A method, system, medium, and apparatus for soil erosion prediction considering tillage disturbance

Abstract

The application discloses a kind of soil erosion prediction methods, systems, medium and equipment considering tillage disturbance, comprising: data acquisition, disturbance determination calculates soil displacement distance, calculates tillage disturbance factor, corrects topographic factor, improves and applies to traditional RUSLE model.The application corrects topographic factor while calculating tillage disturbance factor, and dynamically couples both to traditional RUSLE model, realizes the quantitative characterization of the slope farmland soil physical displacement caused by tillage disturbance activity and the slope reduction effect, so as to significantly reduce the average error of slope farmland soil erosion prediction from 45.67% to 13.53%, provide further theoretical reference for slope farmland soil erosion research work, also provide part of scientific basis for water and soil loss dynamic monitoring and soil and water conservation related work.

Description

Technical Field

[0001] This application relates to the fields of hydrology, water resources and agricultural ecological environment protection technology, and in particular to a method, system, medium and device for predicting soil erosion that takes into account tillage disturbance. Background Technology

[0002] Sloping farmland, as an important arable land resource, is widely distributed throughout China. According to the 2023 National Land Change Survey, the total area of ​​arable land in China reached 1.929 billion mu (approximately 128 million hectares), of which 968 million mu (approximately 64.9 million hectares) were dry land, accounting for 50.2%. Notably, approximately 82.44 million mu (approximately 5.8 million hectares) of arable land with a slope of 25 degrees or more accounted for 4.2% of the total arable land area. Although sloping farmland accounts for a limited area, its contribution to soil erosion is extremely significant, exhibiting the distinct characteristics of "small area, large loss." Existing research indicates that sloping farmland is one of the main sources of soil erosion in my country, with the proportion of soil loss from sloping farmland in the total national soil erosion significantly exceeding its area proportion. In areas where sloping farmland is concentrated, its soil erosion can even account for more than 50% of the total soil erosion in that region. The dramatic topographical undulations combined with intensive human farming activities have made this region one of the most active areas for both hydraulic and gravity erosion in my country. Accurately predicting soil erosion rates on sloping farmland is crucial for developing scientific and rational soil and water conservation measures, preventing non-point source pollution, and ensuring regional ecological security. Current soil erosion models do not consider the impact of tillage disturbance; therefore, adding tillage disturbance as a factor is essential for accurately estimating soil erosion on sloping farmland.

[0003] Since cultivation is an unavoidable agricultural activity on sloping farmland, soil erosion on sloping farmland is not solely caused by natural factors such as rainfall; agricultural activities—especially human disturbance during cultivation—play a significant accelerating role.

[0004] Soil erosion is one of the most serious ecological and environmental problems facing the world, especially in sloping farmland areas. In the field of quantitative prediction of soil erosion, the Revised Universal Soil Loss Equation (RUSLE) is one of the most widely used empirical statistical models internationally. This model estimates the annual average soil loss by comprehensively considering rainfall erosivity (R), soil erodibility (K), topography (LS), vegetation cover and management (C), and soil and water conservation measures (P). Its classic calculation formula is: Each factor can be obtained through field monitoring, remote sensing inversion, or empirical formulas.

[0005] Numerous studies have shown that long-term agricultural activities significantly exacerbate the risk of soil erosion. However, traditional RUSLE models and their derived modifications generally underestimate soil erosion when applied to sloping farmland. The root cause of this bias lies in ignoring the impact of tillage disturbance. Traditional models, when dealing with human tillage activities, simply equate it to a reduction in vegetation cover (i.e., increasing the C factor). This simplified mathematical approach completely ignores the substantial changes that tillage activities bring to the physical disturbance state of the soil.

[0006] Specifically, existing agricultural tillage techniques (such as hoeing and plowing) not only remove surface vegetation but also uplift compacted subsoil to the surface, causing significant physical displacement along the slope. Traditional models cannot quantify the amount of soil particle migration directly caused by tillage, and different tillage methods (such as animal-powered plowing and micro-tractor rotary tillage) have different disturbance depths and frequencies, leading to dynamic changes in soil erosion resistance. Existing technologies lack effective means to map these multi-dimensional tillage parameters into a unified disturbance intensity index. On steep slopes, soil loosening and downslope displacement caused by tillage significantly lower the soil initiation threshold, making it easy for subsequent rainfall runoff to carry away large amounts of loose soil. Traditional RUSLE models do not include a dedicated module to capture this "amplification effect."

