Find research datasets worth reusing

openCC (other)May 2023View details →

PIE LTER marsh sediment porewater nutrient concentrations from Spartina sp. and Typha sp. sites along the Parker River and Rowley River, MA.

Marsh sediment porewater nutrient concentrations [NH4+, NO3-, DOC, TDN, H2S] and salinity are reported from Spartina sp. and Typha sp. sites along the Parker and Rowley Rivers, MA. Porewater peeper poles are used for collection and the poles are located in the vicinity of the marsh water table sites for the Railroad, Typha, Shad and Nelson sites.

openCustomNov 2022View details →

Sediment organic matter and infauna at eight sites on the Virginia Coast, 2016 and 2019

To determine how oysters impact the spatial distribution of infauna and sediment composition through ecosystem engineering, we sampled 8 intertidal mud- flats adjacent to oyster reefs in coastal Virginia, USA. This work describes how local site characteristics, including distance to oysters, elevation, and hydrodynamics, influence infaunal community structure and sediment composition.

openCustomApr 2023View details →

Hydrodynamic, sediment, and bivalve data from seagrass edges in South Bay, VA, 2021 to 2022

The northern edge of the South Bay seagrass meadow was studied for two years to quantify flow characteristics, sediment movement, and bivalve abundance. ADCPs (Aquadopp, Vector, Vectrino) and wave gauges were used to measure hydrodynamic conditions, sediment sensors and sediment traps were used to measure sediment movement, and sediment cores were used to measure bivalve abundance. Data were collected across seagrass edges in vegetated and unvegetated locations, or along transects spanning the natural edge of meadow vegetation. Manmade bare patches were also created in the study area to collect data along patch edges. Study sites 1 and 2 were approximately 100m apart along the northern edge of the seagrass meadow. A PDF figure describing the locations is included as Site_Figure.pdf along with the data tables.

openCustomOct 2023View details →

Sediment elevation transects for the Seagrass Recovery Experiment, South Bay, VA 2022

To understand intra-meadow stability, the Seagrass Recovery Experiment was designed to ask 1) is recovery faster at sites with less thermal stress owing to greater exchange with cooler oceanic water at the meadow edge? 2) what is the shape of recovery? and 3) what are the recovery mechanisms? To conduct this experiment, aboveground seagrass biomass was removed from 28.3 m2 plots within the interior and along an edge of a restored seagrass meadow in South Bay, VA. Sites 1-3 correspond to the meadow interior while sites 4-6 correspond to the northern meadow edge. Each site was comprised of a control (i.e., C) where no seagrass was disturbed and a treatment (i.e., T) where seagrass was removed (n = 12 sites total, e.g., 1C, 1T, 2C...). A nor'easter storm moved through the area in early May 2022 producing 59% and 48% of the year's total Gale and Near Gale force winds. After the storm passed, depressions were noticed within the edge treatment sites. To quantify the depression depths a survey of the sediment surface depth was coordinated among all sites in October 2022. Results provide evidence that the edge treatment sites were depressed by 9.4-10.4 cm relative to outside of the treatment plots.

openCustomAug 2024View details →

Sediment grain size in the Virginia coastal bays, 2022

This dataset contains sediment grain size distributions from benthic sediment cores collected from shallow sites across coastal bays of Virginia, USA. The samples were collected in July 2022 at 50 long-term sampling sites. Most sites were sampled in seagrass meadows (eelgrass Zostera marina), but some sites are unvegetated (bare substrate).

