Effects of Different Tillage Practices on Slope Erosion Characteristics of Peanut Field

Abstract

Under three rainfall intensities (60–90–120 mm/h) and four tillage practices (longitudinal ridge tillage, cross ridge tillage, flat tillage and hole sowing), field experiments was conducted during the podding stage of peanuts to investigate the changes in hydrodynamic parameters and the erosion response on purple soil slope cropland in order to reveal the soil and water conservation benefits of different tillage practices. The results showed that: (1) The sediment yield of the four tillage practices was ranked in descending order: longitudinal ridge tillage, flat tillage, hole sowing, and cross ridge tillage. Under the same rainfall intensity, there were no significant differences in runoff among these four tillage practices (p > 0.05), whereas sediment yield varied significantly. (2) The average flow velocity, Reynolds number, and Froude number of each treatment were positively correlated with rainfall intensity, while the resistance coefficient was negatively correlated. Flat tillage and cross ridge tillage were intermediate. The Reynolds number and Froude number of each treatment did not exceed the critical value and were generally within the laminar flow range, except for the longitudinal ridge tillage treatment at 120 mm/h rainfall intensity. (3) The sediment yield intensity on the slope was negatively correlated with the resistance coefficient, following a power function. The runoff shear stress and runoff power on each treatment were both positively correlated with sediment yield intensity in a linear manner. Compared to longitudinal ridge tillage, the other three tillage practices showed much better soil and water conservation benefits. Among them, cross ridge tillage exhibited the best water storage and soil conservation effects. In terms of hydraulics, longitudinal ridge tillage and flat tillage increased the erosive force required for sediment initiation and suppressed erosion occurrence. The research results were of great significance in revealing the characteristics of runoff erosion in purple soil areas and controlling tillage practices for soil erosion in purple soil areas.

1. Introduction

Abundant natural rainfall and frequent rainstorms in the Sichuan Basin caused severe water erosion in the past. The basin has a large amount of purple soil, primarily located in the middle and upper reaches of the Yangtze River in China. Despite its inherent nutrient richness, soft texture, and tendency for rapid physical weathering [1,2], purple soil has experienced gradual thinning of the cultivated soil layer due to human disturbances. This thinning has not only increased erosion rates, but also significantly affected runoff and sediment yield, negatively impacting local agricultural production [3,4,5]. Therefore, studying the characteristics of soil and water loss in sloping cropland within this region was of the utmost importance.

The results demonstrated that implementing appropriate tillage practices had a positive impact on soil conservation [6]. These practices enhanced soil erosion resistance, reduced soil erosion on sloping farmland, and prevented soil degradation, providing significant benefits for soil and water conservation. By adopting these practices, individuals not only prevented soil degradation, but also made commendable contributions to effective soil and water conservation.

Research also revealed that the interaction between tillage practices and cover material input played a significant role in influencing runoff, the runoff coefficient, soil erosion, as well as the loss of N, P, K, and soil moisture [7]. Additionally, the erosional response of these methods varied depending on the intensity of rainfall. In light rainfall conditions, erosion rates between longitudinal ridges and flat tillage showed minimal disparity. However, under heavy rainfall, the erosion rate of longitudinal ridge tillage could escalate to thirty times that of flat tillage, highlighting the superior soil and water conservation efficacy of the latter in high-intensity rainfall scenarios [8].

In addition to flat tillage, other tillage practices such as ridge tillage and natural grass barrier strips [9] also reduced soil displacement, soil translocation flux, and tillage erosion rates, thereby significantly contributing to soil and water conservation.

Furthermore, it was determined in previous studies that incorporating straw mulching with these tillage practices had multiple benefits. It improved soil quality and nutrients while also significantly reducing surface runoff volume [10,11,12]. This effect was particularly noticeable when tillage practices were combined with straw mulching, resulting in decreased outflow concentrations and reduced volumes of large-size colloids in surface and subsurface runoff. The amount of released colloids showed an inverse relationship with the thickness of the purple soil layer.

Other researchers also favored the combined application of these multifaceted soil and water conservation techniques. Contour ridge cultivation measures, for instance, minimized the depth of runoff and sediment yield, facilitating precipitation infiltration along the ditch, and subsequent absorption by the soil. Additionally, when vegetative hedges were cultivated for three years, they mechanically intercepted sediment [13].

In summary, previous research focused on investigating the soil erosion response caused by tillage practices and gained valuable insights into runoff and sediment loss patterns [7,8,9,10]. Some scholars analyzed the effectiveness of different tillage practices in reducing erosion based on runoff energy. However, one aspect that remained underexplored was the hydrodynamic response of these tillage practices in relation to soil erosion. Therefore, this study utilized artificial field rainfall simulations to examine the hydrodynamic and erosional characteristics of various tillage practices under three different rainfall intensities and four commonly used local cultivation approaches.