[0007] To address these issues, the industry has attempted to introduce empirical coefficients to revise the models. However, these existing technologies remain at the level of superficial adjustments to the original five factors, failing to reconstruct the model parameters based on the physical nature of soil material transport caused by tillage disturbance. Consequently, their prediction accuracy in sloping farmland areas with complex terrain still cannot meet the needs of high-precision ecological assessment.

[0008] Therefore, how to break through the inherent framework of the traditional RUSLE model and propose a correction method that can quantitatively characterize the effects of tillage activities on soil physical displacement and loosening, thereby improving the accuracy of soil erosion prediction on steep slope farmland, has become a technical problem that urgently needs to be solved in this field. Summary of the Invention

[0009] Therefore, it is necessary to provide a method, system, medium, and device for predicting soil erosion that takes into account tillage disturbance in order to address the above-mentioned technical problems.

[0010] The following technical solution is adopted in this specification:

[0011] This specification provides a method for predicting soil erosion that takes into account tillage disturbance, specifically including:

[0012] The basic environmental parameters, actual cultivation parameters, and control cultivation parameters of sloping farmland are obtained. The basic environmental parameters include at least rainfall erosivity factors, soil erodibility factors, topographic factors, vegetation cover and management factors, and soil and water conservation measures factors. The actual cultivation parameters include at least cultivation depth, cultivation frequency, and cultivation disturbance area determined through field surveys. The topographic factors include slope length and slope.

[0013] By measuring the disturbance caused by tillage using magnetic tracers deployed on the target farmland, the displacement distance of the soil after tillage operations is calculated.

[0014] The tillage disturbance factor is calculated based on the displacement distance, actual tillage parameters, and control tillage parameters.

[0015] The terrain factors are corrected based on the actual farming parameters.

[0016] The traditional RUSEL model is improved by using the tillage disturbance factor and the modified topographic factor to obtain the improved RUSEL-Td model.

[0017] The basic environmental parameters and actual farming parameters of the farmland to be predicted are input into the improved RUSEL-Td model to calculate the soil erosion of the farmland to be predicted.

[0018] Furthermore, the control tillage parameters include at least the control tillage displacement distance, control tillage depth, total area of ​​the evaluation object, and control tillage frequency.

[0019] Furthermore, the method involves measuring tillage disturbance using magnetic tracers deployed on the target farmland and calculating the tillage displacement distance of the soil after tillage operations. The methods specifically include:

[0020] ;

[0021] in, To measure the magnetic susceptibility of the marking strip, To mark the initial magnetic susceptibility of the band, This represents the maximum sampling distance.

[0022] Furthermore, based on the tillage displacement distance, actual tillage parameters, and control tillage parameters, the tillage disturbance factor is calculated. The methods specifically include:

[0023] ;

[0024] in, These are tillage depth, tillage disturbance area, and tillage frequency. These are the control displacement distance, control tillage depth, total area of ​​the evaluated object, and control tillage frequency.

[0025] Furthermore, the terrain factors include slope and slope length.

[0026] Furthermore, the method for correcting the topographic factors based on the actual tillage parameters specifically includes:

[0027] Based on the tillage frequency in the actual tillage parameters Calculate the change in slope ;

[0028] ;

[0029] in, This represents the rate of change of slope.

[0030] The slope value is recalculated based on the slope change. This leads to the correction of terrain factors;

[0031] ;

[0032] in, This is the original slope.

[0033] Furthermore, the equations of the improved RUSEL-Td model are:

[0034] ;

[0035] in, To represent the modulus of soil erosion, As the erosivity factor of rainfall, As a soil erodibility factor, For the corrected terrain factors, Factors related to soil and water conservation measures.

[0036] This specification provides a soil erosion prediction system that takes into account tillage disturbance, specifically including:

[0037] The data acquisition module is used to acquire basic environmental parameters, actual cultivation parameters, and control cultivation parameters for sloping farmland.

[0038] The soil displacement distance calculation module is used to measure tillage disturbance and calculate the soil displacement distance after tillage operations.

[0039] The tillage disturbance factor calculation module is used to calculate the tillage disturbance factor based on displacement distance and actual tillage parameters.