opencc-by-4.0Feb 2024View details →

A unified template for sediment source fingerprinting databases

Over the last few years, the sediment source fingerprinting community has been engaged in promoting best practices to improve the design and the implementation of sediment fingerprinting techniques (<a href="https://doi.org/10.1007/s11368-022-03203-1">Evrard et al., 2022</a>). Data sharing is a key part of open science making research more reliable and accessible to the community. To move forward and improve data sharing, we propose these templates for databases and metadata. These templates include: common metadata for samples (soil, river flood deposit, sediment core...) description (name, IGSN, location, sampling date...), list and description of common properties (elemental geochemistry, organic matter, radionuclides…) used in sediment source fingerprinting studies. These templates are intended to evolve thanks to the participation of the community, as part of a collaborative project. In addition, the collectionneur R package was designed to help researchers and data managers maintain an up-to-date and well-organized database. is avalaible on <a href="https://github.com/tchalauxclergue/collectionneur">GitHub (https://github.com/tchalauxclergue/collectionneur)</a> and <a href="https://doi.org/10.5281/zenodo.15146958">Zenodo (https://doi.org/10.5281/zenodo.15146958)</a>. It facilitates the comparison and integration of new data entries into an existing database while keeping a detailed report of all modifications. All database formats are allowed, although it was initially designed for sediment source fingerprinting databases. Published databases following these templates are listed in the References section below.

opencc-by-4.0Mar 2024View details →

Organic Matter, Geochemical, Visible Spectrocolorimetric Properties, Radiocesium Properties, and Grain Size of Potential Source Material, Target Sediment Core Layers and Laboratory Mixtures for Conducting Sediment Fingerprinting Approaches in the Mano Dam Reservoir (Hayama Lake) Catchment, Fukushima Prefecture, Japan

The current dataset was compiled to study sediment fingerprintings practices, i.e tracer selection and contribution modelling. Organic matter, elemental geochemistry, visible difuse spectrocolorimetric properties, radiocesium properties, and grain size were analysed were analysed in potential source material that may supply sediment to coastal rivers, here the upper part of the Mano river, draining the main Fukushima radioactive pollution plume (Japan). Four potential soil source materials (n = 68) were considered: undecontaminated cropland (n = 24), as non-decontaminated soil before the application of local decontamination policies, remediated cropland (n = 10), as decontaminated soil after the application of local decontamination policies, forest soils (n = 24) and subsurface material originating from channel bank collapse or landslides (n = 10; referred to as subsoil). A sediment core was collected in the Mano Dam lake (Hayama lake) on the 6th June 2021 and was sectionned into 1-cm layers (n = 38). Laboratory mixtures (n = 27) were made to assess different contribution levels from the sources. The current dataset comprises four .csv files including data and metadata information and their respective descriptions of variables. The data set is composed of soil samples, sediment core layer and laboratory mixtures. Laboratory mixtures were prepared to provide a dataset to calibrate/validate un-mixing models implemented to address this research question and analysed in the same conditions and using the same equipment as the source/target material. Recommended encoding format: latin1

opencc-by-4.0Jul 2022View details →

Field and laboratory measurements of suspended-sediment particle size and concentration from nine rivers draining to the Great Barrier Reef

