Spatial Variation Characteristics of Soil Erodibility in the Yingwugou Watershed of the Middle Dan River, China

Xiaojun Liu, Yi Zhang and Peng Li
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Xiaojun Liu: Key Laboratory of Silviculture, Collaborative Innovation Center of Jiangxi Typical Trees Cultivation and Utilization, Forestry College of Jiangxi Agricultural University, Nanchang 330045, China
Yi Zhang: State Key Laboratory of Eco-hydraulics in Northwest Arid Region, Xi’an University of Technology, Xi’an 710048, China
Peng Li: State Key Laboratory of Eco-hydraulics in Northwest Arid Region, Xi’an University of Technology, Xi’an 710048, China

IJERPH, 2020, vol. 17, issue 10, 1-11

Abstract: Knowledge of soil erodibility (k-value) is vital for measuring soil erosion and conservation planning. Through field sampling, laboratory analysis, and geostatistical analysis, the effects of land use type and soil depth on soil erodibility were studied in a typical watershed of China. The spatial distribution of k-value was determined by Kriging interpolation. Results showed that: (1) soil organic carbon (SOC) content in the study aera is 0.09–150.00 g/kg, and the soil is dominated by silt. The soil erodibility k-values obeyed normal distribution, with an average value of 0.032 t·hm 2 ·h/(MJ·mm·hm 2 ) and a medium degree variation. (2) k-values increased with soil depth. The k-values of surface soil (0–10 cm) for the six different vegetation types ranked in the following order: oak forest > peanut field > grassland > pine forest > tea field > corn field. (3) The theoretical semivariogram model of k-values was a spherical model; k-values in the study area gradually decreased from south to north and east to west, with an obvious banding distribution. Human activities have the greatest effect on k-value such that specific corresponding managements are needed. This could provide scientific and technological support for soil and water conservation measures and comprehensive utilization of the resources.

Keywords: soil erodibility; geostatistics; Kriging interpolation; spatial variability; influence factor (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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