Quantitatively figuring out the effects of climate and land-use change on water resources and their components is essential for water resource management. This study investigates the effects of climate and land-use change on blue and green water and their components in the upper Ganjiang River basin from the 1980s to the 2010s by comparing the simulated changes in blue and green water resources by using a Soil and Water Assessment Tool (SWAT) model forced by five climate and land-use scenarios. The results suggest that the blue water flow (BWF) decreased by 86.03 mm year⁻¹, while green water flow (GWF) and green water storage (GWS) increased by 8.61 mm year⁻¹ and 12.51 mm year⁻¹, respectively. The spatial distribution of blue and green water was impacted by climate, wind direction, topography, and elevation. Climate change was the main factor affecting blue and green water resources in the basin; land-use change had strong effects only locally. Precipitation changes significantly amplified the BWF changes. The proportion of surface runoff in BWF was positively correlated with precipitation changes; lateral flow showed the opposite tendency. Higher temperatures resulted in increased GWF and decreased BWF, both of which were most sensitive to temperature increases up to 1 °C. All agricultural land and forestland conversion scenarios resulted in decreased BWF and increased GWF in the watershed. GWS was less affected by climate and land-use change than GWF and BWF, and the trends in GWS were not significant. The study provides a reference for blue and green water resource management in humid areas.

The Gongshui River basin exhibits one of the most serious soil erosion areas in southern China, and has always been the key control area of national soil and water conservation programs. This study used daily precipitation, streamflow, and sediment concentration data collected from 1957 to 2015 from the main hydrological stations of the Gongshui River to investigate streamflow and sediment discharge variations and their responses to precipitation and human activities. The Mann-Kendall and Pettitt’s test were used for trend and change-point detection. The double mass curve (DMC) method was employed to quantify the effects of precipitation change and human activities on hydrological regime shifts. The results showed insignificant trends of both annual precipitation and streamflow for all stations, while the sediment discharge of most stations exhibited significant decreasing trends. Change-point analyses revealed that all hydrologic stations except Mazhou had transition years. The estimation via DMC indicated that after the change point years, there was a rapid reduction in sediment discharge at Hanlinqiao, Fengkeng, Julongtan, Xiashan, and Chawu stations, but not at Mazhou, Ruijin, and Yangxinjian stations. Human activity provided a significantly greater contribution to sediment discharge than precipitation. The evidence clearly indicates that the degree and extension of conservation or destruction measures and the construction of large- and medium-sized reservoirs were the major factors significantly decreasing or increasing annual sediment discharge of the Gongshui River. This work could serve as the basis for decision making regarding river basin water resources management to estimate the effects of anthropogenic impacts on water and sediment discharge variations during the last few decades, thereby guiding adaptation and protection of the water resources of the Gongshui River flowing into the Poyang Lake.

Active nitrogen loss mainly includes ammonia (NH₃) volatilization, nitrous oxide (N₂O) emission, NO₃⁻-N and NH₄⁺-N deep leakage (N leaching), and NO₃⁻-N and NH₄⁺-N surface runoff (N runoff), resulting in serious environmental problems. To analyze the characteristics of active nitrogen loss in the four pathways on sloped farmland under conventional fertilization, six lysimeters with a slope of 8° were used. Losses due to NH₃ volatilization, N₂O emission, N leaching, and N runoff were investigated after urea application on a peanut field with red soil in China during the growing season from 2017–2018. Results reveal that at conventional nitrogen levels of 150 and 172 kg hm⁻², the total active nitrogen loss caused by fertilization accounting for the total nitrogen applied was 5.57% and 14.21%, respectively, with the N₂O emission coefficients of 0.18% and 0.10%, respectively; the NH₃ volatilization coefficients of 2.24% and 0.31%, respectively; the N leakage loss rates of 3.07% and 10.50%, respectively; and the N runoff loss rates of 0.08% and 3.30%, respectively. The dry year was dominated by leaching and NH₃ volatilization, while the wet year was dominated by leaching and runoff; the base fertilizer period was dominated by leakage, while the topdressing period was dominated by leakage and runoff, which suggests that the loss of active nitrogen in the soil-peanut system on a sloped red soil was mainly affected by rainfall and fertilization methods. Taken together, reasonable fertilization management and soil and water conservation measures appear to be effective in minimizing the loss of active nitrogen from nitrogen fertilizer.

