Method and device for predicting sediment transport ratio of river basin

Abstract

The present disclosure relates to the technical field of watershed water and sediment regulation, and provides a method and device for predicting a watershed sediment transport ratio. The method comprises: obtaining a slope sediment yield parameter and a runoff parameter of a target watershed; calculating a target slope sediment yield according to the slope sediment yield parameter; calculating a target runoff according to the runoff parameter; and introducing the target slope sediment yield and the target runoff into a preset sediment transport ratio prediction model to predict a target sediment transport ratio. The present disclosure can greatly improve the application range and prediction accuracy of the prediction of the watershed sediment transport ratio.

Description

Technical Field

[0001] This disclosure relates to the field of watershed water and sediment regulation technology, and in particular to a method and apparatus for predicting watershed sediment transport ratio. Background Technology

[0002] The sediment transport ratio in a watershed under natural conditions refers to the ratio of sediment transport at the watershed outlet to sediment yield from slope erosion, and is an important indicator characterizing the runoff sediment transport capacity within a watershed. Given the slope erosion characteristics within the watershed, a sediment transport ratio prediction method can be proposed to effectively calculate the sediment transport at the watershed outlet, providing a computational method for watershed sediment transport prediction. The natural sediment transport ratio in a watershed exhibits characteristics of significant fluctuations over time, tending towards a stable value with increasing time scale. Numerous studies have shown that the multi-year average of the sediment transport ratio in a watershed under natural conditions ranges from 0 to 2, with significant differences between different watersheds. Specifically, the sediment transport ratio in the Loess Plateau region is around 1.00, in the Yangtze River basin it is 0.20–0.60, in the Pearl River basin it is 0.36–0.41, and in the Huai River basin it is 0.10–0.40.

[0003] Under natural conditions, the watershed sediment transport ratio is closely related to watershed area, topography, climate, and vegetation cover type. The variation patterns of the watershed sediment transport ratio are complex, and the accuracy and universality of prediction methods are relatively poor. Currently, there are two methods for calculating the watershed sediment transport ratio: the first method derives the formula based on physical processes; however, the sediment transport ratio involves complex mechanisms of slope sediment yield and runoff sediment transport, leading to poor applicability of the theoretical formula across different watersheds. The second method establishes an empirical relationship between the natural sediment transport ratio and influencing factors by analyzing watershed hydrological observation data. Empirical formulas have the advantages of simplicity and ease of calculation, and are widely used in sediment transport ratio research. Because there are many influencing factors on the sediment transport ratio under natural conditions, and the current sediment transport ratio calculation formulas consider relatively few variables, the applicability and accuracy of the formulas are poor. Summary of the Invention

[0004] In view of this, the present disclosure provides a method and apparatus for predicting the sediment transport ratio in a watershed, in order to solve the problem that in the prior art, due to the large number of influencing factors on the sediment transport ratio under natural conditions, and the fact that the current sediment transport ratio calculation formula considers fewer variables, the applicability and calculation accuracy of the formula are poor.

[0005] A first aspect of this disclosure provides a method for predicting the sediment transport ratio in a watershed, comprising:

[0006] Obtain slope sediment yield parameters and runoff parameters for the target watershed;

[0007] Calculate the target slope sediment yield based on the slope sediment yield parameters;

[0008] Calculate the target runoff based on the runoff parameters;

[0009] The target slope sediment yield and the target runoff are imported into a preset sediment transport ratio prediction model to predict the target sediment transport ratio.

[0010] In some embodiments, the preset sediment transport ratio prediction model is:

[0011]

[0012] Wherein, SDR represents the target sediment transport ratio, M represents the target slope sediment yield, and Q... out The target runoff volume is represented by c, d, and e, which are constant parameters.

[0013] In some embodiments, calculating the target slope sediment yield based on the slope sediment yield parameter includes:

[0014] Based on a preset first calculation formula, and the rainfall erosion factor, soil erosion factor, slope length factor, slope gradient factor, vegetation cover factor, engineering protection measure factor, and watershed area parameters in the slope sediment yield parameters, the target slope sediment yield is calculated, wherein the first calculation formula includes:

[0015] M = 100 * R * K * L * S * C * P * A

[0016] Wherein, M represents the target slope sediment yield, R represents the rainfall erosion factor, K represents the soil erosion factor, L represents the slope length factor, S represents the slope gradient factor, C represents the vegetation coverage factor, P represents the engineering protection measures factor, and A represents the area of ​​the target watershed.

[0017] In some embodiments, the step of determining the rainfall erosion factor R includes:

[0018] Obtain rainfall erosivity data for each year within a preset number of years prior to the current time for the target area, and calculate the rainfall erosivity factor R for the current time using a preset second calculation formula, wherein the second calculation formula includes:

[0019]

[0020]

[0021] Among them, R i R represents the erosivity of rainfall in year i. ij Let F represent the erosivity of rainfall in the j-th half-month of the i-th year, k represent the number of rainy days in the j-th half-month, h represent the number of days with rainfall greater than 10 mm, and F represent the erosivity of rainfall in the j-th half-month. j,k,hThis represents the rainfall when the rainfall in the j-th half-month of the i-th year is greater than 10 mm. α represents a dimensionless correction parameter. When rainfall occurs from May to September, the value of α is 0.3957, and the value of α for other months is 0.3101.

[0022] In some embodiments, the step of determining the soil erosion factor K includes:

[0023] The volume fractions of gravel, fine sand, organic matter, and clay in the soil of the target area are obtained, along with the total integral. The soil erosion factor K is then calculated using a pre-defined third formula. The total integral represents the volume fraction of the soil excluding gravel. The third formula includes:

[0024]

[0025] SN1 = 1 - SAN / 100

[0026] Where K represents the soil erosion factor, SAN represents the volume fraction of sand and gravel, SIL represents the volume fraction of fine sand, SOC represents the volume fraction of organic matter, CLA represents the volume fraction of clay, and SN1 represents the total integral.

