Articles | Volume 21, issue 3
Research article
10 Mar 2017
Research article |  | 10 Mar 2017

An integrated probabilistic assessment to analyse stochasticity of soil erosion in different restoration vegetation types

Ji Zhou, Bojie Fu, Guangyao Gao, Yihe Lü, and Shuai Wang

Abstract. The stochasticity of soil erosion reflects the variability of soil hydrological response to precipitation in a complex environment. Assessing this stochasticity is important for the conservation of soil and water resources; however, the stochasticity of erosion event in restoration vegetation types in water-limited environment has been little investigated. In this study, we constructed an event-driven framework to quantify the stochasticity of runoff and sediment generation in three typical restoration vegetation types (Armeniaca sibirica (T1), Spiraea pubescens (T2) and Artemisia copria (T3)) in closed runoff plots over five rainy seasons in the Loess Plateau of China. The results indicate that, under the same rainfall condition, the average probabilities of runoff and sediment in T1 (3.8 and 1.6 %) and T3 (5.6 and 4.4 %) were lowest and highest, respectively. The binomial and Poisson probabilistic model are two effective ways to simulate the frequency distributions of times of erosion events occurring in all restoration vegetation types. The Bayes model indicated that relatively longer-duration and stronger-intensity rainfall events respectively become the main probabilistic contributors to the stochasticity of an erosion event occurring in T1 and T3. Logistic regression modelling highlighted that the higher-grade rainfall intensity and canopy structure were the two most important factors to respectively improve and restrain the probability of stochastic erosion generation in all restoration vegetation types. The Bayes, binomial, Poisson and logistic regression models constituted an integrated probabilistic assessment to systematically simulate and evaluate soil erosion stochasticity. This should prove to be an innovative and important complement in understanding soil erosion from the stochasticity viewpoint, and also provide an alternative to assess the efficacy of ecological restoration in conserving soil and water resources in a semi-arid environment.

Short summary
We constructed an integrated probabilistic assessment to describe, simulate and evaluate the stochasticity of soil erosion in restoration vegetation in the Loess Plateau. We found that morphological structures in vegetation are the source of different stochasticities of soil erosion, and proved that the Poisson model is fit for predicting erosion stochasticity. This assessment could be an important complement to develop restoration strategies to improve understanding of stochasticity of erosion.