BasinATLAS is a component of the HydroATLAS database, which is a component of HydroSHEDS. BasinATLAS provides a standardized compendium of hydro-environmental attribute information for all watersheds of the world at high spatial resolution. This dataset includes data for 56 variables, partitioned into 281 attributes and organized in six categories: hydrology; physiography; climate; land cover & use; soils & geology; and anthropogenic influences (see Table 1 in the HydroATLAS documentation linked below). Watersheds range from level 1 (coarse) to level 12 (detailed), using Pfastetter codes. The underlying watershed deleniation uses the NASA SRTM Digital Elevatin Map (DEM) below 60oN latitude and the USGS HYDRO1k DEM above 60oN. Technical documentation: https://www.hydrosheds.org/images/inpages/HydroATLAS_TechDoc_v10.pdf Note that the quality of HydroATLAS data is significantly lower for regions above 60 degrees northern latitude as there is no underlying SRTM elevation data available and thus a coarser-resolution DEM was used (HYDRO1k provided by USGS). HydroSHEDS was developed by the World Wildlife Fund (WWF) Conservation Science Program in partnership with the U.S. Geological Survey, the International Centre for Tropical Agriculture, The Nature Conservancy, and the Center for Environmental Systems Research of the University of Kassel, Germany.

BasinATLAS es un componente de la base de datos HydroATLAS, que es un componente de HydroSHEDS. BasinATLAS proporciona un compendio estandarizado de información de atributos hidroambientales para todas las cuencas del mundo con alta resolución espacial. Este conjunto de datos incluye datos de 56 variables, particionados en 281 atributos y organizados en seis categorías: hidrología, …

We present CAMELSH (Catchment Attributes and Hourly HydroMeteorology for Large-Sample Studies), the first hourly large-sample hydrometeorological dataset for the contiguous United States. CAMELSH provides hourly streamflow and meteorological time series, along with catchment attributes and boundaries from GAGES-II and HydroATLAS, covering 7,211 catchments across diverse climatic, hydrological, and anthropogenic conditions. Among these, 2,569 catchments include observed streamflow, while the remaining contain only meteorological forcings. The dataset spans 45 years (1980–2024) with 11 meteorological variables from the NLDAS-2 forcing dataset, from which we compute nine climate indices related to precipitation, evapotranspiration, seasonality, and snow fraction. Additionally, CAMELSH includes two sets of catchment attributes: 439 from GAGES-II and 195 derived from HydroATLAS. Developed in accordance with FAIR (Findability, Accessibility, Interoperability, and Reusability) principles, CAMELSH is the first large-sample dataset at an hourly timescale, supporting machine learning applications for short-term streamflow (flood) prediction and advancing data-driven hydrological research across multiple timescales.

The dataset is organized into the following subfolders:
• The attributes folder comprises three subfolders, each corresponding to a source dataset, and contains CSV (comma-separated values) files that store basin attributes. Specifically, the ‘Attributes-Climate’ subfolder includes the ‘attribute_climate.csv’ file, which contains nine climate attributes (Table 2) derived from NLDAS-2 data. The ‘Attributes-GAGESII’ subfolder contains a total of 26 CSV files and one Excel (*.xlsx) file. Among these, the 26 CSV files include information related to basins/streamflow gauging stations and 439 basin attributes. The name of each file represents a distinct group of attributes, as described in Table S.1. The remaining file, named ‘Var_description.xlsx’, provides explanatory details regarding the variable names included in the 26 CSV files, with information similar to that presented in Table S.1. The final subfolder, ‘Attributes-HydroAtlas’, contains a single file, ‘attribute_HydroATLAS.csv’, which includes 195 basin attributes derived from the HydroATLAS dataset. The first column in all CSV files, labeled ‘STAID,’ contains the identification (ID) names of the streamgages. These IDs are assigned by the USGS and are sourced from the original GAGES-II dataset.
• The shapefiles folder contains two sets of shapefiles for the catchment boundary. The first set, CAMELSH_shapefile.shp, is derived from the original GAGES-II dataset and is used to obtain the corresponding climate forcing data for each catchment. The second set, CAMELSH_shapefile_hydroATLAS.shp, includes catchment boundaries derived from the HydroATLAS dataset. Each polygon in both shapefiles contains a field named GAGE_ID, which represents the ID of the stream gauges.
• The timeseries (7zip) file contains a compressed archive (7zip) that includes time series data for 7,211 basins. Within this 7zip file, there are a total of 7,211 NetCDF files, each corresponding to a specific basin. The name of each NetCDF file matches the stream gauge ID. Each file contains an hourly time series from 1980-01-01 00:00:00 to 2024-12-31 23:00:00 for streamflow (denoted as “Streamflow” in the NetCDF file) and 11 climate variables (see Table 1). The streamflow data series includes missing values, which are represented as “NaN”. Among these, a total of 2,569 stations contain observed streamflow data, while 4,642 stations do not have observed data. Note that streamflow is measured in cubic meters per second. All meteorological forcing data and streamflow records have been standardized to the +0 UTC time zone.
• The info.csv file, located in the main directory of dataset, contains basic information for 7,211 stream stations. This includes the stream gauge ID, the total number of observed hourly data points over 45 years (from 1980 to 2024), and the number of observed hourly data points for each individual year from 1980 to 2024. Stations with and without observed data are distinguished by the value in the second column, where stations without observed streamflow data have a corresponding value of 0.

