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13 results for “large-sample”
LamaH-CE: LArge-SaMple DAta for Hydrology and Environmental Sciences for Central Europe – files
<p><strong>Version 1.0 - This version is the final revised one.</strong></p> <p>This is the LamaH-CE dataset accompanying the paper: Klingler et al., LamaH-CE | LArge-SaMple DAta for Hydrology and Environmental Sciences for Central Europe, published at Earth System Science Data (ESSD), 2021 (<a href="https://doi.org/10.5194/essd-13-4529-2021">https://doi.org/10.5194/essd-13-4529-2021</a>).</p> <p>LamaH-CE contains a collection of runoff and meteorological time series as well as various (catchment) attributes for 859 gauged basins. The hydrometeorological time series are provided with daily and hourly time resolution including quality flags. All meteorological and the majority of runoff time series cover a span of over 35 years, which enables long-term analyses with high temporal resolution.<br> LamaH is in its basics quite sililar to the well-known CAMELS datasets for the contiguous United States (<a href="https://doi.org/10.5194/hess-21-5293-2017">https://doi.org/10.5194/hess-21-5293-2017</a>), Chile (<a href="https://doi.org/10.5194/hess-22-5817-2018">https://doi.org/10.5194/hess-22-5817-2018</a>), Brazil (<a href="https://doi.org/10.5194/essd-12-2075-2020">https://doi.org/10.5194/essd-12-2075-2020</a>), Great Britain (<a href="https://doi.org/10.5194/essd-12-2459-2020">https://doi.org/10.5194/essd-12-2459-2020</a>) and Australia (<a href="https://doi.org/10.5194/essd-13-3847-2021">https://doi.org/10.5194/essd-13-3847-2021</a>), but new features like additional basin delineations (intermediate catchments) and attributes allow to consider the hydrological network and river topology in further applications.</p> <p>We provide two different files to download: 1) Hydrometeorological time series with daily and hourly resolution, which requires decompressed about 70 GB of free disk space. 2) Hydrometeorological time series only with daily resolution, which requires 5 GB. Beyond the temporal resolution of the time series, there are no differences.</p> <p><strong>Note: </strong>It is recommended to read the supplementary info file before using the dataset. For example, it clarifies the time conventions and that <strong>NAs</strong> are indicated by the number<strong> -999</strong> in the <strong>runoff time series</strong>.</p> <p><strong>Disclaimer:</strong> We have created LamaH with care and checked the outputs for plausibility. By downloading the dataset, you agree that we nor the provider of the used source datasets (e.g. runoff time series) cannot be liable for the data provided. The runoff time series of the German federal states Bavaria and Baden-Württemberg are retrospective checked and updated by the hydrographic services. Therefore, it might be appropriate to obtain more up-to-date runoff data from Bavaria (<a href="https://www.gkd.bayern.de/en/rivers/discharge/tables">https://www.gkd.bayern.de/en/rivers/discharge/tables</a>) and Baden-Württemberg (<a href="https://udo.lubw.baden-wuerttemberg.de/public/p/pegel_messwerte_leer">https://udo.lubw.baden-wuerttemberg.de/public/p/pegel_messwerte_leer</a>). Runoff data from the Czech Republic may not be used to set up operational warning systems (<a href="https://www.chmi.cz/files/portal/docs/hydro/denni_data/Podminky_uziti.pdf">https://www.chmi.cz/files/portal/docs/hydro/denni_data/Podminky_uziti.pdf</a>).</p> <p><strong>License: </strong>This work is licensed with CC BY-SA 4.0 (<a href="https://creativecommons.org/licenses/by-sa/4.0/">https://creativecommons.org/licenses/by-sa/4.0/</a>). This means that you may freely use and modify the data (even for commercial purposes). But you have to give appropriate credit (associated ESSD paper, version of dataset and all sources which are declared in the folder "Info"), indicate if and what changes were made and distribute your work under the same public license as the original.