Articles | Volume 2, issue 1
https://doi.org/10.5194/esurf-2-67-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/esurf-2-67-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
28 Jan 2014
Research article |
| 28 Jan 2014
Data-driven components in a model of inner-shelf sorted bedforms: a new hybrid model
E. B. Goldstein
Division of Earth and Ocean Sciences, Nicholas School of the Environment, Center for Nonlinear and Complex Systems, Duke University, P.O. Box 90227, Durham, NC 27708, USA
Environmental Hydraulics Institute, "IH Cantabria", c/Isabel Torres no. 15, Universidad de Cantabria, 39011 Santander, Spain
A. B. Murray
Division of Earth and Ocean Sciences, Nicholas School of the Environment, Center for Nonlinear and Complex Systems, Duke University, P.O. Box 90227, Durham, NC 27708, USA
M. O. Green
National Institute of Water and Atmospheric Research (NIWA), P.O. Box 11-115, Hamilton, New Zealand
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Cited
17 citations as recorded by crossref.
- Physics-Informed Machine Learning in Design and Manufacturing: Status and Challenges L. Pan et al. https://doi.org/10.1115/1.4070100
- When physics meets machine learning: a survey of physics-informed machine learning C. Meng et al. https://doi.org/10.1007/s44379-025-00016-0
- Uncertainty quantification in modeling earth surface processes: more applicable for some types of models than for others A. Murray et al. https://doi.org/10.1016/j.cageo.2016.02.008
- Impact of climate change on beach erosion in the Basque Coast (NE Spain) I. de Santiago et al. https://doi.org/10.1016/j.coastaleng.2021.103916
- Wave-induced internal pumping as a sediment sorting mechanism and its implications for deltaic stratigraphic evolution: Insights from the Yellow River Delta S. Zhang et al. https://doi.org/10.1016/j.sedgeo.2026.107045
- Stability and bistability in a one‐dimensional model of coastal foredune height E. Goldstein & L. Moore https://doi.org/10.1002/2015JF003783
- PhysVENeT: a physiologically-informed deep learning-based framework for the synthesis of 3D hyperpolarized gas MRI ventilation J. Astley et al. https://doi.org/10.1038/s41598-023-38105-w
- Dynamics of inner-shelf, multi-scale bedforms off the south Aquitaine coast over three decades (Southeast Bay of Biscay, France) A. Mazières et al. https://doi.org/10.1016/j.csr.2014.11.002
- Physically sound formula for longitudinal dispersion coefficients of natural rivers Y. Wang et al. https://doi.org/10.1016/j.jhydrol.2016.11.058
- Towards adopting open and data‐driven science practices in bed form dynamics research, and some steps to this end R. Gutierrez et al. https://doi.org/10.1002/esp.4811
- Climate change and coastal morphodynamics: Interactions on regional scales P. Chowdhury et al. https://doi.org/10.1016/j.scitotenv.2023.166432
- Processes, feedbacks, and morphodynamic evolution of tidal flat–marsh systems: Progress and challenges Z. Zhou et al. https://doi.org/10.1016/j.wse.2021.07.002
- Integrating Scientific Knowledge with Machine Learning for Engineering and Environmental Systems J. Willard et al. https://doi.org/10.1145/3514228
- Simulating mesoscale coastal evolution for decadal coastal management: A new framework integrating multiple, complementary modelling approaches B. van Maanen et al. https://doi.org/10.1016/j.geomorph.2015.10.026
- Data-driven discovery of formulas by symbolic regression S. Sun et al. https://doi.org/10.1557/mrs.2019.156
- Iterative integration of deep learning in hybrid Earth surface system modelling M. Chen et al. https://doi.org/10.1038/s43017-023-00452-7
- Modeling sorting dynamics of cohesive and non-cohesive sediments on intertidal flats under the effect of tides and wind waves Z. Zhou et al. https://doi.org/10.1016/j.csr.2015.05.010
17 citations as recorded by crossref.
- Physics-Informed Machine Learning in Design and Manufacturing: Status and Challenges L. Pan et al. https://doi.org/10.1115/1.4070100
- When physics meets machine learning: a survey of physics-informed machine learning C. Meng et al. https://doi.org/10.1007/s44379-025-00016-0
- Uncertainty quantification in modeling earth surface processes: more applicable for some types of models than for others A. Murray et al. https://doi.org/10.1016/j.cageo.2016.02.008
- Impact of climate change on beach erosion in the Basque Coast (NE Spain) I. de Santiago et al. https://doi.org/10.1016/j.coastaleng.2021.103916
- Wave-induced internal pumping as a sediment sorting mechanism and its implications for deltaic stratigraphic evolution: Insights from the Yellow River Delta S. Zhang et al. https://doi.org/10.1016/j.sedgeo.2026.107045
- Stability and bistability in a one‐dimensional model of coastal foredune height E. Goldstein & L. Moore https://doi.org/10.1002/2015JF003783
- PhysVENeT: a physiologically-informed deep learning-based framework for the synthesis of 3D hyperpolarized gas MRI ventilation J. Astley et al. https://doi.org/10.1038/s41598-023-38105-w
- Dynamics of inner-shelf, multi-scale bedforms off the south Aquitaine coast over three decades (Southeast Bay of Biscay, France) A. Mazières et al. https://doi.org/10.1016/j.csr.2014.11.002
- Physically sound formula for longitudinal dispersion coefficients of natural rivers Y. Wang et al. https://doi.org/10.1016/j.jhydrol.2016.11.058
- Towards adopting open and data‐driven science practices in bed form dynamics research, and some steps to this end R. Gutierrez et al. https://doi.org/10.1002/esp.4811
- Climate change and coastal morphodynamics: Interactions on regional scales P. Chowdhury et al. https://doi.org/10.1016/j.scitotenv.2023.166432
- Processes, feedbacks, and morphodynamic evolution of tidal flat–marsh systems: Progress and challenges Z. Zhou et al. https://doi.org/10.1016/j.wse.2021.07.002
- Integrating Scientific Knowledge with Machine Learning for Engineering and Environmental Systems J. Willard et al. https://doi.org/10.1145/3514228
- Simulating mesoscale coastal evolution for decadal coastal management: A new framework integrating multiple, complementary modelling approaches B. van Maanen et al. https://doi.org/10.1016/j.geomorph.2015.10.026
- Data-driven discovery of formulas by symbolic regression S. Sun et al. https://doi.org/10.1557/mrs.2019.156
- Iterative integration of deep learning in hybrid Earth surface system modelling M. Chen et al. https://doi.org/10.1038/s43017-023-00452-7
- Modeling sorting dynamics of cohesive and non-cohesive sediments on intertidal flats under the effect of tides and wind waves Z. Zhou et al. https://doi.org/10.1016/j.csr.2015.05.010
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