Dataset includes in-situ (n = 144,912) and laboratory-dispersed (n = 64) particle size measurements collected using laser diffractometry from nine rivers discharging along 800 km of Great Barrier Reef, Queensland Australia coastline. Two field campaigns (24 February to 5 March 2021 and 24th to 31st of April 2021) were undertaken to collect vertical profiles of in-situ particle size, water velocity, turbidity, and salinity. Water samples were collected for analysis of laboratory-dispersed particle size and suspended-sediment concentration. Water samples were collected using US-P61 or Van-Dorn samplers deployed alongside a LISST 200x laser diffractometer and an EXO2 YSI multiparameter water quality sonde. Total depth and water velocity were measured using a Nortek Signature ADCP and Teledyne RiverRay ADCP during the first and second field campaigns, respectively. During both campaigns, measurements were undertaken during relatively high discharge events when discharge exceeded the 90th percentile of 2020/2021 gauged wet season flows. Data are provided in three csv files. "In_situ_data.csv" contains in situ measurements of particle size, turbidity, salinity, and depth along with estimates of shear rate. Shear rate is estimated from theory and measurements of ADCP-measured total depth and depth-averaged flow (see equation 2 of Livsey et al., 2022). "Lab_data_this_study.csv" contains particle size measurements of suspended-sediment following laboratory dispersion along with coeval measurements of in-situ particle size, turbidity, salinity, and shear rate averaged over the filling time of the US-P61 sampler. "Lab_data_DES_WQI.csv" contains laboratory dispersed particle size measurements collected by the Department of Environment and Science Water Quality Investigation Unit of Queensland Australia (Turner et al., 2013) and compared to data in  "Lab_data_this_study.csv" in Livsey et al (2022).  Further details of the data collection effort and interpretation of the data are published in Livsey et al (2022) at https://doi.org/10.1029/2021JC017988.   Additional data from the 24 February to 5 March 2021 field campaign, funded by CSIRO Oceans and Atmosphere, are available from Crosswell et al (2022) at https://doi.org/10.25919/2vbh-cx08. References: Crosswell, Joey; Carlin, Geoff; Daniel, Livsey; Hillyer, Katie; Steven, Andy (2022): FNQ_2021_V01 Voyage dataset: Feb - March 2021; Biogeochemical and hydrodynamic obervations along the river-reef continuum of estuaries in eastern Cape York, Australia. v1. CSIRO. Data Collection. 10.25919/2vbh-cx08 Livsey, D. L., Crosswell, J. R., Turner, R. R., Steven, A. D. L., & Grace, P. R. (2022) Flocculation of riverine sediment draining to the Great Barrier Reef, implications for monitoring and modelling of sediment dispersal across continental shelves. Journal of Geophysical Research: Oceans. https://doi.org/10.1029/2021JC017988 Turner. R, Huggins. R, Wallace. R, Smith. R, Vardy. S, Warne. M St. J. (2013). Total suspended solids, nutrient, and pesticide loads (2010-2011) for rivers that discharge to the Great Barrier Reef Great Barrier Reef Catchment Loads Monitoring 2010-2011 Department of Science, Information Technology, Innovation and the Arts, Brisbane.