[0027] In some embodiments, the step of determining the slope length factor L includes:

[0028] Obtain the slope angle and slope length of the target area, and calculate the slope length factor L using a preset fourth calculation formula, wherein the fourth calculation formula includes:

[0029]

[0030] Where λ represents the slope length, α represents the slope length exponent, and θ represents the slope angle;

[0031] When tanθ ≥ 0.05, α = 0.5;

[0032] When 0.03 ≤ tanθ < 0.05, α = 0.4;

[0033] When 0.01≤tanθ<0.03, α=0.3; when tanθ<0.01, α=0.2.

[0034] In some embodiments, the step of determining the slope factor S includes:

[0035] Obtain the slope angle of the target area and calculate the slope factor S using a preset fifth calculation formula, wherein the fifth calculation formula includes:

[0036] S = 10.8 * sinθ + 0.03ifθ < 5°

[0037] S=16.8*sinθ-0.5if 5°<θ<10°

[0038] S=21.9*sinθ-0.96 ifθ≥10°

[0039] Where θ represents the slope angle.

[0040] In some embodiments, the step of determining the vegetation cover factor C includes:

[0041] Obtain a preset vegetation coverage comparison table;

[0042] The vegetation type of the target area is matched with the vegetation coverage table to determine the vegetation coverage factor C.

[0043] In some embodiments, the step of determining the engineering protection factor P includes:

[0044] Obtain the slope angle of the target area and calculate the engineering protection measure factor P using a preset third calculation formula, wherein the fourth calculation formula includes:

[0045] P = 0.2 + 0.03 × tanθ × 100

[0046] Where θ represents the slope angle.

[0047] In some embodiments, calculating the target runoff based on the runoff parameters includes:

[0048] The target runoff is calculated based on a preset sixth calculation formula, and the annual average rainfall and minimum runoff rainfall parameters, wherein the sixth calculation formula includes:

[0049] Q out =a*(F-F0) b

[0050] Among them, Q out The target runoff volume is represented by F, the average annual rainfall is represented by F0, the minimum runoff rainfall is represented by a and b, and constant parameters are represented by a and b.

[0051] In some embodiments, the method further includes:

[0052] Based on the target slope sediment yield and target sediment transport ratio, and the preset seventh calculation formula, the target outlet sediment transport is calculated, wherein the seventh calculation formula includes:

[0053]

[0054] Wherein, SDR represents the target sediment transport ratio, and M represents the target slope sediment yield. outThis indicates the target export volume of sand.

[0055] A second aspect of this disclosure provides an apparatus for predicting the sediment transport ratio in a watershed, comprising:

[0056] The acquisition module is used to acquire slope sediment yield parameters and runoff parameters for the target watershed;

[0057] The first calculation module is used to calculate the target slope sediment yield based on the slope sediment yield parameters.

[0058] The second calculation module is used to calculate the target runoff based on the runoff parameters;

[0059] The prediction module is used to import the target slope sediment yield and the target runoff into a preset sediment transport ratio prediction model to predict the target sediment transport ratio.

[0060] In some embodiments, the preset sediment transport ratio prediction model is:

[0061]

[0062] Wherein, SDR represents the target sediment transport ratio, M represents the target slope sediment yield, and Q... out The target runoff volume is represented by c, d, and e, which are constant parameters.

[0063] In some embodiments, the first computing module is further configured to:

[0064] Based on a preset first calculation formula, and the rainfall erosion factor, soil erosion factor, slope length factor, slope gradient factor, vegetation cover factor, engineering protection measure factor, and watershed area parameters in the slope sediment yield parameters, the target slope sediment yield is calculated, wherein the first calculation formula includes:

[0065] M = 100 * R * K * L * S * C * P * A

[0066] Wherein, M represents the target slope sediment yield, R represents the rainfall erosion factor, K represents the soil erosion factor, L represents the slope length factor, S represents the slope gradient factor, C represents the vegetation coverage factor, P represents the engineering protection measures factor, and A represents the area of ​​the target watershed.

[0067] In some embodiments, the step of determining the rainfall erosion factor R includes:

[0068] Obtain rainfall erosivity data for each year within a preset number of years prior to the current time for the target area, and calculate the rainfall erosivity factor R for the current time using a preset second calculation formula, wherein the second calculation formula includes:

[0069]

[0070]

[0071] Among them, R i R represents the erosivity of rainfall in year i. ij Let F represent the erosivity of rainfall in the j-th half-month of the i-th year, k represent the number of rainy days in the j-th half-month, h represent the number of days with rainfall greater than 10 mm, and F represent the erosivity of rainfall in the j-th half-month. j,k,h This represents the rainfall when the rainfall in the j-th half-month of the i-th year is greater than 10 mm. α represents a dimensionless correction parameter. When rainfall occurs from May to September, the value of α is 0.3957, and the value of α for other months is 0.3101.

[0072] In some embodiments, the step of determining the soil erosion factor K includes:

[0073] The volume fractions of gravel, fine sand, organic matter, and clay in the soil of the target area are obtained, along with the total integral. The soil erosion factor K is then calculated using a pre-defined third formula. The total integral represents the volume fraction of the soil excluding gravel. The third formula includes:

[0074]

[0075] SN1 = 1 - SAN / 100

[0076] Where K represents the soil erosion factor, SAN represents the volume fraction of sand and gravel, SIL represents the volume fraction of fine sand, SOC represents the volume fraction of organic matter, CLA represents the volume fraction of clay, and SN1 represents the total integral.

