Slope length is an important topographic factor for controlling soil erosion. There exists limited knowledge of the interactions of slope length, vegetation restoration, and rainfall intensity on soil erosion. This study investigated the impact of the slope length on soil erosion for different grass coverages and different rainfall intensities via simulated rainfall experiments. The experiments included five rainfall intensity treatments (1, 1.5, 2, 2.5, and 3 mm min⁻¹), four grass cover treatments (0%, 30%, 60%, and 90%), and five slope length treatments (2, 4, 6, 8, and 10 m). The change process of soil loss was significantly different (p < 0.05) for different slope lengths. The trend of soil loss changing with slope length is: under a grass cover of 0 or 30%, the soil erosion increased exponentially with increasing slope length. However, under a grass cover of 60%, the soil erosion rate peaked at a slope length of 8 m, and under a grass cover of 90%, the soil erosion rate peaked at a slope length of 6 m. At rainfall intensities of 1.5–2 mm min⁻¹, the overall soil erosion amount was small. The soil loss increased drastically with slope length when the rainfall intensity exceeded 2 mm min⁻¹. Compared with a slope length of 2 m, longer slope lengths increased the erosion rate by 225–930% under different grass coverages treatments. Regression analysis showed that grass cover and rainfall intensity change the trend of erosion with slope length, and the negative effect of slope length on erosion is strengthened with the increase of grass cover, while this negative effect gradually weakens with the increase of rainfall intensity.

Under global warming, the intensification of the hydrological cycle highlights evapotranspiration (ET) as a key process governing land–atmosphere water and energy exchanges. Understanding the spatiotemporal variability of ET and its driving mechanisms is essential for regional hydrological and ecological studies. Based on MOD16 evapotranspiration products, meteorological data, and multi-source remote sensing datasets, this study systematically analyzed the spatiotemporal characteristics of evapotranspiration (ET) and its driving mechanisms in the Yellow River Basin during 2001–2022 using trend analysis, correlation analysis, and geographical detector methods. Results showed that ET exhibited a significant increasing trend across the YRB (5.29 mm·year⁻¹), with extremely significant increases (p < 0.01) observed in 61.93% of the basin. Among climatic factors, precipitation, temperature, and wind speed exhibited significant increasing trends. Human activities were characterized by a significant increase in NDVI and land-use transitions toward forest and built-up land. Geographical detector results identified NDVI and precipitation as the strongest explanatory factors controlling ET spatial heterogeneity, with distinct driving mechanisms across the upper, middle, and lower reaches. Interaction effects among factors were stronger than individual effects, indicating that the spatial differentiation of ET is jointly controlled by climatic conditions and human activities. These findings empirically characterize the spatial heterogeneity, temporal trends, factor hierarchy, and interaction strength of ET variability at the basin scale and provide basin-scale evidence for understanding hydrological cycle responses under the combined influences of climate change and anthropogenic activities.

Accurate monitoring and assessment of forest disturbance and recovery dynamics are essential for sustainable forest management, particularly in ecological transition zones. This study analyzed forest disturbance and recovery patterns in China’s Funiu Mountains from 1991 to 2020 by integrating the LandTrendr algorithm with space-time cube analysis. Using Landsat time series data and the Geodetector method, we examined both the spatiotemporal characteristics and driving factors of forest change across three periods. The results showed that (1) between 1991 and 2020, the study area experienced 131.19 km² of forest disturbance and 495.88 km² of recovery, with both processes most active during the 1990s; (2) spatiotemporal analysis revealed that both disturbance and recovery patterns were predominantly characterized by cold spots, suggesting relatively stable forest conditions despite localized changes; (3) human activities were the primary drivers of forest disturbance in the early period, while forest recovery was consistently influenced by the combined effects of topographic conditions and precipitation. Additionally, forest fires emerged as an important factor affecting both disturbance and recovery patterns after 2010. These findings enhance our understanding of forest dynamics in transition zones and provide empirical support for regional forest management strategies. The results also highlight the importance of considering both spatial and temporal dimensions when monitoring long-term forest changes.

Rainfall events of sufficient intensity can trigger soil erosion on loess hillslopes. Determining the actual threshold of erosive rainfall events is essential for reducing the workload of soil erosion forecasting and for providing scientific guidance for soil erosion prevention. Based on long-term field observations from runoff plots in representative regions of the Loess Plateau, including Suide, Xifeng, and Tianshui, this study applied an improved regression analysis method to identify rainfall thresholds for soil erosion under different erosion intensities. The variation of rainfall thresholds with rainfall intensity was further examined, and a nonlinear regression approach was used to develop predictive models of rainfall thresholds for soil erosion under different land cover conditions. Rainfall thresholds for slope soil erosion under different land cover types decrease exponentially with increasing rainfall intensity. Influenced by soil texture, rainfall thresholds for soil erosion on woodland, grassland, and bare slopes declined as soil texture became finer, while the rate of decline slowed with increasing rainfall intensity. Soil texture, land cover type, and rainfall characteristics exert significant influences on the effectiveness of vegetation in controlling runoff and soil erosion. These findings provide valuable insights into soil erosion prediction and serve as a reference for soil and water conservation planning.