Sand yield prediction method based on wind-water composite erosion energy

Abstract

The invention discloses a sand yield prediction method and system based on wind-water composite erosion energy, and belongs to the technical field of soil erosion prediction.The method comprises the steps that test data including different starting wind speeds, soil moisture content and vegetation coverage variables are obtained through a wind erosion dynamic test; constructing an improved wind erosion energy model based on the obtained test data; key water erosion process parameters under different working conditions are obtained through a simulated rainfall test; constructing a water erosion energy model based on the key water erosion process parameters and the improved runoff erosion energy; and finally, combining the wind erosion energy model and the water erosion energy model to construct a sand production prediction model under the composite erosion energy, and predicting the sand production in the composite erosion environment. According to the method, the physical essence of the erosion process is fully considered from the perspective of energy, the staggering characteristics of wind erosion and water erosion in the time dimension are accurately grasped, the fitting effect is good, and the sediment yield in the composite erosion environment can be predicted.

Description

Technical Field

[0001] The present invention relates to the technical field of soil erosion prediction, and more particularly to a method for predicting sediment yield based on wind-water composite erosion energy. Background Art

[0002] Soil erosion is a key ecological and environmental issue. Its complexity and destructiveness are particularly pronounced in geomorphic environments where wind and water erosion interact. Combined wind and water erosion, a special type of erosion, overlaps spatially and temporally, with wind erosion predominant in winter and water erosion predominating in summer. This temporal and spatial interaction distinguishes the combined wind and water erosion process and its effects from those of either wind or water erosion alone, significantly enhancing soil erosion and sediment transport capacity. Wind erosion also increases the corrosive power of water erosion, leading to high erosion moduli and high sediment concentrations in regional runoff.

[0003] Traditional studies often use independent wind or water erosion models to estimate single-factor erosion, failing to effectively quantify the dynamic coupling of the two erosion forms over time and unable to achieve high-precision sediment yield predictions. Therefore, this paper explores the dynamics of erosion from an energetic perspective and provides a sediment yield prediction method based on the combined energy of wind and water erosion. This method achieves high-precision simulation of sediment production in complex erosion areas, improves the accuracy of sediment yield predictions, and provides a scientific basis for soil and water conservation benefit assessment. Summary of the Invention

[0004] In view of this, the present invention provides a sand production prediction method based on wind and water combined erosion energy. From the perspective of energetics, the wind erosion energy model and the water erosion energy model are combined to construct a sand production prediction model under combined erosion energy, which can make high-precision predictions on sand production in a combined erosion environment.

[0005] To achieve the above object, the technical solution adopted by the present invention is:

[0006] In a first aspect, the present invention provides a method for predicting sediment yield based on wind-water combined erosion energy, the method comprising:

[0007] Through wind erosion dynamics experiments, experimental data including different starting wind speeds, soil moisture content, and vegetation coverage variables were obtained; based on the obtained experimental data, an improved wind erosion energy model was constructed;

[0008] The key water erosion process parameters under different working conditions were obtained through simulated rainfall tests; a water erosion energy model was constructed based on the key water erosion process parameters and the improved runoff erosion energy;

[0009] A wind erosion energy model and a water erosion energy model are combined to construct a sand production prediction model under composite erosion energy, and the sand production prediction model is used to predict the sand production under composite erosion environment.

[0010] Furthermore, in this method, undisturbed soil samples are collected from the wind-water composite erosion area to conduct wind erosion dynamics tests, the test wind speed gradient is determined through meteorological data analysis, and the soil moisture content and vegetation coverage test gradient is established.

[0011] Furthermore, the wind erosion energy model constructed is:

[0012]

[0013] Where: E represents wind erosion energy; EPT i represents monthly potential evaporation; P i represents the average monthly precipitation; ρ represents the atmospheric density; V wind Indicates the wind speed involved in the test; V C W represents the starting wind speed of the test soil sample, that is, the minimum wind speed that can cause wind erosion of the test soil sample; a represents the soil moisture content involved in the experiment; C represents the vegetation coverage; i is a model parameter reflecting W a The degree of influence on wind erosion energy; T represents the unit time of each test.

