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Geoinformatics and water-erosion processes

Geoinformatics and water-erosion processes
Geoinformatics and water-erosion processes
Geomorphologists have commonly published conclusions about soil erosion and water movement based on experimental data obtained at the catchment scale. The underlying assumptions were that there exists little spatial variation in conditions at the hillslope scale (the fundamental unit) and that the catchments are representative of other catchments in the same region. These assumptions are unlikely to be tenable in practice. Indeed, we suggest that there is substantial spatial variation in geomorphological properties even at small distances when observed at fine spatial resolution and that modern geoinformatics approaches can be used to quantify and characterize this variation. This introduction reviews the ten papers that comprise this Special Issue on Studying Water-Erosion Processes with Geoinformatics, drawn from across the geomorphological sciences. The water erosion processes studied in these papers include sediment transport, fluvial processes, slope denudation, landsliding, bank erosion and bank line migration. The findings suggest that innovative measurement and modeling approaches such as GPS measurements, geostatistics, image processing techniques, and physically-based models deliver new data with which to study water erosion processes. These findings involve domains that are associated with fundamental aspects of geomorphology. Hence, there are strong grounds for claiming that geoinformatics can contribute to greater understanding of water erosion processes through characterization of space–time dynamics. We suggest that geomorphologists need to use more geoinformatics to collect more data relating to the outcomes of water erosion processes, to seek out and apply innovative processing methods and, finally, model the data to provide greater understanding of processes and to forecast and explore future scenarios.
DEM, GIS, remote sensing, water erosion
0169-555X
1-4
Svoray, Tal
148011eb-aac4-4311-b76d-9f2fd742fe3e
Atkinson, Peter M.
96e96579-56fe-424d-a21c-17b6eed13b0b
Svoray, Tal
148011eb-aac4-4311-b76d-9f2fd742fe3e
Atkinson, Peter M.
96e96579-56fe-424d-a21c-17b6eed13b0b

Svoray, Tal and Atkinson, Peter M. (2013) Geoinformatics and water-erosion processes. Geomorphology, 183, 1-4. (doi:10.1016/j.geomorph.2012.10.001).

Record type: Article

Abstract

Geomorphologists have commonly published conclusions about soil erosion and water movement based on experimental data obtained at the catchment scale. The underlying assumptions were that there exists little spatial variation in conditions at the hillslope scale (the fundamental unit) and that the catchments are representative of other catchments in the same region. These assumptions are unlikely to be tenable in practice. Indeed, we suggest that there is substantial spatial variation in geomorphological properties even at small distances when observed at fine spatial resolution and that modern geoinformatics approaches can be used to quantify and characterize this variation. This introduction reviews the ten papers that comprise this Special Issue on Studying Water-Erosion Processes with Geoinformatics, drawn from across the geomorphological sciences. The water erosion processes studied in these papers include sediment transport, fluvial processes, slope denudation, landsliding, bank erosion and bank line migration. The findings suggest that innovative measurement and modeling approaches such as GPS measurements, geostatistics, image processing techniques, and physically-based models deliver new data with which to study water erosion processes. These findings involve domains that are associated with fundamental aspects of geomorphology. Hence, there are strong grounds for claiming that geoinformatics can contribute to greater understanding of water erosion processes through characterization of space–time dynamics. We suggest that geomorphologists need to use more geoinformatics to collect more data relating to the outcomes of water erosion processes, to seek out and apply innovative processing methods and, finally, model the data to provide greater understanding of processes and to forecast and explore future scenarios.

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More information

Published date: 1 February 2013
Keywords: DEM, GIS, remote sensing, water erosion
Organisations: Global Env Change & Earth Observation

Identifiers

Local EPrints ID: 357151
URI: http://eprints.soton.ac.uk/id/eprint/357151
ISSN: 0169-555X
PURE UUID: 45b3e041-fdf1-4835-bd0b-c89e1703752e
ORCID for Peter M. Atkinson: ORCID iD orcid.org/0000-0002-5489-6880

Catalogue record

Date deposited: 04 Oct 2013 13:18
Last modified: 15 Mar 2024 02:47

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Contributors

Author: Tal Svoray
Author: Peter M. Atkinson ORCID iD

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