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Type: | Resource | |
Storage: | The size of this resource is 177.8 MB | |
Created: | Jun 24, 2024 at 9:20 a.m. | |
Last updated: | Oct 17, 2024 at 2:58 p.m. (Metadata update) | |
Published date: | Oct 17, 2024 at 2:58 p.m. | |
DOI: | 10.4211/hs.7a45ee06851e41d99e4affb7110d5f97 | |
Citation: | See how to cite this resource | |
Content types: | Geographic Feature Content |
Sharing Status: | Published |
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Abstract
This dataset contains the data related to the research paper 'Trends and drivers of water temperature extremes in mountain rivers' by van Hamel and Brunner (2024), which is published in the journal Water Resources Research: https://doi.org/10.1029/2024WR037518. It contains water temperature data for 177 stations in the European Alps, the Pyrenees, the Central Massif and the Scandinavian mountains. All catchments have at least 5 entire years of water temperature observations available for the period 2008-2022. For each catchment, we have extracted extreme water temperature values and extreme events. Extreme values are the days on which the daily mean water temperature exceeds the locally defined, seasonally varying 95th percentile threshold. Extreme events refer to a continuous period of multiple days (minimum 2 days) for which the locally defined, seasonally varying 95th percentile threshold is exceeded. An extreme event is composed of multiple extreme values.
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ReadME.txt
Title: Water temperature extremes in European mountain rivers Contact: Amber van Hamel, amber.vanhamel@slf.ch Description: This dataset contains water temperature data for 177 stations in the European Alps, the Pyrenees, the Central Massif and the Scandinavian mountains. All catchments have at least 5 entire years of water temperature observations available within the period 2008-2022. Per catchment we have extracted the extreme water temperature values and the extreme events. Extreme values are the days on which the daily mean water temperature exceeds the locally defined, seasonally varying 95th percentile threshold. Extreme events refer to a continuous period of multiple days (minimum 2 days) for which the locally defined, seasonally varying 95th percentile threshold is exceeded. An extreme event is composed of multiple extreme values. This dataset accompanies the paper "Trends and drivers of water temperature extremes in mountain rivers" by van Hamel and Brunner published in WRR under DOI https://doi.org/10.1029/2024WR037518. Structure of the folder: - Selected_catchments.shp : Shapefile with the 177 catchments. - Selected_stations.shp : Shapefile with the 177 measurement stations. - WaterTemp_ExtremeValues_perCatchment.xlsx : Extreme water temperature values per catchment. - WaterTemp_ExtremeEvents_perCatchment.xlsx : Water temperature extreme events per catchment. - 8 hydro-climatic variables obtained from the gridded Copernicus European Regional ReAnalysis (CERRA) and the Copernicus European Regional ReAnalysis Land (CERRA-Land) dataset, with daily mean values per catchment area: - CERRA_Et (evaporation) - CERRA_Ms (snowmelt) - CERRA_Pt (precipitation) - CERRA_Ra (surface net solar radiation) - CERRA_Sm (soil moisture) - CERRA_Swe (snow water equivalent) - CERRA_Ta (air temperature) - CERRA_Ws (windspeed) - 2 hydrological variables (only available for 139 catchments, excluding the French stations): - MEAS_Qt (daily discharge measured at each station) - CALC_Qb (estimated baseflow component derived from MEAS_Qt with the Lyne and Hollick filter). Meta data 'Selected_catchments.shp': "station_ID" : ID of the catchment, can be used to link to the other files "Mountains" : Mountain region "Area (Km2)" : Catchment size [km2] "Min elev" : Minimum catchment elevation [m.a.s.l.] "Mean elev" : Mean catchment elevation [m.a.s.l.] "Max elev" : Maximum catchment elevation [m.a.s.l.] "Glaciers %" : Percentage of area covered by glaciers [%] "Pt as snow" : Percentage of precipitation that comes as snow [%] Meta data 'Selected_stations.shp': "station_number" : Number 1-177 "Mountain_region" : Mountain region "station_ID" : ID of the station, can be used to link to the other files (e.g. catchments) "original_id" : Original ID number "govnr" : Governmental number. Only available for Austrian stations "station_name" : Name of the station "x_coord _EPSG:3035" : x-coordinate in EPSG:3035 "y_coord _EPSG:3035" : y-coordinate in EPSG:3035 "lon_EPSG:4326" : Longitude in EPSG:4326 "lat_EPSG:4326" : Latitude in EPSG:4326 "station_elev" : Station elevation [m.a.s.l.] Meta data 'WaterTemp_ExtremeValues_perCatchment': "Date" : Daily time step [dd/mm/yyyy] starting at 01/01/1985 and ending at 31/12/2020 "{station_ID}" : Every column represents one catchment. Water temperature values [in degrees] are given for the days on which the water temperature was extreme. Meta data 'WaterTemp_ExtremeEvents_perCatchment': "station_ID" : ID of the catchment, can be used to link to the other files "start_date" : Date on which the event started [dd/mm/yyyy] "start_doy" : Day of the year (doy) on which the event started "end_date" : Date on which the event ended [dd/mm/yyyy] "duration" : Duration of the event in number of days [days] "intensity" : Intensity of the event in degrees above the threshold [degrees] "severity" : Severity of the event [degrees*days] Meta data 'CERRA_{variable}': "Date" : Daily time step [yyyy-mm-dd] starting at 1985-01-01 and ending at 2020-12-31 "{station_ID}" : Every column represents the mean daily data of the variable of interest per catchment. Meta data 'MEAS_Qt' and 'CALC_Qb': "datetime" : Daily time step [yyyy-mm-dd] starting at 2008-01-02 and ending at 2022-12-31 "{station_ID}" : Every column represents the mean daily data of the variable of interest per catchment. We thank all institutions that made water temperature and discharge data available: the Swiss Federal Office of the Environment (FOEN / BAFU), Naïades and EauFrance, the LArge-SaMple DAta for Hydrology and Environmental Sciences for Central Europe (LamaH-CE), the Department of water management of the Federal Ministry of Agriculture, Forestry, Regions and Water Management of Austria, the Norwegian Water Resources and Energy Directorate (NVE), and the AquaMonitor of Norwegian Institute for Water Research (NIVA), which was funded by the Norwegian Environmental Agency.
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This resource is referenced by | A. van Hamel and M.I. Brunner (2024). Trends and drivers of water temperature extremes in mountain rivers. Water Resources Research. DOI: https://doi.org/10.1029/2024WR037518 |
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This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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