[0014] Furthermore, the different working conditions include different rainfall intensity gradients and sand cover thickness gradients.

[0015] Furthermore, the key water erosion process parameters include: runoff time, cumulative runoff, erosion sediment yield and peak flow.

[0016] Furthermore, the constructed water erosion energy model is:

[0017] S water =aP b

[0018] P=γQ' m H mean T unit

[0019] Where: S water represents the amount of sediment produced by water erosion; a represents the influence of various factors of the hydrological underlying surface on the sediment production and transport in the basin; b represents the influence of factors such as rainfall and surface runoff on the sediment production and transport in the basin; P represents the runoff erosion energy; γ represents the runoff bulk density; Q' m represents the peak flow modulus, which is the ratio of the peak flow of a rainfall event to the basin area; H mean represents the average rainfall runoff depth; T unit Indicates unit time.

[0020] Furthermore, the sand production prediction model constructed by combining the wind erosion energy model and the water erosion energy model is as follows:

[0021] SF =aP b E c

[0022] Where: S F Indicates the sediment yield under composite erosion energy.

[0023] In a second aspect, the present invention further provides a sediment yield prediction system based on wind-water combined erosion energy, which is applied to the above-mentioned sediment yield prediction method based on wind-water combined erosion energy to predict sediment yield in a combined erosion environment. The system comprises:

[0024] The wind erosion energy module is used to obtain experimental data including different starting wind speeds, soil moisture content, and vegetation coverage variables through wind erosion dynamics experiments; based on the obtained experimental data, an improved wind erosion energy model is constructed;

[0025] The water erosion energy module is used to obtain key water erosion process parameters under different working conditions through simulated rainfall tests; and to construct a water erosion energy model based on key water erosion process parameters and improved runoff erosion energy;

[0026] The sand production prediction module is used to combine the wind erosion energy model and the water erosion energy model to construct a sand production prediction model under composite erosion energy, and to predict the sand production under composite erosion environment.

[0027] In a third aspect, an embodiment of the present invention further provides an electronic device comprising a processor and a memory, wherein the memory stores machine executable instructions that can be executed by the processor, and the processor executes the machine executable instructions to implement the above-mentioned method for predicting sand production based on wind-water combined erosion energy.

[0028] From the above technical solutions, it can be seen that the present invention provides a method and system for predicting sediment yield based on wind-water combined erosion energy. Compared with the existing technology, the present invention has at least the following beneficial effects:

[0029] 1. The present invention is a sediment production prediction method that combines wind erosion and water erosion energy to construct a composite model, which facilitates the high-precision simulation of the sediment production process in composite erosion areas and provides a scientific basis for the evaluation of soil and water conservation benefits.

[0030] 2. This invention takes the perspective of energetics into full consideration of the physical nature of the erosion process, accurately grasps the intertwined characteristics of wind erosion and water erosion in the time dimension, and has a good fitting effect. It can make high-precision predictions of sediment yield in a complex erosion environment.

[0031] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0032] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0034] The accompanying drawings are used to provide further understanding of the present invention and constitute a part of the specification. They are used to explain the present invention together with the embodiments of the present invention and do not constitute a limitation of the present invention.

[0035] Figure 1 A schematic flow chart of a method for predicting sediment yield based on wind-water combined erosion energy provided by an embodiment of the present invention;

[0036] Figure 2 Schematic diagram comparing wind erosion amounts predicted by the optimized model and measured wind erosion amounts in sand-covered bedrock, sand-covered loess, and loess erosion areas provided in an embodiment of the present invention;

[0037] Figure 3 A schematic diagram showing the changing trend of the sediment yield per unit area of a loess slope as a function of runoff erosion energy provided by an embodiment of the present invention;

[0038] Figure 4 A schematic diagram showing the changing trend of sediment yield per unit area of a sand-covered slope with runoff erosion energy provided by an embodiment of the present invention;

[0039] Figure 5 A schematic diagram showing a comparison between the simulated and measured sediment yields of the sediment yield prediction model under composite erosion energy provided by an embodiment of the present invention;

[0040] Figure 6 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0041] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments.