Landscape patterns are a result of the combined action of natural and social factors. Quantifying the relationships between landscape pattern changes, soil erosion, and sediment yield in river basins can provide regulators with a foundation for decision-making. Many studies have investigated how land-use changes and the resulting landscape patterns affect soil erosion in river basins. However, studies examining the effects of terrain, rainfall, soil erodibility, and vegetation cover factors on soil erosion and sediment yield from a landscape pattern perspective remain limited. In this paper, the upper Ganjiang Basin was used as the study area, and the amount of soil erosion and the amount of sediment yield in this basin were first simulated using a hydrological model. The simulated values were then validated. On this basis, new landscape metrics were established through the addition of factors from the revised universal soil loss equation to the land-use pattern. Five combinations of landscape metrics were chosen, and the interactions between the landscape metrics in each combination and their effects on soil erosion and sediment yield in the river basin were examined. The results showed that there were highly similar correlations between the area metrics, between the fragmentation metrics, between the spatial structure metrics, and between the evenness metrics across all the combinations, while the correlations between the shape metrics in Combination 1 (only land use in each year) differed notably from those in the other combinations. The new landscape indicator established based on Combination 4, which integrated the land-use pattern and the terrain, soil erodibility, and rainfall erosivity factors, were the most significantly correlated with the soil erosion and sediment yield of the river basin. Finally, partial least-squares regression models for the soil erosion and sediment yield of the river basin were established based on the five landscape metrics with the highest variable importance in projection scores selected from Combination 4. The results of this study provide a simple approach for quantitatively assessing soil erosion in other river basins for which detailed observation data are lacking.

Rainfall is an important factor that causes riverine flow and sediment transport, and extreme rainfall has a particularly significant effect on the fluctuations of riverine flow and sediment load. Based on the daily rainfall from 1990 to 2020, in the upper watershed of the Lianjiang River, which is one of the source tributaries of China’s largest freshwater lake (Poyang Lake), the 95th percentile method and minimum event interval time were employed to identify extreme rainfall events. Mann–Kendall test was used to check for abrupt changes in annual rainfall, riverine flow discharge, and riverine sediment loads, and to identify abrupt-change years; thus, different periods were divided via the abrupt change years. Multiple linear regression was applied to explore the lag effect of riverine flow-discharge and sediment-load response to antecedent rainfall, with different cumulative durations for each period. The results of the study indicated that (1) the expansion of garden land in 1995 caused a significant and abrupt change in sediment load. (2) Extreme rainfall events had a greater impact on riverine flow and sediment load as compared to ordinary rainfall. These events were found to explain more variations in riverine flow and sediment load, which led to longer lag times for both riverine flow and sediment transport. (3) The expansion of garden land under extreme rainfall conditions resulted in longer lag times for riverine flow and sediment transport, and reduced the need for antecedent rainfall with a longer pre-event time. Therefore, the analysis of antecedent rainfall and the lag response of riverine flow discharge and sediment load can help in understanding the response mechanism of riverine flow discharge and sediment load for the current era of increasing extreme rainfall. This analysis is crucial for improving the accuracy of simulating riverine flow and sediment under extreme rainfall conditions. Ultimately, it can contribute to effective watershed management during extreme rainfall events.

Farmland N₂O emissions exhibit significant fluctuations in subtropical regions due to notable seasonal rainfall and temperature variations. The dominant factors influencing N₂O emissions in red-soil sloping farmland, which is widely distributed and actively cultivated in the region, remain uncertain. To investigate N₂O emission characteristics of red-soil sloping farmland and responses to meteorological and soil environmental variables and tillage practices, a typical planting system (summer peanut-winter rapeseed rotation system) in southern China was selected. Two common soil micro-environments (conventional tillage, CT, n = 6; and conventional tillage with straw mulching, MT, n = 4) were established within this system, and in situ N₂O emissions were monitored over two consecutive years using the static chamber–gas chromatography method. The N₂O emission peaks across various growing seasons occurred primarily within 1 to 16 days after fertilization. The N₂O emission hotspot periods were observed during the first month following fertilization, accounting for 74.13–91.01% of the total emissions during each growing season. Significant interannual variations in seasonal N₂O cumulative emissions were observed, whereas no significant difference in cumulative N₂O emissions was observed between MT and CT. Changes in weather and soil environment jointly drive the dynamics of N₂O emissions from red soil sloping farmland. Rapeseed-season N₂O emissions were driven mainly by rainfall and air temperature, whereas peanut-season N₂O emissions were also influenced by soil temperature and NO₃⁻-N content at 0–10 cm depths. These findings provide a sound basis for developing eco-agricultural mitigation pathways in subtropical red-soil hilly regions.