Due to frequent human disturbance and the influence of crop growth and development, the migration of soil organic carbon (SOC) in sloping farmland is considerably different to those in other ecosystems. The impacts of maize over its entire growth period on the SOC loss in sloping farmland on purple soils under different erosion stages were investigated, in 2016. This was undertaken using rainfall simulation tests on 15° slopes with a rainfall intensity of 1.5 mm·min⁻¹, in Sichuan Province, China. In this study, erosion development, fluctuating increasing trends in the surface runoff yield, interflow runoff yield, sediment yield, and dissolved organic carbon (DOC) migration flux were observed. Opposite trends were observed in the DOC mass concentration, total soil organic carbon (TOC) content of the sediment, the SOC content of sediment particle state, the DOC content of the sediment, and the SOC enrichment ratio. The DOC migration flux in the surface runoff and in interflow of the rill erosion stage was 1.39–2.84, 3.22–7.78 times significantly higher than that of the sheet erosion stage at each maize growth stage, respectively (p < 0.05). The average DOC mass concentration in the surface runoff, the total DOC content of the sediment, and the SOC enrichment ratio in the sheet erosion stage increased by 100.58–146.44%, 44.44–126.15%, 141.32–191.26%, respectively, compared with the rill erosion stage. Under the experimental conditions, we found that DOC loss mainly occurred at the seedling and mature stages for maize. We also found that maize growth could promote the production of soil interflow, leading to intense soil loss occurring at the subsurface. Compared with DOC mass concentrations in the surface runoff, there was an increase of 4.90–28.29% in the soil interflow, indicating that soil interflow plays a more important role in DOC loss. The growth of maize could impact formation of surface runoff and interflow, reducing the loss of SOC caused by soil erosion. This study helps to understand the carbon loss process in agricultural production in purple soil areas.

This study examines the spatiotemporal variations of rainfall erosivity in the Hengduan Mountains, known for their rugged terrain and high potential for soil erosion risks, over the past 30 years. Additionally, it investigates the changing trends of rainfall erosivity between 2025 and 2040 under the Sustainable Development Pathway 2–4.5 (SSP2–4.5), using four Global Climate Models (GCMs) based on the Coupled Model Intercomparison Project phase 6 (CMIP6). The results indicate: (1) The annual distribution of rainfall erosivity in the Hengduan Mountains exhibited significant seasonal variations, ranking in the order of summer > autumn > spring > winter on a seasonal scale. (2) Over the past 30 years, there has been a slight decrease in annual precipitation and a corresponding slight increase in rainfall erosivity. Periodic extreme values occur every 6–8 years. (3) Spatially, rainfall erosivity demonstrates a decreasing gradient from southeast to northwest. There is a significant positive correlation between rainfall erosivity and precipitation, while a significant negative correlation exists with elevation in the vertical direction. Furthermore, the northeastern part of the Hengduan Mountains exhibits an increasing trend of rainfall erosivity, while the southern region experiences a decreasing trend. (4) Considering the joint driving forces of increased precipitation and erosive rainfall events, rainfall erosivity is expected to significantly increase in the future, posing a more severe risk of soil erosion in this region.

The Hilbert–Huang transform (HHT) has been used as a powerful tool for analyzing nonlinear and nonstationary time series. Soil loss is controlled by complicated physical processes and thus fluctuates with nonlinearity and nonstationarity over time. In order to further clarify the relationship between rainfall, surface runoff, and sediment yield, this study adopted the HHT to analyze these characteristics through multiple time scales and investigated their relationship through time-dependent intrinsic correlation (TDIC) in the time series. A six-year study (2015–2020) was conducted on sloping farmlands to explore the relationships between soil loss and rainfall in southwest China. Time series of soil loss and rainfall were identified as the relevant characteristics at different time scales based on the method of HHT. Local correlation between the soil loss and runoff was carried out by the method of TDIC. The original time series of the rainfall, runoff, and soil loss were decomposed into eight intrinsic mode functions (IMFs) and a residue by ensemble empirical mode decomposition (EEMD). The residue indicated that the rainfall and runoff increased and then decreased during the maize-growing season from 2015 to 2020, whereas the soil loss gradually decreased. IMF1 and IMF2 accounted for nearly 80% of the temporal variations in rainfall, runoff, and soil loss, indicating that the variables varied the most at short time scales. The TDIC analysis showed that strong and positive correlations between the soil loss, rainfall, and runoff prevailed over the entire time domain at the scales of IMF1 and IMF2, indicating the rapid response of the soil loss to rainfall and runoff at short time scales. Time-varying correlations were observed at the IMF3–IMF5 scales. At the IMF7 scale, an evident switchover in the nature of the correlation was identified during the years 2018 and 2019; this could be related to a sudden rainstorm under low vegetation coverage conditions. The EEMD-based TDIC tool is an effective means to clarify the relationship between soil loss, rainfall, and runoff. Our results provide a better understanding of the relationship between soil loss and rainfall varied with time at multiple time scales. Short-term heavy rainfall and rapid surface runoff are the important factors causing serious soil and water loss on a short time scale in a mountainous region with yellow soil, which is of great significance for the construction of a regional soil erosion prediction model.