[0042] In describing the present invention, it should be noted that some processes described in this specification and accompanying drawings include multiple operations that appear in a specific order. However, it should be understood that these operations may be performed in a different order than the order in which they appear, or may be performed in parallel. Furthermore, the use of various sequence numbers is for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0043] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention as claimed, but rather merely represents selected embodiments of the present invention. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without creative effort shall fall within the scope of protection of the present invention.

[0044] See also Figure 1 As shown, an embodiment of the present invention provides a method for predicting sediment yield based on wind-water combined erosion energy, which mainly includes the following steps:

[0045] Step 1: Conduct wind erosion dynamics experiments under different wind speed gradients, soil moisture, and vegetation coverage;

[0046] Step 2: Based on the experimental data from step 1, soil moisture content, vegetation coverage, and starting wind speed factors are introduced into the traditional wind erosion energy formula to construct a wind erosion energy model;

[0047] Step 3: Conduct indoor simulated rainfall tests, design different rainfall intensity gradients and sand cover thickness gradients, and accurately measure key water erosion process parameters such as runoff time, cumulative runoff, eroded sediment yield, and peak flow under various conditions;

[0048] Step 4, constructing a water erosion energy model based on the rainfall test data in step 3 and the improved runoff erosion energy;

[0049] In step 5, the wind erosion energy model of step 2 is combined with the water erosion energy model constructed based on runoff erosion energy in step 4 to construct a sand production prediction model under composite erosion energy. The constructed sand production prediction model is used to achieve high-precision simulation of the sand production process in the composite erosion area.

[0050] The method of the present invention innovatively reveals the erosion dynamics mechanism from an energetics perspective, which is conducive to the high-precision simulation of the sand production process in complex erosion areas and provides a scientific basis for the evaluation of soil and water conservation benefits.

[0051] The following combination Figure 2-Figure 5 As shown, taking the sand-covered bedrock, sand-covered loess and loess erosion areas in the wind and water combined erosion area as examples, the specific implementation methods of the method of the present invention are introduced in detail:

[0052] In this embodiment, the method of the present invention is specifically implemented according to the following steps:

[0053] Step 1: The soil used in the wind erosion dynamics test was collected from the sand-covered bedrock (Hailestaigou), sand-covered loess (Liudaogou) and loess erosion area (Zhifanggou) in the wind-water composite erosion area. Through field investigation and analysis of regional meteorological data, the wind speeds required for the wind tunnel simulation test in the study area were determined to be 6m / s, 9m / s, 12m / s, 15m / s and 18m / s, which were consistent with the natural wind speed in the test area, including the maximum wind speed in the study area. By measuring the soil moisture content in the study area, three test gradients of soil moisture content were established: 1%, 3% and 5%. By extracting NDVI data, three test gradients of vegetation coverage were determined: 0%, 20% and 40%.

[0054] The specific process of step 2 includes:

[0055] Step 2.1, construct an improved wind erosion energy model:

[0056] The traditional wind erosion energy formula is as follows:

[0057]

[0058] Where: E Initial represents wind erosion energy, J·a / m2, which is actually the wind erosion energy per unit volume. For the near surface, it is the wind erosion energy per unit area; ρ represents the atmospheric density, kg / m 3 ; V represents the monthly average wind speed, m / s; EPT i represents monthly potential evaporation, mm; P i Indicates the average monthly precipitation, mm; D i Indicates the day of the month.

[0059] By introducing variables such as starting wind speed, soil moisture content, and vegetation coverage into the traditional wind erosion energy formula, an improved wind erosion energy model is constructed as follows:

[0060]

[0061] Where: is the wind erosion energy per unit area per unit time, J / (min·m2); V wind Indicates the wind speed involved in the test, m / s; W aIndicates the soil moisture content involved in the test, %; C indicates the vegetation coverage, %; T indicates the unit time of each test, min. Considering that the evaporation and precipitation are constants in the test conditions of this wind tunnel test, The value of is set to 1.

