Although vegetation restoration plays an important role in the management of surface runoff and soil erosion, the large-scale restoration of vegetation can increase water consumption and reduce surface water resources, thus affecting the health of river ecosystems. Therefore, vegetation restoration should aim to achieve a vegetation landscape pattern that optimizes protection of soil resources while limiting water consumption. This study established field runoff plots with different landscape patch types, including bare land, S-road patches, strip patches, grid patches, and random patches, as well as different quantities patches of 5, 10, 15, and 20. An artificial rainfall experiment was conducted to determine the effect of different vegetation patches in reducing runoff and sediment, and the relationship between the types and number of vegetation patches and hydrodynamic parameters. The results showed that the runoff yields of the four vegetation patch types decreased by 16.1–48.7% compared with that of bare land, whereas sediment yields decreased by 42.1–86.5%. In addition, the resistance coefficients of the poorly connected patch patterns, including strip patches, grid patches, and random patches, ranged between 0.2–1.17 times higher than that of the well-connected S-road patch pattern, and the stream power decreased by 33.3–50.7%. Under a set vegetation coverage rate, an increase in the number of vegetation patches resulted in a significant reduction in runoff velocity, runoff yield, and sediment yield, increases in surface roughness and flow resistance, and reductions in runoff shear force and stream power. Besides, the sensitivity of soil to erosion decreased with an increasing number of the patch in the vegetation landscape, whereas the sensitivities of patch combinations with poor connectivity were lower than those with good connectivity. The results of this study highlight the importance of vegetation patch type and quantity for control of soil erosion.

Soil erosion risk assessment is an essential foundation for the planning and implementation of soil and water conservation projects. The commonality among existing studies is that they considered different indicators (e.g., rainfall and slope) in order to determine the soil erosion risk; however, the majority of studies in China neglect one important indicator, namely the slope aspect. It is widely accepted that the vegetation and distribution of rainfall differs according to the different slope aspects (such as sunny slope and shady slope) and these attributes will accordingly influence the soil erosion. Thus, existing studies neglecting this indicator cannot reflect the soil erosion well. To address this problem, a flexible soil erosion risk assessment method that supports decision makers in identifying priority areas in soil and water conservation planning was developed in the present study. Firstly, in order to verify the impact of the slope aspect on soil erosion, field investigations were conducted, and its impact on the characteristics of the community in the study area was analyzed. Secondly, six assessment indicators were selected, including slope gradient, precipitation, NDVI, land use, soil texture and slope aspect. Next, a developed multi-criteria decision analysis (MCDA) method based on the Choquet integral was adopted to assess the soil erosion risk. The MCDA method, combining objective data with subjective assessment based on Choquet integral, could solve the weight problem encountered when using the quantitative method. The parameters required can be modified according to the soil erosion types, assessment scales, and data availability. The synergistic and inhibitory effects among the soil erosion parameters were also considered in the assessment. Finally, the soil erosion risk results in the Xinshui River watershed revealed that more attention should be paid to the slope of farmland and grassland during the planning and management of soil and water conservation projects. The methodology used in the current study can support decision makers in planning and implementing soil and water conservation measures in regions with different erosion types.

Forests make an important contribution to the global carbon cycle and climate regulation. Caijiachuan watershed false acacia (Robinia pseudoacacia Linn.) plantation forests have been created for 30 years, but a series of problems have arisen due to the irrationality of the density involved at that time. To precisely assess the contribution of R. pseudoacacia plantations with different densities to this cycle, we measured the diameter at breast height (DBH), tree height (H), biomass, and carbon stocks in trees, shrubs, herbs, litter, and soil across different density ranges, denoted as D1 = 900–1400, D2 = 1401–1900, D3 = 1901–2400, D4 = 2401–2900, and D5 = 2901–3400 trees ha⁻¹. In order to achieve the purpose of accurately estimating the biomass, carbon stocks and the contribution rate of each part in different densities of R. pseudoacacia plantations were measured. The results are as follows: (1) Both DBH and H decreased with increasing density, and field surveys were much more difficult and less accurate for H than DBH. Based on the two allometric growth models, it was found that the determination coefficient of the biomass model that incorporated both H and DBH (0.90) closely resembled that of the model using only DBH (0.89), with an error margin of only 0.04%. (2) At the sample scale, stand density significantly affected R. pseudoacacia stem biomass and total biomass. At the individual plant scale, stand density significantly affected R. pseudoacacia organ biomass. Increasing stand densities promoted the accumulation of vegetation biomass within the sample plot but did not improve the growth of individual R. pseudoacacia trees. The stem biomass constituted the majority of the total R. pseudoacacia biomass (58.25%–60.62%); the total R. pseudoacacia biomass represented a significant portion of the vegetation biomass (93.02%–97.37%). (3) The total carbon stock in the sample plots tended to increase with increasing stand density, indicating a positive correlation between density and the carbon stock of the whole plantation forest ecosystem. Hence, in future R. pseudoacacia plantations, appropriate densities should be selected based on specific objectives. For wood utilization, a planting density of 900–1400 trees ha⁻¹ should be controlled. For carbon fixation, an initial planting density of 2900–3400 trees ha⁻¹ should be selected for R. pseudoacacia. This study provides theoretical support for local forest management and how to better sequester carbon.