</p> <p><strong>Additional references: </strong>We ask kindly for compliance in citing the following references when using LamaH, as an agreement to cite was usually a condition of sharing the data: BAFU (2020), CHMI (2020), GKD (2020), HZB (2020), LUBW (2020), BMLFUW (2013), Broxton et al. (2014), CORINE (2012), EEA (2019), ESDB (2004), Farr et al. (2007), Friedl and Sulla-Menashe (2019), Gleeson et al. (2014), HAO (2007), Hartmann and Moosdorf (2012), Hiederer (2013a, b), Linke et al. (2019), Muñoz Sabater et al. (2021), Muñoz Sabater (2019a), Myneni et al. (2015), Pelletier et al. (2016), Toth et al. (2017), Trabucco and Zomer (2019), and Vermote (2015). These references are listed in detail in the accompanying <a href="https://doi.org/10.5194/essd-13-4529-2021">paper</a>.</p> <p><strong>Supplements: </strong>We have created additional files after publication (therefore non peer-reviewed):<br> 1) Shapefiles for reservoirs (points) and cross-basin water transfers (lines) including several attributes as well as tables with information about the accumulated storage volume and effective catchment area (considerung artificial in- and outflows) for every runoff gauge.<br> 2) Water quality data (e.g. dissolved oxygen, water temperature, conductivity, NO3-N), which are suitable to the gauges. The data for water quality may not be used for commercial purposes.<br> If you are interessted, just send us an email with your name, affiliation and the intended purpose for the requested files to the address listed below. If you find any errors in the dataset, feel free to send us an email to: christoph.klingler@boku.ac.at</p>
CAMELS-ES: Catchment Attributes and Meteorology for Large-Sample Studies – Spain
<p>CAMELS-ES is a hydrometeorological dataset covering 269 catchments in Spain and the time period from 1991 to 2020. It is a contribution to the Caravan initiative, a global community that collects open hydrometeorological data to support global hydrological modelling. As other datasets in Caravan, CAMELS-ES includes both catchment attributes extracted from HydroATLAS and ERA5-Land, meteorological time series from ERA5-Land and discharge records from the Spanish Ministry of the Environment. In addition, CAMELS-ES includes information from the European Flood Awareness System (EFASv5): catchment attributes extracted from the input static maps used in the hydrological model LISFLOOD, and the simulated discharge from EFASv5 long run.</p>
CABra: a novel large-sample dataset for Brazilian catchments
<p>Hydrometeorological time series and catchment attributes from the CABra dataset. The manuscript of "CABra: a novel large-sample dataset for Brazilian catchments" is under review in Hydrology and Earth System Sciences (HESS) journal.</p> <p>Here we present the Catchments Attributes for Brazil (CABra), which is a large-sample dataset for Brazilian catchments that includes long-term data (30 years) for 735 catchments in eight main catchment attribute classes (climate, streamflow, groundwater, geology, soil, topography, land-use and land-cover, and hydrologic disturbance). We have collected and synthesized data from multiple sources (ground stations, remote sensing, and gridded datasets). To prepare the dataset, we delineated all the catchments using the Multi-Error-Removed Improved-Terrain Digital Elevation Model and the coordinates of the streamflow stations provided by the Brazilian Water Agency (ANA), where only the stations with 30 years (1980-2010) of data and less than 10% of missing records were included. Catchment areas range from 9 to 4,800,000 km² and the mean daily streamflow varies from 0.02 to 9 mm day<sup>-1</sup>. Several signatures and indices were calculated based on the climate and streamflow data. Additionally, our dataset includes boundary shapefiles, geographic coordinates, and drainage areas for each catchment, aside from more than 100 attributes within the attribute classes.</p> <p>Data can also be accessed at: thecabradataset.shinyapps.io/CABra </p> <p> </p> <p><em><strong>* This version includes water demand in CABra catchments for 2020 and 2040 (projection).</strong></em></p>
EARLS: European aggregated reconstruction for large-sample studies
