The study area is located in Keshan County, Heilongjiang Province (125°07’40”E -125°37’30”E, 48°11’15”N-48°24’07”N), situated at the western foot of the Xiao Hinggan Mountains and the northeastern part of the Songnen Plain, characterized by a hilly and rolling terrain. The total area is approximately 363,200 hectares. This region has a cold-temperate subhumid monsoon climate, with an average annual temperature of 1.3°C and an annual precipitation of around 500 mm, mostly concentrated in summer and autumn. The main land use type in this area is farmland, accounting for about 80.60% of the total area, followed by forestland (approximately 6.43%) and natural grassland (approximately 9.86%). The dominant soil type in this region is black soil, and the soil texture is silty clay loam.

Three land-use types were selected as the research objects in the study. Specifically, natural grassland represents the earliest documented land use type in the black soil region of Northeast China, with no direct human disturbance, and its main dominant species are Artemisia annua Linn and Carex spp. The farmland was converted from natural grassland and used for food crop cultivation, with maize as the primary crop. The artificial Pinus sylvestris plantation had a prior cultivation history; following this, Pinus sylvestris was artificially planted, and it has now developed into a mature forest with a stand age of 30 years.

For each land-use type, three quadrats (20 m×20 m) were randomly established, with three sampling points arranged along the diagonal of each quadrat. After removing the 0–5 cm thick layer of undecomposed litter, cutting ring and aluminum box samples were collected at each sampling point to determine soil bulk density, soil moisture content, and total porosity. To ensure the representativeness of soil chemical properties and minimize microscale spatial heterogeneity, a composite soil sample was prepared for each sampling point (along the diagonal of each quadrat) prior to chemical analysis. Subsequently, 500 g of undisturbed soil was collected from each sampling point to measure the mass percentage of soil aggregates, soil mechanical composition, soil pH, soil organic matter content, soil total phosphorus content, and soil total nitrogen content. Furthermore, surface-layer undisturbed soil was collected using an undisturbed soil sampler (diameter 16 cm × height 6 cm) at each sampling point for the determination of soil anti-scourability. After intact soil samples were transported to the laboratory, they were manually broken along the natural soil texture into clods with a diameter of less than 1 mm. Following air-drying, the wet-sieving method was adopted to determine the particle size distribution of soil aggregates (28). The clay content is 43.04 ± 0.26%, the silt content is 50.21 ± 0.60%, the sand content is 6.75 ± 0.68%. The basic information of the study plots is presented in Table 1.

Soil bulk density, soil moisture content, total porosity, and soil aggregates were determined by conventional methods. Soil mechanical composition was measured via the pipette method. Soil pH was determined using the potentiometric method. Soil organic carbon content and total nitrogen content were analyzed with an elemental analyzer. Soil total phosphorus content was determined by the sulfuric acid-perchloric acid digestion-molybdenum antimony anti-colorimetric method.

After the soil anti-scouribility test, the soil clods were repeatedly rinsed through a fine sieve mesh (pore size 0.25 mm) to obtain clean plant roots, which were subsequently scanned with a root scanner and then analyzed using a root analysis system (EPSON LA 2400; 29) according to four root diameter classes (0-0.5 mm, 0.5-1.0 mm, 1.0-1.5 mm, and 1.5-2.0 mm) to acquire key plant root parameters including root length, root surface area, and root volume. Specifically, root length density (RLD) refers to the root length contained per unit volume of soil and can reflect the degree of root penetration and entanglement in the soil, root surface area density (RSD) is the root surface area per unit volume of soil and reflects the closeness of the root-soil interface, and root volume density (RVD) reflects the space occupied by plant roots (22), all of which (RLD, RSD, and RVD) were computed using Equations 1–3.

Where L is the root length (cm); S is the root surface area (cm²); V is the root volume (cm³); D is the volume of the sampler (cm³).

The runoff scouring device is composed of a scouring tank, a flow-stabilizing tank, and an upper water supply device (Figure 1). The scouring tank has a dimension of 126 cm (length) × 20 cm (width), and a cylindrical soil tank with a diameter of 16 cm and a height of 6 cm is embedded in the lower half, 10 cm above the bottom, for observing the erosion process. The flow-stabilizing tank measures 20 cm (length) × 10 cm (width) × 16 cm (height), and a flow-retarding porous plate is installed in the middle, which mainly functions to maintain the stability of water flow. The water supply device consists of a water supply pipe, a constant head tank, an overflow pipe, and a connecting water pipe.

