This study assessed temporal variation in soil erosion rates in response to energy consumption of flow (ΔE). It employed an in situ bank gully field flume experiment with upstream catchment areas with bare (BLG) or cultivated land (CLG) that drained down to bare gully headcuts. Water discharge treatments ranged from 30 to 120 L Min−1. Concentrated flow discharge clearly affected bank gully soil erosion rates. Excluding minimal discharge in the CLG upstream catchment area (30 L min−1), a declining power function trend (p ≤ 0.1) was observed with time in soil erosion rates for both BLG and CLG upstream catchment areas and downstream gully beds. Non-steady state soil erosion rates were observed after an abrupt collapse along the headcut slope after prolonged scouring treatments. However, as the experiment progressed, ΔE and energy consumption of flow per unit soil loss (ΔEu) exhibited a logarithmic growth trend (p < 0.1) at each BLG and CLG position. Although similar temporal trends in soil erosion and infiltration rates were observed, values clearly differed between BLG and CLG upstream catchment areas. Furthermore, Darcy–Weisbach friction factor (f) values in the CLG upstream catchment area were higher than the corresponding BLG area. In contrast to the BLG upstream catchment area, lower ΔEu and higher soil erosion rates were observed in the CLG upstream catchment area as a result of soil disturbances. This indicated that intensive land use changes accelerate soil erosion rates in upstream catchment areas of bank gullies and increase soil sediment transport to downstream gullies. Accordingly, reducing tillage disturbances and increasing vegetation cover in upstream catchment areas of bank gullies are essential in the dry-hot valley region of Southwest China.
A new spatial consistency quality control method (SRF) based on the spatial regression test (SRT) and random forest (RF) was adapted to identify potential outliers in daily surface temperature observations in this article. For the new method, the SRT method was used to filter the data and the RF method was used to conduct regression. To evaluate the performance of the quality control method, the SRF, SRT and RF methods were applied to a surface temperature dataset with seeded errors from different regions of China from 2005 to 2014. Compared to SRT and RF, the results indicate that the SRF method outperforms the other two methods for the most cases. And the results of the comparison led to the recommendation that the SRF method improves the regression accuracy of traditional spatial consistency quality control methods and reduces the runtime of random forest through data refinement. 相似文献