Effects of vegetation cover and slope on soil erosion in the Eastern Chinese Loess Plateau under different rainfall regimes

Author:

Sun Congjian1,Hou Huixin1,Chen Wei1

Affiliation:

1. School of Geographical Science, Shanxi Normal University, Linfen, China

Abstract

Soil erosion is a critical environmental problem of the Chinese Loess Plateau (CLP). The effects of vegetation cover on soil erosion reduction under different rainfall types are not well understood especially in the eastern Chinese Loess Plateau (ECLP). In this study, we monitored runoff and sediment yield at the Fengjiagou water and soil conservation station with five types of vegetation cover (arbor trees (ARC), shrubs (SHC), arable (ABC), natural vegetation (NVC), and artificial grass (APC)) and three slope gradients (10°, 15°, and 20°) in the ECLP. Based on long-term monitoring data, five rainfall types were classified by the maximum 30 min rainfall intensity (I30). We also quantitatively revealed the interactive effects of different types precipitation, vegetation cover and slope gradients on regional soil erosion. The results showed that (1) The RII (13 times) and RIII (eight times) type are the most threatening erosive rainfall in this region. (2) The ARC and SHC type were most beneficial for soil and water conservation in the ECLP; The APC and ABC are not conductive to the prevention of regional soil erosion. (3) Runoff and sediment yields increased with the slope gradient. The farmland is vulnerable to soil erosion when the slope gradient exceeds 10°. The results of this study can improve the understanding of regional soil erosion processes on the ECLP and provide useful information for managing regional water and land resources.

Funder

Research Project Supported by Shanxi Scholarship Council of China

Fund Program for the Scientific Activities of Selected Returned Overseas Professional in Shanxi Province

Publisher

PeerJ

Subject

General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

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