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RESEARCH ARTICLE

Effects of DEM resolutions on LS and hillslope erosion estimation in a burnt landscape

Linxin Shan A B , Xihua Yang https://orcid.org/0000-0002-5990-2186 C D E and Qinggaozi Zhu D
+ Author Affiliations
- Author Affiliations

A Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, Northwest University, Xi’an, Shaanxi 710127, PR China.

B College of Urban and Environmental Science, Northwest University, Xi’an, Shaanxi 710127, PR China.

C New South Wales Office of Environment and Heritage, PO Box 644, Parramatta, NSW 2124, Australia.

D School of Life Sciences, University of Technology Sydney, Australia.

E Corresponding author. Email: xihua.yang@environment.nsw.gov.au

Soil Research 57(7) 797-804 https://doi.org/10.1071/SR19043
Submitted: 21 February 2019  Accepted: 13 May 2019   Published: 3 July 2019

Abstract

The combined slope length and slope steepness factor (LS) is crucial in soil erosion models such as the revised universal soil loss equation (RUSLE), and is often calculated from digital elevation models (DEMs). With high-resolution DEMs becoming increasingly available in recent years, we face considerable challenges in selecting the optimal DEM for erosion modelling. In this paper, we present a case study on LS factor computation using various DEMs at resolutions ranging from 1 to 90 m over a burnt national park in New South Wales, Australia, aiming to assess the effects of DEM resolution on LS and hillslope erosion estimation. The LS was calculated based on RUSLE specifications and incorporated a variable cutoff slope angle that improves the detection of the beginning and the end of each slope length. Results show the trend of an increase in the estimated LS value as the DEM resolution became coarser. We consider 5–10-m DEMs to have optimal resolution because the LS values calculated at this range were closer to the LS values measured at the 12 soil plots over the study area. We also assessed different sampling methods for LS value extraction and statistical analysis. The sampling method based on contributing area was more representative compared with point-based and buffer sampling methods. Findings from this study will be useful for choosing the optimal DEM resolution and sampling method in hillslope erosion modelling.

Additional keywords: sampling scale, slope, slope length, soil erosion, RUSLE.


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