The National River Flow Archive (NRFA) is the UK's focal point for river flow data and is the primary archive of daily and peak river flows for the United Kingdom. The archive incorporates daily, monthly and flood peak data from over 1500 gauging stations across the UK.

The NRFA holds a wide range of hydrological information to assist in the understanding and interpretation of measured river flows. In addition to time series of gauged river flow, the data centre maintains hydrometric information relating to the gauging stations and the catchments they command and data, quantifying other parts of the hydrological cycle.

The National River Flow Archive (NRFA) is the UK's focal point for hydrometric data, providing stewardship of, and access to, daily and monthly river flow data for some 1500 gauging stations nationally. In addition a range of information concerning the catchments of these gauging station is available either in the form of statistics or spatial data, including digitised catchment boundaries. The NRFA is mandated by UK government (Defra) and the devolved administrations of Northern Ireland, Scotland and Wales to provide data and information on water resources nationally. The NRFA is a major component of the National Water Archive and part of CEH's Environmental Information Data Centre.

Daily mean river flow, a.k.a. gauged daily flows (GDF), measured at over 1500 points on the river network across Great Britain and Northern Ireland. Most stations are managed by the Measuring Authorities (Environment Agency, Scottish Environmental Protection Agency, Natural Resources Wales and the Rivers Agency of Northern Ireland), and the daily flows are generally the average of the raw 15 minute series. GDF values are expressed as cubic metres per second (abbreviated to m3s-1 and sometimes also referred to as cumecs) in a water-day (09.00 to 09.00 GMT) or, where indicated, a calendar day. The National River Flow Archive also holds detailed information about river gauging stations and their catchments.

Since the CORE DA go-live (June 8th 2022), the loop flows calculated during the DA capacity calculation process will not be published on this dataset anymore. Improved calculation results are now available , on CNEC granularity, via the Core CCR Publication Tool on JAO website. The results for Elia CNECs can be found in the pages “Pre-Final (earlyPub)” and “Final Computation”, via the column “R_amr_justification”.The dataset is still available for historical data usage only. Loop flows between Belgium and its neighboring countries. Loop flows are physical flows arising from internal energy transfers inside one bidding zone. They are not the same as transit flows, which are physical flows arising from exports from one zone to another.Elia estimates loop flow values by cancelling commercial exchanges, i.e. changing the net positions of all countries to 0 MW, and treating all remaining flows as loop flows. This calculation is based on data from forecasts two days ahead.

This model archive contains the data and software application necessary to simulate two-dimensional hydraulic parameters along a 1.6 kilometer study reach of the Sacramento River near Glenn, California. The iRIC modeling system and the NAYS2DH solver were used to simulate three river flows (90, 191, and 255 cubic meters per second) and provide spatially distributed depths, velocities, and water-surface elevations along the study reach. The archive is split into child-items to help distinguish the individual components of the archive and make downloading of large files more manageable. The first child item in the archive is the hydraulic model software application. The second child item includes the topographic data used to construct the model grid as well as field measurements of water-surface elevation and depth-averaged velocity used to calibrate the hydraulic roughness parameter. The third child item provides output from the NAYS2DH model using various Manning's n roughness values. A comparison of the root mean square errors between the model simulation and field measurements is included for each roughness parameter. The fourth child item includes model output for the three river flows that were simulated to support the manuscript.

This dataset is model output from the GR4J lumped catchment hydrology model. It provides 500 model realisations of daily river flow, in cubic metres per second (cumecs, m3/s), for 303 UK catchments for the period between 1891-2015. The modelled catchments are part of the National River Flow Archive (NRFA) (https://nrfa.ceh.ac.uk/) and provide good spatial coverage across the UK. These flow reconstructions were produced as part of the Research Councils UK (RCUK) funded Historic Droughts and IMPETUS projects, to provide consistent modelled daily flow data across the UK from 1891-2015, with estimates of uncertainty. This dataset is an outcome of the Historic Droughts Project (grant number: NE/L01016X/1). The data are provided in two formats to help the user account for uncertainty: (1) a 500-member ensemble of daily river flow time series for each catchment, with their corresponding model parameters and evaluation metric scores of model performance. (2) a single river flow time series (one corresponding to the top run of the 500), with the maximum and minimum daily limits of the 500 ensemble members.

Dataset is a model archive containing all relevant files to document and re-run the models that are discussed in the report: Fowler, K.K., 2018, Flood-Inundation Maps for Cedar Creek at 18th Street at Auburn, Indiana: U.S. Geological Survey Scientific Investigations Report 2017-5156.