<p>EARLS is an openly available pan-European runoff–reconstruction dataset.</p> <p>As of now it is structured in the following way: </p> <div> <ul> <li>The `<em>coordinates.csv`</em> file contains basin outlet information with 4 columns: basin id (idx), type, and estimated latitude (lat) and longitude (lon) of the outlet.</li> <li>The `<em>license.md`</em> file contains information about the licensing.</li> <li>The `<em>shapefile` </em>folder includes a shapefile with all basin boundaries (see: <a href="https://www.hydrosheds.org/products/hydrobasins">HydroBASINS</a>).</li> <li>The `<em>reconstructions`</em> folder contains CSV files. Each file is named after the basin id and has at least two columns: date and simulation. The simulations are given in mm. Additional columns can be used to provide more information. For the current EARLS we added two additional columns that provide the remaining parameters for the uncertainty estimation.</li> <li>The `<em>model-card`</em> folder contains 2 files: `<em>model-card.html`</em>, and `<em>earls-crest.png`</em>. The html document includes the png as logo and renders a model card. A <a href="https://arxiv.org/abs/1810.03993">model card </a>is a short summary of the model genesis, designed to increase transparency by communicating information about trained models to broad audiences. We include all three files in the dataset so that future extensions can adapt them with maximal ease. We will also host the markdown files on the main home so that the permanent identifier within the model card can be used to access the data from there.</li> <li>Additional data/folders are optional, but can be used to provide background information. For instance, the EARLS contains an `<em>inputs`</em> folder, which comprises the basin-aggregated dynamic and static inputs: <br> <ul> <li>For the dynamic inputs (derived from <a href="https://www.ecad.eu/download/ensembles/download.php">E-OBS</a>) we use precipitation in mm per day, daily minimum/maximum/average temperature in °C.</li> <li>For the static inputs (derived form <a href="https://www.hydrosheds.org/hydroatlas">HydroATLAS</a>) we use basin area in square kilometers, average elevation in meter, average slopes in degrees, average stream gradient in decimeter per kilometer, average long-term air temperature in degrees Celsius, minimum long-term air temperature in °C, maximum long-term air temperature in °C, a global aridity index, a global climate moisture index, average fraction of sand in %, average fraction of clay in %, average fraction of silt in %, and average organic carbon content in tons per hectar.</li> </ul> </li> </ul> <h2>Changelog</h2> <p><strong>v0.3</strong></p> <ul> <li>Introduced a changelog. yay. </li> <li>Little corrections (spelling mistakes etc.) and nicer formatting in the technical data description. </li> <li>Corrected streamflow and variance normalization from hours to daily (affected versions: v0.0 and v.0.2; thanks to Corinna Frank).</li> <li>Corrected technical description of the area from m2 to km2 (thanks to Corrina Frank).</li> <li>Introduced an example data-file with a single basin (thanks to Juliane Mai).</li> </ul> </div>
Caravan - A global community dataset for large-sample hydrology
<p><strong>This is the </strong><strong>accompanying dataset to the following paper <a href="https://www.nature.com/articles/s41597-023-01975-w">https://www.nature.com/articles/s41597-023-01975-w</a></strong></p> <p><em>Caravan</em> is an open community dataset of meteorological forcing data, catchment attributes, and discharge daat for catchments around the world. Additionally, Caravan provides code to derive meteorological forcing data and catchment attributes from the same data sources in the cloud, making it easy for anyone to extend Caravan to new catchments. The vision of Caravan is to provide the foundation for a truly global open source community resource that will grow over time.</p> <p>If you use Caravan in your research, it would be appreciated to not only cite Caravan itself, but also the source datasets, to pay respect to the amount of work that was put into the creation of these datasets and that made Caravan possible in the first place.