[0062] In step 2.2, perform a nonlinear regression analysis based on the data obtained in step 1 and the improved wind erosion energy model from step 2.1. Based on the simulation results for each study area, calculate the wind erosion energy for each region. Substitute the experimentally obtained wind speed, soil moisture content, vegetation cover, sand table area, erosion time, and sediment yield into the model. Based on the wind erosion energy model for the study area, determine the model parameters m, n, and i for the study area during the calculation process.

[0063] The fitting formula is as follows:

[0064]

[0065] Where: S wind It represents the wind erosion amount per unit area per unit time measured in the experiment, kg / (min·m2); m is the proportional coefficient for adjusting the model results to match the actual values; n reflects the nonlinear degree of the combined effect of various wind erosion factors, affecting the sensitivity of wind erosion amount to changes in variables; i reflects the influence of vegetation coverage on wind erosion amount. The larger its value, the more obvious the inhibitory effect of vegetation coverage on wind erosion amount.

[0066] In this embodiment, the wind erosion energy model is calculated, and the model parameters m, n, and i of the sand-covered bedrock, sand-covered loess, and loess erosion areas are calibrated during the calculation process. The calibrated wind erosion energy model parameters m are 8.118*10 -4 、7.932*10 -4 , 1.727*10 -4 , n are 1.681, 1.423, 1.637, and i are 0.181, 0.342, 0.275, respectively. The fitting results are as follows Figure 2 shown.

[0067] The specific operation process of step 3 is as follows:

[0068] Using an indoor artificial rainfall simulation device, test soil samples were collected from undisturbed loess and aeolian sand in a typical wind-water combined erosion area. Using a controlled variable method, four rainfall intensity gradients of 1.0, 1.5, 2.0, and 2.5 mm / min were set. The experiment involved exposed loess slopes and sand-covered slopes with sand thicknesses of 0.5, 1.0, 2.0, 2.5, 5.0, and 10.0 cm, respectively. Key parameters such as the initial time of runoff generation, cumulative runoff generation, total sediment yield, and peak flow were monitored under different treatment conditions.

[0069] The specific process of step 4 is:

[0070] Step 4.1, Modified runoff erosion energy:

[0071] The formula for initial runoff erosion power is as follows:

[0072] P=Q' m H

[0073] Where: P is the runoff erosion energy, m4 / (s·km2); Q' m is the peak flow modulus, which is the ratio of the peak flow of a rainfall event to the basin area, m3 / (s·km2); H is the rainfall runoff depth, which is the ratio of the total rainfall amount to the basin area.

[0074] In this embodiment, the bulk density parameter is introduced to convert the rainfall runoff depth into the average runoff depth, so that the runoff erosion energy under different conditions can be measured and compared under a unified time standard. The improved formula is:

[0075] P=γQ' m H mean T unit

[0076] Where: γ is the runoff density, N / m 3 ;H mean is the average rainfall runoff depth, m / s; T unit The unit time is s.

[0077] At this time, the physical dimension of P is:

[0078]

[0079] The physical dimension of the basic unit of energy, joule, is:

[0080] dimJ=ML 2 T -2

[0081] Further deduction yields:

[0082] dimP=ML 2 T -2 L -2 T -1 =JL -2 T -1

[0083] It can be seen from this that the improved runoff erosion energy P represents the water erosion energy per unit time and area of a rainfall experiment, J / (min·m2).

[0084] In step 4.2, a nonlinear regression analysis is performed based on the data obtained in step 3 and the improved water erosion energy model in step 4.1. The relationship between the sediment yield per unit area and time and the runoff erosion energy of different events satisfies the power function relationship:

[0085] S water =aP b

[0086] Where: S water It is the sediment yield per unit area per unit time, kg / (min·m2).

