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1,265 results for “discharges”

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dryad40/100

Variability in the discharge of the Mississippi River and tributaries from 1817 to 2020

This is a two-hundred-year long dataset of the annual average, minimum, and maximum discharges at five stations draining the Mississippi River watershed: at Clinton, IA, Herman, MO, St. Louis, MO, Louisville, KY, and Vicksburg, MS. The data are useful to test for increases in the three discharge metrics, and correlations with air pressure differentials represented in the North Atlantic Oscillation (NAO) Index. These data may be useful for climate change assessments through modeling or synthetic assessments using other data sets.

opencc-zeroOct 2022View details →

zenodo40/100

Data on thermodynamic, gas-dynamic and electromagnetic parameters of gas discharge in poly-phase medium

Temperature, concentrations and electromagnetic parameters distribution in the model environment for main poly-phase medium types

opencc-by-4.0May 2024View details →

zenodo40/100

Supplementary data for "Accelerated river mobility linked to water discharge variability"

Supplementary data for the paper "Accelerated river mobility linked to water discharge variability", by Leenman et al. This repository contains 3 datasets underlying the figures in the manuscript and supporting material. ds01_flow_gauge_metadata: Details and locations of flow records used in our analysis. ds02_Qvar_and_TR: Floodplain reworking timescales, channel characteristics, sediment concentrations, and discharge variability metrics (i.e. all metrics used in our figures and modeling). Floodplain reworking timescale data are from <a href="https://doi.org/10.1029/2024GL108537">Greenberg et al., 2024</a>. Channel slopes, widths, planforms and catchment areas are from <a href="https://doi.org/10.1130/G49121.1">Galeazzi et al., 2021.</a> Bed-material sediment concentration estimates are generated from WBMsed (<a href="https://doi.org/10.1029/2021WR031583">Cohen et al., 2022)</a>.  ds03_channel_threads_GRWL: Data used to make one of our supplemental figures. Frequency count of the number of reaches that have a given number of channel threads in the Global River Widths from Landsat (GRWL) database (<a href="https://doi.org/10.1126/science.aat0636">Allen and Pavelsky, 2018</a>). Data downloaded via Google Earth Engine. Only reaches wider than 1000 m are included. Code using these data to generate the plots in the paper / SM using these data can be found at <a href="https://github.com/a-leenman/Discharge-variability-river-mobility">https://github.com/a-leenman/Discharge-variability-river-mobility</a>. This is the 'live' code; the version at the time of paper submission is archived here: <a href="https://doi.org/10.5281/zenodo.12555069">https://doi.org/10.5281/zenodo.12555069</a>.

opencc-by-4.0Jun 2024View details →

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Supplement to "Discriminating non-stationary flood hazard effects via probabilistic estimation of sparse residuals from rescued and rated stage–discharge data"

