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97 results for “river discharge”
Concentration–discharge relationships of chlorophyll describe the origin and fluxes of river algae across ecoregions
Since 2017, the National Ecological Observatory Network (NEON) program provides an extensive network of automated instruments and field sampling at 34 different aquatic sites across the U.S. NEON data provides a rare opportunity to combine high-frequency measurements from sensors with physical samples collected at multiples sites from different biomes. Such combination of data is frequently available only for 1, or few, sites. NEON provides the necessary data to translate some of the methods and research previously applied to single sites to a large spatial and temporal scale. Our approach in this study was to obtain all the available and reliable data from NEON aquatic sites, and analyze high frequency measurements of Chlorophyl a (Chl a) concentration and turbidity during high flows with a common analytical procedure. Then, we relate these high flow patterns to watershed conditions and algal communities to elucidate the controls on river phytoplankton communities and fluxes. The data provided here summarizes multiple storm characteristics and C-Q metrics (hysteresis index) for Chl a and turbidity for several high flow events at 26 different NEON stream and river sites.
RADIT: A Machine Learning-Reconstructed Dataset of River Discharge, Temperature, and Heat Flux into the Arctic Ocean
<p>The Reconstructed Arctic-draining river DIscharge and Temperature (RADIT) dataset provides daily records of river discharge, temperature, and heat flux for 25 major Arctic-draining rivers from 1950 to 2023. Using machine learning methods and ERA5-Land reanalysis data, we reconstructed these key hydrological variables with high accuracy (most NSEs > 0.8).</p> <p>Due to licensing restrictions and to encourage adherence to the stated licenses of the original input data, this dataset only provides the reconstructed (filled) values. Users can obtain the complete historical observational data from their original publicly available sources as detailed in our documentation. By combining these original observations with our reconstructed data, a comprehensive and continuous daily dataset from 1950 to 2023 can be assembled. Clear instructions and links for downloading the original observational data used in this study can be found at: <a href="https://github.com/zhwang24/RADIT-Reconstructed-Arctic-River-Data" target="_blank" rel="noopener">https://github.com/zhwang24/RADIT-Reconstructed-Arctic-River-Data</a>. Should you encounter any issues or have questions, please feel free to contact the first author, Zihan Wang (zhwang2018@163.com).</p>
Global River BankFull Discharge (GQBF) - Siberia(SI) & South Pacific/Australia(SP)
<p>The GQBF is the estimated bankfull discharge across ~2.87 million km (length) of global river reaches. The bankfull discharge here is defined as the maximum flow rate contained within a river just before inundation occurs in the surrounding floodplain. We based our river bankfull discharge estimation on a newly developed river network, Global RIver Topology (GRIT), using GRIT’s river reaches as the spatial scale to represent the variation in bankfull discharge. We included all GRIT river reaches that coincided with the Global River Width from Landsat (GRWL) river masks (with overlapping ratio >=0.5). This selects river reaches with satellite-derived width measurements >=30 m, resulting in a total length of ~2.87 million km. Here, the GQBF represents the time-averaged bankfull discharge at <1 km (river length) spatial resolution.</p> <p><strong>Regions</strong></p> <p>Added regions SI, SP Vector files.</p> <ul> <li>SI - Siberia</li> <li>SP - South Pacific/Australia</li> </ul> <p>The subcontinental catchment groups (vector, polygons) can be found at <a href="https://zenodo.org/records/11219313">GRIT domain polygon</a> (GRITv06_domain_GLOBAL.gpkg.zip). They allow for more fine-grained subsetting of data .</p> <p>Vector files are provided in geographic WGS84 coordinates (EPSG:4326).</p> <p><strong>Change log</strong></p> <ul> <li>v0.1 - 2024-09-29<br> <ul> <li>First globally complete dataset published</li> </ul> </li> <li>v0.1 - 2024-11-19 <ul> <li>Add vector files for regions SI, SP</li> </ul> </li> </ul>
Kuparuk River stream temperature and discharge measured each summer, Dalton Road crossing, Arctic LTER Toolik Field Staion, Alaska 1978-2019
