DOI: 10.5194/hess-21-1491-2017
Scopus记录号: 2-s2.0-85015209847
论文题名: An integrated probabilistic assessment to analyse stochasticity of soil erosion in different restoration vegetation types
作者: Zhou J ; , Fu B ; , Gao G ; , Lü Y ; , Wang S
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2017
卷: 21, 期: 3 起始页码: 1491
结束页码: 1514
语种: 英语
Scopus关键词: Bayesian networks
; Bins
; Erosion
; Poisson distribution
; Probability distributions
; Rain
; Regression analysis
; Restoration
; Runoff
; Soils
; Stochastic systems
; Vegetation
; Water conservation
; Water resources
; Ecological restoration
; Frequency distributions
; Loess plateau of chinas
; Logistic regression models
; Probabilistic assessments
; Probabilistic modeling
; Runoff and sediment generation
; Semi-arid environments
; Soil conservation
; environmental restoration
; hydrological response
; integrated approach
; precipitation intensity
; probability
; restoration ecology
; runoff
; soil erosion
; stochasticity
; vegetation cover
; China
; Loess Plateau
; Artemisia
; Spiraea
英文摘要: 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 1.6ĝ€%) and T3 (5.6 and 4.4ĝ€%) 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. © Author(s) 2017. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79225
Appears in Collections: 气候变化事实与影响
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作者单位: State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Science, Chinese Academy of Science, Beijing, China; University of Chinese Academy of Sciences, Beijing, China
Recommended Citation:
Zhou J,, Fu B,, Gao G,et al. An integrated probabilistic assessment to analyse stochasticity of soil erosion in different restoration vegetation types[J]. Hydrology and Earth System Sciences,2017-01-01,21(3)