Many studies have focused on the impacts of rainfall duration and intensity, while overlooking the role of rainfall patterns on intensive tillage erosion in hilly agricultural landscapes. The objective of this study was to determine the combined effects of rainfall patterns and tillage erosion on surface runoff and soil loss on sloping farmland in the purple soil area of China. Five simulated rainfall patterns (constant, rising, falling, rising–falling, and falling–rising) with the same total precipitation were designed, and the intensive tillage treatment (IT) and no-tillage treatment (NT) were subjected to simulated rainfall using rectangular steel tanks (2 m × 5 m) with a slope of 15°. To analyse the differences in the hydrological characteristics induced by tillage erosion, we calculated the flow velocity (V), Reynolds number (Re), Froude number (Fr), and Darcy–Weisbach resistance coefficient (f). The results indicate that significant differences in surface runoff and sediment yield were found among different rainfall patterns and rainfall stages (p < 0.05). The falling pattern and falling–rising pattern had a shorter time gap between the rainfall initiation and runoff occurrence as well as a larger sediment yield than those of the other rainfall patterns. The value of f varied from 0.30 to 9.05 for the IT and 0.48 to 11.57 for the NT and exhibited an approximately inverse trend to V and Fr over the course of the rainfall events. Compared with the NT, the mean sediment yield rates from the IT increased the dynamic range of 8.34–16.21% among the different rainfall patterns. The net contributions of the IT ranged from 2.77% to 46.39% in terms of surface runoff and 10.14–78.95% in terms of sediment yield on sloping farmland. The surface runoff and sediment yield were positively correlated with rainfall intensity, V, and Fr, but negatively correlated with f irrespective of tillage operation (p < 0.05). The results showed that the tillage erosion effects on soil and water loss were closely related to rainfall patterns in hilly agricultural landscapes. Our study not only sheds light on the mechanism of tillage erosion and rainfall erosion but also provides useful insights for developing tillage water erosion prediction models to evaluate soil and water loss on cultivated hillslopes.

Ensuring the harmonization between urbanization and water environment systems is imperative for fostering sustainable regional development in the future. With urban agglomerations and metropolitan areas increasingly dominating urbanization trends in China, it is crucial to explore the interdependent relationship between urbanization and the water environment. Such exploration holds significant implications for water resource management and the formulation of urbanization policies. This study utilizes a comprehensive index system encompassing urbanization and the water environment. It examines the coupled and coordinated spatial and temporal dynamics of these systems within the Chengdu-Chongqing Urban Agglomeration from 2011 to 2019. This analysis employs the Coupled Coordination Degree model alongside the spatial autocorrelation model. The results show that there is still much room for improving the urbanization development level and the water environment quality. During the study period, a nonlinear and nearly U-shaped evolutionary trajectory was observed between the two systems. The results suggest that there is a progression from basic to more advanced coordination between urbanization and water environment at the city cluster scale. Urbanization appears to generally lag behind the water environment in terms of coordination. At the municipal scale, there is a gradient in which some cities show better coordination compared to others. Spatially, the coupling and coordination of this region exhibited dual-core development characteristics centered around Chengdu and Chongqing. The region is in the transition stage towards a core-type networked and decentralized development mode, which has not yet formed an integrated pattern. This offers a theoretical and technical framework for harmonizing water environments and urbanization in similar regions globally.