Prior to the scouring test, the soil samples were placed in a flat-bottomed water basin with the water level not exceeding the upper edge of the sampler, and soaked for 24 h to achieve capillary water saturation; subsequently, the saturated undisturbed soil was placed on an iron stand for 8 h to remove gravitational water. The test parameters were set as follows: the scouring slope was fixed at 6°; the scouring discharge (unit flow rate) was calculated based on the maximum runoff generated by local standard runoff plots (20 m×5 m), determined to be 30 L/min; the scouring duration was set to 15 min, as preliminary tests confirmed that runoff sediment yield could reach a stable state within this period. During the scouring test, runoff-sediment samples were collected every 1 min with sampling buckets for the first 3 min after runoff initiation, and then every 2 min thereafter, totaling 9 samples. After the test, all sampling buckets were allowed to stand for clarification; once the sediment was completely settled, the supernatant was discarded, and the remaining sediment-water mixture was transferred to iron boxes. These boxes were dried in an oven at 105°C for 8 h to determine the dry mass of sediment (g), which was used to calculate the soil anti-scourability coefficient (AS). Defined as the volume of water required to erode 1 g of soil (unit: L/g), a higher AS value indicates stronger soil anti-scourability (30), and the specific calculation was performed using Equation 4.

Where AS is the soil anti-scouring coefficient (L/g); f is the flow discharge (L/min); t is the scouring duration (min); w is the dry mass of sediment (g).

Excel and Origin 2021 software were used for empirical equation fitting and data processing, while SPSS 21.0 was employed to perform correlation analysis and regression analysis on the data. Both the soil anti-scourability coefficient of different land-use types (Figure 2) and the correlation between soil physical and chemical properties and soil anti-scourability coefficient (Figure 3) were based on a sample size of n = 27, and all data followed a normal distribution.

The soil physical and chemical properties under different land use types are as shown in Table 2. The soil bulk density of natural grassland was the smallest, while that of farmland was the largest, which is 1.781 and 1.199 times higher than that of natural grassland and artificial forest, respectively (P < 0.05). Among the three land-use types, the soil moisture content of natural grassland was the highest, reaching 70.837%, which was 3.308 and 2.914 times that of the artificial forestland and farmland, respectively, with significant differences from the other two land-use types (P < 0.05). The total porosity of natural grassland was significantly higher than that of the other two land-use types (P < 0.05), being 1.215 and 1.240 times that of the artificial forestland and farmland, respectively. Among the three land-use types, the mechanical composition was dominated by silt, with contents ranging from 50.207% to 60.227%, followed by clay and sand. As shown in Table 2, the soil texture of natural grassland and the artificial forestland was silty clay loam, while that of cultivated land was silty clay.

Overall, the soil pH of the three land-use types was weakly acidic, among which farmland had the highest pH value and the artificial forestland had the lowest. For soil organic matter (SOM) content and total nitrogen (TN) content across the three land-use types, both ranked in the order of natural grassland > the artificial forestland > farmland. Specifically, the SOM content of natural grassland was 2.146 and 2.632 times that of the artificial forestland and farmland, respectively, while its TN content was 2.107 and 2.636 times that of the two land-use types mentioned above, respectively. The total phosphorus (TP) content of the three land-use types was in the order of natural grassland > farmland > the artificial forestland, with the TP content of natural grassland being 1.239 and 1.093 times that of the artificial forestland and farmland, respectively.

The variations of soil root geometric characteristic parameters under different land-use types are shown in Table 3. Specifically, the root length density (RLD), root surface area density (RSD), and root volume density (RVD) of natural grassland all followed the order of 0~0.5 mm > 0.5~1 mm > 1~1.5 mm > 1.5~2 mm. Among these, the RLD of the 0~0.5 mm diameter class was significantly different from that of other diameter classes (P < 0.05), while no significant differences were observed in RSD and RVD among the four diameter classes. The variations of root geometric characteristic parameters in the artificial forestland and farmland were consistent with those in natural grassland. For all four diameter classes, the RLD, RSD, and RVD of natural grassland were significantly higher than those of the artificial forestland and farmland (P < 0.05).

Furthermore, under three land-use types, for fine roots in the 0~0.5 mm diameter class, their root length density (RLD) accounted for 82.906%~89.945% of the total root RLD, root surface area density (RSD) for 55.414%~69.595% of the total RSD, and root volume density (RVD) for 35.714%~42.857% of the total RVD. For fine roots in the 0~1 mm diameter class, their RLD accounted for 96.764%~98.700% of the total RLD, RSD for 85.987%~93.216% of the total RSD, and RVD for 71.429%~85.714% of the total RVD. Thus, fine roots in the 0~1 mm diameter class constituted the dominant component of the root system.

