Modelling classical gullies – A review.
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| Title: | Modelling classical gullies – A review. |
|---|---|
| Authors: | Roberts, Melanie E.1,2 (AUTHOR) m.roberts2@griffith.edu.au, Burrows, Ryan M.3 (AUTHOR) ryan.burrows@unimelb.edu.au, Thwaites, Robin N.4 (AUTHOR) r.thwaites@griffith.edu.au, Hamilton, David P.1 (AUTHOR) david.p.hamilton@griffith.edu.au |
| Source: | Geomorphology. Jun2022, Vol. 407, pN.PAG-N.PAG. 1p. |
| Subjects: | Infrastructure (Economics), Water quality, Agricultural productivity, Land management, Machine learning |
| Abstract: | Gully erosion is a significant environmental concern globally. It reduces agricultural productivity, damages urban and rural infrastructure, degrades the quality of receiving waters, and can cause loss of life. In this review we synthesise contemporary models for the erosion of classical gullies An overview of erosion processes provides a context for modelling, and provides a clear delineation for models focussed on classical gullies versus smaller morphological systems. Mathematical models of classical gully erosion have been developed to predict gully initiation and growth, simulate the export of sediments from gullies, and inform land management practices. We identify and summarise 13 classical gully erosion models. These models are classified according to their purpose, mathematical approach, and the scale (spatial and temporal) at which they are applied. The models range from individual gully scale to continental, and from event to decadal timescales. We provide a flowchart to aid in gully erosion model selection based on the modelling objective and data availability. Finally, nine opportunities for the development of gully erosion models are identified: data acquisition, machine learning, sensitivity and uncertainty analysis, climate change risk analysis, model parameterisation and validation, land management implications, gully morphology, neglected processes, and inter-operability of models for catchment-scale applications. • We provide a specific definition of classical gullies. • Classical gully erosion models are reviewed and synthesised. • Nine areas for model improvement are identified to guide future model improvements. • A flow chart is provided to guide gully model selection, implementation and use across a broad range of objectives. • Summary of previous reviews incorporating classical gully erosion models [ABSTRACT FROM AUTHOR] |
| Copyright of Geomorphology is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 156286688 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Modelling classical gullies – A review. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Roberts%2C+Melanie+E%2E%22">Roberts, Melanie E.</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> m.roberts2@griffith.edu.au</i><br /><searchLink fieldCode="AR" term="%22Burrows%2C+Ryan+M%2E%22">Burrows, Ryan M.</searchLink><relatesTo>3</relatesTo> (AUTHOR)<i> ryan.burrows@unimelb.edu.au</i><br /><searchLink fieldCode="AR" term="%22Thwaites%2C+Robin+N%2E%22">Thwaites, Robin N.</searchLink><relatesTo>4</relatesTo> (AUTHOR)<i> r.thwaites@griffith.edu.au</i><br /><searchLink fieldCode="AR" term="%22Hamilton%2C+David+P%2E%22">Hamilton, David P.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> david.p.hamilton@griffith.edu.au</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Geomorphology%22">Geomorphology</searchLink>. Jun2022, Vol. 407, pN.PAG-N.PAG. 1p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Infrastructure+%28Economics%29%22">Infrastructure (Economics)</searchLink><br /><searchLink fieldCode="DE" term="%22Water+quality%22">Water quality</searchLink><br /><searchLink fieldCode="DE" term="%22Agricultural+productivity%22">Agricultural productivity</searchLink><br /><searchLink fieldCode="DE" term="%22Land+management%22">Land management</searchLink><br /><searchLink fieldCode="DE" term="%22Machine+learning%22">Machine learning</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Gully erosion is a significant environmental concern globally. It reduces agricultural productivity, damages urban and rural infrastructure, degrades the quality of receiving waters, and can cause loss of life. In this review we synthesise contemporary models for the erosion of classical gullies An overview of erosion processes provides a context for modelling, and provides a clear delineation for models focussed on classical gullies versus smaller morphological systems. Mathematical models of classical gully erosion have been developed to predict gully initiation and growth, simulate the export of sediments from gullies, and inform land management practices. We identify and summarise 13 classical gully erosion models. These models are classified according to their purpose, mathematical approach, and the scale (spatial and temporal) at which they are applied. The models range from individual gully scale to continental, and from event to decadal timescales. We provide a flowchart to aid in gully erosion model selection based on the modelling objective and data availability. Finally, nine opportunities for the development of gully erosion models are identified: data acquisition, machine learning, sensitivity and uncertainty analysis, climate change risk analysis, model parameterisation and validation, land management implications, gully morphology, neglected processes, and inter-operability of models for catchment-scale applications. • We provide a specific definition of classical gullies. • Classical gully erosion models are reviewed and synthesised. • Nine areas for model improvement are identified to guide future model improvements. • A flow chart is provided to guide gully model selection, implementation and use across a broad range of objectives. • Summary of previous reviews incorporating classical gully erosion models [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Geomorphology is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1016/j.geomorph.2022.108216 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 1 StartPage: N.PAG Subjects: – SubjectFull: Infrastructure (Economics) Type: general – SubjectFull: Water quality Type: general – SubjectFull: Agricultural productivity Type: general – SubjectFull: Land management Type: general – SubjectFull: Machine learning Type: general Titles: – TitleFull: Modelling classical gullies – A review. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Roberts, Melanie E. – PersonEntity: Name: NameFull: Burrows, Ryan M. – PersonEntity: Name: NameFull: Thwaites, Robin N. – PersonEntity: Name: NameFull: Hamilton, David P. IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 06 Text: Jun2022 Type: published Y: 2022 Identifiers: – Type: issn-print Value: 0169555X Numbering: – Type: volume Value: 407 Titles: – TitleFull: Geomorphology Type: main |
| ResultId | 1 |