The presented database is a set of hydrological, meteorological, environmental and geometric values for Russia Federation for the period from 2008 to 2020.

Database consist of next items:

Point geometry for hydrological observation stations from Roshydromet network across Russia

Geometry of the catchment for correspond observation station point

Daily hydrological values

Water level

In relative representation (sm)

In meters of Baltic system (m)

Water discharge

as an observed value (qms/s)

as a layer (mm/day)

Daily meteorological values

Maximum and minimum daily temperatures (°C) from ERA5 and ERA5-Land

Total precipitation (mm/day) from ERA5, ERA5-Land, IMERG v06, GPCP v3.2 and MSWEP

Different kind of evaporation (mm/day) corresponded to each variable calculated in GLEAM model

Set of hydro-environmental characteristics derived from HydroATLAS database

Each variable derived from the grid data was calculated for each watershed, taking into account the intersection weights of the watershed contour geometry and grid cells.

Coordinates of hydrological stations were obtained from resource of Federal Agency for Water Resources of Russia Federation—AIS GMVO

To calculate the contours of the catchment areas, a script was developed that builds the contours in accordance with the rasters of flow directions from MERIT Hydro. To assess the quality of the contour construction, the obtained value of the catchment area was compared with the archival value from the corresponded table from AIS GMVO. The average error in determining the area for 2080 catchments is approximately 2%

To derive values for different hydro-environmental values from HydroATLAS were developed approach which calculate aggregated values for catchment, leaning on type of variable: qualitative (Land cover classes, Lithological classes etc.) Or quantitive (Air temperature, Snow cover extent etc.). Every quantitive variable were calculated as mode value for intersected sub-basins and target catchment, e.g. most popular attribute from sub-basins will describe whole catchment which are they relating. Quantitative values were calculated as mean value of attribute from each sub-basin. More detail could be found in publication.

Files are distributed as follows:

Each file has some connection with the unique identifier of the hydrological observation post. Files in netcdf format (hydrological and meteorological series) are named in response to identifier.

Every file which describe geometry (point, polygon, static attributes) has and column named gauge_id with same correspondence.

attributes/static_data.csv – results from HydroATLAS aggregation

geometry/russia_gauges.gpkg – coordinates of hydrological observation stations

        gauge_id
        name_ru
        name_en
        geometry




        0
        49001
        р. Ковда – пос. Софпорог
        r.Kovda - pos. Sofporog
        POINT (31.41892 65.79876)


        1
        49014
        р. Корпи-Йоки – пос. Пяозерский
        r.Korpi-Joki - pos. Pjaozerskij
        POINT (31.05794 65.77917)


        2
        49017
        р. Тумча – пос. Алакуртти
        r.Tumcha - pos. Alakurtti
        POINT (30.33082 66.95957)

geometry/russia_ws.gpkg – catchments polygon for each hydrological observation stations

        gauge_id
        name_ru
        name_en
        new_area
        ais_dif
        geometry




        0
        9002
        р. Енисей – г. Кызыл
        r.Enisej - g.Kyzyl
        115263.989
        0.230
        POLYGON ((96.87792 53.72792, 96.87792 53.72708...