[0087] The fitting effect of the sediment yield per unit area per unit time and runoff erosion energy on loess slope is as follows: Figure 3 As shown, the fitting formula is S Water =38.728P 1.324 , R 2 The fitting effect of the sediment yield per unit area and time of the sand-covered slope and the runoff erosion energy is as follows: Figure 4 As shown in the figure, the sediment yield per unit area and runoff erosion energy of different events satisfy the power function relationship, that is, S water =18.795P 0.690 , R 2 The fitting degree is 0.565, which is lower than that of loess slope.

[0088] Step 5: Combine the wind erosion energy sediment yield prediction model in step 2.1 with the water erosion energy model based on runoff erosion energy in step 4.1 to construct a sediment yield prediction model under composite erosion energy. This is shown in the following formula:

[0089] S F =aP b E c

[0090] According to the analysis of test data, there is a significant power function relationship between wind erosion energy, water erosion energy and sediment yield at different times, namely: S F =0.493P 0.458 E 0.575 , coefficient of determination R 2 is 0.891, and the fitting effect is as follows Figure 5 As shown in Figure 2, the model has a high degree of fit and good prediction ability. Compared with the model without considering wind erosion energy, R 2 The fitting effect of the sediment production prediction model based on wind-water composite erosion energy is significantly improved.

[0091] From the description of the above embodiments, those skilled in the art can know that: the present invention provides a method for predicting sediment production based on wind-water combined erosion energy. From the perspective of energetics, it fully considers the physical nature of the erosion process, accurately grasps the interlaced characteristics of wind erosion and water erosion in the time dimension, and has a good fitting effect. It can make high-precision predictions of sediment production in a combined erosion environment. This method innovatively reveals the erosion dynamics mechanism from an energetics perspective, achieves high-precision simulation of the sediment production process in a combined erosion area, and provides a scientific basis for the evaluation of soil and water conservation benefits. The present invention analyzes the combined erosion mechanism of wind erosion and water erosion from the perspective of erosion energy by constructing a unified dimensional system of wind erosion energy and water erosion energy, which is of great significance for revealing the deep mechanism of energy interaction and superposition in the process of sediment production and transportation by wind-water combined erosion.

[0092] Furthermore, an embodiment of the present invention also provides a sediment yield prediction system based on wind-water combined erosion energy, which is applied to the sediment yield prediction method based on wind-water combined erosion energy described in the above embodiment to perform sediment yield prediction calculations under a combined erosion environment. The system mainly includes:

[0093] The wind erosion energy module is used to obtain experimental data including different starting wind speeds, soil moisture content, and vegetation coverage variables through wind erosion dynamics experiments; based on the obtained experimental data, an improved wind erosion energy model is constructed;

[0094] The water erosion energy module is used to obtain key water erosion process parameters under different working conditions through simulated rainfall tests; and to construct a water erosion energy model based on key water erosion process parameters and improved runoff erosion energy;

[0095] The sand production prediction module is used to combine the wind erosion energy model and the water erosion energy model to construct a sand production prediction model under composite erosion energy, and use the sand production prediction model to predict the sand production under composite erosion environment.

[0096] The embodiment of the present invention provides a sand production prediction system based on wind and water combined erosion energy. Its implementation principle and technical effects are the same as those of the aforementioned method embodiment. For the sake of brief description, for parts not mentioned in this embodiment, please refer to the corresponding content in the aforementioned method embodiment, and no further details will be given here.

[0097] Further, refer to Figure 6 As shown, an embodiment of the present invention also provides an electronic device that can execute the above method or system. The electronic device may include a processor 10, a memory 11, a communication bus 12 and a communication interface 13, and may also include a computer program stored in the memory 11 and run on the processor 10.

[0098] In some embodiments, the processor 10 may be composed of an integrated circuit, for example, a single packaged integrated circuit, or a plurality of packaged integrated circuits with the same or different functions, including one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and a combination of various control chips. The processor 10 is the control core (Control Unit) of the electronic device, which uses various interfaces and lines to connect the various components of the entire electronic device, and executes or executes programs or modules stored in the memory 11, and calls the data stored in the memory 11 to perform various functions of the electronic device and process data.

[0099] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, electronic devices, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0100] It should be noted that the word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention can be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer.