</p> <p><strong>All current development and additional community extensions can be found at <a href="https://github.com/kratzert/Caravan">https://github.com/kratzert/Caravan</a><br></strong><br><strong>IMPORTANT: Due to size limitations for individual repositories, the netCDF version and the CSV version of Caravan (since Version 1.6) are split into two different repositories. You can find the CSV version at <a href="https://zenodo.org/records/15530021">https://zenodo.org/records/15530021</a></strong></p> <p>Channel Log:</p> <ul> <li><strong>23 May 2022: Version 0.2</strong> - Resolved a bug when renaming the LamaH gauge ids from the LamaH ids to the official gauge ids provided as "govnr" in the LamaH dataset attribute files.</li> <li><strong>24 May 2022: Version 0.3</strong> - Fixed gaps in forcing data in some "camels" (US) basins.</li> <li><strong>15 June 2022: Version 0.4</strong> - Fixed replacing negative CAMELS US values with NaN (-999 in CAMELS indicates missing observation).</li> <li><strong>1 December 2022: Version 0.4 </strong>- Added 4298 basins in the US, Canada and Mexico (part of HYSETS), now totalling to 6830 basins. Fixed a bug in the computation of catchment attributes that are defined as pour point properties, where sometimes the wrong HydroATLAS polygon was picked. Restructured the attribute files and added some more meta data (station name and country).</li> <li><strong>16 January 2023: Version 1.0</strong> - Version of the official paper release. No changes in the data but added a static copy of the accompanying code of the paper. For the most up to date version, please check https://github.com/kratzert/Caravan</li> <li><strong>10 May 2023: Version 1.1</strong> - No data change, just update data description.</li> <li><strong>17 May 2023: Version 1.2</strong> - Updated a handful of attribute values that were affected by a bug in their derivation. See https://github.com/kratzert/Caravan/issues/22 for details.</li> <li><strong>16 April 2024: Version 1.4</strong> - Added 9130 gauges from the original source dataset that were initially not included because of the area thresholds (i.e. basins smaller than 100sqkm or larger than 2000sqkm). Also extended the forcing period for all gauges (including the original ones) to 1950-2023. Added two different download options that include timeseries data only as either csv files (Caravan-csv.tar.xz) or netcdf files (Caravan-nc.tar.xz). Including the large basins also required an update in the earth engine code</li> <li><strong>16 Jan 2025: Version 1.5</strong> - Added FAO Penman-Monteith PET (potential_evaporation_sum_FAO_PENMAN_MONTEITH) and renamed the ERA5-LAND potential_evaporation band to potential_evaporation_sum_ERA5_LAND. Also added all PET-related climated indices derived with the Penman-Monteith PET band (suffix "_FAO_PM") and renamed the old PET-related indices accordingly (suffix "_ERA5_LAND"). </li> <li><strong>27 May 2025: Version 1.6</strong><br> <ul> <li>Updated the CAMELS-AUS data to source from CAMELS-AUS v2. This means more basins (561 compared to 222) and more recent streamflow data (2022 compared to 2014). Note that the gauge id for four basins changed between the original CAMELS-AUS version and v2. Those gauges are ['camelsaus_224213A', 'camelsaus_224214A', 'camelsaus_227225A', 'camelsaus_403213A'] that all lost their trailing "A". To stay synced with CAMELS-AUS (v2), we also adapted the new naming.</li> <li>Added VERSION file to the root directory that contains the current version number.</li> <li>Updated the code to the most recent GitHub snapshot (commit 6eab036).</li> <li>Due to the 50GB repository limit, we had to split the netCDF version and the CSV version into two separate repositories. The CSV version can be found under https://zenodo.org/records/15530021</li> </ul> </li> </ul>
Caravan-DE: Caravan extension Germany - German dataset for large-sample hydrology