        1
        9022
        р. Енисей – пос. Никитино
        r.Enisej - pos. Nikitino
        184499.118
        1.373
        POLYGON ((96.87792 53.72708, 96.88042 53.72708...


        2
        9053
        р. Енисей – пос. Базаиха
        r.Enisej - pos.Bazaiha
        302690.417
        0.897
        POLYGON ((92.38292 56.11042, 92.38292 56.10958...

Column ais_diff is corresponded to % error in area definition

nc_all_q

netcdf files for hydrological observation stations which has no missing values on discharge for 2008-2020 period

nc_all_h

netcdf files for hydrological observation stations which has no missing values on level for 2008-2020 period

nc_all_q_h

netcdf files for hydrological observation stations which has no missing values on discharge and level for 2008-2020 period

nc_concat

data for all available geometry provided in dataset

More details on processing scripts which were used for development of this database can be found in folder of GitHub repository where I store results for my PhD dissertation

05.04.2023 – Significant data changes. Removed catchments and related files that have more than ±15% absolute error in calculated area relative to AIS GMVO information. Now these are data for 1886 catchments across the Russia.

17.05.2023 – Significant data changes. Major review of parsing algorithm for AIS GMVO data. Fixed the way of how 0.0xx values were read. Use previous versions with caution.

11.10.2023 – Significant data changes. Added 278 catchments for CIS region from GRDC resource. Calculate meteorological and environmental attributes for each catchment. New folder /nc_all_q_h with no missing observations on discharge and level. Now these are data for 2164 catchments across CIS.

BasinATLAS, HydroSHEDS'in bir bileşeni olan HydroATLAS veritabanının bir bileşenidir. BasinATLAS, dünyanın tüm havzaları için yüksek mekansal çözünürlükte hidro-çevresel özellik bilgilerinin standartlaştırılmış bir derlemesini sağlar. Bu veri kümesi, 281 özelliğe bölünmüş ve altı kategoride düzenlenmiş 56 değişkene ait veriler içerir: hidroloji; …

The GIS HydroAtlas of Madagascar is the final output from the small hydro resource mapping component of the activity “ Renewable Energy Resource Mapping and Geospatial Planning – Madagascar” [Project ID: P145350]. You can find more information about the project here: https://www.esmap.org/re_mapping_madagascar Please cite as: [Data/information/map obtained from the] “World Bank via ENERGYDATA.info, under a project funded by the Energy Sector Management Assistance Program (ESMAP). For more information: Madagascar Small Hydro GIS Atlas, 2017, https://energydata.info/dataset/madagscar-small-hydro-gis-atlas-2017"

The current version of the CAMELSH dataset, containing data for 9,008 basins,. Due to the total data volume in the repository being approximately 57 GB, which exceeds Zenodo's size limit, we split it into two different links. This link contains data on attributes, shapefiles, and time series data for basins with observed streamflow. The second link (xxx) contains time series data for the 'non-obs' basins. All data is compressed in 7zip format. After extraction, the dataset is organized into the following subfolders:

