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The file includes velocity data taken using an acoustic Doppler current profiler (ADCP) (Sontek M9 sensor) (Sontek, 2018) measured in March and June 2018 at the Sävar River, Sweden. The raw data are found in an Excel file and include the longitudinal flow speed (m/s) from each of the measured water depths. We have exported the data from RiverSurveyorLive software (https://www.sontek.com/softwaredetail.php?RiverSurveyor-LIVE-RSL-34#RSL) and cleaned the files to remove extra information, so that they include only the data we used in reported analyses.These velocity profiles were taken within a larger project to examine differences in hydraulics and sediment transport during ice-covered and open channel flow conditions. Within this project, seismic signals of these geomorphic processes were recorded encompassing the velocity measurement periods (Dietze & Polvi 2019).In winter (March 2018), the measurements were taken via holes drilled through the ice. The ‘moving boat’ method was applied in the RiverSurveyorLive software, but the sensor was kept static during the whole ~5-minute long measurement period in each hole. The velocity measurements for each hole are presented in separate Excel sheets in the file. During summer (June 2018), a similar method was ap-plied—the ADCP sensor was kept static for the same length of time in the same locations as the holes. Note that the winter measurements also had ice cover above them.The starting depth was the depth under the ice-water interface during winter, and at the water-air interface during summer. In the file, the velocity measurement cell closest to the surface is in the column “Cell1 Spd”. This column title refers to the speed (i.e., velocity) in m/s, of the corresponding measurement cell number. “Cell1 loc” refers to the depth of the cell from the surface in meters. Similarly, the near-bed layer velocity is in the column “Cell Spd xx,” with the highest number for that measurement location. Each measure-ment time step is found on a new row. If there is #N/A written in the cell, or the cell is empty, it means that there is no data from the corresponding cell.
Version history17. July 2019: release of Version 2.0. This version includes additionally the catchment boundaries provided as subfolder of geodata.zip. The version 1.0 is available in the "previous-versions" subfolder via the Data Download link. The time series did not change and are not included in the V1.0 zip folder. Data descriptionWe used different sensing techniques including time-lapse imagery, electric conductivity and stage measurements to generate a combined dataset of presence and absence of streamflow within a large number of nested sub-catchments in the Attert Catchment, Luxembourg. The first sites of observation were established in 2013 and successively extended to a total number of 182 in 2016 as part of the project “Catchments As Organized Systems” (CAOS, Zehe et al., 2014). Setup for time-lapse imagery measurements was inspired by Gilmore et al. (2013) while the setup for EC-sensor was proposed by Chapin et al. (2014). Temporal resolution ranged from 5 to 15 minutes intervals. Each single dataset was carefully processed and quality controlled before the time interval was homogenized to 30 minutes. The dataset provides valuable information of the dynamics of a meso-scale stream network in space and time.The Attert basin is located in the border region of Luxembourg and Belgium and covers an area of 247 km². The elevation of the catchment ranges from 245 m a.s.l. in Useldange to 549 m a.s.l. in the Ar-dennes. Climate conditions across the catchment are rather similar in terms of temperature and pre-cipitation. Hydrological regimes are mainly driven by seasonal fluctuations in evapotranspiration caus-ing flow to cease in intermittent reaches during dry periods. The catchment covers three predominant geologies: Slate, Marls and Sandstone. The dataset features data from catchments covering all geologi-cal characteristics from single geology to mixed geology. It can be used to test and evaluate hydrologic models, but also for the assessment of the intermittent stream ecosystem in the Attert basin.
The main component of this data publication is a dataset of predicted daily nutrient concentrations for NO3-N and TP for 150 monitoring stations along 60 German rivers (main rivers). The aim of this dataset is to fill the data gap of daily nutrient concentrations for a better understanding of nutrient transport from the rivers to the seas. So far, nutrient concentrations are sampled on a fortnightly basis, which can be insufficient for nutrient retention models working on a daily basis. With this method and available datasets, river basin managers have the opportunity to look at nutrient concentrations or load patterns on a finer resolution to adapt their management to improve water quality. The dataset was obtained by a random forest model (RF) based on measured NO3-N and TP concentrations between the years 2000 and 2019. The data was requested or where available downloaded from official websites of the Federal States or River Basins. Different variables for NO3-N and TP were finally considered in the models to produce the RF, like discharge, land use, day of the year.