[0101] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0102] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present invention. The above description is only a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art who can easily conceive of changes or substitutions within the technical scope disclosed in the present invention should be covered by the scope of protection of the present invention.

Claims

1. A method for predicting sediment yield based on wind and water combined erosion energy, characterized in that: The method includes: Through wind erosion dynamics experiments, experimental data including different starting wind speeds, soil moisture content, and vegetation coverage variables were obtained; based on the obtained experimental data, an improved wind erosion energy model was constructed; The key water erosion process parameters under different working conditions were obtained through simulated rainfall tests; a water erosion energy model was constructed based on the key water erosion process parameters and the improved runoff erosion energy; A sand production prediction model under composite erosion energy is constructed by combining the wind erosion energy model and the water erosion energy model. The sand production prediction model is used to predict the sand production under composite erosion environment.

2. The method for predicting sediment yield based on wind-water combined erosion energy according to claim 1, characterized in that: In this method, undisturbed soil samples are collected from the wind-water composite erosion area for wind erosion dynamics tests. The test wind speed gradient is determined through meteorological data analysis, and the test gradient of soil moisture content and vegetation coverage is established.

3. The method for predicting sediment yield based on wind-water combined erosion energy according to claim 1, characterized in that: The constructed wind erosion energy model is: Where: E represents wind erosion energy; EPT i represents monthly potential evaporation; P i represents the average monthly precipitation; ρ represents the atmospheric density; V wind Indicates the wind speed involved in the test; V C Indicates starting wind speed; W a represents soil moisture content; C represents vegetation coverage; i is a model parameter; T represents the unit time of each test.

4. The method for predicting sediment yield based on wind-water combined erosion energy according to claim 1, characterized in that: The different working conditions include different rainfall intensity gradients and sand cover thickness gradients.

5. The method for predicting sediment yield based on wind-water combined erosion energy according to claim 1, characterized in that: The key water erosion process parameters include: runoff time, cumulative runoff, erosion sediment yield and peak flow.

6. The method for predicting sediment yield based on wind-water combined erosion energy according to claim 3, characterized in that: The constructed water erosion energy model is: S water =aP b P=γQ’ m H mean T unit Where: S water represents the amount of sediment produced by water erosion; a represents the influence of various factors of the hydrological underlying surface on the sediment production and transport in the basin; b represents the influence of factors such as rainfall and surface runoff on the sediment production and transport in the basin; P represents the runoff erosion energy; γ represents the runoff bulk density; Q' m represents the peak flow modulus, which is the ratio of the peak flow of a rainfall event to the basin area; H mean represents the average rainfall runoff depth; T unit Indicates unit time.

7. The method for predicting sediment yield based on wind-water combined erosion energy according to claim 6, characterized in that: The sediment production prediction model constructed by combining the wind erosion energy model and the water erosion energy model is: S F =aP b E c Where: S F Indicates the sediment yield under composite erosion energy.

8. A sediment yield prediction system based on wind and water combined erosion energy, characterized by: When applied, the method for predicting sediment yield based on wind-water combined erosion energy according to any one of claims 1 to 7 is executed to predict sediment yield in a combined erosion environment, the system comprising: The wind erosion energy module is used to obtain experimental data including different starting wind speeds, soil moisture content, and vegetation coverage variables through wind erosion dynamics experiments; based on the obtained experimental data, an improved wind erosion energy model is constructed; The water erosion energy module is used to obtain key water erosion process parameters under different working conditions through simulated rainfall tests; and to construct a water erosion energy model based on key water erosion process parameters and improved runoff erosion energy; The sand production prediction module is used to combine the wind erosion energy model and the water erosion energy model to construct a sand production prediction model under composite erosion energy, and to predict the sand production under composite erosion environment.

9. An electronic device, characterized in that: It includes a processor and a memory, the memory stores machine executable instructions that can be executed by the processor, and the processor executes the machine executable instructions to implement a sand production prediction method based on wind-water combined erosion energy as described in any one of claims 1 to 7.

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