts are available in two different worksheets within the Excel file.

en: Description of the study site, extreme event (trigger event) and informations about the survey.

en: Case study website

media_type: text/html

en: Page of the case study on the project website. It includes figures fo all questions of the survey and additional synthesis graphs.

format: HTML

en: Factsheet summarising the methods used in this project (in German).

en: Factsheet summarising the key results of the study (in French).

en: Factsheet summarising the key results of the study (in German).

en: Conclusions and recommendations of the project (in German).

en: Factsheet summarising the key results of the study (in Italian).

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

bark-beetles

display_name: bark-beetles

compound-events

display_name: compound-events

drought

display_name: drought

extreme-events

display_name: extreme-events

forest-fire

display_name: forest-fire

natural-hazards

display_name: natural-hazards

protection-forest

display_name: protection-forest

protective-effect

display_name: protective-effect

envidat

en: EnviDat: the Environmental Data Portal

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: Experts survey protective forest and combined extremes in Val Mesolcina


maintainer: Felix Neff

en: diversity restoration grassland insects topsoil-removal long-term-experiment functional-diversity functional-traits

en: Plot information

en:
Information on the experimental plots.

- **Plot**: ID of Plot
- **Treatment**: Experimental treatment
- **Landuse_history**: recent agricultural use for Initial; agricultural use before restoration for all restored sites
- **Last_tilled**: Last time the site was tilled
- **Intensity**: Frequency and intensity of mowing and manuring (*intensity1*: mowing once and no manure, i*ntensity2*: 2-3 times mowing and no manure, *intensity3*: 2-3 times mowing and manuring, *intensity4*: 4-5 times mowing and manuring)
- **Slope**: slope gradient according to classes defined by FAO (1990)
- **X**: X coordinate of the plot (CH1903)
- **Y**: Y coordinate of the plot (CH1903)
- **Cluster**: Spatial cluster of the plot

en: Insect traits

en:
Functional traits of all herbivorous insect species sampled in the study.

- **Species**: Insect species name (following [Fauna Europaea](https://fauna-eu.org))
- **Author**: Author and year of species' description (following [Fauna Europaea](https://fauna-eu.org))
- **Group**: Insect group as used in the analyses
- **Body volume**: Body volume determined by body length, body width and body height (in mm$^3$)
- **Body_shape**: Ratio of body length to body width
- **Hind_femur_shape**: Ratio of hind-femur length to hind-femur width
- **Hind_front_leg_ratio**: Ratio of front-leg length to hind-leg length (leg length = femur length + tibia length)
- **Wing_length_rel**: Ratio of wing length to body length
- **Leg_length_rel**: Ratio of front-leg length to body length (leg length = femur length + tibia length)
- **Antenna_length_rel**: Ratio antenna length to body length
- **Eye_width_rel**: Ratio of eye width to head width (Auchenorrhyncha, Heteroptera) / to head height (Orthoptera)
- **Feeding_specialization**: Insect specialization on food source (*m*: monophagous, *o*: oligophagous, *p*: polyphagous)
- **Feeding_tissue**: Feeding tissue used for feeding (*c*: chewers, *x*: xylem, *p*: phloem, *m*: mesophyll, *m-p/r*: mesophyll as well as phloem and/or reproductive organs, *r*: reproductive organs, *se*: ripe seeds)
- **Hibernation**: Hibernation stage (*e*: egg, *e/n*: egg and nymph, *n*: nymph, *a*: adult)
- **Generations**: Number of generations per year (*1.5* stands for *1-2* generations per year)
- **Moisture_pref_mean**: mean of preferred habitat moistures (*1*: xerophilous, *2*: moderately xerophilous, *3*: moderately mesohygrophilous, *4*: mesohygrophilous, *5*: moderately hygrophilous, *6*: hygrophilous, *7*: moderately hydrophilous, *8*: hydrophilous)
- **Moisture_pref_range**: range of preferred habitat moistures (indicating degree of specialization)

en: Insect abundance

en:
Abundance of adult insects recorded in the samplings on all experimental sites

- **Plot**: ID of Plot
- **Treatment**: Experimental treatment
- **Species**: Insect species name (following [Fauna Europaea](https://fauna-eu.org))
- **Author**: Author and year of species' description (following [Fauna Europaea](https://fauna-eu.org))
- **Group**: Insect group as used in the analyses
- **Number_Adults**: Number of adult individuals recorded
- **Herbivore**: Logical indicating whether the species is feeding as a herbivore (*TRUE*) or not (*FALSE*)

en:
This dataset contains all data, on which the following publication below is based.

