Abstract

Physical soil crust (PSC), a key component of surface soil structure, exists extensively in loess areas. PSC is considered to have a significant effect on soil detachment processes. However, the long-term effects and the corresponding mechanisms of PSC on soil detachment by overland flow are still not well understood, especially in natural environments. To investigate temporal variation in soil erosion resistance and the underlying factors during PSC formation, an 8 × 8-m soil plot was exposed to natural conditions in the Loess Plateau over a 524-day period spanning two rainy seasons and a winter between them. A flume test was conducted to determine soil detachment capacity (Dc) under six designed flow shear stress levels (5.66–22.11 Pa) using crusted (SC) and non-crusted (NSC) soil samples at different PSC development stages. Subsequently, two soil erosion resistance parameters, rill erodibility (Kr) and critical shear stress (τc), were calculated. Over time, in the SC and NSC treatments, Kr decreased from 0.516 to 0.120 s m−1 and 0.521 to 0.223 s m−1, respectively, while τc increased from 0.49 to 4.42 Pa and 0.26–2.46 Pa, respectively. Variation in soil erosion resistance was rapid in the first one to two months, and then slowed down, with slight fluctuations afterwards. In the SC treatment, Kr was 42% lower and τc was 67% greater than those in the NSC treatment. Soil properties changed greatly for both treatments. SCT increased from 0 to 7.09 mm in the SC treatment. Coh increased from 2.91 to 9.04 kPa and 3.01–4.78 kPa in SC and NSC treatments, respectively. Both soil erosion resistance parameters could be well predicted by SCT and Coh in the SC treatment (R2 ≥ 0.82), while their best predictor was Coh in the NSC treatment (R2 ≥ 0.90). The results demonstrate that PSC formation enhances soil erosion resistance in the soil detachment process in the loess region under natural conditions. Our study revealed the important role and complexity of PSC in the process of soil erosion, and provided theoretical and data support for accurate understanding and prediction of soil erosion.

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