4.7 Article

Runoff and soil loss from Pinus massoniana forest in southern China after simulated rainfall

Journal

CATENA
Volume 129, Issue -, Pages 1-8

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.catena.2015.02.009

Keywords

Under forest erosion; Pinus massoniana forests; Interrill erosion; Rainfall simulation; Red soil region

Funding

  1. National Natural Science Foundation of China [41101253]
  2. Key Technologies Research and Development Program of China [2011BAD31B04-2]
  3. ISSCAS Innovation Program [ISSASIP1116]

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Secondary forests with little understory vegetation and litter accumulation are facing a serious threat of erosion in the red soil region of southern China. To quantify the soil loss and develop prediction equations, 30 field rainfall simulation experiments were conducted with two rainfall intensities and five slope gradients in a 20-year-old Pinus massoniana forest. The results show that under the higher rainfall intensity, the runoff generation from the forest floor was high, even on gentle slopes. During simulated rainstorms, the initial soil losses increased rapidly and reached the peak value nearly at the same time as the peak runoff. Then soil loss decreased and runoff leveled out. Soil losses were significantly correlated with rainfall intensity, slope steepness and runoff rate. Further regression between soil loss as a dependent variable and runoff coefficient on different slopes verified that there exist interactions between slope and runoff factors in affecting soil loss. Stream power, which reflects the effect of both slope steepness and runoff rate can provide a more precise estimation (R-2 = 0.71) of the soil loss rate than the single factors. Finally, an erosion model composed of rainfall, slope steepness and runoff rate was proved to be able to estimate interrill erosion for the large slope range data set of this study (R-2 = 0.828). Therefore the model was proposed to predict the interrill soil erosion under the forest. The results will help us to understand the influential factors and build models to predict soil loss from forest with little understory vegetation in the red soil region of China. (C) 2015 Elsevier B.V. All rights reserved.

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