opencc-by-4.0Sep 2022View details →

Sediment size dataset for Australia

This repository contains a dataset of median grain size (d50) for the Australian coastline. The sediment samples were collected by <a href="https://www.sydney.edu.au/science/about/our-people/academic-staff/andrew-short.html">Professor Andrew D. Short</a> during field campaigns between 1979 and 1999. This dataset includes all the sand samples collected in the swash zone. More information about this dataset can be found in <a href="https://link.springer.com/book/10.1007/978-3-030-14294-0#bibliographic-information">Australian Coastal Systems book</a>. The beach sand sample collection is physically stored at Geoscience Australia (Canberra) and can be viewed by contacting <a href="mailto:AusGeoSamples@ga.gov.au">AusGeoSamples@ga.gov.au</a>. Dataset description The data is contained in the file Australia_dataset.geojson. This geospatial layer contains a linestring for each individual beach/embayment. The coordinate system of the geospatial layer is WGS84. This geospatial layer matches and complements the Australian beach-face slope dataset published here <a href="https://doi.org/10.5281/zenodo.5606216">https://doi.org/10.5281/zenodo.5606216</a> and described in <a href="https://doi.org/10.5194/essd-14-1345-2022">Vos et al. 2022</a>. Note that not every beach in the layer contains a sediment size value. Each feature has the following attributes: Grain-size and location attributes   - d50: Median grain-size in millimetres. Obtained by sieving the sand samples. The original sand samples were donated to Geoscience Australia.   - beach_id: Database id for each beach, e.g., aus0001, aus0002, …, aus5255 (same as in <a href="http://doi.org/10.5281/zenodo.5606216">Vos et al. 2022</a>),   - ABSAMP_id: id of the sample in the ABSAMP database, e.g., nsw0001, tas001, qld001 etc. See the <a href="https://ecat.ga.gov.au/geonetwork/srv/api/records/d14b2b5b-332d-4e8f-b732-3d01a06866b2">Smartline</a> from Geoscience Australia for the location of each id.   - distance_to_sample: Distance in metres between the linestring in the ABSAMP database and the linestring in this layer.   - latitude: Latitude of the centroid of the beach in WGS84.   - longitude: Longitude of the centroid of the beach in WGS84.   - beach_length: Length of the beach or embayment, very long beaches (>50km) were split to optimise memory usage.   - coastal_region: Database id corresponding to the 23 coastal regions as identified by <a href="https://www.sciencedirect.com/science/article/pii/S0964569117306129">Thom et al. (2018)</a>.   - primary_comp_id: Database id corresponding to the 100 primary sediment compartments as identified by <a href="https://www.sciencedirect.com/science/article/pii/S0964569117306129">Thom et al. (2018)</a>.   - secondary_comp_id: Database id corresponding  to the 361 secondary sediment Compartments as identified by <a href="https://www.sciencedirect.com/science/article/pii/S0964569117306129">Thom et al. (2018)</a>. Wave climate and tide range attributes   - Hs_mean: Mean Significant Wave Height at the closest grid point in the ERA5 re-analysis dataset (computed using 6-hourly time-series between 2010 and 2020).   - Hs_max: Max Significant Wave Height at the closest grid point in the ERA5 re-analysis dataset (computed using 6-hourly time-series between 2010 and 2020).   - Tp_mean: Mean Peak Wave Period at the closest grid point in the ERA5 re-analysis dataset (computed using 6-hourly time-series between 2010 and 2020).   - Wdir_mean: Mean Wave Direction at the closest grid point in the ERA5 re-analysis dataset (computed using 6-hourly time-series between 2010 and 2020).   - Wdir_weighted_average: More robust estimator of the Mean Wave Direction obtained by computing the average wave direction weighted by wave energy flux.   - hsig_median: Median Significant Wave Height from the closest grid point in the CAWCR re-analysis dataset   - mstr: Mean Spring Tide Range at the beach calculated from the closest grid point in the FES2014 global tide model Beach-face slope attributes (same as in <a href="http://doi.org/10.5281/zenodo.5606216">Vos et al. 2022</a>)   - beach_slope_average: Average of the beach-face slope at the site, weighted by the width of the confidence bands, value between 0.01 and 0.2   - width_ci_average: Average width of confidence band over the comprised transects, value between 0 and 0.19   - quality_flag: Quality flag indicating the confidence in the slope estimate at this transect (High, Medium or Low)   - prc_msrt_obs: percentage of the Mean Spring Tide Range observed by the satellite-derived shorelines   - min_tide_obs: Lowest tide level observed by the satellite-derived shorelines   - max_tide_obs: Highest tide level observed by the satellite-derived shorelines   - sl_points_average: Average number of datapoints in the shoreline time-series over the comprised transects

opencc-by-4.0Aug 2024View details →

Water quality data (River sediment, Nitrogen and Phosphorus loads) for Africa

Output data on African water quality and scripts for preprint - "One third of African rivers fail to meet the 'good ambient water quality' nutrient targets" at <a href="https://dx.doi.org/10.2139/ssrn.4829742">https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4829742</a> . Please check the readme file for data description. The data includes river flow, sediment load, nitrogen and Phosphorus loads for Africa at daily and yearly time scale. This work is currently under review in Ecological Indicators journal.

opencc-by-4.0Aug 2024View details →

Sediment Budget for Timber Harvest in a California Coastal Watershed

Dataset for Publication: Sediment Budget for Timber Harvest in a California Coastal Watershed