<p><em>Caravan</em> is an open community dataset of meteorological forcing data, catchment attributes, and discharge data for catchments around the world:<a href="../record/6578598" target="_blank" rel="noopener"> https://zenodo.org/record/6578598</a>. <br>We have employed the published code to derive meteorological forcing data and catchment attributes from global data sources to extend Caravan with data for <strong>1887 catchments</strong> in Germany. The time series data are in <strong>daily resolution and span up to 70 years, from January 1951 to December 2020</strong>.</p> <p>Most of the catchments in Caravan-DE are also part of the CAMELS-DE dataset (<a href="https://doi.org/10.5281/zenodo.13837553" target="_blank" rel="noopener">10.5281/zenodo.13837553</a>, 1582 catchments). As CAMELS-DE relies on meteorological forcing data that is only available within the borders of Germany, catchments going beyond the German national borders had to be discarded. Caravan uses global data products for the meteorological forcing data and catchment attributes, which is why Caravan-DE includes these catchments that are partly located outside of Germany. As catchments in Caravan-DE and CAMELS-DE are identified by the same ID, the datasets can be used together.<br>Please refer to the CAMELS-DE paper (<a href="https://doi.org/10.5194/essd-2024-318">https://doi.org/10.5194/essd-2024-318</a>) for information about discharge data and the catchment geometries used for both Caravan-DE and CAMELS-DE.</p> <p>For the processing of the data the following guide was followed step by step: <a href="https://github.com/kratzert/Caravan/wiki/Extending-Caravan-with-new-basins">https://github.com/kratzert/Caravan/wiki/Extending-Caravan-with-new-basins</a></p> <h3> </h3> <h3>Disclaimer for discharge and water level data provided by the German federal state agencies:</h3> <p>english:<em><br>The state agencies do not guarantee the accuracy or completeness of the discharge or water level data provided. In addition, all hydrological data may be subject to future revisions, including adjustments to the rating curves or corrections of errors. Therefore, it is necessary to obtain the most recent discharge time series directly from the federal state authorities for projects that require water law permits. Additionally, the regulations of the respective federal state apply and specific enquiries should be made as needed. It is also important to note that the state agencies explicitly disclaim any warranty as to the accuracy or completeness of the data and therefore any liability claims against any of the federal states are also excluded.</em></p> <p>german:<em><br>Die Ländesämter gewährleisten nicht die Genauigkeit oder Vollständigkeit der bereitgestellten Abfluss oder Wasserstandsdaten. Zudem können alle hydrologischen Daten zukünftigen Überarbeitungen unterliegen, einschließlich Anpassungen der Wasserstands-Abflussbeziehung oder der Korrektur von Fehlern. Daher ist es notwendig, die aktuellsten Abflusszeitreihen direkt bei den Landesbehörden zu beziehen, falls Wasserrechtsgenehmigungen erforderlich sind. Zusätzlich gelten die Vorschriften des jeweiligen Bundeslandes, und spezifische Anfragen sollten bei Bedarf gestellt werden. Es ist ebenfalls wichtig zu beachten, dass die staatlichen Behörden ausdrücklich jegliche Gewährleistung hinsichtlich der Genauigkeit oder Vollständigkeit der Daten ausschließen und somit auch jegliche Haftungsansprüche gegenüber einem der Bundesländer ausgeschlossen sind.</em></p> <p> </p> <h3>Changelog</h3> <ul> <li>v1.0.1 <ul> <li>Small changes to be consistent with other Caravan extensions (see <a href="https://github.com/kratzert/Caravan/issues/35" target="_blank" rel="noopener">https://github.com/kratzert/Caravan/issues/35</a>): <ul> <li>camelsde_basin_shapes.shp: removed column gauge_name</li> <li> <div>attributes_other_camelsde.csv: added river name to gauge_name column</div> </li> </ul> </li> </ul> </li> <li>v1.1.0 <ul> <li>Added FAO Penman-Monteith PET (potential_evaporation_sum_FAO_PENMAN_MONTEITH) and renamed the ERA5-LAND potential_evaporation band to potential_evaporation_sum_ERA5_LAND. Also added all PET-related climate indices derived with the Penman-Monteith PET band (suffix "_FAO_PM") and renamed the old PET-related indices accordingly (suffix "_ERA5_LAND"). <br>This was conducted to be consistent with <a href="https://doi.org/10.5281/zenodo.14673536" target="_blank" rel="noopener">Caravan version 1.5</a>.</li> </ul> </li> <li>v1.1.1 <ul> <li>By mistake, the new variables for v1.1.0 were missing in the climatic indices, these have now been added.</li> </ul> </li> </ul>
