FU T G, GAO Y, LIU L L, GAO H, QI F, WANG F, LIU J T. Factors influencing soil water content during dry period in the middle part of the Taihang Mountain[J]. Chinese Journal of Eco-Agriculture, 2022, 30(7): 1054−1063. DOI: 10.12357/cjea.20210793
Citation: FU T G, GAO Y, LIU L L, GAO H, QI F, WANG F, LIU J T. Factors influencing soil water content during dry period in the middle part of the Taihang Mountain[J]. Chinese Journal of Eco-Agriculture, 2022, 30(7): 1054−1063. DOI: 10.12357/cjea.20210793

Factors influencing soil water content during dry period in the middle part of the Taihang Mountain

  • Taihang Mountain is an important natural boundary between the second and third steps in China. The elevation of this mountains decreases drastically from west to east. Owing to the complex environment in this transition zone, the spatial pattern of and the factors influencing soil water content (SWC) are complex and unclear. This limits further understanding of the soil hydrological processes. In this study, two line transects (140 km and 164 km long, respectively) were set in the middle part of the Taihang Mountain, which are 85 km apart. Both disturbed and undisturbed soils were sampled along two line transects during the dry period in the middle part of Taihang Mountain region. Soil water content, bulk density (BD), capillary porosity (CP), non-capillary porosity (NCP), soil organic carbon (SOC), and soil particle composition (sand, silt, and clay contents) were measured. Topographical conditions (including slope gradient, slope aspect, and elevation) and vegetation conditions (including vegetation type, vegetation cover, and litter information) were also investigated for each sampling point. Classical statistical, geostatistical, and structural equation modeling methods were used to study the variation and influencing factors of the SWC in the surface (0–10 cm) and subsurface (10–20 cm) layers along the two line transects in the middle part of the Taihang Mountain. The results showed that the SWC of the surface soil layer was significantly lower than that of the subsurface layer. No significant differences were observed between the two studied line transects. In geostatistical analysis, the most suitable SWC model was a linear model for the surface soil layer, but an exponential model for the subsurface layer. This indicated that random factors played a dominant role, and the influencing factors may be more complex for the surface soil layer. For the subsurface layer, an obvious nugget effect was observed, suggesting the coexistence of random and structural factors. The nugget to sill value of the subsurface layer was 48.01% and 31.62%, respectively, for the two-line transects. This indicated that both line transects showed moderate spatial dependence. Among the considered environmental factors, precipitation and elevation significantly influenced the SWC. Other environmental factors showed no significant effects. Among the studied soil properties, BD significantly influenced the SWC of the surface layer, whereas the CP and clay content significantly influenced the SWC of the subsurface soil layer. Structural equation modeling showed that soil properties were the direct factor, and environmental factors were indirect factors of SWC. Over 80% of the environmental factors acted through the soil properties. These results can be helpful in further understanding the soil water characteristics in the middle part of the Taihang Mountain and provide a scientific basis for studying soil hydrological processes in similar mountainous areas.
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