[0040] The terrain factor correction module is used to correct the terrain factors based on the actual farming parameters.

[0041] The model improvement module is used to improve the model by incorporating tillage disturbance factors and modified terrain factors.

[0042] The model application module is used to input the basic environmental parameters and actual farming parameters of the farmland to be predicted into the improved RUSEL-Td model to calculate the soil erosion of the farmland to be tested.

[0043] This specification provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method described above.

[0044] This specification provides a computer device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method described above.

[0045] The beneficial effects of this invention are as follows: Compared with the prior art, this invention, by calculating the tillage disturbance factor while correcting the topographic factor and dynamically coupling the two into the traditional RUSLE model, achieves a quantitative characterization of the physical displacement and loosening effect of soil on sloping farmland caused by tillage activities. This significantly reduces the average error of soil erosion prediction on steep sloping farmland from 45.67% to 13.53%, providing further theoretical reference for the study of soil erosion on sloping farmland, and also providing some scientific basis for dynamic monitoring of soil erosion and related work on soil and water conservation. Attached Figure Description

[0046] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0047] Figure 1 This is a schematic diagram of the process of the present invention;

[0048] Figure 2 This is a schematic diagram of the research area location in an embodiment of the present invention;

[0049] Figure 3 This is a diagram showing the relationship between soil migration distance caused by tillage and slope in an embodiment of the present invention.

[0050] Figure 4 This is a schematic diagram of the calculation results based on the RUSEL-Td model in an embodiment of the present invention. Detailed Implementation

[0051] To make the objectives, technical solutions, and advantages of this specification clearer, the technical solutions of this application will be clearly and completely described below in conjunction with specific embodiments and corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments in this specification without creative effort are within the scope of protection of this application.

[0052] This invention provides a method for predicting soil erosion considering tillage disturbance, comprising six steps: data acquisition, disturbance measurement and calculation of soil displacement distance, calculation of tillage disturbance factor, correction of topographic factor, improvement and application of the traditional RUSLE model. This method, by calculating the tillage disturbance factor and correcting the topographic factor, and dynamically coupling them into the traditional RUSLE model, achieves a quantitative characterization of the physical displacement and loosening effect of soil on sloping farmland caused by tillage activities. This significantly reduces the average error of predicting soil erosion on steep sloping farmland from 45.67% to 13.53%, providing further theoretical reference for research on soil erosion on sloping farmland, and also providing some scientific basis for dynamic monitoring of soil erosion and related work on soil and water conservation.

[0053] The technical solutions provided by the various embodiments of this application are described in detail below with reference to the accompanying drawings.

[0054] A method for predicting soil erosion that takes into account tillage disturbance, such as Figure 1 As shown, it specifically includes:

[0055] Step 1: Obtain basic environmental parameters, actual cultivation parameters, and control cultivation parameters for sloping farmland; basic environmental parameters include at least rainfall erosivity factors, soil erodibility factors, topographic factors, vegetation cover and management factors, and soil and water conservation measures factors; actual cultivation parameters include at least cultivation depth, cultivation frequency, and cultivation disturbance area determined through field surveys; topographic factors include slope length and slope.

[0056] Preferably, the control tillage parameters include at least the control displacement distance, control tillage depth, total area of ​​the evaluation object, and control tillage frequency.

[0057] Step 2: Measure the soil displacement distance after tillage by deploying magnetic tracers on the target farmland to measure tillage disturbance.

[0058] Preferably, the soil displacement distance after tillage is calculated by measuring tillage disturbance using magnetic tracers deployed on the target farmland. The methods specifically include:

[0059] ;

[0060] in, To measure the magnetic susceptibility of the marking strip, To mark the initial magnetic susceptibility of the band, This represents the maximum sampling distance.

[0061] Step 3: Calculate the tillage disturbance factor based on displacement distance, actual tillage parameters, and control tillage parameters.

[0062] Preferably, the tillage disturbance factor is calculated based on the displacement distance, actual tillage parameters, and control tillage parameters. The methods specifically include:

[0063] ;

[0064] in, These are tillage depth, tillage disturbance area, and tillage frequency. These are the control displacement distance, control tillage depth, total area of ​​the evaluated object, and control tillage frequency.

[0065] Step 4: Correct the terrain factors based on the actual farming parameters.

[0066] Preferably, the topographic factors include slope and slope length.

