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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.
The German-Swiss Hillscape project focuses on the vertical and lateral redistribution of water and matter along hillslopes and how this redistribution is affected by soil, vegetation and landscape development. The overall research question of the project is: How does the hillslope feedback cycle evolve in the first 10,000 years and how is this related to the evolution of hillslope structure? In order to tackle this research question, chronosequences in alpine glacier forelands were selected and artificial rainfall experiments were conducted. These datasets specifically contain data at the interface of sediment transport and hillslope hydrology. Specifically, they contain data about changes in soil surface characteristics (saturated hydraulic conductivity for three soil depths, soil aggregate stability for the surface soil layer), overland and shallow subsurface flow (runoff characteristics as peak flow rates, duration of flow, runoff ratios, event water fractions) and sediment yield values for overland flow along the moraine chronosequence. We measured the near-surface hydrological characteristics of four moraines with different age on a carbonate glacier foreland (forefield of the Griessfirn, close to the Klausenpass alpine road) and silicate glacier foreland (glacier forefield of the Steingletscher, close to the Sustenpass alpine road). The ages of the four moraines were ~30, ~160, ~3000 and ~10000 years (Sustenpass) and ~80, ~160, 4900 and 13500 years (Klausenpass). We selected 3 plots (dimensions: 4m x 6m) on each moraine, based on the vegetation complexity (low, medium and high), to cover as much of the potential variability within each moraine as possible. The structural vegetation complexity was based on the vegetation cover, number of different species, and functional diversity (based on stem growth form, root type, clonal growth organ, seed mass, Raunkiaer’s life form, leaf dry matter content, nitrogen content and specific leaf area (Garnier et al., 2016). We measured the near-surface hydrological properties of each plot (the saturated hydraulic conductivity and the soil aggregate stability) because the properties are essential for the runoff response on each plot. The runoff response and its characteristics for each plot was determined for sprinkling experiments of different intensities and during natural rainfall events (only at Klausenpass). We used tracers (Deuteriumoxid and NaCl) that we added to the sprinkling water and took samples of the soil water, then rainfall and the runoff to perform a 3-end-member hydrograph separation, using the method of Gibson et al. (2000). With that, we were able to identify the mixing (e.g. event water fraction), storage and flow pathways of the overland flow and subsurface flow. We filtered the overland flow samples to define the total sediment flux per experiment.
This dataset contains element concentrations of six different hydrological compartments sampled on a daily basis over the course of one year in two neighboured first order headwater catchments located in the Conventwald (Black Forest, Germany). Critical Zone water compartments include above-canopy precipitation (bulk precipitation including rainwater, snow and fog water), below-canopy precipitation (throughfall), subsurface flow from three distinct soil layers (organic layer, upper mineral soil, deep mineral soil), groundwater, creek water and spring water. Element concentrations include major elements (Ca, K, Mg, Na, Si, S), trace elements (Al, Ba, Cr, Cu, Fe, Li, Mn, P, Sr, Zn), anion (Cl), and dissolved organic elements (DOC, DON). The data were used to explore concentration (C) - discharge (Q) relationships and to calculate short-term element-specific chemical weathering fluxes, which were compared with previously published long-term element-specific chemical weathering fluxes. The ratio of both weathering fluxes, described by the so-called “Dissolved Export Efficiency” (DEE) metric revealed deficits in the stream dissolved load. These deficits were attributed to colloid-bound export and either storage in re-growing forest biomass or export in biogenic particulate form. Tables supplementary to the article, including data quality control, are provided in .pdf and .xlsx formats. In addition, data measured in the course of the study are also provided as machine readable ASCII files.