The soil loss rates of different land-use types are shown in Figure 4. Overall, the soil loss rate of natural grassland was 1.947 g/min during the scouring time of 0~1 min, decreased rapidly to a lower level during 1~2 min, and tended to stabilize after 6 min of scouring. For the artificial forestland, the soil loss rate was 4.421 g/min during 0~1 min, dropped sharply during 1~2 min, and became stable after 10 min of scouring. As for forestland, the soil loss rate reached 25.249 g/min during 0~1 min, decreased rapidly to only 2.042 g/min during 1~2 min, and stabilized after 2 min of scouring. In summary, the soil loss rate of all three land-use types peaked during the 0~1 min scouring time. Among them, cultivated land had the highest soil loss rate, which was 12.968 and 5.711 times that of natural grassland and the artificial forestland, respectively. Additionally, with the increase of scouring time, the soil loss rates of the three land-use types gradually tended to stabilize.

As shown in Figure 2, the soil anti-scourability coefficients of natural grassland and the artificial forestland were both higher than that of farmland, with significant differences from farmland (P < 0.05). Specifically, the anti-scourability coefficient of natural grassland was 152.498 L/g, which was 117.487 times that of farmland; the anti-scourability coefficient of the artificial forestland was 136.598 L/g, being 105.237 times that of farmland.

As revealed by the correlation analysis between soil physical and chemical properties and soil anti-scourability coefficient under the three land-use types (Figure 3), soil silt content showed an extremely significant positive correlation with soil anti-scourability coefficient (P < 0.01), while soil sand content and bulk density exhibited an extremely significant negative correlation with the soil anti-scourability coefficient (P < 0.01). Soil pH was significantly negatively correlated with soil anti-scourability coefficient (P < 0.05), and soil moisture content, total porosity, organic matter content, and total nitrogen (TN) content were significantly positively correlated with the soil anti-scourability coefficient (P < 0.05). No significant correlation was observed between soil clay content, total phosphorus (TP) content and soil anti-scourability coefficient. The order of correlation strength from strongest to weakest was: silt content > sand content > soil bulk density > total nitrogen content > organic matter content > total porosity > soil moisture content > soil pH.

As revealed by the correlation analysis between root characteristic parameters and soil anti-scourability coefficient under the three land-use types (Figure 5), the root length density (RLD), root surface area density (RSD), and root volume density (RVD) of fine roots in the 0.5~1 mm, 1~1.5 mm, and 1.5~2 mm diameter classes showed an extremely significant positive correlation with the soil anti-scourability coefficient (P<0.01). In contrast, the RLD, RSD, and RVD of fine roots in the 0~0.5 mm diameter class exhibited a significantly positive correlation with the soil anti-scourability coefficient (P<0.05). In terms of correlation strength, the order from strongest to weakest was: RLD (1.5-2) > RSD_(1.5-2) > RVD_(1.5-2) > RVD_(1-1.5) > RSD_(1-1.5) > RLD_(1-1.5) > RVD_(0.5-1) > RSD_(0.5-1) > RLD_(0.5-1) > RVD_(0-0.5) > RSD_(0-0.5) > RLD_(0-0.5).

Soil bulk density and porosity are the main indicators for evaluating soil compaction. The higher the soil compaction, the less likely the soil is to be eroded and transported, and the stronger its anti-scourability. Among different land-use types, soil bulk density followed the order of farmland > the artificial forestland > natural grassland, while total porosity showed the opposite trend (Figure 2). One reason is the minimal human disturbance (5). In addition, plant roots exert network consolidation and biochemical effects, which promote the formation of soil aggregates (29, 31). These aggregates further loosen the soil structure, increase soil porosity, and ultimately reduce soil bulk density (32). One reason is the minimal human disturbance; in addition, the network consolidation and biochemical effects of plant roots promote the formation of soil aggregates, loosen the soil, increase soil porosity, and reduce soil bulk density (31, 32). On the other hand, compared with forestland, the vegetation in natural grassland has more sufficient light and water conditions, leading to active soil microorganisms and high organic matter content, which is manifested in a loose soil structure and reduced bulk density (30).

