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Application of 3D Laser Image Scanning Technology and Cellular Automata Model in the Prediction of the Dynamic Process of Rill Erosion

Authors :
Song Li
Qiqi Li
Jian Chen
Yu Han
Source :
Remote Sensing, Vol 13, Iss 13, p 2586 (2021)
Publication Year :
2021
Publisher :
MDPI AG, 2021.

Abstract

Black soil areas are strongly affected by rill erosion due to the geomorphic characteristics of flood plains and heavy rainfall. To study the problem of rill erosion in black soil areas and achieve ecological restoration, based on the method of artificially simulated rainfall, the effects of rainfall intensity and slope on the characteristics of flow and sand production on the slope surface of black soil areas were studied, and the erosion pattern of the slope surface after rainfall was monitored by a 3D laser scanner to analyze the erosion of the soil on the slope surface. The slope erosion model was constructed on the basis of the cellular automata (CA) method, and the results of the model’s operation were compared with actual rainfall measurement results to deepen research on the slope erosion mechanism in black soil areas. By analyzing the slope erosion pattern after rainfall, it was found that the surface area and erosion volume of serious slope erosion areas increased with increases in slope gradient. Based on the physical model test results combined with the CA model to simulate flow and sand production on bare slopes under different rainfall intensities, comparison showed that the CA model can accurately simulate flow and sand production on a slope where the Ens coefficient of the flow production rate is between 0.70 and 0.97, thus theoretically verifying the reliability of the model, and on this basis, the erosion pattern of the slope after rainfall was predicted to explore the evolution and development law of erosion.

Details

Language :
English
ISSN :
20724292
Volume :
13
Issue :
13
Database :
Directory of Open Access Journals
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
edsdoj.9277929139394d95b131c4905982f52e
Document Type :
article
Full Text :
https://doi.org/10.3390/rs13132586