[0077] In some embodiments, the step of determining the slope length factor L includes:

[0078] Obtain the slope angle and slope length of the target area, and calculate the slope length factor L using a preset fourth calculation formula, wherein the fourth calculation formula includes:

[0079]

[0080] Where λ represents the slope length, α represents the slope length exponent, and θ represents the slope angle;

[0081] When tanθ ≥ 0.05, α = 0.5;

[0082] When 0.03 ≤ tanθ < 0.05, α = 0.4;

[0083] When 0.01≤tanθ<0.03, α=0.3; when tanθ<0.01, α=0.2.

[0084] In some embodiments, the step of determining the slope factor S includes:

[0085] Obtain the slope angle of the target area and calculate the slope factor S using a preset fifth calculation formula, wherein the fifth calculation formula includes:

[0086] S = 10.8 * sinθ + 0.03ifθ < 5°

[0087] S=16.8*sinθ-0.5if 5°<θ<10°

[0088] S=21.9*sinθ-0.96 ifθ≥10°

[0089] Where θ represents the slope angle.

[0090] In some embodiments, the step of determining the vegetation cover factor C includes:

[0091] Obtain a preset vegetation coverage comparison table;

[0092] The vegetation type of the target area is matched with the vegetation coverage table to determine the vegetation coverage factor C.

[0093] In some embodiments, the step of determining the engineering protection factor P includes:

[0094] Obtain the slope angle of the target area and calculate the engineering protection measure factor P using a preset third calculation formula, wherein the fourth calculation formula includes:

[0095] P = 0.2 + 0.03 × tanθ × 100

[0096] Where θ represents the slope angle.

[0097] In some embodiments, the second computing module is further configured to:

[0098] The target runoff is calculated based on a preset sixth calculation formula, and the annual average rainfall and minimum runoff rainfall parameters, wherein the sixth calculation formula includes:

[0099] Q out =a*(F-F0) b

[0100] Among them, Q out The target runoff volume is represented by F, the average annual rainfall is represented by F0, the minimum runoff rainfall is represented by a and b, and constant parameters are represented by a and b.

[0101] In some embodiments, the watershed sediment transport ratio prediction device further includes:

[0102] The third calculation module is used to calculate the target outlet sediment transport volume based on the target slope sediment yield and the target sediment transport ratio, as well as a preset seventh calculation formula, wherein the seventh calculation formula includes:

[0103]

[0104] Wherein, SDR represents the target sediment transport ratio, and M represents the target slope sediment yield. out This indicates the target export volume of sand.

[0105] A third aspect of this disclosure provides an electronic device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method described above.

[0106] A fourth aspect of this disclosure provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the above-described method.

[0107] A fifth aspect of this disclosure provides a computer program product comprising a computer program or instructions that, when executed by a processor, implement the steps of the method described above.

[0108] Beneficial effects

[0109] The beneficial effects of this disclosure compared to the prior art include at least the following: by obtaining the slope sediment yield parameters and runoff parameters of the target watershed; calculating the target slope sediment yield based on the slope sediment yield parameters; calculating the target runoff based on the runoff parameters; and importing the target slope sediment yield and the target runoff into a preset sediment transport ratio prediction model to predict the target sediment transport ratio, the applicability and accuracy of the prediction of the watershed sediment transport ratio are greatly improved. Attached Figure Description

[0110] To more clearly illustrate the technical solutions in the embodiments of this disclosure, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0111] Figure 1 This is a schematic diagram of an application scenario of the method for predicting the watershed sediment transport ratio provided in the embodiments of this disclosure;

[0112] Figure 2This is a flowchart of some embodiments of a method for predicting watershed sediment transport ratio according to the present disclosure;

[0113] Figure 3 This is a flowchart of some other embodiments of a method for predicting watershed sediment transport ratios provided in this disclosure;

[0114] Figure 4 This is a simplified structural schematic diagram of a watershed sediment transport ratio prediction device provided according to an embodiment of this disclosure;

[0115] Figure 5 This is a schematic diagram of an electronic device provided according to an embodiment of the present disclosure;

[0116] Figure 6 This is a schematic diagram illustrating a method for predicting the sediment transport ratio in a watershed according to an embodiment of this disclosure, and the results of prediction for watershed A using existing technology.

[0117] Figure 7 This is a schematic diagram of the fitting results of a watershed sediment transport ratio prediction method provided in an embodiment of this disclosure for watershed A. Detailed Implementation

[0118] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.

[0119] It should also be noted that, for ease of description, only the parts relevant to this disclosure are shown in the accompanying drawings. Unless otherwise specified, the embodiments and features described in this disclosure can be combined with each other.

[0120] It should be noted that the concepts of "first" and "second" mentioned in this disclosure are used only to distinguish different systems, devices, modules or units, and are not used to limit the order of functions performed by these systems, devices, modules or units or their interdependencies.

[0121] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0122] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

[0123] This disclosure will now be described in detail with reference to the accompanying drawings and embodiments.

[0124] Figure 1 This is a schematic diagram of an application scenario of a method for predicting watershed sediment transport ratio according to some embodiments of the present disclosure.

[0125] exist Figure 1 In the application scenario, firstly, the computing device 101 can obtain the slope sediment yield parameter 102 and runoff parameter 103 of the target watershed.

[0126] Secondly, the calculation device 101 can calculate the target slope sand yield 104 based on the slope sand yield parameter 102.

[0127] Furthermore, the calculation device 101 can calculate the target runoff 105 based on the runoff parameter 103.

[0128] Finally, the computing device 101 can import the target slope sediment yield 104 and the target runoff 105 into the preset sediment transport ratio prediction model 106 to predict the target sediment transport ratio 107.

[0129] It should be noted that the aforementioned computing device 101 can be either hardware or software. When the computing device is hardware, it can be implemented as a distributed cluster consisting of multiple servers or terminal devices, or as a single server or a single terminal device. When the computing device is software, it can be installed within the hardware devices listed above. It can be implemented as, for example, multiple software programs or software modules used to provide distributed services, or as a single software program or software module. No specific limitations are made here.