The objective of this study was to identify the runoff and sediment loss patterns under different tillage practices, examine the variations in hydraulic parameters, and clarify the relationship between various hydraulic parameters of surface runoff and the erosion rate. By doing so, we aimed to establish theoretical foundations for effective soil erosion management and the protection of the agricultural water and soil environment in sloping cropland within purple soil regions.

2. Materials and Methods

2.1. Study Area Overview

This experiment was conducted on cultivated land at the farm of Sichuan Agricultural University in Ya’an City, Sichuan Province, China (Figure 1).

The study area was located on the western edge of the Sichuan Basin (29°98′ N, 102°99′ E) with a subtropical monsoon climate. The region experienced concentrated rainfall in the summer, with an annual average rainfall of 1650.4 mm, average temperature of 16.8 °C, and annual sunshine duration of 977.7 h. The experiment employed local purple soil samples, which were derived from the weathering and development of purple rock layers, classified as Dystric Leopic Cambisols according to WRB classification. Soil samples were collected from a depth range of 0–20 cm under cultivation, with a moisture content of 14.38% at 10 cm and 10.13% at 20 cm. The humus content in the soil sample was (13.76 ± 4.16) g·kg⁻¹, where the humic component humin constituted (4.82 ± 1.039) g·kg⁻¹, accounting for 60.12% of soil humus; fulvic acid accounted for (1.58 ± 0.932) g·kg⁻¹, representing 20.17% of soil humus; Humic acid had the least proportion, with a content of (1.55 ± 0.533) g·kg⁻¹, accounting for 19.71% of soil humus. The soil texture, based on the soil texture triangle, was classified as Loam, with the following particle composition: 38.43% sand (2~0.02 mm), 46.38% silt (0.02~0.002 mm), and 15.19% clay (<0.002 mm). The liquid limit was 32.9%, the plastic limit was 19.4%, and the soil bulk density was 1.39 g·cm⁻³. Refer to

Table 1. Monthly rainfall and temperature data during the experimental period.

Period	Rainfall (mm)	Temperature (°C)
May 2023	110.6	21.4
June 2023	28.1	25.6
July 2023	316.3	27.5

for the rainfall and temperature data during the experiment period.

2.2. Research Methods

A randomized block design was employed for this experiment. To replicate the high precipitation levels in the Ya’an region, which has an average annual precipitation of around 1800 mm, and to enhance comparability with previous studies, three rainfall intensities (60, 90 and 120 mm·h⁻¹) were selected. Each intensity had a 60-min duration. Light rainfall (60 mm·h⁻¹), moderate rainfall (90 mm·h⁻¹), and heavy rainfall (120 mm·h⁻¹) were the classifications.

Based on local farming practices, four tillage practices were implemented for peanut cultivation: Longitudinal ridge tillage (LR), cross ridge tillage (CR), flat tillage (FT), and hole sowing (HS). In total, 12 experimental treatments were arranged under the three rainfall intensities, with each treatment replicated three times. This resulted in 36 runoff plots, each with a projection area of 2 m² (length 2 m × width 1 m), ensuring a stable slope runoff condition. To simulate rainfall, field artificial rainfall equipment was utilized, including portable side-spray rainfall simulators (Figure 2).

During the rainfall, spraying occurred simultaneously from both sides to promote raindrop collisions in the air. This reduced the horizontal velocity of raindrops upon reaching the ground, minimizing their impact on the experiment. The height of the rainfall equipment was 6 m, and the rainfall area could be adjusted as needed. The rainfall uniformity was maintained above 85%, and the intensity could be regulated between 30–150 mm·h⁻¹. Before the experiment, the surface vegetation on the plots was cleared, and the plots were plowed twice. They were then left fallow for one year. During this year, we would weed once a week to keep the experimental community in a bare land state during the year of abandonment. Considering the local distribution characteristics of sloping farmland, the slope gradient of the plots was set at 5°. Peanuts, the main local agricultural crop, were chosen as the test crop, and sowing took place on 10 May 2023. The planting density was 30 plants·m⁻² (Figure 3).

LR and CR involved furrowing and ridging longitudinally and horizontally, respectively, with a ridge height of 11 cm, a ridge width of 30 cm, and a ridge spacing of 10 cm. FP entailed direct, evenly spaced planting in three rows along the longitudinal direction, without furrowing or ridging. The row width was 20 cm and the row spacing was 10 cm. HS was planted in a triangle shape, with concave depressions of 15 cm in diameter and a spacing of 18 cm. The simulated rainfall experiment took place during the pod formation stage of peanuts, from 5 July 2023 to 25 July 2023.