Stream temperature and discharge measured each summer for several streams in the Toolik area. In many years, temperature and stream height were recorded manually each day. In recent years, dataloggers have measured stream temperature and stream height at regular intervals. The Kuparuk River data was maintained by Doug Kane and the Water and Environmental Research Center at UAF through 2017 (http://ine.uaf.edu/werc/projects/NorthSlope/upper_kuparuk/upper_kuparuk....). Stream height is converted into stream discharge based on a rating curve calculated from manual discharge measurements throughout the season. The principal investigator in charge of the temperature and discharge measurements is Dr. Breck Bowden. Note: This file replaces older yearly files of discharge and temperatures
Seasonal high-frequency measurements of discharge, water temperature, and specific conductivity from the Onyx River at Lower Wright, McMurdo Dry Valleys, Antarctica (1972-2023, ongoing)
As part of the Long Term Ecological Research (LTER) project in the McMurdo Dry Valleys of Antarctica, a systematic sampling program has been undertaken to monitor the glacial meltwater streams in that region. This package contains data pertaining to continuous monitored water quality and quantity parameters measured with automatic recording devices on streams in this region. Specifically, this metadata record describes the hydrology data set for the McMurdo Dry Valleys' Onyx River at the Lower Wright streamgage, located in the Wright Valley. Measurements commenced in 1972 and are ongoing. This dataset extends through the first half of the 2022-23 field season.
Seasonal high-frequency measurements of discharge, water temperature, and specific conductivity from the Onyx River at Lake Vanda, McMurdo Dry Valleys, Antarctica (1969-2023, ongoing)
As part of the Long Term Ecological Research (LTER) project in the McMurdo Dry Valleys of Antarctica, a systematic sampling program has been undertaken to monitor the glacial meltwater streams in that region. This package contains data pertaining to continuous monitored water quality and quantity parameters measured with automatic recording devices on streams in this region. Specifically, this metadata record describes the hydrology data set for the McMurdo Dry Valleys' Onyx River at the Lake Vanda streamgage, located in the Wright Valley. Measurements commenced in 1969 and are ongoing. This dataset extends through the first half of the 2022-23 field season.
Daily summarized seasonal measurements of discharge, water temperature, and specific conductivity from the Onyx River at Lake Vanda, McMurdo Dry Valleys, Antarctica (1969-2023, ongoing)
As part of the Long Term Ecological Research (LTER) project in the McMurdo Dry Valleys of Antarctica, a systematic sampling program has been undertaken to monitor the glacial meltwater streams in that region. This package contains daily summaries derived from 15-minute measurements of water quality and quantity parameters measured with automatic recording devices on streams in this region. Specifically, this metadata record describes the daily hydrological summaries for the McMurdo Dry Valley's Onyx River at Lake Vanda, located in the Wright Valley. Measurements commenced in 1969 and are ongoing. This dataset extends through the first half of the 2022-23 field season.
Daily summarized seasonal measurements of discharge, water temperature, and specific conductivity from the Onyx River at Lower Wright, McMurdo Dry Valleys, Antarctica (1972-2023, ongoing)
As part of the Long Term Ecological Research (LTER) project in the McMurdo Dry Valleys of Antarctica, a systematic sampling program has been undertaken to monitor the glacial meltwater streams in that region. This package contains daily summaries derived from 15-minute measurements of water quality and quantity parameters measured with automatic recording devices on streams in this region. Specifically, this metadata record describes the daily hydrological summaries for the McMurdo Dry Valley's Onyx River, located in the Wright Valley. Measurements commenced in 1972 and are ongoing. This dataset extends through the first half of the 2022-23 field season.
Parker River daily discharge, at Byfield, MA
USGS gaged daily discharge from the Parker River at Byfield, Massachusetts (Station 01101000), draining 55.1637 km2 of watershed. Data are used for determining freshwater flows into the Plum Island Sound Estuary, MA.
Ipswich River daily discharge, South Middleton, MA
USGS gaged daily discharge from the Ipswich River at South Middleton, Massachusetts (Station 01101500), draining 112.13 km2 of watershed. Data are used for determining freshwater flows into the Plum Island Sound Estuary, MA.
