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 article
| 
24 Feb 2022
Data description article |
| 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
Viewed
Total article views: 6,448 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 08 Jul 2021)
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 4,137 | 2,156 | 155 | 6,448 | 579 | 174 | 244 |
- HTML: 4,137
- PDF: 2,156
- XML: 155
- Total: 6,448
- Supplement: 579
- BibTeX: 174
- EndNote: 244
Total article views: 4,993 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 24 Feb 2022)
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 3,329 | 1,542 | 122 | 4,993 | 367 | 158 | 221 |
- HTML: 3,329
- PDF: 1,542
- XML: 122
- Total: 4,993
- Supplement: 367
- BibTeX: 158
- EndNote: 221
Total article views: 1,455 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 08 Jul 2021)
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 808 | 614 | 33 | 1,455 | 212 | 16 | 23 |
- HTML: 808
- PDF: 614
- XML: 33
- Total: 1,455
- Supplement: 212
- BibTeX: 16
- EndNote: 23
Viewed (geographical distribution)
Total article views: 6,448 (including HTML, PDF, and XML)
Thereof 6,239 with geography defined
and 209 with unknown origin.
Total article views: 4,993 (including HTML, PDF, and XML)
Thereof 4,844 with geography defined
and 149 with unknown origin.
Total article views: 1,455 (including HTML, PDF, and XML)
Thereof 1,395 with geography defined
and 60 with unknown origin.
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
Cited
27 citations as recorded by crossref.
- Methane Production Reduced by Lignin Derivatives in Pulping Wastewater: Inhibition of Free Hydrolase J. Lei et al. https://doi.org/10.3390/fermentation10050247
- Influences of aquatic and terrestrial habitat characteristics on abundance patterns of adult wood turtles J. Staggs et al. https://doi.org/10.1002/jwmg.22589
- Hyporheic exchange processes of pore-scale microplastics B. Stride et al. https://doi.org/10.1016/j.scitotenv.2025.179573
- Suspended sediment load modeling using Hydro-Climate variables and Machine learning S. Aldin Shojaeezadeh et al. https://doi.org/10.1016/j.jhydrol.2024.130948
- Enhancing the representation of water management in global hydrological models G. Abeshu et al. https://doi.org/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. https://doi.org/10.1029/2022WR034401
- Gravity currents with large salinity in a gravel bed valley: an experimental study E. Keramaris et al. https://doi.org/10.2166/ws.2022.150
- Investigation of mechanisms governing turbulence-induced initiation of motion in non-cohesive sediment layers J. Mao et al. https://doi.org/10.2166/wst.2025.177
- Stochasticity and Intermittency of Microplastic Movements in Open Channel Flows Z. Yu et al. https://doi.org/10.1021/acs.est.6c03893
- Rainfall-driven machine learning models for accurate flood inundation mapping in Karachi, Pakistan U. Rasool et al. https://doi.org/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. https://doi.org/10.1016/j.porgcoat.2024.108668
- Predicting synthetic rating curve adjustment factors with explainable machine learning for enhancing the United States operational flood inundation mapping framework A. Baruah et al. https://doi.org/10.1016/j.jhydrol.2025.134086
- Projected contemporary habitat distribution and quality for wood turtles in the midwestern United States S. Spaid et al. https://doi.org/10.1002/jwmg.70108
- Channel confluence hydrodynamics over a gravel bed S. Yuan et al. https://doi.org/10.1063/5.0326003
- Selective Separation of Rare Earth Ions from Mine Wastewater Using Synthetic Hematite Nanoparticles from Natural Pyrite C. Zhao et al. https://doi.org/10.3390/min14050464
- Transformation rate maps of dissolved organic carbon in the contiguous US L. Li et al. https://doi.org/10.5194/essd-17-2713-2025
- Unraveling the complexities of urban fluvial flood hydraulics through AI M. Mehedi et al. https://doi.org/10.1038/s41598-022-23214-9
- The ResNet network of dams impounding storage reservoirs across the continental United States A. Hurst et al. https://doi.org/10.1038/s41597-025-06315-8
- Landslide risk assessment on the China–Pakistan Economic Corridor (CPEC): a comparative study of quantitative and machine learning approaches A. Siddique et al. https://doi.org/10.1007/s12046-025-02749-3
- An extrapolation algorithm for estimating river bed grain size distributions across basins J. Gilbert https://doi.org/10.5194/esurf-13-1307-2025
- CRHyME (Climatic Rainfall Hydrogeological Modelling Experiment): a new model for geo-hydrological hazard assessment at the basin scale A. Abbate et al. https://doi.org/10.5194/nhess-24-501-2024
- Interpretable machine learning for predicting rating curve parameters using channel geometry and hydrological attributes across the United States A. Baruah et al. https://doi.org/10.1038/s41598-025-27881-2
- Influence of Vertical Hydrologic Exchange Flow, Channel Flow, and Biogeochemical Kinetics on CH4 Emissions From Rivers K. Chen et al. https://doi.org/10.1029/2023WR035341
- Automated probabilistic spatial co-occurrence assessments for aquatic endangered species J. Dunne et al. https://doi.org/10.1093/inteam/vjaf042
- Investigating controls on fluvial grain sizes in post-glacial landscapes using citizen science A. Towers et al. https://doi.org/10.5194/esurf-14-95-2026
- Erosion of heterogeneous rock drives diversification of Appalachian fishes M. Stokes et al. https://doi.org/10.1126/science.add9791
- Different methods of estimating riverbed sediment grain size diverge at the basin scale P. Regier et al. https://doi.org/10.3389/feart.2025.1529503
27 citations as recorded by crossref.