Catchment attributes and hydro-meteorological time series for large-sample studies across hydrologic Switzerland (CAMELS-CH)
<p>CAMELS-CH (Catchment Attributes and MEteorology for large-sample Studies - Switzerland) is a large-sample hydro-meteorological data set for hydrological Switzerland in Central Europe that covers 331 basins within Switzerland and neighboring countries (Austria, France, Germany and Italy). CAMELS-CH comprises dynamic hydro-meteorological variables and static catchment attributes.</p> <p>The data set covers 40 years of data between 1st January 1981 and 31st December 2020 for each catchment: daily time series of stream flow and water levels, of meteorological data such as precipitation and air temperature and of daily snow water equivalent data. Additionally, CAMELS-CH encompasses annual time series of land cover change and glacier evolution per catchment. The static catchment attributes comprise the following categories: location and topography, climate, hydrology, soil, hydrogeology, geology, land use, human impact and glaciers.</p> <p>The corresponding manuscript is published at the journal "Earth System Science Data" (ESSD) and available <a href="https://essd.copernicus.org/articles/15/5755/2023/">here</a>. The code used to generate the dataset is available on <a href="https://github.com/camels-ch">Github</a>.</p> <p>The data description file below contains a comprehensive list of all time series and attribute variables covered by the dataset and references to the original data sources. Further, this repository contains the "Caravan extension CH" for the "Caravan - A global community dataset for large-sample hydrology" <a href="../records/7944025">Caravan dataset</a> (see the <a href="https://github.com/kratzert/Caravan/discussions/10">list of extensions</a>). This extension has the same format like other Caravan parts and is based on the same data sources. Note that some features like the annual glacier time series, etc. are therefore only available in the original CAMELS-CH dataset.</p> <p> </p> <h2>Updates:</h2> <p>- Update version 0.9: affects "Caravan_extension_CH" - In version 1.5 of the Caravan dataset, Penman-Monteith PET was added as an additional time series feature. Additional to the new time series feature, also all pet-related climate indices were recomputed using the new Penman-Monteith PET. For consistency, the old ERA5-Land potential_evaporation time series and climate indices were kept, but renamed for a better identification of the differences. </p> <p>- Update version 0.8: resolving projection issue for shapefiles in "Caravan_extension_CH" using EPSG:4326 (WGS84); updating readme file of "camels_ch" regarding the <a href="../communities/dischma/">Dischma</a> catchment</p> <p>- Update version 0.7: update corresponding to the revision of the manuscript at "Earth System Science Data" (ESSD)</p> <ul> <li>dataset file delimiters have been changed to commas from semicolons</li> <li>the "time_series" folder was renamed to "timeseries"</li> <li>in the simulation-based data, there was an error in the previous aggregation of precipitation and evapotranspiration. The corresponding time series, affected hydrologic signatures and climatic indices were corrected</li> <li>the order of simulation-based variables in the timeseries files was changed to resemble the order shown in the tables of the corresponding publication in ESSD</li> <li>blank values that were masked by "NA" are now consistently indicated by "NaN"</li> <li>the readme file has been extended</li> </ul> <p>- Update version 0.6: updating links to related material (all links and references are available in the preprint/manuscript) and abstract</p> <p>- Update version 0.5: adding the "camels_ch_data_description.pdf" file</p> <p>- Update version 0.4: update of several static attributes in "Caravan_extension_CH" following a general update in Caravan and all its extensions + adopting the geographic coordinate system to Caravan-standard EPSG:4326</p> <p>- Update version 0.3: renaming single files/entries in "Caravan_extension_CH" to start with "camelsch" as unique Caravan extension identifier</p> <p>- Update version 0.2: CH extension to <a href="../records/7944025">Caravan</a> added</p>