[0067] Preferably, the method for correcting topographic factors based on actual tillage parameters specifically includes:

[0068] Based on the tillage frequency in the actual tillage parameters Calculate the change in slope ;

[0069] ;

[0070] in, This represents the rate of change of slope.

[0071] Recalculate the slope value based on the change in slope. This leads to the correction of terrain factors;

[0072] ;

[0073] in, This is the original slope.

[0074] Step 5: Improve the traditional RUSEL model by using the tillage disturbance factor and the modified topographic factor to obtain the improved RUSEL-Td model.

[0075] Preferably, the equations of the improved RUSEL-Td model are:

[0076] ;

[0077] in, To represent the modulus of soil erosion, As the erosivity factor of rainfall, As a soil erodibility factor, For the corrected terrain factors, Factors related to soil and water conservation measures.

[0078] Step 6: Input the basic environmental parameters and actual farming parameters of the farmland to be predicted into the improved RUSEL-Td model to calculate the soil erosion of the farmland to be tested.

[0079] Example

[0080] This embodiment uses sloping farmland in the Jiangjiagou small watershed of Xide County, Liangshan Yi Autonomous Prefecture, Sichuan Province as the application object to specifically illustrate the implementation process of the invention. For example... Figure 2 As shown, the geographical location of this watershed is between 102°53′~102°57′ east longitude and 26°13′~26°19′ north latitude. The terrain in the area is highly undulating, with a high proportion of sloping farmland above 15°. Farming activities are very intense, and long-term downhill farming is the most common farming method, resulting in prominent soil erosion problems.

[0081] This embodiment provides the following specific steps:

[0082] S1: Obtain basic environmental parameters and actual cultivation parameters of the target sloping farmland.

[0083] Obtain basic environment parameters

[0084] Rainfall erosivity factor (R): Daily rainfall data from meteorological stations in and around the basin from 2000 to 2024 were collected, and spatial distribution raster data (30m resolution) of the multi-year average rainfall erosivity factor R value was obtained by using a semi-monthly rainfall erosivity model.

[0085] Soil erodibility factor (K): Typical soil samples were collected from the watershed, and their organic matter content (SOM) and particle composition were measured. The soil erodibility factor K value of sloping farmland in the Jiangjiagou watershed was calculated using the EPIC model.

[0086] Topographic factors ( Based on a 30m resolution digital elevation model (DEM), slope and slope length are extracted using a GIS hydrological analysis module, and then calculated using a piecewise function method (the method mentioned in the background of this invention). Factor raster data. Simultaneously, through 50 consecutive tillage experiments, the change in slope of farmland with different slopes after long-term tillage disturbance was measured, as shown in Table 1. Furthermore, the slope of sloping farmland in the Jiangjiagou small watershed was calculated. .

[0087]

[0088] Vegetation cover and management factor (C) and soil and water conservation measures factor (P): The annual average vegetation cover was obtained by inversion from Landsat remote sensing images. Combined with the land use type map, the spatial distribution values ​​of C and P factors were initially determined by empirical table lookup method.

[0089] Obtain actual farming parameters

[0090] Through field interviews with farmers and sample plot surveys, it was determined that the typical farming method in this area is manual tillage downhill, with an average tillage depth (H) of 0.16m, a tillage frequency (F) of once a year, and a tillage disturbance area percentage ( Within cultivated land, 1 is considered. The cultivation method is defined as downhill.

[0091] S2: Measurement of soil displacement parameters caused by tillage disturbance

[0092] S2.1 Magnetic Tracer Experiment: Experimental plots were set up on sloping farmland with different slope gradients (0–33°) within the watershed. Before cultivation, magnetic tracers (magnetite powder) were evenly distributed along contour lines on the slope to form marked bands. After routine downslope tillage, soil profile samples were collected at fixed intervals along the slope direction, and the magnetic susceptibility values ​​of each sample were measured using a magnetic susceptibility meter. The calculation results are as follows Figure 3 As shown.

[0093] S2.2 Calculate displacement distance: Calculate tillage displacement distance The calculation results under different slope conditions are shown in Table 3.

[0094] ;

[0095] in, To mark the initial magnetic susceptibility of the band, This represents the maximum sampling distance.

[0096] S3: Constructing Tillage Disturbance Factors

[0097] Reference parameters were determined as follows: As shown in Tables 2 and 3, based on regional surveys and references, the reference average tillage migration distance was determined to be 0.325m, the reference average depth was 0.162m, and the reference average frequency was 1 time / year.