Furthermore, farmland had the highest bulk density, with significant differences from the other two land-use types, which is consistent with the conclusion of Schäffer et al. (33). This is primarily attributed to mechanical tillage. Tillage disturbs the soil matrix, breaking down large soil aggregates into smaller particles (34). The loss of aggregate structure then increases soil bulk density and reduces soil structural stability. The lowest porosity of farmland is partly due to underdeveloped root systems and the inhibition of soil biological activities by chemical fertilizers and pesticides. Additionally, agricultural practices such as irrigation and sowing, coupled with frequent trampling, cause soil compaction and hardening, impairing the connectivity of soil pores (35).

Under different land-use types, soil pH followed the order of farmland > natural grassland > the artificial forestland, while both organic matter content and total nitrogen (TN) content showed the trend of natural grassland > the artificial forestland > farmland. Combined with Table 2, the soil organic matter content and TN content of farmland were significantly lower than those of natural grassland and the artificial forestland, indicating severe soil nutrient loss in farmland. This is because artificial mechanical tillage damages the soil structure, which further reduces the physical protection of soil organic matter, thereby increasing the mineralization and decomposition of soil organic carbon and nitrogen (36). Meanwhile, a decrease in organic matter content impairs aggregate formation and stability, thereby reducing the soil’s ability to resist erosion. This ultimately leads farmland into a vicious circle of gradual degradation (37).

In contrast, the significant increase in soil organic matter content and TN content of the artificial forestland (converted from farmland to forest) indicates that due to the reduction in human activities, litter in the forestland can return to the soil under natural conditions. The litter contains a large amount of tannins, resins, and lignin, whose decomposition produces acidic substances, improving the utilization efficiency of soil nutrients. Additionally, the high humus content in forestland contributes to the acidification of the topsoil (5). Moreover, the type of litter also affects soil pH. This suggests that the large amount of litter returning to the soil in the artificial forestland improves soil texture, thereby enhancing soil anti-scourability to a certain extent (38). Natural grassland has a well-developed root system, and the root network formed by intertwined fine roots facilitates the renewal of the ecosystem and accelerates its rate, enabling better production, storage, and protection of organic matter and nitrogen. However, there are still significant differences in soil organic matter content and TN content between the artificial forestland and the undisturbed natural grassland.

The enhancing effect of plant roots on soil anti-scourability is an important aspect of vegetation control of soil and water loss (39). Plant roots can enhance soil anti-scourability through network connection and root-soil bonding effects (40). On the one hand, roots penetrate and entangle in the soil to form a root network, which consolidates the soil mass. This mechanical network effect stabilizes the soil structure by locking soil particles between root strands, making it less likely to be scoured and fragmented by water flow. On the other hand, roots improve soil physicochemical properties by exuding organic compounds (e.g., mucilage), which act as cementing agents to promote aggregate formation. This optimized soil structure further enhances anti-scourability (29). As shown in Table 3, the changes in soil root geometric characteristic parameters under different land-use types indicate that the four diameter class parameters of root length density (RLD), root surface area density (RSD), and root volume density (RVD) all followed the order of natural grassland > the artificial forestland > farmland. It can be seen that the roots of natural grassland have high density in the topsoil and large contact area with the soil mass, forming a good root network. The consolidation, network connection, root-soil bonding, and biochemical effects of vegetation roots weaken the ability of runoff to scour the soil, indicating that vegetation with abundant roots can significantly improve soil anti-scourability (41). The root geometric characteristic parameters of the artificial forestland are 3 to 5 times those of farmland, suggesting that the conversion of farmland to forest can increase soil root parameters and enhance root consolidation capacity.

Correlation analysis between root geometric parameters and soil anti-scourability within the same diameter class shows the following trend: root volume density (RVD) > root surface area density (RSD) > root length density (RLD) for all diameter classes except 1.5~2 mm fine roots, which showed RLD > RSD > RVD. Among these parameters, RVD had the highest average correlation coefficient. This is because RVD represents the proportion of space occupied by roots in the soil—the larger the RVD, the greater the space occupied by roots. Due to the small size of roots themselves, minor changes in RVD can induce significant changes in soil anti-scourability (14). An excessively small RVD has a limited effect on improving soil anti-scourability. When RVD increases, the vegetation roots become dense, which greatly enhances soil resistance to water scouring and erosion (42). Overall, the 1.5~2 mm diameter fine roots have a closer relationship with the soil anti-scourability coefficient, and all root characteristic parameters show a positive correlation with the coefficient. This indicates that the longer the roots, the larger the surface area they occupy, and the greater their volume, the stronger the soil anti-scourability.