2.3. Data Collection

Runoff occurrence time was recorded from the beginning of rainfall when continuous flow initiated. Every 2 min, sediment samples were collected from each treatment throughout the rainfall period. After 24 h of settling, the supernatant was removed, and the sediment samples were collected and dried to obtain runoff volume and sediment yield data.

The surface flow velocity of runoff was determined using the potassium permanganate staining method. Flow velocity measurements were taken at 1 m intervals from the upper and lower sections of the experimental plots. In total, 10 repetitions were performed at each section, and the average values were used to calculate the average surface flow velocity. Correction factors of 0.67 for laminar flow, 0.7 for transition flow, and 0.8 for turbulent flow were applied [14]. This allowed effective measurement of runoff flow velocity, as the runoff depth on the cross-ridge slope exceeded the depth of the ridge furrow.

The plot was divided into 9 observation zones horizontally and vertically. Water depth measurements were taken at 3 locations within each observation zone using a ruler with 0.1 mm accuracy. Outliers were excluded, and the average water depth was calculated. Runoff temperature was monitored. Finally, the mean values from the three repeated experiments were analyzed.

2.4. Calculation of Hydrological Runoff Parameters

2.4.1. Reynolds Number

The flow state of water is determined by the Reynolds number. When Re is less than 500, the flow is laminar; when Re is greater than 500, it is turbulent. The transitional flow is considered to be around a Re of 500. The formula for calculating it is [15]:

$$Re=\frac{Vh}{v}$$

(1)

$$v=\frac{0.01775}{1+0.0337t+0.000221t^2}$$

(2)

where V represents the average flow velocity in meters per second (m·s⁻¹), h represents the average water depth in meters (m), v represents the kinematic viscosity in square meters per second (m²·s⁻¹), and t represents the water temperature in degrees Celsius (°C).

2.4.2. Froude Number

The Froude number is a key parameter for determining the flow regime of water. When Fr < 1, the flow is considered a tranquil flow; when Fr = 1, it is a critical flow, and when Fr > 1, it is a rapid flow. Its calculation formula is [15]:

$$Fr=\frac{V}{\sqrt{gh}}$$

(3)

where g represents the gravitational acceleration, which is taken as 9.8 m·s⁻².

2.4.3. Resistance Coefficient

The resistance coefficient is a collective term for the resistive forces experienced by runoff as it moves downward, and its calculation formula is [15]:

$$f=\frac{8ghJ}{V^2}$$

(4)

where f is the resistance coefficient; J is the hydraulic slope, which is approximately taken as the sinusoidal value of the slope.

2.4.4. Runoff Shear Stress

Runoff shear stress is the primary force responsible for the detachment and transport of soil particles and sediment. Its calculation formula is [16]:

$$\tau =\rho ghJ$$

(5)

where τ represents the runoff shear stress in pascals (Pa), and ρ is the density of water in kilograms per cubic meter (kg·m⁻³).

2.4.5. Runoff Power

Runoff power is the measure of power consumed by water flow acting on a unit area. Its calculation formula is [16]:

$$\omega =\tau V$$

(6)

where ω represents hydraulic power, measured in N·m⁻¹·s⁻¹.

2.4.6. Sediment Yield Intensity

Sediment yield intensity can reflect the relationship between rainfall and soil loss under different tillage practices. Its calculation formula is:

$$D_r=\frac{E}{A}$$

(7)

where Dr represents sediment yield intensity, measured in g·(min⁻¹·m⁻²); E is the sediment yield rate (g·min⁻¹); A is the area of the experimental plot (m²).

2.5. Data Processing and Analysis

The experimental data were stored in Excel and imported into SPSS 22.0 for statistical analysis. In order to reflect the significance between different treatments, we used two-factor analysis and used the Duncan method to test for significance. The Duncan test was applied to the data, which involved grouping based on means and comparing adjacent groups to assess the significance of differences. Additionally, Excel 2010 was used to create charts for a comprehensive presentation and analysis of the results.

3. Results

3.1. Runoff and Sediment Characteristics under Different Tillage Practices

From

Table 2. Runoff and sediment yield under different rainfall intensity and tillage practices.