This dataset contains monthly river flow data for stations (gauges) on Canadian rivers and streams.

This dataset is an update to the National River Flow Archive's Peak Flow Dataset including the files for use in the WINFAP software for flood estimation. The dataset includes Annual Maxima (AMAX) and Peaks over Threshold (POT) data for 939 gauging stations which have been updated with an additional water year of data (October 2019 to September 2020) in England, Northern Ireland and Wales. No update was available for sites in Scotland due to issues with the hydrometric archive. This dataset is superseded by NRFA Peak Flow Dataset V11.0. This work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability.

Quality characteristics for 21586 river flow time series from 13 datasets worldwide. The 13 datasets are: the Global Runoff Database from the Global Runoff Data Center (GRDC), the Global River Discharge Data (RIVDIS; Vörösmarty et al., 1998), Surface-Water Data from the United States Geological Survey (USGS), HYDAT from the Water Survey of Canada (WSC), WISKI from the Swedish Meteorological and Hydrological Institute (SMHI), Hidroweb from the Brazilian National Water Agency (ANA), National data from the Australian Bureau of Meteorology (BOM), Spanish river flow data from the Ecological Transition Ministry (Spain), R-ArcticNet v. 4.0 from the Pan-Arctic Project Consortium (R-ArcticNet), Russian River data (NCAR-UCAR; Bodo, 2000), Chinese river flow data from the China Hydrology Data Project (CHDP; Henck et al., 2010, 2011), the European Water Archive from GRDC - EURO-FRIEND-Water (EWA), and the GEWEX Asian Monsoon Experiment (GAME) – Tropics dataset provided by the Royal Irrigation Department of Thailand. Quality characteristics are based on availability, outliers, homogeneity and trends: overall availability (%), longest availability (%), continuity (%), monthly availability (%), outliers ratio (%), homogeneity of annual flows (number of statistical tests agreeing), trend in annual flows, trend in one month of the year.

Bodo, B. (2000) Russian River Flow Data by Bodo. Boulder CO: Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory. Retrieved from http://rda.ucar.edu/datasets/ds553.1/

Henck, A. C., Huntington, K. W., Stone, J. O., Montgomery, D. R. & Hallet, B. (2011) Spatial controls on erosion in the Three Rivers Region, southeastern Tibet and southwestern China. Earth and Planetary Science Letters 303(1–2), 71–83. doi:10.1016/j.epsl.2010.12.038

Henck, A. C., Montgomery, David R., Huntington, K. W. & Liang, C. (2010) Monsoon control of effective discharge, Yunnan and Tibet. Geology 38(11), 975–978. doi:10.1130/G31444.1

Vörösmarty, C. J., Fekete, B. M. & Tucker, B. A. (1998) Global River Discharge, 1807-1991, V[ersion]. 1.1 (RivDIS). doi:10.3334/ornldaac/199

Dataset is a model archive containing all relevant files to document and re-run the models that are discussed in the report: Fowler, K.K., 2017, Flood-Inundation Maps for the Patoka River in and near Jasper, southwestern Indiana: U.S. Geological Survey Scientific Investigations Report 2017-5138.

This model archive contains the MODFLOW 6 model used to simulate groundwater flow in the Treasure Valley for 1986 through 2015. The simulated results are described in the associated U.S. Geological Survey Professional Paper xxxx. The model archive includes the MODFLOW 6 model, PEST parameter estimation files, and a collection of python scripts that were used to develop the model. The README file describes all the files and directories in the archive and provides instructions for running the model.

This compilation of monthly river flow rate data, for most of the globe except former Soviet Union countries, was prepared by Byron Bodo from a combination of datasets from UNESCO, WMO GRDC, the RIVDIS by Vorosmarty (1998), and others. The overall average length of period of record is about 26.7 years. About 2/3 of the gauge records have from 10-100+ years of data. The USGS offers the CDROM "Hydro-Climatic Data Network: Streamflow Data Set, 1874-1988". This consists of streamflow data measured at 1659 sites throughout the US and its territories. Daily mean, monthly mean, annual mean, minimum and maximum values of discharge are given for each water year. Stations selected distinguish human influences.

This dataset contains time series of all available monthly river flow rates observed at the farthest downstream station for the world's largest 925 rivers, plus long-term mean river flow rates and continental discharge into the individual and global oceans, produced originally by Dai and Trenberth (2002, JHM) and Dai et al. (2009, Journal of Climate), and updated by Dai (2016, AGU Monograph 221) and Dai (2021, Climate Dynamics).

