Prevention and control of soil erosion can be represented as one of the most important protocols in the ecological environment. Particularly, the soil and water conservation can be subjected to significant land-use variation in the ecologically fragile regions. Among them, the red soil hilly region of southern China is highly susceptible to soil erosion. The rapid expansion of cash crops (like citrus orchards) has introduced new dynamics to soil erosion and carbon cycling. This study aims to explore the spatiotemporal pattern and driving factors of soil erosion, conservation and carbon sequestration capacity against the citrus orchard expansion. Pingjiang River Basin was also selected as the representative targets in the critical zone of red soil erosion. The data was collected from the multi-temporal remote sensing images, land use/cover data, rainfall records, normalized difference vegetation index (NDVI), topographic data, and soil properties in the years 1995, 2005, 2015, and 2023. The object-based image analysis within eCognition software was utilized to combine with the spatial analysis in ArcGIS. Firstly, the spatiotemporal distribution of the citrus orchard areas was precisely delineated over the basin. Subsequently, the revised universal soil loss equation (RUSLE) model was applied to quantitatively assess the soil erosion dynamics. The key parameters were calculated from the datasets for each time period. According to the erosion assessment, the different land use types were evaluated for the soil conservation and carbon sequestration capacity. Finally, the geographical detector was employed to identify the primary driving factors of the spatiotemporal variations in soil conservation and carbon sequestration over these land use types. The results demonstrate that: 1) The soil erosion in the Pingjiang River Basin exhibited a significant overall decreasing trend over the study period (1995–2023). Specifically, the soil erosion modulus decreased markedly from 904.88 t/(km²·a) in 1995 to 395.30 t/(km²·a) in 2023. The year 2015 was recorded as the lowest average erosion modulus (251.28 t/(km²·a). The micro- and slight erosion grades collectively covered 94.61% of the basin area. There was a dominant shift towards the lower erosion intensities. The severe and very severe erosion grades also displayed a distinct point-like or patchy distribution pattern. Specifically for the citrus orchards, the average erosion modulus also decreased from 781.96 t/(km²·a) in 1995 to 381.54 t/(km²·a) in 2023. It also peaked sharply at 1070.6 t/(km²·a) in 2005 during the initial expansion. However, the localized intensification of the moderate and higher intensity erosion occurred in some orchard areas post-2015. This trend was attributed primarily to the citrus Huanglongbing (HLB) disease outbreaks and anthropogenic disturbances, like orchard abandonment or replanting. 2) Significant disparities existed in the soil conservation and carbon sequestration potential among different land use types. Forest land consistently exhibited the highest total carbon sequestration capacity. But there was the outstanding trend: increasing from 1995 to 2015, followed by a decrease from 2015 to 2023. Cultivated land was ranked second in total sequestration. But there was an inverse temporal trend, compared with the forest land. Furthermore, the shrubland, grassland, water bodies, construction land, and unused land generally demonstrated lower and relatively stable soil carbon content. Overall, the basin was functioned as a net carbon sink in the study periods, with the carbon sequestration in most land types; Nevertheless, the grassland and water bodies shared the minor net carbon losses. Crucially, the citrus orchards displayed a clear temporal evolution in their carbon budget: A net soil carbon loss of 3.8 ×10⁴ t in the establishment phase (1995–2005), followed by significant carbon sequestration of 7.5 × 10⁴ t (2005–2015) and 6.8 ×10⁴ t (2015–2023), as the orchards developed. 3) Factor detector analysis revealed that the vegetation coverage was the dominant explanatory factor for the variations in the soil conservation and carbon sequestration in citrus orchards. Conversely, the slope gradient was emerged as the primary explanatory factor for the variations in the forest, cultivated land, and grassland. The interaction detector indicated that all paired factors exhibited either bi-enhancement or non-linear enhancement interactions. Importantly, the interaction between slope gradient and other factors (especially, vegetation coverage and rainfall erosivity) consistently demonstrated the strongest explanatory power (highest q-values) for the driving changes in the soil conservation and carbon sequestration across all major land use types. Therefore, the future soil and water conservation strategies should prioritize the synergistic effects of the slope conditions, anthropogenic disturbances (like those induced by HLB), and vegetation cover dynamics. Particularly, those aimed enhancing the carbon sink potential. The findings can provide practical references to formulate the targeted strategies for the soil and water loss control, especially for the ecosystem carbon sequestration capacity in the ecologically sensitive red soil hilly basins under agricultural intensification. Effective decision-making on the landscape can also be made on the land-use dynamics and the key driver interactions, especially slope-vegetation coupling.

Non-point source phosphorus (P) loss from farmland is one of the most serious causes of agricultural non-point source pollution. It is very necessary to identify the critical source areas and influence factors for the risk of P loss from farmland in a watershed, in order to prevent non-point source pollution. The objective of this study was to assess the risk of P loss from farmland in China from 2000 to 2020. P index model was also used. Among them, the soil available P content and fertilizer-P application rate were selected as the source factors. The soil-erosion modulus, annual runoff depth, and the normalized differential distance index between farmland and river network were used as the transport factors. Additionally, the GIS technology was then combined to identify the critical source areas of P loss from farmland. Random Forest (RF) was utilized to derive the critical influencing factors on the P loss from farmland in China. Structural Equation Modeling (SEM) was constructed to explore the relationship between the P index and influencing factors. The results show that: 1) The low, medium, high, and very high-risk areas of P loss from 2000 to 2020 accounted for 43.8%, 40.5%, 13.4%, and 2.4% of the total area of farmland, respectively. 2) The annual average percentage of the total area at high and very high risk of P loss from farmland in 2000, 2005, 2010, 2015, and 2020 was ranked in the descending order: the Huaihe River Basin, Yangtze River Basin, Pearl River Basin, Southeast River Basin, Songhua and Liaohe River Basin, Southwest River Basin, Yellow River Basin, Continental River Basin, and Haihe River Basin. 3) The RF results showed that the available P content and normalized differential distance index were the critical influencing factors of the P index, whose importance eigenvalues were 129.53 and 65.12, respectively. The available P content was the critical influencing factor of the P loss from the farmland. 4) SEM images showed that the P index was extremely significantly positively correlated with the source and transport factor indexes. The P index of the 14 selected index factors amounted to 0.62, in which the contribution rates of the source factor and the migration factor to the P index were 0.77 and 0.19, respectively (P<0.001). In conclusion, the findings can provide scientific references for the evaluation of non-point source pollution in farmland. It is of great significance for the decision-making on the prevention and control of agricultural surface pollution.

Based on the research results on drought in the Yangtze River Basin, the current research status of drought assessment indicators in the Yangtze River Basin was reviewed from perspectives of meteorological drought, hydrological drought, and agricultural drought, and the spatio-temporal characteristics and causes of drought in the Yangtze River Basin were described. It was pointed out that the current research still faced serious challenges in the accurate identification of regional drought and the interaction of multiple factors. The main directions of drought research in the Yangtze River Basin in the future are put forward, including to improve the comprehensive utilization level of multi-source data and enhance the timeliness and accuracy of drought monitoring, to improve the system of drought monitoring and forecasting and enhance the scientificity and reliability of drought prediction, and to deepen the research on the response of human activities to drought and reveal the interaction mechanism between human activities and natural factors in drought events.