• The attributes folder contains 28 CSV (comma-separated values) files that store basin attributes with all files beginning with "attributes_" and one excel file. Of these, the 'attributes_nldas2_climate.csv' file contains nine climate attributes (Table 2) derived from NLDAS-2 data. The 'attributes_hydroATLAS.csv' file includes 195 basin attributes derived from the HydroATLAS dataset. 26 files with names starting with 'attributes_gageii_' contain a total of 439 basin attributes extracted from the GAGES-II dataset. The name of each file represents a distinct group of attributes, as described in Table S.1. The remaining file, named 'Var_description_gageii.xlsx', provides explanatory details regarding the variable names included in the 26 CSV files, with information similar to that presented in Table S.1. The first column in all CSV files, labeled 'STAID', contains the identification (ID) names of the stream gauges. These IDs are assigned by the USGS and are sourced from the original GAGES-II dataset.
• The shapefiles folder contains two sets of shapefiles for the catchment boundary. The first set, CAMELSH_shapefile.shp, is derived from the original GAGES-II dataset and is used to obtain the corresponding climate forcing data for each catchment. The second set, CAMELSH_shapefile_hydroATLAS.shp, includes catchment boundaries derived from the HydroATLAS dataset. Each polygon in both shapefiles contains a field named GAGE_ID, which represents the ID of the stream gauges.
• The timeseries (7zip) file contains a compressed archive (7zip) that includes time series data for 3,166 basins with observed streamflow data. Within this 7zip file, there are a total of 3,166 NetCDF files, each corresponding to a specific basin. The name of each NetCDF file matches the stream gauge ID. Each file contains an hourly time series from 1980-01-01 00:00:00 to 2024-12-31 23:00:00 for streamflow (denoted as "Streamflow" in the NetCDF file) and 11 climate variables (see Table 1). The streamflow data series includes missing values, which are represented as "NaN". All meteorological forcing data and streamflow records have been standardized to the +0 UTC time zone.
• The timeseries_nonobs (7zip) file contains time series data for 5,842 basins without observed streamflow data. The structure of each NetCDF file is similar to the one described above.
• The info.csv file, located in the main directory of the dataset, contains basic information for 9,008 stream stations. This includes the stream gauge ID, the total number of observed hourly data points over 45 years (from 1980 to 2024), and the number of observed hourly data points for each year from 1980 to 2024. Stations with and without observed data are distinguished by the value in the second column, where stations without observed streamflow data have a corresponding value of 0.

BasinATLAS は、HydroSHEDS のコンポーネントである HydroATLAS データベースのコンポーネントです。 BasinATLAS は、世界中のすべての流域について、水環境属性情報の標準化されたコンペンディアを高空間解像度で提供します。このデータセットには、56 の変数のデータが含まれており、281 の属性に分割され、水文学、地形、気候、土地被覆と土地利用、土壌と地質、人間活動の影響の 6 つのカテゴリに編成されています（下記の HydroATLAS ドキュメントの表 1 を参照）。 水域は、Pfastetter コードを使用して、レベル 1（粗い）からレベル 12（詳細）まであります。基盤となる水域の境界線には、北緯 60 度以南では NASA SRTM デジタル標高地図（DEM）、北緯 60 度以北では USGS HYDRO1k DEM が使用されています。 技術ドキュメント: https://www.hydrosheds.org/images/inpages/HydroATLAS_TechDoc_v10.pdf 北緯 60 度以上の地域では、基盤となる SRTM 標高データがないため、粗い解像度の DEM（USGS が提供する HYDRO1k）が使用されているため、HydroATLAS データの品質が大幅に低下します。 HydroSHEDS は、米国地質調査所、国際熱帯農業センター、The Nature Conservancy、ドイツのカセル大学環境システム研究センターと提携して、世界自然保護基金（WWF）の保全科学プログラムによって開発されました。

BasinATLAS 是 HydroATLAS 資料庫的一部分，而 HydroATLAS 是 HydroSHEDS 的一部分。BasinATLAS 提供全球所有流域的高解析度水文環境屬性資訊的標準化總集。這個資料集包含56 個變數的資料，已劃分為281 個屬性，並分成六個類別：水文學；…

Lakes are vital landscape units with ecological, economic, and social importance, and there has been a surge in scientific research aimed at understanding and addressing the challenges to ensure the preservation and sustainable management of lakes. However, there is limited knowledge regarding the geographical distribution of the studied lakes, the specific issues and driving factors in the research. There is still a need for comprehensive datasets that combine lake morphology and watershed characteristics with research topics.