**Paper Citation**:

Neff, F., Resch, M. C., Marty, A., Rolley, J. D., Schütz, M., Risch, A. C, Gossner, M. M. 2020. Long-term restoration success of insect herbivore communities in semi-natural grasslands: a functional approach. Ecological Applications, 30, e02133. [10.1002/eap.2133](https://doi.org/10.1002/eap.2133)

Please cite this paper together with the citation for the datafile.

 Methods

 Study site
The study area is situated within and nearby to Eigental nature reserve (47°27’36” to 47°29’06” N, 8°37’12” to 8°37’44” E, 461 to 507 m a.s.l.) in the vicinity of Zurich airport (Canton Zurich, Switzerland). Mean annual precipitation and temperature is 903 ± 136 mm and 9.14°C ± 0.50°C (mean ± SD for 2007-2017 (*MeteoSchweiz 2018*)). In 1967, the Eigental nature reserve was established to protect small and isolated remnants of species-rich, semi-natural grasslands (roughly 12 ha), which were embedded in an otherwise intensively managed landscape. It is characterized by oligo- to mesotrophic Molinion (semi-wet, matrix species *Molinia caerulea*) and Mesobromion (semi-dry, matrix species *Bromus erectus*) meadows (*Delarze et al. 2015*), reflecting small-scale habitat heterogeneity, mainly due to site-specific groundwater levels and slope inclination. As in most Central European grasslands, management is necessary to prevent shrub and tree invasions as well as to secure low levels of available soil nutrients and thus to maintain these species-rich habitats ([*Poschlod and WallisDeVries 2002*](https://doi.org/10.1016/S0006-3207(01)00201-4)).
In 1990, the government of the Canton Zurich decided to enlarge the Eigental nature reserve as a counter measure against degradation and biodiversity loss in semi-natural grasslands due to overutilization and the excessive input of nutrients (mostly nitrogen). Eleven patches of adjacent intensively managed grassland (in total roughly 20 ha) were targeted to be transformed into semi-natural grasslands. As a first restoration measure, fertilization was ceased, and biomass harvested three times to remove excessive soil nutrients from the original system and thus benefit plant species with low competitive ability on the long run. In 1995, the restoration efforts were increased and a large-scale experiment comprising three restoration measures with increasing intervention intensities was implemented:

- **Harvest only**: Initial restoration measures were continued with mowing and removing of the aboveground biomass two times a year (early summer and autumn).
- **Topsoil**: Removal of topsoil, depending on the thickness of the A horizon the upper 10 to 20 cm, in four randomly selected areas within the eleven patches in late autumn 1995. The size of the restoration area depended on individual patch size (2700 to 7000 m2).
- **Topsoil + Propagules**: Plant propagules were added on half of the area where topsoil was removed via application of fresh, seed-containing hay and hand-collected propagules of target species originating from semi-dry and semi-wet species-rich grasslands with local and regional provenance (within radius of 7 to 30 km) (1995, 1996, 1997).

Management of *Topsoil* and *Topsoil + Propagules* started five years after treatment implementation and included yearly mowing and removing of aboveground biomass (late summer or early autumn). The experiment was complemented with intensively managed grassland sites that share the same agricultural history as the restored sites (**Initial**; swards dominated by *Lolium perenne*, *L. multiflorum* and *Trifolium repens*): mowing and subsequent fertilizing (manure) up to five times a year, as well as different tillage regimes. Finally, sites were selected in target semi-dry and semi-wet grasslands (**Target**) located within the Eigental nature reserve and another nature reserve nearby (Altläufe der Glatt; 47°28’29” to 47°27’41” N, 8°31’56” to 8°32’26” E, 418 to 420 m a.s.l.). The selected target sites are mown and aboveground biomass removed once a year in late summer or early autumn. For each of the five treatments, we selected eleven plots (5 m × 5 m) spread across the sites. Altogether, the experiment included 55 plots.