This supplement contains the data and script associated with “Sparse hydrometric data rescue for exploratory analyses of conveyance-driven flood hazard trends and controls,” which has been submitted to a journal for consideration. This supplement is deposited on Zenodo.   Code, Data, and Attribute Descriptions   Uploaded are five directories (indicated in bold font, with their contents detailed below) containing input data and various outputs of the analyses performed for our case study on the Pulangi River at Lumayong (Philippines). Please consider this description equivalent to an omnibus README file for the deposited files. Note that we collected and rescued the hydrometric data herein from the archives of the Water Projects Division (WPD) of the Philippine Department of Public Works and Highways (DPWH).   ●      Pln_R_code contains (1) Pln_RC.R, the R script file, and (2) 240601_Pln_RC.RData, which stores objects generated from the script based on the last execution (on 1 June 2024). The script consists of admittedly too many lines of code (e.g., for data wrangling, formal analyses, and producing figures used in the manuscript) that should have been split into multiple .R files. Apologies. Please be guided by the outline and the comments and kindly reach out lest issues with the code arise.   ●      Pln_GH_PDFs contains the scanned gaugekeeper’s reports of gauge heights (“stages”).    ○      The name of each file varies. For example, Pln-GH-1100.pdf contains daily stage readings for all months in the year 2011. But, if the last two digits are not zeroes, as in Pln-GH-1204.pdf, they refer to the month of that year; in this case, for example, the PDF file contains stage data for the month of April in the year 2012. ○      Each scanned sheet contains sub-daily (with readings at “AM,” “NOON,” and “PM”) and mean daily stages for a given month. ○      Also indicated are the gaugekeeper’s remarks on the daily weather (e.g., “fair,” “cloudy”). Under inclement weather, the gaugekeeper would note the duration of rainfall and its intensity and might, at times, record extra stage readings.   ●      Pln_DM_PDFs contains the following PDF files and a sub-directory: ○      Pln-DM-<XXXXXX>.pdf contains the scanned log for each direct stage—discharge measurement, otherwise known as “gaugings.” Each file is named according to the date of gauging (YYMMDD). For example, the log for the gauging performed on 24 February 2011 can be found in the file Pln-DM-110224.pdf. Data from these gaugings are summarized in Pln-DM-filtered.csv in the Pln_In_CSVs directory. ■      The readability of each file varies based on the original quality of the original paper-format data. ■      The first page in each file contains, on the left side, a summary of the gauging data and metadata (e.g., date of measurement, number of gauging verticals or “sections” used, method of crossing or measuring the cross-section), and on the right side, the velocity—area readings at each gauging vertical. ■      The second page in each file contains the plotted cross-section of the channel at the time of measurement. ○      Pln-RC.pdf contains various other paper-format data and some annotations relevant to the historical rating at the station. ■      P. 1: The hydrographic engineer’s comment (dated 19 January 2012) on the evaluation of the discharge data, specifically detailing the periods of validity of the rating curves developed for different sub-periods of monitoring. ■      PP. 2—3: A summary table of all the gaugings performed from 1983 to 2010 whose logs were no longer retrievable (and hence not included as a DM-PDF file in this directory). ■      PP. 4—5: Plots of the official stage—discharge rating curves developed by DPWH hydrographers. ■      PP. 6—8: Rating tables used to convert daily mean stages to deterministic discharge estimates. Two of these rating tables were digitized and can be found in the Pln_RatingTables sub-directory in Pln_In_CSVs. ■      PP. 9—22: Daily stage (m) and its corresponding daily discharge (L/s) for the 2004—2010 sub-period. The stages were digitized and included in Pln-H_arch.csv in the Pln_In_CSVs directory. ○      Pln_DM_unused contains the PDF files of logs (including data and metadata) corresponding to the gaugings that were excluded from our analysis following our filtering step for gauging location consistency.   ●      Pln_In_CSVs contains the following CSV files and two sub-directories; these files were used as inputs to the R script for formal analyses: ○      Pln-H_arch.csv contains the mean daily stage values [“H_bar_arch”] (m) for every day in the 2004—2020 sub-period [“Date”] (YYYY-MM-DD). The stages in this file are already corrected for gross errors. ○      Pln-DM-filtered.csv contains the following information on the gaugings performed on the Pulangi at Lumayong (1983—2020): (i) date [“Date”] (YYYY-MM-DD); (ii) stage [“H”] (m); (iii) discharge in L/s [“Q_lps”] and m3/s [“Q_cms”]; (iv) wetted area [“A_sqm”] (m2); (v) mean flow velocity [“Vel_mps”] (m/s); (vi) channel width [“W_m”] (m); (vii) mean flow depth [“D_ave_m”] (m); (viii) location of the measurement cross-section with respect to the staff gauge, with negative values meaning downstream of the gauge and positive values meaning upstream of the gauge [“XS_loc_wrt_gage”]; (ix) maximum flow depth [“Max_Depth_m”] (m); and (x) minimum streambed elevation [“MINSBE”] (m). Note that this file includes only gaugings that passed our filtering step for measurement location consistency. ○      Pln-DM_oview.csv contains information on the temporal coverage (bounded by “Start_date” and “End_date”) of the available hydrometric data from the station archives. ○      Pln-H_sample_GrossE_corr.csv contains a sample sub-period (2017-06-15 through 2017-11-30) and the corresponding values of stages (m), uncorrected [“H_uncorrected”] and corrected for gross errors [“H_corrected”]. This CSV file was used as an input to the R script to produce one of the figures in the manuscript.  ○      Pln-XS-csv.csv contains data on the gauging transects: gauging ID [“GaugingID”]; date [“Date”] (YYYY-MM-DD); lateral distance from a fixed initial point [“Lat_distance”] (m); width of the gauging vertical [“Width_vert..m.”] (m); depth relative to the water surface [“Depth..m.”] (m); stage at the gauging vertical [“H_m_vert..m.”] (m); and elevation with respect to a fixed arbitrary datum at the station [“Elev..m.”] (m). ○      Pln_Rating_Tables contains two rating tables, Pln-DM - RatingTable_A.csv and Pln-DM - RatingTable_B.csv, prepared and used by DPWH hydrographers for converting stage values to deterministic discharge estimates for the Pulangi River at Lumayong for the 1980s—early 2000s sub-period. Each rating table contains columns for stage [“H”], discharge in L/s [“Q_lps”], and discharge in m3/s [“Q_cms”]. ○      Pln_Q_rated contains two CSV files: Pulangi.csv has the columns “YEAR”, “DAY”, and every month of the year [“JAN” through “DEC”] for the 1983—2003 sub-period, with the values under each month column indicating the deterministic discharge estimates in L/s; Pulangi_trunc.csv contains similarly formatted data, but for the 2009—2010 sub-period.   ●      Pln_Out_CSVs contains two CSV files, the primary outputs of the hydrometric data rescue effort. ○      Pln_Q_recon.csv contains the reconstructed discharge time series (1983—2020) and its associated uncertainties at the 95% credibility interval. It has the following columns: date [“Date”] (YYYY-MM-DD); daily stage [“H”] (m); lower bound of the discharge estimate [“Q_lwr”] (m3/s); median discharge estimate [“Q_med”] (m3/s); and the upper bound of the discharge estimate [“Q_upr”] (m3/s). Pln_H_recon.csv contains the reconstructed and quality-controlled stage time series (1983—2020). It has the following columns: date [“Date”] (YYYY-MM-DD); mean daily stage that has been corrected for gross errors, but not yet filtered through other quality checks [“H_bar_arch”] (m); quality check for low outliers [“Low_Outlier”] (TRUE/FALSE); quality check for flatliners [“Flatliner”] (TRUE/FALSE); difference between the stage values on day i and day i-1 [“Daily_Step”] (m); quality check for large steps [“Large_Step”] (TRUE/FALSE); and the corrected and quality-controlled mean daily stage values [“H”] (m).