Rainfall Intensity (mm·h−1)	Tillage Practices	Runoff (L)	Runoff Rate (L·min−1·m−2)	Sediment Yield (kg)	Sediment Yield Intensity (g·min−1·m−2)
60	LR	36.32 ± 2.54 Ca	0.37 ± 0.06 Ca	0.12 ± 0.01 Ca	1.19 ± 0.12 Ca
	FT	31.18 ± 3.28 Cb	0.35 ± 0.05 Cab	0.09 ± 0.01 Cb	1.05 ± 0.10 Ca
	HS	29.03 ± 1.39 Cc	0.38 ± 0.04 Cb	0.05 ± 0.01 Cc	0.71 ± 0.14 Cb
	CR	22.56 ± 2.52 Cd	0.31 ± 0.07 Cc	0.03 ± 0.01 Cd	0.41 ± 0.05 Cc
90	LR	69.28 ± 4.63 Ba	0.67 ± 0.04 Ba	0.27 ± 0.02 Ba	2.68 ± 0.18 Ba
	FT	64.94 ± 5.83 Bb	0.65 ± 0.07 Bab	0.20 ± 0.03 Bb	2.09 ± 0.50 Ba
	HS	57.51 ± 2.65 Bc	0.59 ± 0.06 Bb	0.13 ± 0.02 Bc	1.38 ± 0.25 Bb
	CR	44.96 ± 2.91 Bd	0.53 ± 0.05 Bc	0.06 ± 0.01 Bd	0.76 ± 0.12 Bc
120	LR	105.43 ± 4.44 Aa	1.06 ± 0.02 Aa	0.45 ± 0.03 Aa	4.51 ± 0.24 Aa
	FT	97.55 ± 6.61 Ab	0.97 ± 0.06 Aab	0.43 ± 0.05 Ab	4.60 ± 0.40 Aa
	HS	93.71 ± 2.54 Ac	0.91 ± 0.05 Ab	0.34 ± 0.05 Ac	3.38 ± 0.46 Ab
	CR	81.05 ± 3.91 Ad	0.84 ± 0.04 Ac	0.13 ± 0.01 Ad	1.39 ± 0.16 Ac

LR represents longitudinal ridge tillage; FT represents flat tillage; HS represents hole sowing; CR represents cross ridge tillage. The data in the table are represented as: mean value ± standard deviation. Different uppercase letters indicate significant differences in the same tillage practice under different rainfall intensities, while different lowercase letters indicate significant differences between different tillage practices under the same rainfall intensity (p < 0.05, Duncan). Same as below.

, it can be observed that the variations in runoff volume and runoff ratio followed a similar trend under different tillage practices. They increased with higher rainfall intensity, and gradually decreased when changing from longitudinal ridges to flat tillage, hole sowing, and cross ridges.

At a rainfall intensity of 60 mm·h⁻¹, significant differences in runoff were observed among the four tillage practices. However, only the runoff rate corresponding to the cross slope ridge showed significant differences in terms of runoff yield compared to the other three practices. As the rainfall intensity increased to 90 and 120 mm·h⁻¹, the runoff ratio of cross ridge tillage significantly differed from the other three practices.

Among the different practices, longitudinal ridge exhibited the highest runoff volume and runoff ratio, while cross ridge tillage showed the lowest values, representing only 74.34% of the longitudinal ridge values. This difference increased gradually with higher rainfall intensities. Flat tillage and hole sowing had similar effects on runoff regulation, and the variation in rainfall intensity had little impact on their effectiveness.

Overall, as the rainfall intensity increased, the increment in runoff volume for different practices gradually decreased. When changing from a light to a moderate rainfall intensity, the runoff volume increment for different practices was approximately 100%. However, when changing from moderate to heavy rainfall, the runoff increment was only around 60%. The variation trend of total sediment yield and sediment yield intensity on the slope was observed under different experimental conditions. It showed an increase with higher rainfall intensity, and a decrease when changing from longitudinal ridge tillage to flat tillage, hole sowing, and cross ridge tillage. At these three rainfall intensities, the total sediment yield and sediment yield intensity on the cross slope ridge were significantly lower compared to other tillage practices. Compared to longitudinal ridge tillage, flat tillage, and hole sowing, the total sediment yield and sediment yield intensity on the cross ridge decreased by 74.63%, 68.81%, and 51.87%, respectively. This indicates that cross ridge tillage had a better effect in controlling sediment yield on the slope. Unlike the runoff characteristics, the effect of rainfall on sediment yield did not weaken with a higher rainfall intensity. The increment in sediment yield remained approximately the same under the same increase in rainfall intensity.

Flat tillage and longitudinal ridge exhibited the closest runoff ratios and sediment yield intensities. This similarity was due to their similar planting shapes. However, longitudinal ridges were more prone to soil erosion caused by the splashing effect of raindrops, leading to slightly higher soil and water loss compared to flat tillage.