[0130] It should be understood that Figure 1 The number of computing devices shown is merely illustrative. Any number of computing devices can be used depending on implementation needs.

[0131] Continue to refer to Figure 2 The diagram illustrates a flow 200 of some embodiments of a method for predicting watershed sediment transport ratios according to the present disclosure. This method can be... Figure 1 The calculation device 101 in the middle is used to perform the calculation. The method for predicting the sediment transport ratio in this watershed includes the following steps:

[0132] Step 201: Obtain the slope sediment yield parameters and runoff parameters of the target watershed.

[0133] In some embodiments, the entity performing the method for predicting the watershed sediment transport ratio (e.g., Figure 1 The computing device 101 shown can be connected to the target device via a wired or wireless connection, and then obtain the slope sediment yield parameters and runoff parameters of the target watershed.

[0134] The target watershed can refer to the watershed area that needs to be predicted. Slope sediment yield parameters can refer to parameters related to slope sediment yield. Runoff parameters can refer to parameters related to runoff.

[0135] In some embodiments, slope sediment yield parameters may include rainfall erosion factors, soil erosion factors, slope length factors, slope gradient factors, vegetation cover factors, engineering protection measures factors, and watershed area, etc.; flow parameters may include average annual rainfall and minimum runoff rainfall, etc. The vegetation cover factor can refer to the calculation coefficient corresponding to different vegetation types covering different watersheds, and can be specified empirically. The engineering protection measures factor can refer to the coefficient corresponding to the construction protection related to the target watershed, and can be set empirically for different slope angles, where the slope angle can refer to the angle between the slope surface and the horizontal plane. The watershed area can refer to the measured area of ​​the target watershed. The average annual rainfall can refer to the average rainfall of the target watershed in the previous preset number of years. For example, the preset number can be 2, 3, 8, 15, etc., and can be set as needed. The average annual rainfall can refer to the minimum annual runoff rainfall, which can refer to the minimum annual rainfall that can generate surface runoff in the target watershed. Furthermore, rainfall erosion factors, soil erosion factors, slope length factors, and slope gradient factors are commonly used terms in this field and will not be elaborated upon further here.

[0136] In some optional implementations, the execution entity can determine the vegetation coverage factor C through the following steps: First, the execution entity can obtain a preset vegetation coverage reference table. Second, the execution entity can match the vegetation type of the target area with the vegetation coverage reference table to determine the vegetation coverage factor C.

[0137] A vegetation cover comparison table can refer to calculated coefficients corresponding to different vegetation types, set based on experience. As an example, this vegetation cover comparison table can be found in Table 1 below:

[0138] arable land orchard woodland shrub grassland water body other vegetation cover factor 0.05 0.08 0.001 0.05 0.10 0.00 0.05

[0139] Table 1. Vegetation Coverage Comparison Table

[0140] It should be noted that the aforementioned wireless connection methods may include, but are not limited to, 3G / 4G / 5G connections, WiFi connections, Bluetooth connections, WiMAX connections, Zigbee connections, UWB (ultra wideband) connections, and other currently known or future wireless connection methods.

[0141] Step 202: Calculate the target slope sediment yield based on the slope sediment yield parameters.

[0142] In some embodiments, the aforementioned executing entity can calculate the target slope sediment yield based on the slope sediment yield parameters. The target slope sediment yield can be the amount of sediment generated on the slope by the target watershed.

[0143] In some optional implementations, the aforementioned execution entity can calculate the target slope sediment yield based on a preset first calculation formula and the rainfall erosion factor, soil erosion factor, slope length factor, slope gradient factor, vegetation cover factor, engineering protection measure factor, and watershed area among the slope sediment yield parameters, wherein the first calculation formula includes:

[0144] M = 100 * R * K * L * S * C * P * A

[0145] Wherein, M represents the target slope sediment yield, R represents the rainfall erosion factor, K represents the soil erosion factor, L represents the slope length factor, S represents the slope gradient factor, C represents the vegetation coverage factor, P represents the engineering protection measures factor, and A represents the area of ​​the target watershed.

[0146] Step 203: Calculate the target runoff based on the runoff parameters.

[0147] In some embodiments, the aforementioned implementing entity may calculate the target runoff based on the runoff parameters. The target runoff may refer to the runoff of the target watershed under climate change conditions, caused by rainfall or other river transport mechanisms.

[0148] In some optional implementations, the aforementioned execution entity can calculate the target runoff based on a preset sixth calculation formula, and the annual average rainfall and minimum runoff rainfall in the runoff parameters, wherein the sixth calculation formula includes:

[0149] Q out =a*(F-F0) b

[0150] Among them, Q out The target runoff volume is represented by F, the average annual rainfall is represented by F0, the minimum runoff rainfall is represented by a and b, and constant parameters are represented by a and b.

[0151] Step 204: Input the target slope sediment yield and the target runoff into a preset sediment transport ratio prediction model to predict the target sediment transport ratio.

[0152] In some embodiments, the aforementioned executing entity can import the target slope sediment yield and the target runoff into a preset sediment transport ratio prediction model to predict the target sediment transport ratio. The sediment transport ratio prediction model can refer to a computational model used to predict the sediment transport ratio based on the target slope sediment yield and the target runoff. This computational model can be a fitting computational model.

[0153] In some alternative implementations, the sediment transport ratio prediction model is as follows:

[0154]

[0155] Wherein, SDR represents the target sediment transport ratio, M represents the target slope sediment yield, and Q... out The target runoff volume is represented by c, d, and e, which are constant parameters.