[0098]

[0099]

[0100] Based on displacement distance, actual tillage parameters, and control tillage parameters, tillage disturbance factors were constructed. :

[0101] ;

[0102] in, These are tillage depth, tillage disturbance area, and tillage frequency. These are the control displacement distance, control tillage depth, total area of ​​the evaluated object, and control tillage frequency.

[0103] S4: Corrected Terrain Factors

[0104] As the frequency of cultivation increases, the slope toe extends, the overall projected slope length increases, and the elevation at the slope toe increases significantly, leading to soil deposition, a decrease in slope gradient, and consequently, an impact on the soil erosion rate. The slope changes after long-term cultivation disturbance are as follows: ,in, For the frequency of cultivation, This represents the rate of change of slope.

[0105] Recalculate the slope value based on the change in slope. This leads to the correction of terrain factors;

[0106] ;

[0107] in, This is the original slope.

[0108] S5: Calculate soil erosion modulus

[0109] The R, K, and P factor raster layers obtained in step S1, along with the tillage disturbance factor and the corrected topographic factor raster layers, are used in GIS with a raster calculator to perform pixel-by-pixel calculations based on the RUSLE model formula, ultimately yielding a spatial distribution map of the soil erosion modulus in the Jiangjiagou watershed after considering tillage disturbance.

[0110] ;

[0111] in, To represent the modulus of soil erosion, As the erosivity factor of rainfall, As a soil erodibility factor, For the corrected terrain factors, Factors for soil and water conservation measures

[0112] Validation and Effect Analysis

[0113] Cesium-137 ( Tracer techniques have been widely used in soil erosion research due to their advantages of speed, simplicity, and high accuracy. However, this method involves a large sampling workload and high sample testing costs. To verify the accuracy of the modified model, samples were collected in 2024 at different slopes (ranging from 0° to 30°). Samples were collected from slopes 15–20 m long. For each slope gradient, soil samples were taken from three locations (upper, middle, and lower) at a depth of 0–20 cm. Two parallel samples were collected from each location, and samples were layered every 5 cm. The content of each sample was then determined. The results determined the average erosion rate of sloping farmland with six slopes (<5°, 5–10°, 10–15°, 15–20°, 20–25°, and >25°) in the Jiangjiahe watershed since 1963.

[0114] Using radioactive nuclides As a tracer of slope soil erosion and deposition, it can be used to estimate soil erosion rates.

[0115]

[0116] In the formula, Cumulative per unit area Quality activity, For the erosion rate, The cumulative mass depth is the average tillage depth. for decay constant, for Annual subsidence flux For newly deposited The percentage of radioactive fallout that was eroded away before being incorporated into the topsoil. This is the particle size correction factor.

[0117] The results of soil erosion rate calculation for sloping farmland in the Jiangjiagou watershed based on the RUSEL-Td model are as follows: Figure 4 As shown. The prediction results of the traditional RUSLE model and the modified model of this invention are compared with... Compare the measured data.

[0118] As shown in Table 4, with 137 Compared with soil erosion results calculated using Cs data, the RUSLE-Td model with added tillage disturbance factors showed an error range of 6.39%–22.74%, with an average error of 13.53%. In contrast, the RUSLE model before correction showed an error range of 40.19%–51.70%, with an average error of 45.67%. Therefore, adding tillage disturbance factors significantly increased the calculation accuracy and reduced costs of the RUSLE-Td model.

[0119]

[0120] This specification also provides a soil erosion prediction system that takes into account tillage disturbance, including:

[0121] The data acquisition module is used to acquire basic environmental parameters, actual cultivation parameters, and control cultivation parameters for sloping farmland.

[0122] The soil displacement distance calculation module is used to measure tillage disturbance and calculate the soil displacement distance after tillage operations.

[0123] The tillage disturbance factor calculation module is used to calculate the tillage disturbance factor based on displacement distance and actual tillage parameters.

[0124] The terrain factor correction module is used to correct terrain factors based on actual farming parameters.

[0125] The model improvement module is used to construct a modified general soil loss equation RUSEL-Td model and improve it using tillage disturbance factors and modified topographic factors.