opencc-by-4.0Jun 2024View details →

zenodo40/100

Figure 1 in Discharge compliance at Shanghai port - a case study on discharged ballast water from vessels with Ballast Water Treatment System

Figure 1. Water quality parameters of ballast water samples. Sal.: salinity; Temp.: temperature; DO: dissolved oxygen.

opencc-by-4.0Jan 2023View details →

zenodo40/100

Рис. 1. Устье р. Туманной (Λевый берег). ВиΑны постоянно Αействующий (А) и формирую- щийся (Б) воΑотоки, сбрасывающие воΑу из озера Αебяжьего Fig. 1. The mouth of the Tumannaya river (left bank). Visible permanent (A) and forming (B) watercourses that discharge water from lake Lebyazhye in Transboundary Migration And The Local Constraints In The Dynamic Of Fish Fauna In The Lower Reaches Of Tumannaya River

Рис. 1. Устье р. Туманной (Λевый берег). ВиΑны постоянно Αействующий (А) и формирую- щийся (Б) воΑотоки, сбрасывающие воΑу из озера Αебяжьего Fig. 1. The mouth of the Tumannaya river (left bank). Visible permanent (A) and forming (B) watercourses that discharge water from lake Lebyazhye

opencc-by-4.0Dec 2019View details →

zenodo40/100

Fig. 3 in Spatial Distribution of Suspended Solids During Short-Term High River Discharge in the Bay of Koper, Northern Adriatic Sea