Ipswich River daily discharge, Ipswich, MA
USGS gaged daily discharge from the Ipswich River near Ipswich (01102000), draining 317.56 km2 of watershed. Data are used for determining freshwater flows into the Plum Island Sound Estuary, MA.
Datasets for manuscript: Global River Discharge and Floods in the Warmer Climate of the Last Interglacial
<p>This datasets contains results of the global hydrological and hydrodynamic modeling presented in the paper referenced in the title (doi: 10.1029/2020GL089375). The dataset comprises results for one set of simulations, based on Global Climate Model CESM1.2, out of the eight sets of simulations for eight GCMs included in the paper. The corresponding results for the other seven sets of simulations (based on GCMs CESM2, EC‐EARTH3.2, HadGEM3‐GC3.1, IPSL‐CM6‐LR, MPI‐ESM 1.2.01p1‐LR, NorESM1‐F, and NUIST‐CSM) can be obtained by writing to the corresponding author at paolo.scussolini@vu.nl.</p> <p>Files description:</p> <p>fldare_yearmean_timmean_CEM1.2_LIG.nc : Annual average flood area for the Last Interglacial simulation with GCM CESM1.2, hydrological model PCR-GLOBWB and hydrodynamic model CaMa-Flood.<br> <br> fldare_yearmean_timmean_CESM1.2_PI.nc 4 Mb : Annual average flood area for the Pre-Industrial simulation with GCM CESM1.2, hydrological model PCR-GLOBWB and hydrodynamic model CaMa-Flood.<br> <br> fldsto_yearmean_timmean_CESM1.2_LIG.nc 4 Mb : Annual average flood volume for the Last Interglacial simulation with GCM CESM1.2, hydrological model PCR-GLOBWB and hydrodynamic model CaMa-Flood.<br> <br> fldsto_yearmean_timmean_CESM1.2_PI.nc 4 Mb : Annual average flood volume for the Pre-Industrial simulation with GCM CESM1.2, hydrological model PCR-GLOBWB and hydrodynamic model CaMa-Flood.<br> <br> outflw_yearmean_timmean_CESM1.2_LIG.nc 4 Mb : Annual average river discharge for the Last Interglacial simulation with GCM CESM1.2, hydrological model PCR-GLOBWB and hydrodynamic model CaMa-Flood.<br> <br> outflw_yearmean_timmean_CESM1.2_PI.nc 4 Mb : Annual average river discharge for the Pre-Industrial simulation with GCM CESM1.2, hydrological model PCR-GLOBWB and hydrodynamic model CaMa-Flood.<br> <br> runoff_annuaTot_output_mergetime_timmean_CESM1.2_LIG.nc : Annual average runoff for the Last Interglacial simulation with GCM CESM1.2 and hydrological model PCR-GLOBWB.<br> <br> runoff_annuaTot_output_mergetime_timmean_CESM1.2_PI.nc : Annual average runoff for the Pre-Industrial simulation with GCM CESM1.2 and hydrological model PCR-GLOBWB.</p> <p> </p>
Level A Pan Europe Natural river discharge, E-HYPE 3.0
Simulated river discharge at each subbasin from E-HYPEv3.0 in m3/s. Daily data for 1961 to 2001 as time-series. Dam regulation and irrigation are NOT simulated in the natural runs. However, dams will still function as lakes with some amount of attenuation. Original data source: See information about the E-HYPE setup. Tools for repurposing: HYPE. Temporal resolution: Daily. Spatial resolution: 215 km2. Unit: m3/s. Data format: Zipped text file. On the first row there is a brief description and the rest of the file contains one row per time step, with the sub basin id as each column header on the second row. The first item on each line is the time step using the format YYYY-MM-DD, so 1961-01-01 for the first of January 1961. The dataset, Subbasin(EHYPEv3pt0).zip (shapefile with subbasin polygons) can be linked with the data.
Level A Pan Europe Modelled river discharge, E-HYPE 3.0
Simulated river discharge at each subbasin from E-HYPEv3.0 in m3/s. Daily data for 1961 to 2001 as time-series. Original data source: See information about the E-HYPE setup. Tools for repurposing: HYPE. Temporal resolution: Daily. Spatial resolution: 215 km2. Unit: m3/s. Data format: Zipped text file. On the first row there is a brief description and the rest of the file contains one row per time step, with the sub basin id as each column header on the second row. The first item on each line is the time step using the format YYYY-MM-DD, so 1961-01-01 for the first of January 1961. The dataset, Subbasin(EHYPEv3pt0).zip (shapefile with subbasin polygons) can be linked with the data.