Version history: This datased is an updated version of Francke et al. (2017; http://doi.org/10.5880/fidgeo.2017.003) for a revised version of this discussion paper. It contains further data collected, some of which also resulted in the revision of previous data (e.g. updated rating curves).A comprehensive hydro-sedimentological dataset for the Isábena catchment, NE Spain, for the period 2010-2018 is presented to analyse water and sediment fluxes in a Mediterranean meso-scale catchment. The dataset includes rainfall data from twelve rain gauges distributed within the study area complemented by meteorological data of twelve official meteo-stations. It comprises discharge data derived from water stage measurements as well as suspended sediment concentrations (SSC) at six gauging stations of the Isábena river and its sub-catchments. Soil spectroscopic data from 351 suspended sediment samples and 152 soil samples were collected to characterize sediment source regions and sediment properties via fingerprinting analyses.The Isábena catchment (445 km²) is located in the Southern Central Pyrenees ranging from 450 m to 2,720 m in elevation, together with a pronounced topography this leads to distinct temperature and precipitation gradients. The Isábena river shows marked discharge variations and high sediment yields causing severe siltation problems in the downstream Barasona reservoir. Main sediment source are badland areas located on Eocene marls that are well connected to the river network. The dataset features a wide set of parameters in a high spatial and temporal resolution suitable for advanced process understanding of water and sediment fluxes, their origin and connectivity, sediment budgeting and for evaluating and further developing hydro-sedimentological models in Mediterranean meso-scale mountainous catchments.The data have been published with the CUAHSI Water Data Center and is structured according to its guidelines (.csv format). For more detailed information please read the user guide on cloud publications with the CUAHSI Water Dater Center or the ODM guide for uploading data using CUAHSI´s ODM uploader added to the folder CUAHSI_ODM-Guide.zip. The database can be found in the HISCENTRAL catalogue (http://hiscentral.cuahsi.org/pub_network.aspx?n=5622). It is directly accessible via the API (http://hydroportal.cuahsi.org/isabena/cuahsi_1_1.asmx?WSDL) or in zipped archives at this DOI Landing Page (http://doi.org/10.5880/fidgeo.2018.011). For more detailed information, please read the user guide on cloud publications with the CUAHSI Water Dater Center (UserGuide.pdf) or the ODM guide for uploading data using CUAHSI´s ODM uploader in the ODM_Guide.zip archive.The data are available in four thematic zip folders:(1) hydro (hydrological data): water stage (manual readings and automatically recorded), river discharge (meterings and converted from stage)(2) meta (metadata) with the description of the different datafiles relevant for this dataset according to the CUAHSI HIS Standards(3) meteo (meteorological data): rainfall, temperature, radiation, humidity(4) sediment (sedimentological data): turbidity, suspended sediment concentration (from samples and from turbidity), sediment and soil reflectance spectraand are complemented by:(5) CUAHSI_ODM-Guide: User Guide, CUAHSI´s ODM uploader in Excel (.xlsx) and Open Office (.ods) formats(6) scripts: auxiliary R-script templates for data access, data analysis and visualisation(7) supplementary materials: stage-discharge- and turbidimeter rating curves
The dataset comprises a range of variables describing characteristics of flood events and river catchments for 480 gauging stations in Germany and Austria. The event characteristics are asscoiated with annual maximum flood events in the period from 1951 to 2010. They include variables on event precipitation, antecedent catchment state, event catchment response, event timing, and event types. The catchment characteristics include variables on catchment area, catchment wetness, tail heaviness of rainfall, nonlinearity of catchment response, and synchronicity of precipitation and catchment state. The variables were compiled as potential predictors of heavy tail behaviour of flood peak distributions. They are based on gauge observations of discharge, E-OBS meteorological data (Haylock et al. 2008), mHM hydrological model simulations (Samaniego et al., 2010), 4DAS climate reanalysis data (Primo et al., 2019), and the 25x25 m resolution EU-DEM v1.1. A short description of the data processing is included in the file inventory and more details can be found in Macdonald et al. (2022).
Version history:We recommend to use the revised version of this data publication (http://doi.org/10.5880/fidgeo.2018.011) which contains further data collected (2010-2018), some of which also resulted in the revision of previous data (e.g. updated rating curves).A comprehensive hydro-sedimentological dataset for the Isábena catchment, NE Spain, for the period 2010-2016 is presented to analyse water and sediment fluxes in a Mediterranean meso-scale catchment. The dataset includes rainfall data from twelve rain gauges distributed within the study area complemented by meteorological data of twelve official meteo-stations. It comprises discharge data derived from water stage measurements as well as suspended sediment concentrations (SSC) at six gauging stations of the Isábena river and its sub-catchments.Soil spectroscopic data from 351 suspended sediment samples and 152 soil samples were collected to characterize sediment source regions and sediment properties via fingerprinting analyses. The Isábena catchment (445 km²) is located in the Southern Central Pyrenees ranging from 450 m to 2,720 m in elevation, together with a pronounced topography this leads to distinct temperature and precipitation gradients.The Isábena river shows marked discharge variations and high sediment yields causing severe siltation problems in the downstream Barasona reservoir. Main sediment source are badland areas located on Eocene marls that are well connected to the river network. The dataset features a wide set of parameters in a high spatial and temporal resolution suitable for advanced process understanding of water and sediment fluxes, their origin and connectivity, sediment budgeting and for evaluating and further developing hydro-sedimentological models in Mediterranean meso-scale mountainous catchments.The data are available in .csv format folllowing the CUAHSI Community Observations Data Model (ODM) as .zip files via this DOI Landing Page and directly from the CUASI HIS Database via http://hydroportal.cuahsi.org/isabena/cuahsi_1_1.asmx?WSDL.The data are provided in four thematic zip folders:(1) hydro (hydrological data): water stage (manual readings and automatically recorded), river discharge (meterings and converted from stage)(2) meta (metadata) with the description of the different datafiles relevant for this dataset according to the CUAHSI HIS Standards(3) meteo (meteorological data): rainfall, temperature, radiation, humidity(4) sediment (sedimentological data): turbidity, suspended sediment concentration (from samples and from turbidity), sediment and soil reflectance spectraFor more detailed information, please read the user guide on cloud publications with the CUAHSI Water Dater Center (UserGuide.pdf) or the ODM guide for uploading data using CUAHSI´s ODM uploader (ODMGuide.xlsx in folder ODM_Guide_2017.zip).
