Articles | Volume 14, issue 2
https://doi.org/10.5194/essd-14-929-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-14-929-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
24 Feb 2022
Data description paper |
| 24 Feb 2022
| 24 Feb 2022
Median bed-material sediment particle size across rivers in the contiguous US
Guta Wakbulcho Abeshu
Department of Civil and Environmental Engineering, University of Houston, Texas 77204, USA
Department of Civil and Environmental Engineering, University of Houston, Texas 77204, USA
Department of Civil, Structural and Environmental Engineering, University at Buffalo, The State University of New York, Buffalo, New York 14260, USA
Pacific Northwest National Laboratory, Richland, Washington 99352, USA
L. Ruby Leung
Pacific Northwest National Laboratory, Richland, Washington 99352, USA
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Cited
15 citations as recorded by crossref.
- Methane Production Reduced by Lignin Derivatives in Pulping Wastewater: Inhibition of Free Hydrolase J. Lei et al. 10.3390/fermentation10050247
- Selective Separation of Rare Earth Ions from Mine Wastewater Using Synthetic Hematite Nanoparticles from Natural Pyrite C. Zhao et al. 10.3390/min14050464
- Influences of aquatic and terrestrial habitat characteristics on abundance patterns of adult wood turtles J. Staggs et al. 10.1002/jwmg.22589
- Suspended sediment load modeling using Hydro-Climate variables and Machine learning S. Aldin Shojaeezadeh et al. 10.1016/j.jhydrol.2024.130948
- Unraveling the complexities of urban fluvial flood hydraulics through AI M. Mehedi et al. 10.1038/s41598-022-23214-9
- Enhancing the representation of water management in global hydrological models G. Abeshu et al. 10.5194/gmd-16-5449-2023
- A Novel Efficient Method of Estimating Suspended‐To‐Total Sediment Load Fraction in Natural Rivers H. Noh et al. 10.1029/2022WR034401
- CRHyME (Climatic Rainfall Hydrogeological Modelling Experiment): a new model for geo-hydrological hazard assessment at the basin scale A. Abbate et al. 10.5194/nhess-24-501-2024
- Gravity currents with large salinity in a gravel bed valley: an experimental study E. Keramaris et al. 10.2166/ws.2022.150
- Influence of Vertical Hydrologic Exchange Flow, Channel Flow, and Biogeochemical Kinetics on CH4 Emissions From Rivers K. Chen et al. 10.1029/2023WR035341
- Erosion of heterogeneous rock drives diversification of Appalachian fishes M. Stokes et al. 10.1126/science.add9791
- Rainfall-driven machine learning models for accurate flood inundation mapping in Karachi, Pakistan U. Rasool et al. 10.1016/j.uclim.2023.101573
- An experimental and theoretical study on effects of particle size distribution on flowability and film properties of organic powder coatings J. Xie et al. 10.1016/j.porgcoat.2024.108668
- Spatial Microbial Respiration Variations in the Hyporheic Zones Within the Columbia River Basin K. Son et al. 10.1029/2021JG006654
- Spatial Trends and Drivers of Bedload and Suspended Sediment Fluxes in Global Rivers S. Cohen et al. 10.1029/2021WR031583
13 citations as recorded by crossref.
- Methane Production Reduced by Lignin Derivatives in Pulping Wastewater: Inhibition of Free Hydrolase J. Lei et al. 10.3390/fermentation10050247
- Selective Separation of Rare Earth Ions from Mine Wastewater Using Synthetic Hematite Nanoparticles from Natural Pyrite C. Zhao et al. 10.3390/min14050464
- Influences of aquatic and terrestrial habitat characteristics on abundance patterns of adult wood turtles J. Staggs et al. 10.1002/jwmg.22589
- Suspended sediment load modeling using Hydro-Climate variables and Machine learning S. Aldin Shojaeezadeh et al. 10.1016/j.jhydrol.2024.130948
- Unraveling the complexities of urban fluvial flood hydraulics through AI M. Mehedi et al. 10.1038/s41598-022-23214-9
- Enhancing the representation of water management in global hydrological models G. Abeshu et al. 10.5194/gmd-16-5449-2023
- A Novel Efficient Method of Estimating Suspended‐To‐Total Sediment Load Fraction in Natural Rivers H. Noh et al. 10.1029/2022WR034401
- CRHyME (Climatic Rainfall Hydrogeological Modelling Experiment): a new model for geo-hydrological hazard assessment at the basin scale A. Abbate et al. 10.5194/nhess-24-501-2024
- Gravity currents with large salinity in a gravel bed valley: an experimental study E. Keramaris et al. 10.2166/ws.2022.150
- Influence of Vertical Hydrologic Exchange Flow, Channel Flow, and Biogeochemical Kinetics on CH4 Emissions From Rivers K. Chen et al. 10.1029/2023WR035341
- Erosion of heterogeneous rock drives diversification of Appalachian fishes M. Stokes et al. 10.1126/science.add9791
- Rainfall-driven machine learning models for accurate flood inundation mapping in Karachi, Pakistan U. Rasool et al. 10.1016/j.uclim.2023.101573
- An experimental and theoretical study on effects of particle size distribution on flowability and film properties of organic powder coatings J. Xie et al. 10.1016/j.porgcoat.2024.108668
Latest update: 23 Dec 2024
Short summary
Existing riverbed sediment particle size data are sparsely available at individual sites. We develop a continuous map of median riverbed sediment particle size over the contiguous US corresponding to millions of river segments based on the existing observations and machine learning methods. This map is useful for research in large-scale river sediment using model- and data-driven approaches, teaching environmental and earth system sciences, planning and managing floodplain zones, etc.
Existing riverbed sediment particle size data are sparsely available at individual sites. We...
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