Level A Pan Europe Modelled river discharge, E-HYPE 2.5
Simulated river discharge at each subbasin from E-HYPEv2.5 in m3/s. Daily data for 1961 to 2001 as time-series. Original data source: See information about the E-HYPE setup. Tools for repurposing: HYPE. Temporal resolution: Daily. Spatial resolution: 215 km2. Unit: m3/s. Data format: Zipped text file. On the first row there is a brief description and the rest of the file contains one row per time step, with the sub basin id as each column header on the second row. The first item on each line is the time step using the format YYYY-MM-DD, so 1961-01-01 for the first of January 1961. The dataset, Subbasin(EHYPE2pt5).zip (shapefile with subbasin polygons) can be linked with the data.
Fully differentiable, fully distributed River Discharge Prediction: data sets
<p>This repository contains the data sets used in: Scholz et al. (2025). Fully differentiable, fully distributed River Discharge Prediction.</p> <ul> <li><code>dem_1000.h5</code> based on EU-DEM v1.1, reprojected to RADOLAN grid: <a href="https://sdi.eea.europa.eu/catalogue/srv/api/records/3473589f-0854-4601-919e-2e7dd172ff50">https://sdi.eea.europa.eu/catalogue/srv/api/records/3473589f-0854-4601-919e-2e7dd172ff50</a></li> <li><code>efas.h5</code> based on EFAS historical: <a href="https://ewds.climate.copernicus.eu/datasets/efas-historical?tab=overview">https://ewds.climate.copernicus.eu/datasets/efas-historical?tab=overview</a></li> <li><code>era5_ssrd_neckar*.nc</code> based on ERA5 provided by ECMWF, reprojected to RADOLAN grid: <a href="https://www.ecmwf.int/en/forecasts/dataset/ecmwf-reanalysis-v5">https://www.ecmwf.int/en/forecasts/dataset/ecmwf-reanalysis-v5</a></li> <li><code>radolan_neckar_*.h5</code> based on RADOLAN rw product provided by the Deutsche Wetterdienst: <a href="https://opendata.dwd.de/climate_environment/CDC/grids_germany/hourly/radolan/">https://opendata.dwd.de/climate_environment/CDC/grids_germany/hourly/radolan/</a></li> </ul> <p>Due to copyright, the discharge data has to be downloaded manually from the Global Runoff Data Centre (<a href="https://grdc.bafg.de/">https://grdc.bafg.de/</a>), and then preprocessed with the provided <code>bafg_parser.py</code> python script. We use the following stations in our work:</p> <ul> <li>6335290: STEIN</li> <li>6335291: GAILDORF</li> <li>6335565: BAD IMNAU</li> <li>6335600: ROCKENAU SKA</li> <li>6335601: LAUFFEN</li> <li>6335602: PLOCHINGEN</li> <li>6335603: ROTTWEIL</li> <li>6335604: KIRCHENTELLINSFURT</li> <li>6335620: MOSBACH</li> <li>6335660: PFORZHEIM</li> <li>6335665: DENKENDORF</li> <li>6335671: ALTENSTEIG</li> <li>6335675: MURR</li> <li>6335676: OPPENWEILER</li> <li>6335680: SCHWABSBERG</li> <li>6335681: UNTERGRIESHEIM</li> <li>6335690: NEUSTADT</li> </ul> <p>To preprocess the discharge data, additionally the river network data "Fließgewässer (AWGN)" provided by the Landesanstalt für Umwelt Baden-Württemberg (LUBW) is required: <a href="https://rips-metadaten.lubw.de/trefferanzeige?docuuid=7251515f-6aed-4555-8319-ab6314155ab1">https://rips-metadaten.lubw.de/trefferanzeige?docuuid=7251515f-6aed-4555-8319-ab6314155ab1</a></p> <p> </p>
Global River Discharge Reanalysis dataset (GRDR)
<p>The Global River Discharge Reanalysis dataset (GRDR) is a global river discharge product that contains daily flows in ~2.9 million vectorized river reaches for 1984-2018.</p> <p>For more details about GRDR, please refer to the following publication: Feng D. and Gleason C.J., 2024, More flow upstream and less flow downstream: The changing form and function of global rivers, <em>Science</em></p>
River flows and nutrient discharges to the Atlantic ocean basin
