Dynamic Modelling of Water and Wind Erosion in Australia over the Past Two Decades

Zhang, M; Viscarra Rossel, RA; Zhu, Q; Leys, J; Gray, JM; Yu, Q; Yang, X

Dynamic Modelling of Water and Wind Erosion in Australia over the Past Two Decades

Zhang, M

Viscarra Rossel, RA Zhu, Q

Leys, J Gray, JM Yu, Q Yang, X

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Publisher:: MDPI
Publication Type:: Journal Article
Citation:: Remote Sensing, 2022, 14, (21)
Issue Date:: 2022-11-01

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Field	Value	Language
dc.contributor.author	Zhang, M https://orcid.org/0000-0002-5431-9274
dc.contributor.author	Viscarra Rossel, RA
dc.contributor.author	Zhu, Q https://orcid.org/0000-0002-2371-4626
dc.contributor.author	Leys, J
dc.contributor.author	Gray, JM
dc.contributor.author	Yu, Q
dc.contributor.author	Yang, X https://orcid.org/0000-0002-5990-2186
dc.date.accessioned	2023-02-28T04:18:04Z
dc.date.available	2023-02-28T04:18:04Z
dc.date.issued	2022-11-01
dc.identifier.citation	Remote Sensing, 2022, 14, (21)
dc.identifier.issn	2072-4292
dc.identifier.issn	2072-4292
dc.identifier.uri	http://hdl.handle.net/10453/166554
dc.description.abstract	Soil erosion caused by water and wind is a complicated natural process that has been accelerated by human activity. It results in increasing areas of land degradation, which further threaten the productive potential of landscapes. Consistent and continuous erosion monitoring will help identify the location, magnitude, and trends of soil erosion. This information can then be used to evaluate the impact of land management practices and inform programs that aim to improve soil conditions. In this study, we applied the Revised Universal Soil Loss Equation (RUSLE) and the Revised Wind Erosion Equation (RWEQ) to simulate water and wind erosion dynamics. With the emerging earth observation big data, we estimated the monthly and annual water erosion (with a resolution of 90 m) and wind erosion (at 1 km) from 2001 to 2020. We evaluated the performance of three gridded precipitation products (SILO, GPM, and TRMM) for monthly rainfall erosivity estimation using ground-based rainfall. For model validation, water erosion products were compared with existing products and wind erosion results were verified with observations. The datasets we developed are particularly useful for identifying finer-scale erosion dynamics, where more sustainable land management practices should be encouraged.
dc.language	English
dc.publisher	MDPI
dc.relation.ispartof	Remote Sensing
dc.relation.isbasedon	10.3390/rs14215437
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	0203 Classical Physics, 0406 Physical Geography and Environmental Geoscience, 0909 Geomatic Engineering
dc.title	Dynamic Modelling of Water and Wind Erosion in Australia over the Past Two Decades
dc.type	Journal Article
utslib.citation.volume	14
utslib.for	0203 Classical Physics
utslib.for	0406 Physical Geography and Environmental Geoscience
utslib.for	0909 Geomatic Engineering
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Life Sciences
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Mathematical and Physical Sciences
utslib.copyright.status	open_access	*
dc.date.updated	2023-02-28T04:18:02Z
pubs.issue	21
pubs.publication-status	Published
pubs.volume	14
utslib.citation.issue	21

Abstract:

Soil erosion caused by water and wind is a complicated natural process that has been accelerated by human activity. It results in increasing areas of land degradation, which further threaten the productive potential of landscapes. Consistent and continuous erosion monitoring will help identify the location, magnitude, and trends of soil erosion. This information can then be used to evaluate the impact of land management practices and inform programs that aim to improve soil conditions. In this study, we applied the Revised Universal Soil Loss Equation (RUSLE) and the Revised Wind Erosion Equation (RWEQ) to simulate water and wind erosion dynamics. With the emerging earth observation big data, we estimated the monthly and annual water erosion (with a resolution of 90 m) and wind erosion (at 1 km) from 2001 to 2020. We evaluated the performance of three gridded precipitation products (SILO, GPM, and TRMM) for monthly rainfall erosivity estimation using ground-based rainfall. For model validation, water erosion products were compared with existing products and wind erosion results were verified with observations. The datasets we developed are particularly useful for identifying finer-scale erosion dynamics, where more sustainable land management practices should be encouraged.

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http://hdl.handle.net/10453/166554