On the other hand, hole sowing, with its numerous small depressions, had the ability to intercept and accumulate surface runoff. Some of the overland flow and interflow infiltrated into these depressions, storing water in the ground [17]. When rainfall was light, the water in the depressions was gradually consumed through infiltration and evaporation, making it difficult for runoff to form. However, when rainfall intensity increased, the depressions became filled and overflowed, resulting in runoff along the slope. Consequently, the runoff ratio and sediment yield intensity of hole sowing were lower than that of flat tillage.

In contrast, cross ridges, with their perpendicular orientation to the flow direction and deeper ridges, effectively intercept surface runoff and accumulate a significant amount of rainfall. This greatly delayed the initial generation of runoff. Consequently, cross ridges demonstrated the lowest runoff ratio and sediment yield intensity.

To analyze the relationship between runoff, sediment yield, and rainfall, we conducted multiple regression analyses on the parameters in the table. This resulted in the following regression equations:

$$Q=55.6739 I^{0.1268}R{r}^{1.0981} (R^2=0.9685, n=36)$$

(8)

$$W=0.0825I^{0.0079}D{r}^{1.1196} (R^2=0.9893, n=36)$$

(9)

where Q represents the total runoff in L, W represents the total erosion in kg, I represents the rainfall intensity in mm·h⁻¹, Rr represents the runoff ratio in L·(min⁻¹·m⁻²), and Dr represents the sediment yield intensity in g·(min⁻¹·m⁻²).

From the equations above, it is evident that both total runoff and total erosion exhibited an exponential relationship with rainfall intensity. However, the exponent (0.1268) of rainfall intensity in the regression of total runoff was higher compared to the exponent (0.0079) in the regression of total erosion. This suggests that changes in rainfall intensity had a significant impact on total runoff on the slope, while the influence on total erosion was relatively weaker.

3.2. Hydraulic Characteristics Parameters

3.2.1. Average Flow Velocity

Runoff velocity played a crucial role in hydraulic studies by providing insight into the types of runoff and the primary erosive forces on slopes. Figure 4 presented the average flow velocities of various tillage practices across three rainfall intensities.

Different uppercase letters indicate significant differences within the same tillage practice across different rainfall intensities, while different lowercase letters indicate significant differences between different tillage practices under the same rainfall intensity (p < 0.05, Duncan).

Based on Figure 4, it is observed that hole sowing exhibited the lowest average flow velocity at rainfall intensities of 60 and 90 mm·h⁻¹. However, as the rainfall intensity increased, the disparity between hole sowing and other practices diminished. All practices displayed an increasing trend in average flow velocities with higher rainfall intensities, ranging from approximately 3.85 cm·s⁻¹ to 10.33 cm·s⁻¹. The narrow furrows and limited interception along the downhill direction of the slope facilitated a significant convergence of rainwater and slope runoff within the furrows, ensuring a steady water flow. Consequently, the average flow velocity on longitudinal ridges surpassed that of other tillage practices. The flow velocity on the flat tillage slopes closely resembled that of longitudinal ridges due to their similar planting methods. However, as flat tillage slopes lacked furrows, which served as effective runoff interceptors and reduced acceleration space, the flow velocity on these slopes was lower than that on longitudinal ridges. Cross slope ridges situated perpendicular to the slope hindered water flow, leading to puddling in the furrows and impeding runoff generation, resulting in lower flow velocities. Hole sowing, with its depressions and improved soil structure from the peanut root system, intercepted runoff in the hollows and facilitated effective infiltration and storage capacity. This prolonged the infiltration time and led to the smallest average flow velocity at rainfall intensities of 60 and 90 mm·h⁻¹.

3.2.2. Runoff Types

In

Table 3. Reynolds numbers and Froude numbers under various rainfall intensities and tillage practices.

Rainfall Intensity	Tillage Practices	Reynolds Number	Froude Number
60	LR	389 ± 10 Ca	0.35 ± 0.03 Ba
	FT	281 ± 29 Cb	0.28 ± 0.02 Bb
	HS	174 ± 46 Cc	0.19 ± 0.05 Bc
	CR	136 ± 22 Cd	0.27 ± 0.05 Bb
90	LR	482 ± 65 Ba	0.37 ± 0.05 Aa
	FT	379 ± 19 Bb	0.35 ± 0.03 Ab
	HS	254 ± 30 Bc	0.26 ± 0.02 Ac
	CR	232 ± 18 Bd	0.33 ± 0.03 Ab
120	LR	642 ± 36 Aa	0.43 ± 0.03 Aa
	FT	450 ± 38 Ab	0.36 ± 0.04 Ab
	HS	342 ± 71 Ac	0.30 ± 0.04 Ac
	CR	276 ± 12 Ad	0.32 ± 0.04 Ab

LR represents longitudinal ridge tillage; FT represents flat tillage; HS represents hole sowing; CR represents cross ridge tillage. The data in the table are represented as: mean value ± standard deviation. Different uppercase letters indicate significant differences in the same tillage practice under dif-ferent rainfall intensities, while different lowercase letters indicate significant differences between different tillage practices under the same rainfall intensity (p < 0.05, Duncan). Same as below.