Caravan extension Israel - Israel dataset for large-sample hydrology
<p>Caravan is an open community dataset of meteorological forcing data, catchment attributes, and discharge data for catchments around the world: https://doi.org/10.1038/s41597-023-01975-w; https://zenodo.org/record/6578598. <br>We have employed the published code to derive daily meteorological forcing data and catchment attributes from global data sources to extend Caravan with data for 95 catchments from Israel. </p> <p>For the data processing, the following guide was followed: https://github.com/kratzert/Caravan/wiki/Extending-Caravan-with-new-basins.</p>
Dataset for Symptoms of performance degradation during multi-annual drought: a large-sample, multi-model study
<p>This dataset contains the data described in the journal article "Symptoms of performance degradation during multi-annual drought: a large-sample, multi-model study" (Trotter et al., 2023, <strong>DOI: </strong>10.1029/2021WR031845)</p>
BULL Database – Spanish Basin attributes for Unraveling Learning in Large-sample hydrology
<p>We present a novel basin dataset for large-sample hydrological studies in Spain. BULL<br>comprises data for … basins, combining hydrometeorological time series (streamflow and …<br>climatic variables) with … attributes related to geology, soil, topography, land cover,<br>anthropogenic influence and hydroclimatology.</p>
Caravan extension Denmark - Danish dataset for large-sample hydrology
<p><em>Caravan</em> is an open community dataset of meteorological forcing data, catchment attributes, and discharge data for catchments around the world: https://zenodo.org/record/6578598. We have employed the published code to derive meteorological forcing data and catchment attributes from global data sources to extend Caravan with data for 308 Danish catchments. </p> <p>For the processing of the data the following guide was followed step by step: https://github.com/kratzert/Caravan/wiki/Extending-Caravan-with-new-basins</p> <p>The basins and the runoff data are described in more detail by Koch & Schneider (2022).</p> <p>Koch, J., & Schneider, R. (2022). Long short-term memory networks enhance rainfall-runoff modelling at the national scale of Denmark. <em>GEUS Bulletin</em>, <em>49</em>. https://doi.org/10.34194/geusb.v49.8292</p> <p>Version log:</p> <p>11-04-2025 v_7 - Addition of Penman-Monteith PET. </p> <p>23-05-2023 v_05 - Catchment attributes updated. </p> <p>04-12-2022 v_04.1 - Erroneous zip file replace. </p> <p>04-12-2022 v_04 - HydroAtlas attributes reprocessed (more info: https://github.com/kratzert/Caravan/issues/15). Also, attribute file structure (now three per dataset instead of two) has been adjusted to meet the new Caravan convention. attributes_other_camelsdk.csv is added as third attribute file. </p> <p>27-06-2022 v_03 - Change of folder naming. "license" renamed to "licenses" to be in agreement with the Caravan convention. </p> <p>20-06-2022 v_02 - Sporadic erroneous gap filling has been removed for a handful of basins. </p> <p> </p>
The Establishment of Large-sample Database of "Multiple-MRI/Gene/Cognition"
ClinicalTrials.gov study NCT02144467. IPD Sharing: NO. Countries: 1. Publications: 1.
Clinical Outcomes of PIMSRA Treating for Hypertrophic Obstructive Cardiomyopathy: A Large-Sample Study
ClinicalTrials.gov study NCT07003945. IPD Sharing: NO. Countries: 1. Publications: 0.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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International Brain Laboratory public data
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OpenNeuro
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