[0156] The beneficial effects of one of the above embodiments of this disclosure include at least the following: by obtaining the slope sediment yield parameters and runoff parameters of the target watershed; calculating the target slope sediment yield based on the slope sediment yield parameters; calculating the target runoff based on the runoff parameters; and importing the target slope sediment yield and the target runoff into a preset sediment transport ratio prediction model to predict the target sediment transport ratio, the applicability and accuracy of the prediction of the watershed sediment transport ratio are greatly improved.

[0157] In some embodiments, the step of determining the rainfall erosion factor R includes:

[0158] Obtain rainfall erosivity data for each year within a preset number of years prior to the current time for the target area, and calculate the rainfall erosivity factor R for the current time using a preset second calculation formula, wherein the second calculation formula includes:

[0159]

[0160]

[0161] Among them, R i R represents the erosivity of rainfall in year i. ij Let F represent the erosivity of rainfall in the j-th half-month of the i-th year, k represent the number of rainy days in the j-th half-month, h represent the number of days with rainfall greater than 10 mm, and F represent the erosivity of rainfall in the j-th half-month. j,k,h This represents the rainfall amount when the rainfall in the j-th half-month of the i-th year is greater than 10 mm. α represents a dimensionless correction parameter. When rainfall occurs from May to September, the value of α is 0.3957, and for other months, the value of α is 0.3101. The preset quantities can be 2, 3, 5, 8, 10, 15, etc., which will not be elaborated further here.

[0162] In some embodiments, the step of determining the soil erosion factor K includes:

[0163] The volume fractions of gravel, fine sand, organic matter, and clay in the soil of the target area are obtained, along with the total integral. The soil erosion factor K is then calculated using a pre-defined third formula. The total integral represents the volume fraction of the soil excluding gravel. The third formula includes:

[0164]

[0165] SN1 = 1 - SAN / 100

[0166] Where K represents the soil erosion factor, SAN represents the volume fraction of sand and gravel, SIL represents the volume fraction of fine sand, SOC represents the volume fraction of organic matter, CLA represents the volume fraction of clay, and SN1 represents the total integral.

[0167] Gravel volume fraction refers to the volume percentage of gravel in the soil of a target watershed. Fine sand volume fraction refers to the volume percentage of fine sand in the soil of a target watershed. Organic matter volume fraction refers to the volume percentage of organic matter in the soil of a target watershed. Clay volume fraction refers to the volume percentage of clay in the soil of a target watershed. Total integral refers to the volume percentage of other substances in the soil of a target watershed after removing gravel.

[0168] In some embodiments, the step of determining the slope length factor L includes:

[0169] Obtain the slope angle and slope length of the target area, and calculate the slope length factor L using a preset fourth calculation formula, wherein the fourth calculation formula includes:

[0170]

[0171] Where λ represents the slope length, α represents the slope length exponent, and θ represents the slope angle;

[0172] When tanθ ≥ 0.05, α = 0.5;

[0173] When 0.03 ≤ tanθ < 0.05, α = 0.4;

[0174] When 0.01≤tanθ<0.03, α=0.3; when tanθ<0.01, α=0.2.

[0175] Slope length and slope length index are commonly used calculation terms, and will not be explained in detail here.

[0176] In some embodiments, the step of determining the slope factor S includes:

[0177] Obtain the slope angle of the target area and calculate the slope factor S using a preset fifth calculation formula, wherein the fifth calculation formula includes:

[0178] S = 10.8 * sinθ + 0.03ifθ < 5°

[0179] S=16.8*sinθ-0.5if 5°<θ<10°

[0180] S=21.9*sinθ-0.96 ifθ≥10°

[0181] Where θ represents the slope angle.

[0182] In some embodiments, the step of determining the engineering protection factor P includes:

[0183] Obtain the slope angle of the target area and calculate the engineering protection measure factor P using a preset third calculation formula, wherein the fourth calculation formula includes:

[0184] P = 0.2 + 0.03 × tanθ × 100

[0185] Where θ represents the slope angle.

[0186] In some embodiments, calculating the target runoff based on the runoff parameters includes:

[0187] The target runoff is calculated based on a preset sixth calculation formula, and the annual average rainfall and minimum runoff rainfall parameters, wherein the sixth calculation formula includes:

[0188] Q out =a*(F-F0) b

[0189] Among them, Q out The target runoff volume is represented by F, the average annual rainfall is represented by F0, the minimum runoff rainfall is represented by a and b, and constant parameters are represented by a and b.

[0190] In some embodiments, the method further includes:

[0191] Based on the target slope sediment yield and target sediment transport ratio, and the preset seventh calculation formula, the target outlet sediment transport is calculated, wherein the seventh calculation formula includes:

[0192]

[0193] Wherein, SDR represents the target sediment transport ratio, and M represents the target slope sediment yield. out This indicates the target outflow sediment load. The target outflow sediment load can refer to the amount of sediment discharged from the target watershed.

[0194] The following is a specific example to illustrate this disclosure:

[0195] Because a large reservoir was built in Basin A in 2009, the period prior to 2009 was a phase of natural variation in the basin's sediment transport ratio. Historical data for Basin A were obtained, and the variation process of the sediment transport ratio in Basin A under natural conditions was calculated using the prediction method disclosed in this publication, the Sun Houcai formula, the Williams formula, the Gao Xubiao formula, and the Zhao Xiaoguang formula (the result of the Mutler formula is negative and is not shown here). The results are as follows. Figure 6 As shown.

[0196] Comparing the calculation results of different formulas, the sediment transport ratio change process obtained by the patented method basically covers the calculation results of other formulas.

[0197] The goodness of fit obtained by the first existing technology (Sun Houcai formula) in calculating the sediment transport ratio is 0.78.

[0198] The goodness of fit obtained by the second existing technology (Williams formula) in calculating the sediment transport ratio is 0.47.

[0199] The goodness of fit obtained by the third existing technology (Gao Xubiao formula) in calculating the sediment transport ratio is 0.12.