<p>This dataset includes i) River flows and ii) nutrient discharges to the Atlantic ocean basin:</p> <p><strong>River flow</strong> data are a subset of the WaterGAP 2.2d model (Monthly data on a 0.5° x 0.5° grid between 90°N and 60°S. 1901–2016) (Müller Schmied et al. 2020)</p> <p>The original watergap2.2d data is provided in netcdf format. Our postprocessing includes the selection of the coastal cells and the extraction of the monthly values in these cells. The resulting dataset is provided as a shapefile (Global_YearMonthly_River_flow_watermap22_coast.shp), including Date, latitude and longitude of the coastal cell’s centroids and the discharge values (m3s-1).</p> <p>Watergap2.2d outputs offers a very good spatio-temporal extent and resolution, and according to the Müller Schmied et al. 2020, the validation results for streamflow (or discharges values) are reasonably satisfactory, although there is some spatial variability in the performance results. Moreover, the recently published “Global Freshwater Fluxes into the World's Oceans (GRDC, 2021)” product and paper, uses the yearly outcomes of this model, which has also supported our selection.</p> <p><strong>River nutrient discharges</strong> are a subset of observations from the “Global River Water Quality Archive”. (<a href="https://essd.copernicus.org/preprints/essd-2021-51/">Virro et al, 2021</a>), that among the publicly available and downloadable datasets, gathers the highest number of observations as includes data from different international and national databases.</p> <p>The GRQA data is provided as csv files (one file for each nutrient). These files have been processed to subset only observations at stations near the coastline. To do this a intersection between station locations and a buffer of 0.2 degrees around the coastline has been made. For each nutrient, a shapefile with the subsetted observations is provided.</p> <p>All shapefiles provided are accompanied by a “.qmd” file that includes metadata information in QGIS 3 format.</p>
Remote sensing of river discharge (RSQ) estimates derived from multi-temporal Landsat width observations and BAM/geoBAM discharge inversion algorithms
<p><strong>This repository provides three data files in CSV format:</strong><br> 1. Gauge name, lat/lon information<br> 2. Gauge name, date, and multi-temporal river width extracted from Landsat<br> 3. Gauge name, date, and BAM/geoBAM estimates of river discharge with monthly Q priors</p> <p>Note: the multi-temporal river width data were extracted from Landsat imageries using RivWidthCloud, where the river centerline/orthogonal line definition and the cross-section sampling strategies were made prior to, and different from Feng et al. (2022). So the width values may be different from Feng et al. (2022) at some locations due to these differences. The discharge estimates were derived from BAM/geoBAM algorithms with width-only observations. More details of the technical workflow and the inner workings of BAM/geoBAM were provided in the literature below and papers therein.</p> <p> </p> <p><strong>Reference:</strong></p> <p>Lin, P., D. Feng, C.J. Gleason, M. Pan, C.B. Brinkerhoff, X. Yang, H.E. Beck, R. Frasson (2023). Inversion of river discharge from remotely sensed river widths: a critical assessment at three-thousand global river gauges. <em>RSE</em>.</p> <p> </p> <p>Updated: 2022/6/17, 2023/1/19</p> <p> </p>
Computed Basic Statistics of Hydraulics and Discharge Measures at USGS River Monitoring Stations
<p>The shared table contains basic statistics (average, standard deviation, minimum, maximum, and coefficient of variation [%]) river channel hydraulics and discharge records of the 4472 USGS river monitoring stations. The required raw data are free to access by the USGS-<em>National Water Information System</em> (<a href="https://waterdata.usgs.gov/nwis">https://waterdata.usgs.gov/nwis</a>). Hydraulics and discharge records that measured at each USGS monitoring site, given a long time period, were assembled, assessed, and finally used for computing the basic statistics. </p>
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