opencc-by-4.0Sep 2024View details →

Road-deposited sediment wash-off experiments on a large-scale laboratory

This dataset includes raw and processed data from a series of large-scale laboratory tests that were conducted to assess and study the wash-off process of RDS (Road deposited sediments) considering variations in rainfall intensity, for two scenarios: 30 mm/h and 50 mm/h; and modifying RDS loads applied on BLOCK for three scenarios: 100 g/m2, 150 g/m2, 200 g/m2. First, the hydraulic was detailly characterized including rainfall intensity maps, water flows, surface water depths and surface water velocities for both rainfall intensities tested. A synthetic granulometric of RDS was homogeneously distributed on the physical model surface and then washed-off by the simulated rainfall. A total of 31 water samples were collected at the manhole discharge per each experiment. Total RDS mass that remain on the surface and inside the gully was collected by a wet vacuum after the rainfall event. A mass balance considering the initial RDS applied and the total RDS recollected in the three samples locations, was calculated. TUR (Turbidity), EC (Conductivity), TS (Total Solids), TSS (Total suspended solids), TDS (Total dissolved solids), RDS mass by flow, and RDS mass flow variables were measured for the RDS samples recollected in the Manhole discharge. The behaviour of each RDS fraction was also analysed through laser diffraction (Beckman Coulter LS 13 320, Aqueous Liquids Module). This work is part of a Transnational Access developed by the Universidad Distrital Francisco José de Caldas (Colombia) and Universidade da Coruña (Spain) within the scope of Co-UDlabs project. Data may be used to increase knowledge on road-deposited sediment wash-off process, allowing also for calibrating, developing, and validating new and existing urban wash-off models.

opencc-by-4.0Nov 2024View details →

Geochemistry of soils and eroded suspended sediments from two large rural catchments in southern Brazil for studies on Suspended Sediment Fingerprinting