, the Reynolds numbers and Froude numbers were presented for various experimental conditions. The Reynolds numbers exhibited similar patterns across different treatments. They increased with higher rainfall intensities and decreased as the tillage practices transitioned from longitudinal ridges to flat tillage, hole sowing, and cross ridges. There was no significant difference in Reynolds numbers between cross ridges and hole sowing under the same rainfall intensity, while the Reynolds number of longitudinal ridges was notably higher than the other three practices. As the rainfall intensity increased from 90 mm·h⁻¹ to 120 mm·h⁻¹, the flow regime on the longitudinal ridge shifted from laminar to turbulent, indicating that the higher rainfall intensity caused changes in flow regime and increased turbulence levels in the water flow. The Reynolds numbers of runoff on the slope varied from 136 to 642 under different practices, with most of them in the laminar flow regime. Only the flow on the longitudinal ridges under a rainfall intensity of 120 mm·h⁻¹ exhibited turbulent flow.

In relation to the changes in Froude numbers, when the rainfall intensity changed from light to moderate, all treatments exhibited significant increases in Froude numbers. However, when the rainfall intensity increased from moderate to heavy, the Froude numbers generally did not fluctuate significantly. Froude numbers for all rainfall events remained between 0.19 to 0.43, which was below one, and indicated subcritical flow. Based on the previous analysis, we can conclude that the runoff patterns on the slope under different tillage practices generally fall into the subcritical flow regime. Rainfall intensity had a significant influence on the Reynolds numbers of the water flow, but had a minor impact on the Froude numbers.

3.2.3. Resistance Coefficient

Figure 5 showed the resistance coefficients under different experimental conditions. It can be observed that the resistance coefficients of different treatment groups decreased gradually as the rainfall intensity increased. The trend in resistance coefficients among different tillage practices aligned with the findings of average flow velocity, where practices with higher resistance coefficients exhibited lower average flow velocities. The range of resistance coefficients under the experimental conditions ranged from 3.83 to 16.16. Under a light rainfall intensity, hole sowing demonstrated a significantly higher resistance coefficient compared to other practices, resulting in all practices exhibiting their maximum resistance coefficients and effectively intercepting runoff. However, as the rainfall intensity increased to moderate or heavy, the resistance coefficients decreased, thus limiting the ability of tillage practices to regulate sediment-laden runoff.

Figure 6 displayed the relationship curve between slope sediment yield intensity and resistance coefficient. It revealed a power function relationship between the two variables, indicating that as the resistance coefficient increased, the sediment yield intensity decreased. This was because a higher resistance coefficient impeded and infiltrated more runoff, lading to reduced runoff and sediment yield. The negative power function nature of the curve resulted in an increasing derivative at the corresponding point of the resistance coefficient. When the ratio between the increment of sediment yield intensity (ΔDr) and the increment of resistance coefficient (Δf) reached −1, the resistance coefficient was approximately 3.96. This suggested that if the resistance coefficient was below this value, increasing it would lead to a sharp decline in sediment yield intensity. However, once this threshold was surpassed, the impact of the increasing the resistance coefficient on sediment yield intensity gradually diminished.

3.3. Response of Erosion to Hydraulic Parameters

3.3.1. Relationship between Sediment Yield Intensity and Runoff Shear Stress

Runoff shear stress acts as the main force responsible for soil particle detachment and sediment transport. As the runoff shear stress surpassed the soil’s critical shear stress, the excess effective shear stress disrupted the soil structure, resulting in the erosion of soil particles by runoff and their subsequent transportation to the slope surface. By analyzing the relationship between sediment yield intensity on the slope and runoff shear stress under different tillage practices, as depicted in Figure 7, it is evident that the sediment yield intensity increased linearly with the rise in runoff shear stress for each practice.

Table 4. Regression equation of sediment yield intensity and runoff shear stress under different tillage practices.