[0200] The fourth existing technology (Zhao Xiaoguang formula) yielded a goodness of fit of 0.20 for calculating the sediment transport ratio.

[0201] The fifth existing technique (Mutchler's formula) yielded a negative goodness of fit for calculating the sediment transport ratio.

[0202] The formulas of Sun Houcai, Williams, Gao Xubiao, Zhao Xiaoguang, and Mutchler are all existing technologies and will not be elaborated upon here.

[0203] And such Figure 7 As shown, the goodness of fit between the sediment transport ratio predicted in this disclosure and the actual observed value is 0.92, which is far higher than the calculation formula of the prior art.

[0204] Since the sediment transport ratio is closely related to the runoff and sediment production processes in a watershed, it changes dynamically over time under climate change conditions. Using a constant sediment transport ratio to predict short-term sediment loads will result in significant prediction errors. Therefore, the sediment transport ratio calculation method proposed in this patent should be used, as it offers higher prediction accuracy.

[0205] Continue to refer to Figure 3 The flowchart 300 illustrates further embodiments of the method for predicting watershed sediment transport ratios according to the present disclosure, which can be performed by... Figure 1The calculation device 101 in the middle is used to perform the operation. The method for predicting the sediment transport ratio in this watershed includes:

[0206] Step 301: Obtain slope sediment yield parameters and runoff parameters for the target watershed;

[0207] Step 302: Calculate the target slope sediment yield based on the slope sediment yield parameters;

[0208] Step 303: Calculate the target runoff based on the runoff parameters;

[0209] Step 304: Input the target slope sediment yield and the target runoff into a preset sediment transport ratio prediction model to predict the target sediment transport ratio, wherein the preset sediment transport ratio prediction model is:

[0210]

[0211] Wherein, SDR represents the target sediment transport ratio, M represents the target slope sediment yield, and Q... out The target runoff volume is represented by c, d, and e, which are constant parameters.

[0212] Step 305: Calculate the target outlet sediment transport volume based on the target slope sediment yield and target sediment transport ratio, and the preset seventh calculation formula, wherein the seventh calculation formula includes:

[0213]

[0214] Wherein, SDR represents the target sediment transport ratio, and M represents the target slope sediment yield. out This indicates the target export volume of sand.

[0215] In some embodiments, the specific implementation of steps 301-305 and the resulting technical effects can be found in [reference needed]. Figure 2 The steps in those corresponding embodiments will not be repeated here.

[0216] All of the above-mentioned optional technical solutions can be combined in any way to form the optional embodiments of this application, and will not be described in detail here.

[0217] The following are embodiments of the apparatus disclosed herein, which can be used to execute embodiments of the method disclosed herein. For details not disclosed in the apparatus embodiments of this disclosure, please refer to the embodiments of the method disclosed herein.

[0218] Further reference Figure 4 As an implementation of the above figures and methods, this disclosure provides some embodiments of a device for predicting watershed sediment transport ratios, which are similar to... Figure 2 The above-described method embodiments correspond to these.

[0219] like Figure 4 As shown, the watershed sediment transport ratio prediction device 400 in some embodiments includes:

[0220] The acquisition module 401 is used to acquire the slope sediment yield parameters and runoff parameters of the target watershed;

[0221] The first calculation module 402 is used to calculate the target slope sediment yield based on the slope sediment yield parameters.

[0222] The second calculation module 403 is used to calculate the target runoff based on the runoff parameters;

[0223] The prediction module 404 is used to import the target slope sediment yield and the target runoff into a preset sediment transport ratio prediction model to predict the target sediment transport ratio.

[0224] In some optional implementations of certain embodiments, the preset sediment transport ratio prediction model is as follows:

[0225]

[0226] Wherein, SDR represents the target sediment transport ratio, M represents the target slope sediment yield, and Q... out The target runoff volume is represented by c, d, and e, which are constant parameters.

[0227] In some optional implementations of certain embodiments, the first computing module 402 is further configured as follows:

[0228] Based on a preset first calculation formula, and the rainfall erosion factor, soil erosion factor, slope length factor, slope gradient factor, vegetation cover factor, engineering protection measure factor, and watershed area parameters in the slope sediment yield parameters, the target slope sediment yield is calculated, wherein the first calculation formula includes:

[0229] M = 100 * R * K * L * S * C * P * A

[0230] Wherein, M represents the target slope sediment yield, R represents the rainfall erosion factor, K represents the soil erosion factor, L represents the slope length factor, S represents the slope gradient factor, C represents the vegetation coverage factor, P represents the engineering protection measures factor, and A represents the area of ​​the target watershed.

[0231] In some optional implementations of certain embodiments, the step of determining the rainfall erosion factor R includes:

[0232] Obtain rainfall erosivity data for each year within a preset number of years prior to the current time for the target area, and calculate the rainfall erosivity factor R for the current time using a preset second calculation formula, wherein the second calculation formula includes:

[0233]

[0234]

[0235] Among them, R i R represents the erosivity of rainfall in year i. ij Let F represent the erosivity of rainfall in the j-th half-month of the i-th year, k represent the number of rainy days in the j-th half-month, h represent the number of days with rainfall greater than 10 mm, and F represent the erosivity of rainfall in the j-th half-month. j,k,h This represents the rainfall when the rainfall in the j-th half-month of the i-th year is greater than 10 mm. α represents a dimensionless correction parameter. When rainfall occurs from May to September, the value of α is 0.3957, and the value of α for other months is 0.3101.

[0236] In some optional implementations of certain embodiments, the step of determining the soil erosion factor K includes:

[0237] The volume fractions of gravel, fine sand, organic matter, and clay in the soil of the target area are obtained, along with the total integral. The soil erosion factor K is then calculated using a pre-defined third formula. The total integral represents the volume fraction of the soil excluding gravel. The third formula includes:

[0238]

[0239] SN1 = 1 - SAN / 100

[0240] Where K represents the soil erosion factor, SAN represents the volume fraction of sand and gravel, SIL represents the volume fraction of fine sand, SOC represents the volume fraction of organic matter, CLA represents the volume fraction of clay, and SN1 represents the total integral.