1. Introduction This dataset comes from a research project entitled "Water and pollutants, from cropfields to cities: evaluation and improved of soil management technologies in a catchment network " supported by the Foundation for Research Support of the State of Rio Grande do Sul (FAPERGS) and National Council for Scientific and Technological Development (CNPq) (process n°10/0034-0). The project was carried out between 2010 and 2014 under the coordination of José Miguel Reichert and Danilo Rheinheimer dos Santos, professors at the Federal University of Santa Maria. One of the aims of this project was to understand the main pollutant transfer process from hillslopes to fluvial systems in large rural catchments representative of the agricultural production system in Southern Brazil. In this context, the Suspended Sediment Fingerprinting (SSF) was extremely useful for quantifying the origin of the sediment yield monitored at the outlet of these catchments. Among the various works carried out in this project, we highlight Tales Tiecher's doctoral thesis (Tiecher, 2015) that explored the SSF in many catchments, including the Conceição and Guaporé river basins. 2. Material and Methods The catchments represent the magnitude of erosive and hydrological processes representative of Southern Brazil. The Conceição catchment has a drainage area of 804 km2 (28°27′22″S and 53°58′24″ W). According to Köppen, the climate is Cfa type, with an annual rainfall between 1,750 and 2,000 mm. Geology is riodacithe basalt, with a formation of deep and highly weathered soils (Oxisols, Ultisols, and Alfisols). The relief is characterized by gentle slopes (6–9 %) on top and hillside slopes and higher steepness (10–14%) near the drainage channels. Farming based on the production of soybeans (Glycine max) in summer and wheat (Triticumspp.), oats (Avena strigosa), and ryegrass (Lolium multiflorum) in winter. The Guaporé catchment has a drainage area of 1,980 km2 (28°54′41″S and 51°57′10″W), it covers part of the meridional plateau border. The climate is classified as Cfa, with annual rainfall varies between 1,400 and 2,000 mm. Geology is characterized by volcanic lava flows, and topography is undulating to hilly. Due to variations in landscape, several classes of soils (Entisols, Luvisol, Cambisol, Oxisol, Ultisol, and Chernosol). The land use is highly heterogeneous. In the upper third of the catchment, there is a predominance of soybean cultivated under no-tillage soil management. In the other two-thirds (middle and lower parts), land use and soil management are very heterogeneous. The main land uses are tobacco (Nicotiana tabacum) and maize (Zea mays) crops, Eucalyptus (Eucalyptus spp.), as well as pastures for dairy cattle. The contribution of unpaved roads is relevant to the sediment yield in both catchments (Didoné et al., 2014). Composite samples of potential sediment sources (cropland, unpaved roads, and stream channel banks) were collected. Sediment source samples were taken from the surface soil layer (0–0.05 m) of cropland and unpaved roads and on exposed sites located along the river channel network. Each sample was composed of at least 10 subsamples. To obtain representative samples of suspended sediment transported in the catchment’s outlet were used three strategies: (1) to collect flood suspended sediments (FSS) through the manual sampling (USDH-48) at different periods during the rising and falling stages of floods; (2) to deploy time-integrated suspended sediment samplers (TISS), by installing the device developed by Phillips et al. (2000) at different sites within the catchments; to collect fine-bed sediment (FBS) with a suction stainless sampler limiting the loss of fine material at the bed river. Source and sediment samples were oven‐dried at 50 °C, gently disaggregated using a pestle and mortar, and then sieved to 62,5 μm. The geochemical tracers evaluated were total organic carbon estimated by wet oxidation (K2Cr2O7 + H2SO4) and the total concentration of Al, Ba, Be, Ca, Co, Cr, Cu, Fe, K, La, Li, Mg, Mn, Na, Ni, P, Pb, Sr, Ti, V, and Zn using inductively coupled plasma optical emission spectrometry after microwave‐assisted digestion with concentrated HCl and HNO3 (ratio 3:1) for 9.5 min at 182 °C (Tiecher, 2015; Tiecher et al. 2017, 2018).   3. Final remarks             The SSF results provided by this dataset (Tiecher, 2015) combined with sediment yield monitoring were very important for the assessment and modeling studies in these two catchments that took place after that (Didoné et al., 2015; 2017). In addition, other studies have explored the same sample bank, expanding upon the array of tracer properties and increasing our understanding about the mechanisms of sediment and pollutant transfer in these catchments (Le Gall et al. 2017; Zafar et al., 2017; Ramon et al., 2020).  4. References  Didoné, E. J., Minella, J. P. G., Reichert, J. M., Merten G. H., Dalbianco, L., Barros, C. A. P., Ramon, R. (2014) Impact of no-tillage agricultural systems on sediment yield in two large catchments in southern Brazil. J Soils Sediments 14:1287–1297. Didoné, E.J., Minella, J.P.G., Evrard, O. (2017). Measuring and modelling soil erosion and sediment yields in a large cultivated catchment under no-till of Southern Brazil. Soil Tillage Res. 174, 24-33. https://doi.org/10.1016/j.still.2017.05.011 Didoné, E. J.; Minela, J. P. G.; Merten, G. H. (2015). Quantifying soil erosion and sediment yield in a catchment in southern Brazil and implications for land conservation. J. Soils Sediments 11, 2334-2346. https://doi.org/10.1007/s11368-015-1160-0 le Gall, M., Evrard, O., Dapoigny, A., Tiecher, T., Zafar, M., Minella, J. P. G., Laceby, J. P., & Ayrault, S. (2017). Tracing sediment sources in a subtropical agricultural catchment of southern Brazil cultivated with conventional and conservation farming practices. Land Degradation and Development, 28(4). https://doi.org/10.1002/ldr.2662 Ramon, R., Evrard, O., Laceby, J. P., Caner, L., Inda, A. v., Barros, C. A. P., Minella, J. P. G., & Tiecher, T. (2020). Combining spectroscopy and magnetism with geochemical tracers to improve the discrimination of sediment sources in a homogeneous subtropical catchment. Catena, 195, 104800. https://doi.org/10.1016/j.catena.2020.104800 Tiecher, T. (2015). Fingerprinting sediment sources in agricultural catchments in Southern Brazil. Doctoral Dissertation in Soil Science. Universidade Federal de Santa Maria, Santa Maria, RS. Tiecher, T., Minella, J. P. G., Caner, L., Evrard, O., Zafar, M., Capoane, V., le Gall, M., & Santos, D. R. D. (2017). Quantifying land use contributions to suspended sediment in a large cultivated catchment of Southern Brazil (Guaporé River, Rio Grande do Sul). Agriculture, Ecosystems and Environment, 237. https://doi.org/10.1016/j.agee.2016.12.004 Tiecher, T., Minella, J. P. G., Evrard, O., Caner, L., Merten, G. H., Capoane, V., Didoné, E. J., & dos Santos, D. R. (2018). Fingerprinting sediment sources in a large agricultural catchment under no-tillage in Southern Brazil (Conceição River). Land Degradation and Development, 29(4). https://doi.org/10.1002/ldr.2917. Zafar, M., Tiecher, T., Capoane, V., Troian, A., dos Santos, D.R. (2017). Characteristics, lability and distribution of phosphorus in suspended sediment from a subtropical catchment under diverse anthropic pressure in Southern Brazil. Ecol. Eng. 100, 28–45.