VERSION HISTORY:-On October 18, 2018 we republished all simulation data for all water (global) sector impact models to get the data sets into the new ESGF search facet structure. There were no changes to the simulation data.- On November 27, 2018 we republished simulation data for monthly variables swe, soilmoist and rootmoist for impact model PCR-GLOBWB due to an error in the units. Instead of reporting mass per area (kg/m2), values corresponded to mass flux rate (kg/m2/s). Values were thus multiplied by 86400 in order to obtain the correct values in kg/m2. This data caveat was documented in the ISIMIP website (ISIMIP2a: PCR-GLOBWB reported three variables in wrong unit).----------------------------------------------------------------------------The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) simulation data is under continuous review and improvement, and updates are thus likely to happen. All changes and caveats are documented under https://www.isimip.org/outputdata/output-data-changelog/. For accessing the data set as in http://doi.org/10.5880/PIK.2017.010 before November 27, 2018 please write to the ISIMIP Data Management Team: isimip-data[at]pik-potsdam.de.----------------------------------------------------------------------------DATA DESCRIPTION:The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) provides a framework for the collation of a set of consistent, multi-sector, multi-scale climate-impact simulations, based on scientifically and politically-relevant historical and future scenarios. This framework serves as a basis for robust projections of climate impacts, as well as facilitating model evaluation and improvement, allowing for improved estimates of the biophysical and socio-economic impacts of climate change at different levels of global warming. It also provides a unique opportunity to consider interactions between climate change impacts across sectors.ISIMIP2a is the second ISIMIP simulation round, focusing on historical simulations (1971-2010 approx.) of climate impacts on agriculture, fisheries, permafrost, biomes, regional and global water and forests. This may serve as a basis for model evaluation and improvement, allowing for improved estimates of the biophysical and socio-economic impacts of climate change at different levels of global warming.The focus topic for ISIMIP2a is model evaluation and validation, in particular with respect to the representation of impacts of extreme weather events and climate variability. During this phase, four common global observational climate data sets were provided across all impact models and sectors. In addition, appropriate observational data sets of impacts for each sector were collected, against which the models can be benchmarked. Access to the input data for the impact models is provided through a central ISIMIP archive (see https://www.isimip.org/gettingstarted/#input-data-bias-correction).This entry refers to the ISIMIP2a simulation data from global hydrology models: CLM4, DBH, H08, JULES_W1, JULES_B1, LPJmL, MATSIRO, MPI-HM, ORCHIDEE, PCR-GLOBWB, SWBM, VIC, WaterGAP2
The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) provides a framework for the collation of a set of consistent, multi-sector, multi-scale climate-impact simulations, based on scientifically and politically-relevant historical and future scenarios. This framework serves as a basis for robust projections of climate impacts, as well as facilitating model evaluation and improvement, allowing for improved estimates of the biophysical and socio-economic impacts of climate change at different levels of global warming. It also provides a unique opportunity to consider interactions between climate change impacts across sectors.ISIMIP2a is the second ISIMIP simulation round, focusing on historical simulations (1971-2010 approx.) of climate impacts on agriculture, fisheries, permafrost, biomes, regional and global water and forests. This may serve as a basis for model evaluation and improvement, allowing for improved estimates of the biophysical and socio-economic impacts of climate change at different levels of global warming.The focus topic for ISIMIP2a is model evaluation and validation, in particular with respect to the representation of impacts of extreme weather events and climate variability. During this phase, four common global observational climate data sets were provided across all impact models and sectors. In addition, appropriate observational data sets of impacts for each sector were collected, against which the models can be benchmarked. Access to the input data for the impact models is provided through a central ISIMIP archive (see https://www.isimip.org/gettingstarted/#input-data-bias-correction).This entry refers to the ISIMIP2a simulation data from global hydrology models: CLM4, DBH, H08, JULES_W1, JULES_B1, LPJmL, MATSIRO, MPI-HM, ORCHIDEE, PCR-GLOBWB, SWBM, VIC, WaterGAP2.
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