Tillage Practices	Regression Equation	Critical Shear Stress (Pa)	R2	n
LR	Dr = 2.860τ − 10.397	3.64	0.779	9
FT	Dr = 4.461τ − 16.097	3.61	0.782	9
HS	Dr = 3.414τ − 11.663	3.42	0.692	9
CR	Dr = 0.815τ − 1.630	2.00	0.697	9

LR represents longitudinal ridge tillage; FT represents flat tillage; HS represents hole sowing; CR represents cross ridge tillage.

displayed the regression equations between sediment yield intensity on the slope and runoff shear stress, indicating a strong correlation between the two variables with coefficients of determination ranging from 0.7 to 0.8. This indicated the effectiveness of runoff shear stress in predicting slope erosion intensity. Among the four practices, cross ridge exhibited the lowest critical shear stress, while longitudinal ridge, flat tillage, and hole sowing had similar critical values, being 1.82, 1.81, and 1.71 times higher than that of cross ridge, respectively. In this study, the critical shear stresses of longitudinal ridge and cross ridge were 3.64 and 2.00 Pa, respectively, accounting for only 73.98% and 45.87% of their respective critical values. The critical shear stress of bare soil was 0.86 Pa, indicating that tillage practices increase the critical shear stress of the slope. A higher initial shear stress requirement for the initiation of runoff-induced erosion and sediment transport strengthens the soil’s resistance to runoff erosion, thereby reducing water and soil loss on the slope.

3.3.2. Relationship between Runoff Power and Sediment Yield Intensity

Runoff power represented the rate of change in gravitational potential energy per unit weight of water over time. It indicated the potential energy of runoff as it flowed downslope at a specific elevation. Similar to runoff shear stress, soil particles were detached and transported downslope when the slope surface’s runoff power exceeded a critical value. In Figure 8, the relationship between sediment yield intensity and runoff power under various tillage practices was illustrated. It was observed that both variables showed a strong positive linear relationship, with the sediment transport rate on the slope increasing as the runoff power increased.

Table 5. Regression equation of sediment yield intensity and runoff power under different tillage practices.

Tillage Practices	Regression Equation	Critical Runoff Power (N·m−1·s−1)	R2	n
LR	Dr = 13.411ω − 2.742	0.205	0.739	9
FT	Dr = 22.592ω − 4.323	0.191	0.819	9
HS	Dr = 15.695ω − 1.512	0.096	0.820	9
CR	Dr = 7.659ω − 0.500	0.065	0.700	9

LR represents longitudinal ridge tillage; FT represents flat tillage; HS represents hole sowing; CR represents cross ridge tillage.

presented the correlation equations between sediment yield intensity and runoff power. The coefficients of determination ranged from 0.7 to 0.9. Runoff power exhibited a higher coefficient of determination than runoff shear stress, indicating that it was a more accurate predictor of slope sediment production. The critical runoff power patterns for different tillage practices aligned with the conclusions drawn for critical shear stress. Cross ridge had the lowest critical power, hole sowing was in the middle, and longitudinal ridges and flat tillage had similar critical values, which were the highest. In this study, the critical runoff powers for the cross ridge and longitudinal ridge were 0.065 and 0.205 N·m⁻¹·s⁻¹, respectively, close to Wang et al.’s [18] determined critical power of 0.071 N·m⁻¹·s⁻¹ for cross ridge, and significantly lower than their determined critical power of 0.941 N·m⁻¹·s⁻¹ for longitudinal ridge. However, the critical runoff power for exposed slopes was often 0.004 N·m⁻¹·s⁻¹. In comparison, the tillage practices in this study significantly increased the critical runoff power, ranging from 15.19 to 47.56 times. Combining the conclusions drawn for runoff shear stress, longitudinal ridge and flat tillage had the best effect on regulating the critical threshold of erosion dynamics, while cross ridge had a less significant delaying effect on the critical value.

The analysis of runoff shear stress and runoff power under different tillage practices revealed that the critical values for both variables were lower than those reported in previous studies [19]. This difference could be attributed to variations in soil properties and experimental methods. Previous studies mainly conducted flume erosion experiments with slope angles ranging from 5° to 15°, which were one to three times steeper than the slope angles in our experiment. Additionally, this study utilized simulated rainfall experiments, where the impact of raindrops on the soil surface increased soil particle susceptibility to erosion and intensified the turbulence of surface runoff. As a result, the critical values for runoff shear stress and runoff power were relatively low, indicating an increase in sediment transport in runoff from the slope surface.

3.3.3. Correlation Analysis between Erosion Rate and Hydraulic Parameters

To investigate the relationship between various hydraulic factors of runoff and the erosion rate on the slope, a Pearson correlation analysis was conducted using SPSS 24.0. Seven hydraulic parameters and sediment yield intensity were analyzed. The results shown in

Table 6. Correlation coefficient between sediment yield intensity and various hydraulic parameters.

	V	h	Re	Fr	f	τ	ω
Dr	0.738 **	0.789 **	0.813 **	0.581 **	−0.455 **	0.789 **	0.816 **

** indicates p < 0.01.

revealed a significant correlation between sediment yield intensity and all seven hydraulic parameters. The correlation coefficients were ranked as follows: ω > Re > τ ≥ h > V > Fr > f. According to Table 6, it can be seen that the resistance coefficient displayed a negative correlation with sediment yield intensity. The correlation coefficient between runoff power and sediment yield intensity was the highest, indicating that runoff power was more effective in predicting slope erosion intensity.