opencc-by-4.0May 2023View details →

River Sediment Database (RivSed)

The River Sediment Database (RivSed) database contains surface suspended sediment concentrations (SSC) derived from Landsat 5, 7, and 8 Level 1 Collection 1 surface reflectance from all rivers in the contiguous USA that are ~60 meters wide or greater. SSC represent spatially integrated "reach" median concentrations over the footprint of NHDPlusV2 centerlines where high quality river water pixels were detected within each Landsat image from 1984-2018. This is built in the River Surface Reflectance database (RiverSR) also in Zenodo (Gardner et al,. 2020 Geophysical Research Letters).  The paper associated with RivSed: Gardner, J., Pavelsky, T. M., Topp, S., Yang, X., Ross, M. R., & Cohen, S. (2023). Human activities change suspended sediment concentration along rivers. Environmental Research Letters. <a href="https://iopscience.iop.org/article/10.1088/1748-9326/acd8d8">https://iopscience.iop.org/article/10.1088/1748-9326/acd8d8</a>     Files: 1) Metadata (riverSed_v1.0_metadata.pdf): Description of all data files associated with this repository.  2) RiverSed (RiverSed_USA_v1.1.txt). Table of  SSC  and associated data that is joinable to nhdplusv2_modified_v1.0.shp based on the "ID" column and to the original NHDplusV2 flowlines with the "COMID" column. 3) Shapefile of river centerlines to which the reflectance data can be attached (nhdplusv2_modified_v1.0.shp). 4) Shapefile of the reach polygons associated with each nhdplusv2_modified reach. (nhdplusv2_polygons_v1.0.shp). 5) The look up table for reach IDs of original (COMID) and modified (ID) NHDplusV2 centerlines. (COMID_ID.csv). Short reaches were joined together to optimize for remote sensing data collection and make more consistent reach lengths. 6) SSC-Landsat matchup database with extended metadata on locations and in-situ data derived from Aquasat (Ross et al., 2019) (Aquasat_TSS_v1.1.csv) 7) The final training data used to build the xgboost machine learning model (train_clean_xgb_v1.1.csv) 8) The xgboost model that can make SSC predictions over inland waters in USA using Landsat bands/band combinations (finalmodel_xgb_v1.1.rds and .RData). The model can only be loaded in R for now.

opencc-by-4.0Nov 2022View details →

Identification of microbial exopolymer producers in sandy and muddy intertidal sediments by compound-specific isotope analysis.

This dataset supports the version 2 of the paper entitled Identification of microbial exopolymer producers in sandy and muddy intertidal sediments by compound-specific isotope analysis : Hubas, Cédric; Gaubert-Boussarie, Julie; D’Hondt, An-Sofie; Jesus, Bruno; Lamy, Dominique; Meleder, Vona; Prins, Antoine; Rosa, Philippe; Stock, Willem; Sabbe, Koen. Identification of microbial exopolymer producers in sandy and muddy intertidal sediments by compound-specific isotope analysis. Peer Community Journal, Volume 3 (2023), article no. e104. doi : <a href="https://doi.org/10.24072/pcjournal.336">10.24072/pcjournal.336</a>. <a href="https://peercommunityjournal.org/articles/10.24072/pcjournal.336/">https://peercommunityjournal.org/articles/10.24072/pcjournal.336/</a>

opencc-by-4.0Jul 2023View details →

Paired field measurements of suspended-sediment concentration, turbidity, acoustic backscatter, and particle size compiled from various estuaries in the United States and Australia