 Arthropod sampling
Aboveground arthropods were sampled using suction sampling on four consecutive days in early July 2017 before the grasslands were mown. Arthropods were sampled in two locations on each 5 m × 5 m plot, once in the south-western and once in the north-eastern corner to account for possible spatial heterogeneity within the plots. Arthropods were sorted to order or lower taxonomic levels and individuals were identified to species level. We focused on three groups (Hemiptera: Auchenorrhyncha, Hemiptera: Heteroptera, Orthoptera),

 Functional traits
We used two sets of functional traits in this study.

**Morphometric traits**:
Body volume, body shape, hind femur shape, hind/front leg ratio, wing length, leg length, antenna length and eye width. We used trait measurements from [*Simons et al. (2016)*](http://dx.doi.org/10.1890/15-0616.1) and [*Neff et al. (2019)*](https://doi.org/10.1007/s10980-019-00872-1) and complemented them with measurements on study specimens. These measurements were conducted using a high-resolution measuring stereo microscope (Leica DVM6, Leica Microsystems) including automated high-resolution photo stacking with the software Leica Application Suite X (LAS X, © 2018 Leica Microsystems CMS GmbH) and Leica Map Premium (Leica Microsystems, © 1996-2017 Digital Surf) at WSL Birmensdorf. The eight morphometric traits were calculated from direct measurements of body parts on specimens of all sampled species. From each species, we measured at least one female and one male specimen. Additionally, for species that show wing dimorphism, we included the different wing morphs and weighted them by their prevalence reported in literature. For few species, of which not all wing morphs were available for measurements (10 cases), we estimated relative wing length from congeneric species or from the literature.

**Life-history traits**
Based on an existing data set collected by [*Gossner et al. (2015)*](http://dx.doi.org/10.1890/14-2159.1). We included traits describing different life-history characteristics of herbivore insect species, namely: feeding specialization, feeding tissue, hibernation stage and number of generations per year, which are related to insect species’ vulnerability to changes in plant community composition, microhabitat use and disturbance tolerance. To represent potential changes in habitat moisture with abandonment of intensive land use (e.g., change in ground-water level), we also included two traits related to preferred habitat moisture of the study species: moisture preference, describing species’ optimum habitat moisture, and moisture range, which describes the species’ range of preferable moisture conditions.

 References

Delarze, R., Y. Gonseth, S. Eggenberg, and M. Vust. 2015. Lebensräume der Schweiz: Ökologie - Gefährdung - Kennarten. 3rd ed. Ott, Bern.

Gossner, M. M., N. K. Simons, R. Achtziger, T. Blick, W. H. O. Dorow, F. Dziock, F. Köhler, W. Rabitsch, and W. W. Weisser. 2015. A summary of eight traits of Coleoptera, Hemiptera, Orthoptera and Araneae, occurring in grasslands in Germany. Scientific Data 2:150013.

MeteoSchweiz. 2018. Klimabulletin Jahr 2017. MeteoSchweiz, Zürich.

Neff, F., N. Blüthgen, M. N. Chisté, N. K. Simons, J. Steckel, W. W. Weisser, C. Westphal, L. Pellissier, and M. M. Gossner. 2019. Cross-scale effects of land use on the functional composition of herbivorous insect communities. Landscape Ecology 34:2001–2015.

Poschlod, P., and M. F. WallisDeVries. 2002. The historical and socioeconomic perspective of calcareous grasslands—lessons from the distant and recent past. Biological Conservation 104:361–376.

Simons, N. K., W. W. Weisser, and M. M. Gossner. 2016. Multi-taxa approach shows consistent shifts in arthropod functional traits along grassland land-use intensity gradient. Ecology 97:754–764.

diversity

display_name: diversity

functional-diversity

display_name: functional-diversity

functional-traits

display_name: functional-traits

grassland

display_name: grassland

insects

display_name: insects

long-term-experiment

display_name: long-term-experiment

restoration

display_name: restoration

topsoil-removal

display_name: topsoil-removal

educ

en: Education, culture and sport

en: Grassland restoration: insects and insect traits


maintainer: Dirk Nikolaus Karger

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

en: CHELSA Technical Documentation

en: Technical documentation document including the variable names, units, scaling, offset, and background.

en: CHELSA V1.2 (deprecated)

en: CHELSA Version 1.2 based on ERA-Interim forcings and CMIP5

format: GeoTIFF

en: CHELSA V2.1 (current)

en: CHELSA Version 2.1 based on ERA5 forcings and CMIP6

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)._

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