[0241] In some optional implementations of certain embodiments, the step of determining the slope length factor L includes:

[0242] Obtain the slope angle and slope length of the target area, and calculate the slope length factor L using a preset fourth calculation formula, wherein the fourth calculation formula includes:

[0243]

[0244] Where λ represents the slope length, α represents the slope length exponent, and θ represents the slope angle;

[0245] When tanθ ≥ 0.05, α = 0.5;

[0246] When 0.03 ≤ tanθ < 0.05, α = 0.4;

[0247] When 0.01≤tanθ<0.03, α=0.3; when tanθ<0.01, α=0.2.

[0248] In some alternative implementations of certain embodiments, the step of determining the slope factor S includes:

[0249] Obtain the slope angle of the target area and calculate the slope factor S using a preset fifth calculation formula, wherein the fifth calculation formula includes:

[0250] S = 10.8 * sinθ + 0.03ifθ < 5°

[0251] S=16.8*sinθ-0.5if 5°<θ<10°

[0252] S=21.9*sinθ-0.96 ifθ≥10°

[0253] Where θ represents the slope angle.

[0254] In some optional implementations of certain embodiments, the step of determining the vegetation cover factor C includes:

[0255] Obtain a preset vegetation coverage comparison table;

[0256] The vegetation type of the target area is matched with the vegetation coverage table to determine the vegetation coverage factor C.

[0257] In some optional implementations of certain embodiments, the step of determining the engineering protection factor P includes:

[0258] Obtain the slope angle of the target area and calculate the engineering protection measure factor P using a preset third calculation formula, wherein the fourth calculation formula includes:

[0259] P = 0.2 + 0.03 × tanθ × 100

[0260] Where θ represents the slope angle.

[0261] In some optional implementations of certain embodiments, the second computing module 403 is further configured as follows:

[0262] The target runoff is calculated based on a preset sixth calculation formula, and the annual average rainfall and minimum runoff rainfall parameters, wherein the sixth calculation formula includes:

[0263] Q out =a*(F-F0) b

[0264] Among them, Q outThe target runoff volume is represented by F, the average annual rainfall is represented by F0, the minimum runoff rainfall is represented by a and b, and constant parameters are represented by a and b.

[0265] In some optional implementations of certain embodiments, the watershed sediment transport ratio prediction device further includes:

[0266] The third calculation module is used to calculate the target outlet sediment transport volume based on the target slope sediment yield and the target sediment transport ratio, as well as a preset seventh calculation formula, wherein the seventh calculation formula includes:

[0267]

[0268] Wherein, SDR represents the target sediment transport ratio, and M represents the target slope sediment yield. out This indicates the target export volume of sand.

[0269] It is understandable that the modules described in the device 400 are similar to those in the reference. Figure 2 The steps in the described method correspond accordingly. Therefore, the operations, features, and beneficial effects described above for the method also apply to device 400 and the modules contained therein, and will not be repeated here.

[0270] like Figure 5 As shown, the electronic device 500 may include a processing unit (e.g., a central processing unit, a graphics processor, etc.) 501, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 502 or a program loaded from a storage device 508 into a random access memory (RAM) 503. The RAM 503 also stores various programs and data required for the operation of the electronic device 500. The processing unit 501, ROM 502, and RAM 503 are interconnected via a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.

[0271] Typically, the following devices can be connected to I / O interface 505: input devices 506 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 507 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 508 including, for example, magnetic tapes, hard disks, etc.; and communication devices 509. Communication device 509 allows electronic device 500 to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 5 An electronic device 500 with various devices is shown; however, it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed alternatively. Figure 5 Each box shown can represent a device or multiple devices as needed.

[0272] In particular, according to some embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, some embodiments of this disclosure include a computer program product comprising a computer program or instructions carried on a computer-readable medium, the computer program or instructions containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 509, or installed from a storage device 508, or installed from a ROM 502. When the computer program is executed by the processing device 501, it performs the functions defined in the methods of some embodiments of this disclosure.

[0273] It should be noted that, in some embodiments of this disclosure, the computer-readable medium described above may be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium may be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In some embodiments of this disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In some embodiments of this disclosure, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0274] In some implementations, clients and servers can communicate using any currently known or future-developed network protocol such as HTTP (Hypertext Transfer Protocol) and can interconnect with digital data communication (e.g., communication networks) of any form or medium. Examples of communication networks include local area networks (“LANs”), wide area networks (“WANs”), the Internet (e.g., the Internet of Things), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future-developed networks.

[0275] The aforementioned computer-readable medium may be included in the aforementioned device; or it may exist independently and not assembled into the electronic device. The aforementioned computer-readable medium carries one or more programs that, when executed by the electronic device, cause the electronic device to: acquire slope sediment yield parameters and runoff parameters of the target watershed; calculate the target slope sediment yield based on the slope sediment yield parameters; calculate the target runoff based on the runoff parameters; and import the target slope sediment yield and the target runoff into a preset sediment transport ratio prediction model to predict the target sediment transport ratio.

[0276] Computer program code for performing operations of some embodiments of this disclosure can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0277] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0278] The modules described in some embodiments of this disclosure can be implemented in software or hardware. The described modules can also be located in a processor, for example, and can be described as:

[0279] The system comprises an acquisition module, a first calculation module, a second calculation module, and a prediction module. For example, the acquisition module can also be described as "a module for acquiring slope sediment yield parameters and runoff parameters of a target watershed".