Knowledge of groundwater flow is of high relevance for groundwater management and the planning of different subsurface utilizations such as deep geothermal facilities. While numerical models can help to understand the hydrodynamics of the targeted reservoir, their predictive capabilities are limited by the assumptions made in their set up. Among others, the choice of appropriate hydraulic boundary conditions, adopted to represent the regional to local flow dynamics in the simulation run, is of crucial importance for the final modelling result. In this publication we present the hydrogeological models to obtain results to quantify how and to which degree different upper hydraulic boundary conditions and vertical cross boundary fluid movement influence the calculated deep fluid conditions Therefore, we take the central Upper Rhine Graben area as a natural laboratory. The presented three models are set up with different sets of boundary conditions. The Reference Model uses the topography as upper hydraulic pressure surface of 0 kPa. In model S1, a subdued replica of the topography, which was built on the base of hydraulic head measurements is applied as the upper hydraulic boundary condition and in model S2 vertical cross boundary flow is implemented. Based on our results, we illustrate in the landing paper that for the Upper Rhine Graben specific characteristics of the flow field are robust and insensitive to the choice of imposed hydraulic boundary conditions, while specific local characteristics are more sensitive. Accordingly, these robust features characterizing the first order groundwater flow dynamics in the Upper Rhine Graben include: (i) a regional groundwater flow component descending from the graben shoulders to rise at its centre; (ii) infiltration of fluids across the graben shoulders, which locally rise along the main border faults; (iii) the presence of heterogeneous hydraulic potentials at the rift shoulders. The configuration of the adopted boundary conditions influence primarily calculated flow velocities and the absolute position of the upflow axis within the graben sediments. In addition, the choice of upper hydraulic boundary conditions exerts a direct control on the evolving local flow dynamics, with the degree of influence gradually decreasing with increasing depth. With respect to regional flow modelling of basin hosted, deep water resources, the main conclusions derived from this study are: (i) the often considered water table as an exact replica of the model topography (Reference Model) likely introduces a source of error in the simulations in regional hydraulic modelling approaches. Here, we show that these errors can be minimized by making use of a water table as upper boundary condition derived from available hydraulic head measurements (model S1). If the study area is part of a supra-regional flow system - like the central Upper Rhine Graben is part of the whole Upper Rhine Graben - the in- and outflow across vertical boundaries need to be considered (model S2).
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.
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
For the article “How to Tailor my Process-based Model? Dynamic Identifiability Analysis of Flexible Model Structures” (Pilz et al., submitted) a flexible simulation environment is coupled with an algorithm for dynamic identifiability analysis to form a diagnostic tool for process-based model building. This associated data description describes first which software is needed (R and the ECHSE model) and how to configure your computer in order to run the model and the analysis. Second, the input data provided within this data set are described. Eventually, the R scripts are described, which were used to initialize and run the model and conduct the subsequent identifiability analysis. This publication comprises the ECHSE model, all R packages in their employed versions, the model setup and results, figures and data presented in the associated research paper, and the R scripts used to initialize and run the model and conduct all analyses.
The Regional Research Network „Water in Central Asia“ (CAWa) funded by the German Federal Foreign Office consists of 19 remotely operated multi-parameter stations (ROMPS) in Central Asia. These stations were installed by the German Research Centre for Geosciences (GFZ) in Potsdam, Germany in close cooperation with the Central-Asian Institute for Applied Geosciences (CAIAG) in Bishkek, Kyrgyzstan, the national hydrometeorological services in Uzbekistan and Tajikistan, the Ulugh Beg Astronomical Institute in Tashkent, Uzbekistan, and the Kabul Polytechnic University, Afghanistan. The primary objective of these stations is to support the establishment of a reliable data basis of meteorological and hydrological data especially in remote areas with extreme climate conditions in Central Asia for applications in climate and water monitoring. Up to now, ten years of data are provided for an area of scarce station distribution and with limited open access data which can be used for a wide range of scientific or engineering applications. This dataset provides different types of raw hydrometeorological data such as air temperature, relative humidity, air pressure, wind speed and direction, precipitation, solar radiation, soil moisture and soil temperature as well as snow parameters and river discharge information for selected sites. The data has not undergone any quality control mechanism and should, therefore, be seen as raw data. A visual inspection of the data set has been made and some errors and quality degradation are listed in Zech et al. (2020) but does not claim to be complete. A quality control is strongly recommended by the authors before using the data. Each station data has its own storage directory at the data dissemination server named with the abbreviation (4-letter code) of the station. The data is sampled with a 5-minute interval and stored in hourly files separated by the type of data. These files are then archived as monthly files named with the station abbreviation, type of data, year and month. After one year, these monthly files are further archived to a yearly file. A detailed description for the stations is provided by the Station Exposure Descriptions. Further information about the dataset can be found in Zech et al. (2020). All data is compiled as ASCII data in two different formats which are explained in the documents GITW-SSP-FMT-GFZ-003.pdf (for the stations ALAI, ALA6, and SARY) and CAWA-SSP-FMT-GFZ-006.pdf (for all other stations). Monthly, the data will be dynamically extended as long as data can be acquired from the stations. Additionally, the near real-time data can be displayed and downloaded without any registration from the Sensor Data Storage System (SDSS) hosted at the Central-Asian Institute for Applied Geosciences (CAIAG) in Bishkek, Kyrgyzstan.
For the article “How to Tailor my Process-based Model? Dynamic Identifiability Analysis of Flexible Model Structures” (Pilz et al., submitted) a flexible simulation environment is coupled with an algorithm for dynamic identifiability analysis to form a diagnostic tool for process-based model building. This software publication provides the simulation environment ECHSE along with the new WASA engine. The latter was developed and employed for the associated research article. The original ECHSE software was introduced by Kneis (2015) and can be obtained from http://echse.github.io/.
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).
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