Fig. 3: Rižana and Badaševica river hourly (QR and QB) and daily mean (Qr and Qb) discharge with related inflow concentrations of ISS (ISS and ISS) (a). Density profile (b) and wind direction and velocity applied (average wind velocity of 1.5 m s-1 221°) during the r b high-discharge event 21st June 2013 (c) (ARSO, 2014a).

opencc-by-4.0May 2018View details →

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Fig. 8 in Spatial Distribution of Suspended Solids During Short-Term High River Discharge in the Bay of Koper, Northern Adriatic Sea

Fig. 8: Salinity and ISS profiles after 24-hour simulation at comparison sites (P1- right, P2-center and P3-left); the event on 21st June 2013.

opencc-by-4.0May 2018View details →

zenodo40/100

Fig. 4 in Spatial Distribution of Suspended Solids During Short-Term High River Discharge in the Bay of Koper, Northern Adriatic Sea

Fig. 4: ISS distribution in the surface layer on 8th June 2011: measurements (a) and model simulation – average velocities and ISS distribution (b). Spatial map of discrepancies between model and measurements (c) and ranging of cells with regard to discrepancies (d); ΔMIN and ΔMAX depict minimum and maximum discrepancy, respectively.

opencc-by-4.0May 2018View details →

zenodo40/100

Fig. 7 in Spatial Distribution of Suspended Solids During Short-Term High River Discharge in the Bay of Koper, Northern Adriatic Sea

Fig. 7: ISS distribution in the surface layer on 21st June 2013: measurements (a) and model simulation – average velocities and ISS distribution (b). Spatial map of discrepancies between model and measurements (c) and ranging of cells with regard to discrepancies (d); ΔMIN and ΔMAX depict minimum and maximum discrepancy, respectively.

opencc-by-4.0May 2018View details →

zenodo40/100

Fig. 2 in Spatial Distribution of Suspended Solids During Short-Term High River Discharge in the Bay of Koper, Northern Adriatic Sea

Fig. 2: Rižana and Badaševica river hourly (QR and QB) and daily mean (Qr and Qb) discharge with related inflow concentrations of ISS (ISS and ISS) (a). Density profile (b) and wind direction and velocity applied (average wind velocity of 1.7 m s-1 188°) during r b the high-discharge event 8th June 2011 (c) (ARSO, 2014a).

opencc-by-4.0May 2018View details →

zenodo40/100

Fig. 6 in Spatial Distribution of Suspended Solids During Short-Term High River Discharge in the Bay of Koper, Northern Adriatic Sea

Fig. 6: Salinity and ISS profiles after 24-hour simulation at the comparison sites (P1- right, P2-center and P3-left); the event on 8th June 2011.

opencc-by-4.0May 2018View details →

zenodo40/100

Fig. 529. Kouhrang Tunnel, which discharge annually 320 million m3 in Fig. 4 in Fig. 4 in Fig. 3 in Fig. 21. Sesarmops mora n in Paralbunea dayriti

Fig. 529. Kouhrang Tunnel, which discharge annually 320 million m3 water annually from the Tigris to Esfahan basin.