- Methane Production Reduced by Lignin Derivatives in Pulping Wastewater: Inhibition of Free Hydrolase J. Lei et al. https://doi.org/10.3390/fermentation10050247
- Influences of aquatic and terrestrial habitat characteristics on abundance patterns of adult wood turtles J. Staggs et al. https://doi.org/10.1002/jwmg.22589
- Hyporheic exchange processes of pore-scale microplastics B. Stride et al. https://doi.org/10.1016/j.scitotenv.2025.179573
- Suspended sediment load modeling using Hydro-Climate variables and Machine learning S. Aldin Shojaeezadeh et al. https://doi.org/10.1016/j.jhydrol.2024.130948
- Enhancing the representation of water management in global hydrological models G. Abeshu et al. https://doi.org/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. https://doi.org/10.1029/2022WR034401
- Gravity currents with large salinity in a gravel bed valley: an experimental study E. Keramaris et al. https://doi.org/10.2166/ws.2022.150
- Investigation of mechanisms governing turbulence-induced initiation of motion in non-cohesive sediment layers J. Mao et al. https://doi.org/10.2166/wst.2025.177
- Stochasticity and Intermittency of Microplastic Movements in Open Channel Flows Z. Yu et al. https://doi.org/10.1021/acs.est.6c03893
- Rainfall-driven machine learning models for accurate flood inundation mapping in Karachi, Pakistan U. Rasool et al. https://doi.org/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. https://doi.org/10.1016/j.porgcoat.2024.108668
- Predicting synthetic rating curve adjustment factors with explainable machine learning for enhancing the United States operational flood inundation mapping framework A. Baruah et al. https://doi.org/10.1016/j.jhydrol.2025.134086
- Projected contemporary habitat distribution and quality for wood turtles in the midwestern United States S. Spaid et al. https://doi.org/10.1002/jwmg.70108
- Channel confluence hydrodynamics over a gravel bed S. Yuan et al. https://doi.org/10.1063/5.0326003
- Selective Separation of Rare Earth Ions from Mine Wastewater Using Synthetic Hematite Nanoparticles from Natural Pyrite C. Zhao et al. https://doi.org/10.3390/min14050464
- Transformation rate maps of dissolved organic carbon in the contiguous US L. Li et al. https://doi.org/10.5194/essd-17-2713-2025
- Unraveling the complexities of urban fluvial flood hydraulics through AI M. Mehedi et al. https://doi.org/10.1038/s41598-022-23214-9
- The ResNet network of dams impounding storage reservoirs across the continental United States A. Hurst et al. https://doi.org/10.1038/s41597-025-06315-8
- Landslide risk assessment on the China–Pakistan Economic Corridor (CPEC): a comparative study of quantitative and machine learning approaches A. Siddique et al. https://doi.org/10.1007/s12046-025-02749-3
- An extrapolation algorithm for estimating river bed grain size distributions across basins J. Gilbert https://doi.org/10.5194/esurf-13-1307-2025
- CRHyME (Climatic Rainfall Hydrogeological Modelling Experiment): a new model for geo-hydrological hazard assessment at the basin scale A. Abbate et al. https://doi.org/10.5194/nhess-24-501-2024
- Interpretable machine learning for predicting rating curve parameters using channel geometry and hydrological attributes across the United States A. Baruah et al. https://doi.org/10.1038/s41598-025-27881-2
- Influence of Vertical Hydrologic Exchange Flow, Channel Flow, and Biogeochemical Kinetics on CH4 Emissions From Rivers K. Chen et al. https://doi.org/10.1029/2023WR035341
- Automated probabilistic spatial co-occurrence assessments for aquatic endangered species J. Dunne et al. https://doi.org/10.1093/inteam/vjaf042
- Investigating controls on fluvial grain sizes in post-glacial landscapes using citizen science A. Towers et al. https://doi.org/10.5194/esurf-14-95-2026
- Erosion of heterogeneous rock drives diversification of Appalachian fishes M. Stokes et al. https://doi.org/10.1126/science.add9791
- Different methods of estimating riverbed sediment grain size diverge at the basin scale P. Regier et al. https://doi.org/10.3389/feart.2025.1529503
Saved (final revised paper)
Latest update: 03 Jun 2026
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...
Altmetrics
Final-revised paper
Preprint