[0126] The model application module is used to input the basic environmental parameters and actual farming parameters of the farmland to be predicted into the improved RUSEL-Td model to calculate the soil erosion of the farmland to be measured.

[0127] For specific limitations regarding a soil erosion prediction system that considers tillage disturbance, please refer to the limitations of a soil erosion prediction method that considers tillage disturbance described above, which will not be repeated here. The modules in the aforementioned soil erosion prediction system that considers tillage disturbance can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0128] This specification also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.

[0129] This specification also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method described above.

[0130] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical storage, etc. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0131] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

Claims

1. A method for predicting soil erosion that takes into account tillage disturbance, characterized in that, include: The basic environmental parameters, actual tillage parameters, and control tillage parameters of sloping farmland were obtained. The basic environmental parameters included at least rainfall erosivity factors, soil erodibility factors, topographic factors, vegetation cover and management factors, and soil and water conservation measures factors. The actual tillage parameters included at least tillage depth, tillage frequency, and tillage disturbance surface determined through field surveys. The topographic factors included slope length and slope. The soil displacement distance after tillage operations is calculated by measuring tillage disturbance using magnetic tracers deployed on the target farmland. Based on the displacement distance, actual tillage parameters, and control tillage parameters, the tillage disturbance factor is calculated. The terrain factors are corrected based on the actual farming parameters. Using the aforementioned tillage disturbance factor and the modified topographic factor, the traditional general soil loss equation RUSEL model is improved to obtain the improved RUSEL-Td model. The basic environmental parameters and actual farming parameters of the farmland to be predicted are input into the improved RUSEL-Td model to calculate the soil erosion of the farmland to be predicted.

2. The soil erosion prediction method considering tillage disturbance as described in claim 1, characterized in that: The control tillage parameters include at least the control displacement distance, control tillage depth, total area of ​​the evaluation object, and control tillage frequency.

3. The soil erosion prediction method considering tillage disturbance as described in claim 2, characterized in that, The method involves measuring tillage disturbance using magnetic tracers deployed on the target farmland and calculating the soil displacement distance after tillage operations. The methods specifically include: ； in, To measure the magnetic susceptibility of the marking strip, To mark the initial magnetic susceptibility of the band, This represents the maximum sampling distance.

4. The soil erosion prediction method considering tillage disturbance as described in claim 3, characterized in that, Based on the displacement distance, actual tillage parameters, and control tillage parameters, the tillage disturbance factor is calculated. The methods specifically include: ； in, These are tillage depth, tillage disturbance area, and tillage frequency. These are the control displacement distance, control tillage depth, total area of ​​the evaluated object, and control tillage frequency.

5. The soil erosion prediction method considering tillage disturbance as described in claim 1, characterized in that: The topographic factors include slope and slope length.

6. A method for predicting soil erosion considering tillage disturbance as described in claim 5, characterized in that, The method for correcting the topographic factors based on the actual farming parameters specifically includes: Based on the tillage frequency in the actual tillage parameters Calculate the change in slope ; ； in, This represents the rate of change of slope. The slope value is recalculated based on the slope change. This leads to the correction of terrain factors; ； in, This is the original slope.

7. A method for predicting soil erosion considering tillage disturbance as described in claim 6, characterized in that, The equations of the improved RUSEL-Td model are as follows: ； in, To represent the modulus of soil erosion, As the erosivity factor of rainfall, As a soil erodibility factor, For the corrected terrain factors, Factors related to soil and water conservation measures.

8. A soil erosion prediction system that takes into account tillage disturbance, characterized in that, include: The data acquisition module is used to acquire basic environmental parameters, actual cultivation parameters, and control cultivation parameters for sloping farmland. The soil displacement distance calculation module is used to measure tillage disturbance and calculate the displacement distance of the soil after tillage operations. The tillage disturbance factor calculation module is used to calculate the tillage disturbance factor based on displacement distance and actual tillage parameters; The terrain factor correction module is used to correct the terrain factors according to the actual farming parameters. The model improvement module is used to improve the model using tillage disturbance factors and corrected topographic factors; The model application module is used to input the basic environmental parameters and actual farming parameters of the farmland to be predicted into the improved RUSEL-Td model to calculate the soil erosion of the farmland to be tested.

9. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, which, when executed by a processor, implements the method described in any one of claims 1 to 7.

10. A computer device, characterized in that, The method includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method described in any one of claims 1 to 7.

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