opencc-by-4.0Jun 2020View details →

zenodo40/100

FVCOM_Petermann_Discharge_Input_Files

<h2>Overview</h2> This repository contains all the input files that are required to run the subglacial discharge experiments for the Petermann Ice Shelf-fjord system using the Finite Volume Community Ocean Model (FVCOM). You can access the corresponding peer-reviewed, open-access research article here: <a href="https://doi.org/10.1038/s41467-025-59469-9" target="_blank" rel="noopener">Enhanced subglacial discharge amplifies Petermann Ice Shelf melting when ocean thermal forcing saturates</a> <h2>Pre-requisites</h2> The open source code Finite Volume Community Ocean Model version 4.0 (FVCOM v4.0) augmented by an ice shelf (Zhou and Hattermann, 2020) and sea ice module (Prakash et al., 2022) is required to conduct the numerical experiments, and is made publicly available at <a href="https://doi.org/10.5281/zenodo.15084570" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.15084570</a>. A detailed description of our high-resolution (200 m) unstructured grid 3-D regional model setup centered on the Petermann ice shelf and fjord is available from Prakash et al. (2022) and Prakash et al. (2023). <h2>File description</h2> The model input files can be classified under 2 broad categories, namely  <ul> <li>static, and </li> <li>time-varying.</li> </ul> Static : These include the following files <ol> <li>zisf.dat (realistic Petermann ice shelf draft derived from BedMachine v3 (Morlighem et al., 2017)), </li> <li>dep.dat (smoothed bathymetry, which has been modified to provide an improved (with respect to BedMachine v3 (Morlighem et al., 2017)) representation of the sub-ice shelf topography), </li> <li>cor.dat (Coriolis),</li> <li>sigma.dat (terrain-following vertical coordinate system),</li> <li>grd.dat (FVCOM Petermann Fjord regional model grid)</li> </ol> Time-varying: These include the following files (a) Atmospheric Forcing <ol> <li>ocnice_YYYY_wnd.nc (wind forcing), </li> <li>ocnice_YYYY_fwf.nc (freshwater flux), and</li> <li>ocnice_YYYY_hf.nc (heat flux), </li> </ol> where YYYY represents the forcing year, e.g. 2014. (b) Sea ice forcing <ol> <li>ocnice_YYYY_icenudge.nc (includes sea ice concentration and thickness, bulk ice salinity, and sea ice velocities),</li> </ol> where YYYY represents the forcing year, e.g. 2014. (c) Ocean boundary conditions <ol> <li>pf_l_bcorr_climaYY.nc (bias-corrected lateral ocean boundary conditions which includes temperature, salinity, ocean velocities, and sea surface elevation)</li> </ol> where YY represents the forcing year, e.g. 14 (for 2014). In addition to these two broad categories, a restart file (*_restart_*.nc) is included in each run directory, which is used to provide "realistic" (a.k.a. "hotstart") initial ocean conditions. The restart file in the directory control_run_2014 includes a "realistic" initial (July 01, 2014 00:00:00 UTC) ocean condition derived from a 4-km pan-Arctic (A4) ROMS model (Hattermann et al., 2016). Thereafter, the FVCOM model solution on January 01, 2015 00:00:00 UTC is used to "hotstart" the 2015 calendar year. Lastly, the stable FVCOM model solution from January 01, 2016 00:00:00 UTC is used to "hotstart" the 2016 calendar year, as well as the discharge experiments. Note that the discharge experiments depart from the control experiment (control_run_2016) by introducing subglacial discharge of varying magnitudes. All other conditions are kept the same, in order to isolate and investigate the impact of subglacial discharge on the basal melting of the Petermann ice shelf. The namelist file (*.nml) for each run is also included in the corresponding directory. To minimize storage space, each run directory is populated with only the input files that are unique to that run. For e.g., control_run_2015/2016 and the discharge_experiments do not include the static files from control_run_2014, however, they are required to conduct each of these runs. Likewise, discharge_experiments do not include the time-varying forcing files, since they are identical to the ones contained in control_run_2016. The discharge_experiments do however include the discharge forcings for the present, RCP 8.5, and median(present,RCP 8.5) scenarios. These are the riverdata (riverdata.nc (present), riverdata_expC.nc (median), and riverdata_expD.nc (RCP 8.5)) and the corresponding rivernamelist (riverNamelist.nml, riverNamelist_expC.nml, riverNamelist_expD.nml) files. Note that a rivernamelist is different from a namelist file, in that it only contains information about the subglacial discharge. Development of the smoothed model topography datasets for our unstructured grid (horizontal resolutions of 200 m, 2km, and 4km) regional model domain, including localized improvements made within the Petermann Fjord; the ocean nesting and surface forcing methodologies (models used, downscaling procedure etc.); bias-correction, among other technical details, are detailed in Prakash et al. (2022) and Prakash et al. (2023).