[0280] The functions described above in this document can be performed, at least in part, by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: Field Programmable Gate Arrays (FPGAs), Application-Specific Integrated Circuits (ASICs), Application Standard Products (ASSPs), System-on-Chip (SoCs), Complex Programmable Logic Devices (CPLDs), and so on.

[0281] The above description is merely a selection of preferred embodiments of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in the embodiments of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described inventive concept. For example, technical solutions formed by substituting the above-described features with (but not limited to) technical features with similar functions disclosed in the embodiments of this disclosure.

Claims

1. A method for predicting the sediment transport ratio in a watershed, characterized in that, include: Obtain slope sediment yield parameters and runoff parameters for the target watershed; Calculate the target slope sediment yield based on the slope sediment yield parameters; Calculate the target runoff based on the runoff parameters; The target slope sediment yield and the target runoff are imported into a preset sediment transport ratio prediction model to predict the target sediment transport ratio. The preset sediment transport ratio prediction model is as follows: Wherein, SDR represents the target sediment transport ratio, and M represents the target slope sediment yield. The target runoff volume is represented by c, d, and e, which are constant parameters.

2. The method according to claim 1, characterized in that, The calculation of the target slope sediment yield based on the slope sediment yield parameters includes: Based on a preset first calculation formula, and considering the rainfall erosion factor, soil erosion factor, slope length factor, slope gradient factor, vegetation cover factor, engineering protection measure factor, and watershed area among the slope sediment yield parameters, the target slope sediment yield is calculated, wherein the first calculation formula includes: Wherein, M represents the target slope sediment yield, R represents the rainfall erosion factor, K represents the soil erosion factor, L represents the slope length factor, S represents the slope gradient factor, C represents the vegetation coverage factor, P represents the engineering protection measures factor, and A represents the area of ​​the target watershed.

3. The method according to claim 2, characterized in that, The steps for determining the rainfall erosion factor R include: Obtain rainfall erosivity data for each year within a preset number of years prior to the current time for the target watershed, and calculate the rainfall erosivity factor R for the current time using a preset second calculation formula, wherein the second calculation formula includes: in, This represents the erosive force of rainfall in year i. Let represent the erosivity of rainfall in the j-th half-month of the i-th year, k represent the number of rainy days in the j-th half-month, and h represent the number of days with rainfall greater than 10 mm. This represents the rainfall when the rainfall in the j-th half-month of the i-th year is greater than 10 mm. α represents a dimensionless correction parameter. When the rainfall occurs from May to September, the value of α is 0.3957, and the value of α for other months is 0.3101.

4. The method according to claim 2, characterized in that, The steps for determining the soil erosion factor K include: The volume fractions of gravel, fine sand, organic matter, and clay in the soil of the target watershed are obtained, along with the total integral. The soil erosion factor K is then calculated using a pre-defined third formula. The total integral represents the volume fraction of the soil excluding gravel. The third formula includes: Where K represents the soil erosion factor, SAN represents the volume fraction of sand and gravel, SIL represents the volume fraction of fine sand, SOC represents the volume fraction of organic matter, CLA represents the volume fraction of clay, and SN1 represents the total integral.

5. The method according to claim 2, characterized in that, The steps for determining the slope length factor L include: Obtain the slope angle and slope length of the target watershed, and calculate the slope length factor L using a preset fourth calculation formula, wherein the fourth calculation formula includes: Where λ represents the slope length, α represents the slope length exponent, and θ represents the slope angle; when hour, ; when hour, ; when hour, ;when hour, .

6. The method according to claim 2, characterized in that, The steps for determining the slope factor S include: Obtain the slope angle of the target watershed and calculate the slope factor S using a preset fifth calculation formula, wherein the fifth calculation formula includes: Where θ represents the slope angle.

7. The method according to claim 2, characterized in that, The steps for determining the vegetation cover factor C include: Obtain a preset vegetation coverage comparison table; The vegetation type of the target watershed is matched with the vegetation coverage table to determine the vegetation coverage factor C.

8. The method according to claim 2, characterized in that, The steps for determining the engineering protection measure factor P include: Obtain the slope angle of the target watershed and calculate the engineering protection measure factor P using a preset eighth calculation formula, wherein the eighth calculation formula includes: Where θ represents the slope angle.

9. The method according to claim 1, characterized in that, The step of calculating the target runoff based on the runoff parameters includes: The target runoff is calculated based on a preset sixth calculation formula, and the annual average rainfall and minimum runoff rainfall parameters, wherein the sixth calculation formula includes: in, The target runoff volume is represented by F, and the average annual rainfall is represented by F. This represents the minimum runoff rainfall, and a and b represent constant parameters.

10. The method according to any one of claims 1 to 9, characterized in that, The method further includes: Based on the target slope sediment yield and target sediment transport ratio, and the preset seventh calculation formula, the target outlet sediment transport is calculated, wherein the seventh calculation formula includes: Wherein, SDR represents the target sediment transport ratio, and M represents the target slope sediment yield. This indicates the target export volume of sand.

11. A device for predicting the sediment transport ratio in a watershed, characterized in that, include: The acquisition module is used to acquire slope sediment yield parameters and runoff parameters for the target watershed; The first calculation module is used to calculate the target slope sediment yield based on the slope sediment yield parameters. The second calculation module is used to calculate the target runoff based on the runoff parameters; The prediction module is used to import the target slope sediment yield and the target runoff into a preset sediment transport ratio prediction model to predict the target sediment transport ratio. The preset sediment transport ratio prediction model is as follows: Wherein, SDR represents the target sediment transport ratio, and M represents the target slope sediment yield. The target runoff volume is represented by c, d, and e, which are constant parameters.

12. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 10.

13. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 10.

14. A computer program product, said computer program product comprising a computer program or instructions, characterized in that, When the computer program or instructions are executed by a processor, they implement the steps of the method as described in any one of claims 1 to 10.

Images