In this dataset, we assembled metadata from 58,024 peer-reviewed publications on 2,542 lakes and geometric, meteorological, and socioeconomic attributes from multisource databases, including HydroATLAS, NOAA PSL, GCP, and HILDA+. These datasets were aggregated into the Global Lake Atlas in REsearch (GLARE) by parsing the literature documents, extracting the lake entities based on deep learning, geocoding the lakes, and allocating 17 topics and 54 subtopics.

The open-source GLARE dataset is essential for addressing global lake challenges and strengthening research in underrepresented regions by linking literature information with physical and biogeochemical data. Furthermore, the methodology applied in GLARE can be employed to extract any unstructured data, making it highly applicable to various other academic fields.

BasinATLAS는 HydroSHEDS의 구성요소인 HydroATLAS 데이터베이스의 구성요소입니다. BasinATLAS는 높은 공간 해상도로 전 세계 모든 유역의 수질 환경 속성 정보를 표준화된 집계로 제공합니다. 이 데이터 세트에는 281개의 속성으로 분할되고 수문학, 지형학, 기후, 토지 피복 및 사용, 토양 및 지질학, 인위적 영향이라는 6가지 카테고리로 구성된 56개 변수의 데이터가 포함되어 있습니다 (아래 링크된 HydroATLAS 문서의 표 1 참고). 유역은 Pfastetter 코드를 사용하여 1단계 (대략적)에서 12단계 (상세)까지 다양합니다. 기본적인 유역 경계는 북위 60도 아래에서는 NASA SRTM 디지털 고도 지도 (DEM)를, 북위 60도 위에서는 USGS HYDRO1k DEM을 사용합니다. 기술 문서: https://www.hydrosheds.org/images/inpages/HydroATLAS_TechDoc_v10.pdf 북위 60도 이상의 지역에서는 기본 SRTM 고도 데이터를 사용할 수 없으므로 더 낮은 해상도의 DEM(USGS에서 제공하는 HYDRO1k)이 사용되어 HydroATLAS 데이터의 품질이 상당히 낮습니다. HydroSHEDS는 세계자연기금 (WWF) 보존과학 프로그램이 미국지질조사소, 국제열대농업센터, 자연보존협회, 독일 카셀 대학교의 환경시스템연구센터와 협력하여 개발했습니다.

[Keywords] Market include Eutech, Hach Instruments, Stevens Water, RS Hydro, Keze

While some rivers have been modified and regulated for centuries requiring recovery efforts and restoration, other rivers are currently under development and facing the challenges of environmental degradation and loss of ecological functionality. As countries, such as China, expand current infrastructure to develop and construct flood reduction, hydropower, and water storage facilities along their rivers, the threat of detrimental ecological impacts expands too. To address these pressing challenges, this data set was used in the referenced article's analysis. Climatic, hydrogeomorphic, ecological, and anthropogenic characteristics summarized in this dataset were analyzed to determine the key principal components relevant to decision-making for environmental flows in the river basin. This resulting dataset includes a summary of the applied variables by subbasin cluster as discussed in detail in the article.

Methods Data was collected from global data sets compiled within HydroATLAS and MODIS supported datasets in other publications. Variables with monthly information were aggregated to quarterly for analysis.

Variables were evaluated for their relevent influence to e-flows with a pricipal component analysis (PCA) applied to the dataset. With the results from the PCA, the list of variables was reduced to the most important or pricipal components. K-means clustering facilitated the grouping of subbasins according to the characteristics and variable values.

This table includes those values used in clustering.

BasinATLAS เป็นคอมโพเนนต์ของฐานข้อมูล HydroATLAS ซึ่งเป็นคอมโพเนนต์ของ HydroSHEDS BasinATLAS เป็นแหล่งรวบรวมข้อมูลแอตทริบิวต์ด้านสิ่งแวดล้อมและน้ำที่เป็นมาตรฐานสำหรับลุ่มน้ำทั้งหมดของโลกที่ความละเอียดเชิงพื้นที่สูง ชุดข้อมูลนี้ประกอบด้วยข้อมูลของตัวแปร 56 รายการ ซึ่งแบ่งออกเป็นแอตทริบิวต์ 281 รายการและจัดระเบียบเป็น 6 หมวดหมู่ ได้แก่ อุทกวิทยา …

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.