Field measurements of suspended-sediment concentration, turbidity, acoustic backscatter, and particle size are compiled from various estuaries in the United States and Australia to investigate the utility of combining optical and acoustic backscatter measurements for the estimation of suspended-sediment concentration under changes in floc particle size and density.  Theory, analysis, and interpretation of the data is available in Livsey et al (2023). Data collected from the Chesapeake Bay, US were compiled from Fall et al (2022). Data collected on the Brisbane River were collected by Livsey et al (2022).  Data collected for all other locations were compiled from Livsey et al (2022).   Data collected by Fall et al (2022) utilized a LISST 100x. Data collected by Livsey et al (2022, 2023) utilized a LISST 200x. Data files for each instrument are provided.  Funding for this research was provided by an Advance Queensland Industry Research Fellowship, Queensland University of Technology, and Queensland Department of Environment and Science. References Fall, Kelsey A., Massey, Grace M., and Friedrichs, Carl T., (2020). The importance of organic content to fractal floc properties in estuarine surface waters, insights from video, LISST, and pump sampling: Supporting data. Data. William & Mary. https://doi.org/10.25773/7gbc-794 6739 Livsey, D., Turner, R., Grace, P., and Crosswell, & Andy Steven. (2022). Field and laboratory measurements of suspended-sediment particle size and concentration from nine rivers draining to the Great Barrier Reef (1.0). Data. Zenodo. https://doi.org/10.5281/zenodo.6788303 Livsey, D., Turner, R., and Grace, P. (2023). Combining optical and acoustic backscatter measurements for monitoring of fine suspended-sediment concentration under changes in particle size and density. Water Resources Research. <a href="https://doi.org/10.1029/2022WR033982">https://doi.org/10.1029/2022WR033982</a>

openCC (other)Oct 2021View details →

Spatiotemporal variation in internal phosphorus loading, sediment characteristics, water column chemistry, and thermal mixing in a hypereutrophic reservoir in southwest Iowa, USA (2019-2020)

The primary aim of the data product is to quantify seasonal and spatial variation in sediment phosphorus fluxes in a temperate reservoir and evaluate mechanisms responsible for instances of elevated sediment phosphorus release. We studied Green Valley Lake, a hypereutrophic reservoir in southwest Iowa, USA, from 2019 to 2020. We measured sediment phosphorus flux rates and potential explanatory variables at three sites along the longitudinal gradient of the reservoir over six sampling events during winter and summer stratification as well as mixing events in the spring, summer, and fall. Ex situ sediment core incubations were used to measure sediment P release rates under ambient temperature and dissolved oxygen conditions. Explanatory variables measured included sediment phosphorus chemistry, sediment physical characteristics, epilimnetic and hypolimnetic nutrient concentrations, and thermal stratification patterns. These data will be used to identify mechanisms driving hot spots and hot moments of sediment phosphorus release, which will contribute to our understanding of how areas of lakebed and times of the year can disproportionately influence whole-lake water chemistry.

openCC (other)Mar 2025View details →

Sediment porewater salinity and moisture at runnel restoration sites in SE Massachusetts from 2020 - 2022.

Natural disturbances, sea level rise, and historic human impacts to salt marshes have increased impounded water on marsh surfaces, resulting in vegetation loss and the associated loss of important ecosystem services. Runnels are a climate adaptation technique designed to restore salt marsh habitat by reestablishing a tidal connection between impounded water and a nearby drainage feature. Porewater salinity and moisture content are two sediment characteristics that could potentially be altered by panne formation and runneling, which could impact rates of carbon decomposition. We installed runnels in two marshes in SE Massachusetts in 2020, and monitored salinity and moisture content changes for two years (2021-2022).

openCC0May 2025View details →

Sediment organic phosphorus mineralization through extreme drought experiment, Poyang Lake, China, 2022

Sediment samples from Poyang Lake before and after the extreme drought were analyzed by FT ICR-MS, and the samples were named Pre-drought and Post-drought, respectively; initial samples from the simulated drought experiment and samples from the treatment groups at the end of the drought were analyzed by FT ICR-MS, and the samples were named Initial, Light, Light+, respectively. 16S rRNA gene sequence analysis was performed on samples from each bacterial treatment group at the end of the drought and the initial samples, which were named Initial, Micerbe, Microbe+light, respectively.