4. Discussion

The relationship between Reynolds number and rainfall intensity—as well as the relationship between Reynolds number and tillage methods—observed in our study were consistent with the conclusions drawn by Guo et al. [20] They conducted a study on red soil slope simulation under three rainfall intensities of 60 mm·h⁻¹, 90 mm·h⁻¹, and 120 mm·h⁻¹. Our research also revealed that as rainfall intensity increased, the resistance coefficients of different treatments decreased. This finding aligns with the conclusions drawn by Liu et al. [21], who studied five rainfall intensities ranging from 60 to 210 mm·h⁻¹ and indicated a negative correlation between the resistance coefficient and rainfall intensity. Furthermore, our article discussed the power function relationship between sediment yield intensity and resistance coefficient. This relationship was corroborated by the research results of Lin [22] and Guo [20]. Both studies demonstrated that sediment yield rate and cumulative sediment yield followed a power function relationship with the resistance coefficient, and the fitting results indicated a negative correlation between the two.

In our study, we investigated runoff erosion based on runoff shear stress and the critical shear stress of the soil. The critical shear stress of the soil is a crucial indicator of its resistance to runoff erosion and its susceptibility to shear deformation failure [23,24,25]. Typically, the value of the critical shear stress is determined through empirical relationships or reference tables [19]. In our dataset, the cross ridge treatment exhibited the best performance in terms of critical shear stress. Interestingly, in the research conducted by Wang et al. [18] on red soil slopes, the critical shear stresses of both the longitudinal ridge and cross ridge treatments were reported as 4.92 and 4.36 Pa, respectively. Moreover, our data on critical shear stress can be compared with the research conducted by Xiao et al. [26], which highlighted the influence of different tillage measures on soil.

The article described a consistent linear relationship between runoff power and sediment yield intensity, which aligns with the conclusions drawn by Chen et al. [27] and Wang [28] regarding the linear relationship between soil erosion rate and runoff power.

In comparison to the critical runoff powers reported in the studies conducted by Hawks et al. [29] and Xiao et al. [30] for cross ridge and longitudinal ridge treatments, this significant difference further elucidates the impact of tillage practices on this study.

In Wang’s study [18], the critical values of runoff shear stress and runoff power were both numerically higher than our research data. This disparity could be attributed to differences in experimental details and soil properties. However, it is important to acknowledge that the experimental area used in this study was relatively small, and the boundaries of the community may have introduced some errors in the data. Additionally, maintaining a constant rainfall intensity throughout the entire event, as observed in our study, is challenging to replicate under natural conditions. Therefore, the next step will involve conducting field experiments with natural rainfall to investigate runoff erosion in purple soil.

5. Conclusions

(1)

The runoff and sediment characteristics exhibited similarities under different tillage practices. Both runoff and sediment yield increased with higher rainfall intensities, gradually decreasing as the tillage practices transitioned from longitudinal ridge to flat tillage, hole sowing, and cross ridge. As rainfall intensity grew, the regulating effect on runoff weakened for each practice, while the control on sediment remained relatively stable.

(2)

The flow velocity demonstrated an increasing trend under various tillage practices as rainfall intensity escalated, with the order being LR > FT > CR > HS. The differences between tillage practices diminished with higher rainfall intensities. Each treatment presented a laminar flow regime, with notable Reynolds number discrepancies between longitudinal ridge, flat tillage, hole sowing, and cross ridge, but there was only a significant difference in the Froude number between longitudinal ridge, hole sowing, and cross ridge. The resistance coefficient showed the opposite pattern, different from flow velocity, with practices that possess higher resistance coefficients generally displaying lower average flow velocities. Moreover, the resistance coefficient exhibited a power function relationship with sediment yield intensity.

(3)

The shear stress and runoff power of runoff exhibited a linear increase with sediment yield intensity under the four tillage practices. Runoff power demonstrated a higher coefficient of determination compared to shear stress, offering a more accurate prediction of slope sediment yield. Longitudinal ridge and flat tillage practices significantly raised the initial erosion energy required for sediment initiation, enhancing the soil’s erosion resistance. Therefore, while longitudinal ridge tillage and flat tillage can still be utilized, it is crucial to design drainage systems to regulate slope water flow and effectively control slope velocity and sediment yield.

(4)

This study provided insight into the soil and water conservation capabilities of different tillage practices, establishing a scientific foundation for managing soil erosion in arable land and preventing soil erosion in purple soil areas of Sichuan Province.