opencc-by-4.0Jul 2024View details →

zenodo40/100

Annual minima and maxima of present day and future discharge, derived from PCR-GLOBWB

Global dataset of annual minima and maxima for major river system in the world. Dataset provides the present day and 2C warming simulation derived from a combination of the Global Hydrological Model, PCR-GLOBWB (https://doi.org/10.5194/gmd-11-2429-2018) and the EC-EARTH Global Climate Model (https://doi.org/10.1007/s00382-011-1228-5). The large-ensemble dataset is part of the HiWAVES3 project (https://www.knmi.nl/research/weather-climate-models/projects/hiwaves3)

opencc-by-4.0Jan 2019View details →

zenodo40/100

Tributary bay oscillations generated by diurnal discharge regulation in Three Gorges Reservoir

The dataset include absolute water level (in m.a.s.l.) from six gauging stations along Three Gorges Reservoir and discharge data for the period January to November 2018. And the relative water level and vertical profiles of flow velocity were measured in the middle (Xiakou) and upper reach (Pingyikou) of Xiangxi bay by two RDI ADCP from September 16 - October 12, 2018. For water level, water depth and flow velocity, the respective time series were high-pass filtered with cut-off frequencies corresponding to periods of 36 h and 4 h (see excel files), respectively (half-power frequencies of a zero-phase, 20-pole Butterworth filter). Power spectra were calculated using Welch’s method. Horizontal current velocities were measured in earth coordinates and rotated into longitudinal (along the river channel) and transversal velocity components by rotation into the respective mean (depth and temporarily averaged) flow direction at the sampling sites (see 'long_trans_vel.mat').

opencc-by-4.0Sep 2019View details →

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Paired time series of daily discharge and storm surge

This dataset presents daily time series of discharge and maximum storm surge at river mouths globally from 1980 - 2014.   Daily river discharge is the product of routing the mean daily runoff of the JULES model from the eartH2Observe WRR2 reanalysis data at 0.5° resolution (Best et al., 2011; Clark et al., 2011; Schellekens et al., 2017) with CaMa-Flood at a 0.25° resolution (Yamazaki et al., 2011). The maximum daily storm surge is obtained from the Global Tide and Surge Model (GTSM) (Muis et al., 2016; Verlaan et al., 2015). Each discharge location at the river mouth of coastal catchments larger than 1,000 km2 is paired with the nearest (≤ 75 km) GTSM output location (Eilander et al., 2019).

opencc-by-4.0Jun 2019View details →

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Figure 5 in Notes on the electric organ discharges (EODs) of four Mormyrus-species (Osteoglossomorpha: Mormyridae) from the Nilo-Sahelo-Sudan ichthyofaunal province of Africa

Figure 5. - Scatterplot of logarithmic total signal duration in µs versus logarithmic peak of fast Fourier transformation in Hz. Each symbol represents a single EOD from M. caschive (open triangle, n = 8), M. hasselquistii (open inverse triangle, n = 31), M. kannume (filled triangle, n = 3) and M. rume (filled inverse triangle, n = 7).

opencc-by-4.0Mar 2015View details →

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Figure 4 in Notes on the electric organ discharges (EODs) of four Mormyrus-species (Osteoglossomorpha: Mormyridae) from the Nilo-Sahelo-Sudan ichthyofaunal province of Africa

Figure 4. - Boxplots of selected signal characteristics. A: Total EOD duration in µs; B: Relative amplitude of main positive phase; C: Peak frequency of fast Fourier transformation in Hz.

opencc-by-4.0Mar 2015View details →

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Figure 3 in Notes on the electric organ discharges (EODs) of four Mormyrus-species (Osteoglossomorpha: Mormyridae) from the Nilo-Sahelo-Sudan ichthyofaunal province of Africa