This data archive contains datasets developed for the purpose of training and applying random forest models to the Mississippi Embayment Regional Aquifer. The random forest models are designed to predict total stream flow and baseflow as a function of a combination of watershed characteristics and monthly weather data. These datasets are associated with a report (SIR 2022-xxxx) and code contained in a USGS GitLab repository. The GitLab repository (https://code.usgs.gov/map/maprandomforest/) contains much more information about how these data may be used to supply predictions of stream flow and baseflow.

This dataset provides hydro-meteorological timeseries and landscape attributes for 671 catchments across Great Britain. It collates river flows, catchment attributes and catchment boundaries from the UK National River Flow Archive together with a suite of new meteorological timeseries and catchment attributes. Daily timeseries for the time period 1st October 1970 to the 30th September 2015 are provided for a range of hydro-meteorological data (including rainfall, potential evapotranspiration, temperature, radiation, humidity and flow). A comprehensive set of catchment attributes are quantified describing a range of catchment characteristics including topography, climate, hydrology, land cover, soils, hydrogeology, human influences and discharge uncertainty. This dataset is intended for the community as a freely available, easily accessible dataset to use in a wide range of environmental data and modelling analyses. A research paper (Coxon et al, CAMELS-GB: Hydrometeorological time series and landscape attributes for 671 catchments in Great Britain) describing the dataset in detail will be made available in Earth System Science Data (https://www.earth-system-science-data.net/). Full details about this dataset can be found at https://doi.org/10.5285/8344e4f3-d2ea-44f5-8afa-86d2987543a9

HYDRUS 1D is an open source, Windows-based software package for simulation of of one-dimensional water movement through variably saturated porous media. The model solves Richards equation for increments of soil depth with thickness and hydrologic characteristics specified by the user. Soil hydrologic characteristics can be assigned based on van Genuchten parameters provided within HYDRUS based on soil texture, or can be specified by the user. The model incorporates a sink term for plant water uptake and provides different options for specifying rooting depth and growth rate. The model provides water content and flux values for observation points at depths specified by the user. The program has a graphical user interface for modifying inputs and visualizing model results, but it is also possible to modify model inputs and visualize outputs by working with the HYDRUS 1D text files, using a program such as R. Using R to modify model input files allows for running many model scenarios in a loop, which streamlines analysis on complex sets of model runs.

No description is available. Visit https://dataone.org/datasets/ab3382c586ed5c81bc1d537f90a58129 for complete metadata about this dataset.

The identification of transport parameters by inverse modeling often suffers from equifinality or parameter correlation when models are fitted to observations of the solute breakthrough in column outflow experiments. This parameters uncertainty can be approached by the application of multiple experimental designs such as column experiments in open-flow mode and the recently proposed closed-flow mode. Latter are characterized by the recirculation of the column effluent into the solution supply vessel that feeds the inflow. Depending on the experimental conditions, the solute concentration in the solution supply vessel and the effluent follows a damped sinusoidal oscillation. As a result, the closed-flow experiment provides additional observables in the breakthrough curve. The evaluation of these emergent features allows intrinsic control over boundary conditions and impacts the uncertainty of parameters in inverse modeling. We present a comprehensive sensitivity analysis to illustrate the potential application of closed-flow experiments. We show that the sensitivity with respect to the apparent dispersion can be controlled by the experimenter leading to a decrease in parameter uncertainty as compared to classical experiments by an order of magnitude for optimal settings. With these finding we are also able to reduce the equifinality found for situations, where rate-limited interactions impede a proper determination of the apparent dispersion and rate coefficients. Furthermore, we show the expected breakthrough curve for equilibrium and kinetic sorption, the latter showing strong similarities to the behavior found for completely mixed batch reactor experiments. This renders the closed-flow mode a useful complementary approach to classical column experiments.

The dataset includes six files of UK physical river characteristics including five files of gridded data at 1 km x 1 km resolution and one comma separated table. The data includes: • Drainage directions (D8 flow method), ESRI coding • Drainage directions (D8 flow method), unifhy (python hydrology framework) coding • Catchment areas (km2) • Widths of bankfull rivers (m) • Depths of bankfull rivers (m) • NRFA gauging station locations (easting (m), northing (m)) Two versions of drainage directions are provided, both have the same drainage directions but different numbering systems. The comma separated NRFA (National River Flow Archive) gauging station locations table provides the best locations of 1499 river flow gauging stations on the 1km grids, together with the approximate error in the 1km × 1km gridded delineation of the upstream catchment area. All datasets are provided on the British National Grid.