Figure 3. - Exemplary AC coupled measurements of electric organ discharges (EODs) of Mormyrus species. A: M. caschive, 97 mm SL, White Nile at Kosti, Sudan. B: M. kannume, 169 mm SL, White Nile at Khartoum, Sudan. C: M. hasselquistii, 188 mm SL, Mare Diwouni, Pendjari National Park, Benin. D: M. rume, 230 mm SL, Ouémé at Kpoto, Benin.

opencc-by-4.0Mar 2015View details →

ScienceDex guides

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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

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Allen Brain Atlas

Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.

allen-brain-atlas

neuroscienceopenDocumentation, web resources, and API references are available online.

Last verified 2026-04-30Open record

Annotated Behaviour and Observability Dataset (ABODe)

ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.

abode-home-cage

behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.

Last verified 2026-04-30Open record

DANDI Archive for NWB datasets

DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.

dandi-nwb

electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.

Last verified 2026-04-30Open record

International Brain Laboratory public data

The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.

ibl

behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.

Last verified 2026-04-29Open record

OpenNeuro

OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.

openneuro

neuroscienceopenPublished datasets are available on demand over the internet.

Last verified 2026-04-29Open record

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Dataset results

Variability in the discharge of the Mississippi River and tributaries from 1817 to 2020

Data on thermodynamic, gas-dynamic and electromagnetic parameters of gas discharge in poly-phase medium

Supplementary data for "Accelerated river mobility linked to water discharge variability"

Supplement to "Discriminating non-stationary flood hazard effects via probabilistic estimation of sparse residuals from rescued and rated stage–discharge data"

Figure 1 in Discharge compliance at Shanghai port - a case study on discharged ballast water from vessels with Ballast Water Treatment System

Fig. 3 in Spatial Distribution of Suspended Solids During Short-Term High River Discharge in the Bay of Koper, Northern Adriatic Sea

Fig. 8 in Spatial Distribution of Suspended Solids During Short-Term High River Discharge in the Bay of Koper, Northern Adriatic Sea

Fig. 4 in Spatial Distribution of Suspended Solids During Short-Term High River Discharge in the Bay of Koper, Northern Adriatic Sea

Fig. 7 in Spatial Distribution of Suspended Solids During Short-Term High River Discharge in the Bay of Koper, Northern Adriatic Sea

Fig. 2 in Spatial Distribution of Suspended Solids During Short-Term High River Discharge in the Bay of Koper, Northern Adriatic Sea

Fig. 6 in Spatial Distribution of Suspended Solids During Short-Term High River Discharge in the Bay of Koper, Northern Adriatic Sea

Fig. 529. Kouhrang Tunnel, which discharge annually 320 million m3 in Fig. 4 in Fig. 4 in Fig. 3 in Fig. 21. Sesarmops mora n in Paralbunea dayriti

FVCOM_Petermann_Discharge_Input_Files

Annual minima and maxima of present day and future discharge, derived from PCR-GLOBWB

Tributary bay oscillations generated by diurnal discharge regulation in Three Gorges Reservoir

Paired time series of daily discharge and storm surge

Figure 5 in Notes on the electric organ discharges (EODs) of four Mormyrus-species (Osteoglossomorpha: Mormyridae) from the Nilo-Sahelo-Sudan ichthyofaunal province of Africa

Figure 4 in Notes on the electric organ discharges (EODs) of four Mormyrus-species (Osteoglossomorpha: Mormyridae) from the Nilo-Sahelo-Sudan ichthyofaunal province of Africa

Figure 3 in Notes on the electric organ discharges (EODs) of four Mormyrus-species (Osteoglossomorpha: Mormyridae) from the Nilo-Sahelo-Sudan ichthyofaunal province of Africa

Understand access before you commit

Allen Brain Atlas

Annotated Behaviour and Observability Dataset (ABODe)

DANDI Archive for NWB datasets

International Brain Laboratory public data

OpenNeuro

Your academic CV and NIH biosketch