Infiltration method and system for calculating straw-covered slope

Abstract

The invention discloses an infiltration method and system for calculating a straw-covered slope, and the method comprises the steps: S1, obtaining a test sample based on an indoor artificial simulation rainfall test, and obtaining a sample index based on the test sample; s2, on the basis of the sample indexes, a classic infiltration model serves as a basic framework, and a bare soil infiltration forecasting model suitable for bare soil is constructed on the basis of measured data; s3, the proportional relation between the accumulated infiltration amount of the straw-covered slope and the corresponding bare slope is calculated; s4, constructing a straw coverage infiltration model based on the proportional relation and the bare soil infiltration forecasting model; and S5, inputting measured data to be detected into the straw covering infiltration model to forecast the accumulated infiltration amount of the straw covering measure slope. According to the method, the accumulated infiltration amount of the slope with the straw covering measure is forecasted in a product form. The method has an important value for evaluating the infiltration benefit of a straw covering measure.

Description

Technical Field

[0001] The present invention relates to the technical field of slope infiltration calculation, and in particular to a method and system for calculating the infiltration of a straw-covered slope. Background Art

[0002] Infiltration is the process by which rainwater, falling on the ground, seeps into the soil from the surface. It is a crucial component of the field water cycle, determining the rate at which rainfall enters the soil, the amount of surface runoff generated during rainstorms, and the risk of soil erosion (Hu Fangrong, 1988; Warren and Lewis, 1995; Lei Tingwu et al., 2017). Infiltration estimation generally falls into two types: one is to develop an empirical model based on measured data through statistical methods, which lacks a practical physical basis; the other is to develop a process model based on water balance principles and Darcy's law, taking into account parameters with practical physical significance, such as flow dynamics, saturated hydraulic conductivity, initial water content, and other boundary conditions.

[0003] Infiltration estimation methods are generally based on bare soil forecasts, that is, by fitting measured rainfall process data into a classic infiltration model, and evaluating the model's applicability through statistical indicators. However, when straw mulching measures are implemented on slopes, such as covering or mixing crop straw into the soil, the hydrological process of slope infiltration is completely changed, increasing the difficulty of infiltration forecasting. Straw mulching measures can effectively promote rainfall infiltration and reduce soil erosion, making them an important factor to consider in soil erosion prediction models. However, existing infiltration models rarely consider the impact of crop straw mixing in the soil on water movement after straw mulching is implemented, and there is a lack of suitable estimation models. Summary of the Invention

[0004] In order to solve the above problems, the present invention proposes a method for calculating the infiltration of straw-covered slopes, which specifically includes:

[0005] Step S1: obtaining test samples based on an indoor artificial simulated rainfall test, and obtaining sample indicators based on the test samples;

[0006] Step S2: Based on the sample indicators, the classical infiltration model is used as a basic framework, and a bare soil infiltration prediction model suitable for bare soil is constructed based on the measured data;

[0007] Step S3: using the straw mulching measure as an infiltration factor, calculating the proportional relationship between the cumulative infiltration amount of the straw-covered slope and the corresponding bare slope;

[0008] Step S4: constructing a straw mulching infiltration model based on the proportional relationship and the bare soil infiltration prediction model;

[0009] Step S5: inputting the measured data to be detected into the straw mulching infiltration model to predict the cumulative infiltration amount of the straw mulching measure.

[0010] Optionally, the indoor artificial simulated rainfall test is carried out using a trough-type down-spraying rainfall machine and a soil water tank. The rainfall intensity simulated by the rainfall machine is in the range of 20-120 mm / h, and the simulation is performed by controlling the swing frequency of the sprinkler nozzle. The experimental object is a variable slope soil water tank with a specification of 2m×1m×0.5m. There are wheels at the bottom of the tank for easy movement, and a triangular confluence is provided in the front to facilitate the smooth discharge of runoff and sediment.

[0011] Optionally, the process of obtaining the test sampling includes: before each rainfall, the soil is sieved through a 1 cm sieve, fully air-dried, and filled by weighing and layering to ensure that the soil bulk density is consistent. After the test begins, the runoff time is recorded. After the runoff begins, runoff and sediment samples are taken every 5 minutes. The rainfall lasts for 1 hour. After the test ends, the runoff volume is measured to obtain the test sampling.

[0012] Optionally, the sample indicators include single rainfall runoff and single rainfall infiltration.

[0013] Optional, the details of the sub-rainfall runoff depth include:

[0014] R=(V1+V2+V3+…+V N ) / S q

[0015] Among them, R is the runoff depth of the rainfall, in mm, V1 to V N is the total runoff in each rainfall period, in L, N is the number of rainfall runoff periods, in times, Sq is the slope area, in m 2 .

[0016] Optionally, the rainfall infiltration amount specifically includes:

[0017] I=PR

[0018] Among them, I is the rainfall infiltration, unit is mm, P is the rainfall, unit is mm, R is the rainfall runoff, unit is mm.

[0019] Optionally, in step S2, the content of the infiltration prediction model specifically includes:

[0020] i(t)=0.5St -0.5 +i c

[0021] Where i(t) is the infiltration rate, S is the imbibition rate, i c is the steady permeability rate.

[0022] Optionally, in step S3, the content of the proportional relationship specifically includes:

[0023] Ic =CI r / CI b

[0024] Among them, CI r 、CI b are the cumulative infiltration of the covered slope and the corresponding bare soil slope, respectively.

[0025] Optionally, in step S4, the contents of the straw mulching infiltration model specifically include:

[0026] I(t) c =I c ×I(t) b

[0027] Where, I(t) c is the infiltration amount of the slope with straw mulching, I c is the infiltration factor, I(t) b is the infiltration rate of bare soil slope.

[0028] The present invention also discloses a system for calculating infiltration of a straw-covered slope, the system comprising:

[0029] An index acquisition module is used to obtain test samples based on an indoor artificial simulated rainfall test, and obtain sample indicators based on the test samples;

[0030] A prediction initial model construction module is used to construct a bare soil infiltration prediction model suitable for bare soil based on the sample indicators and the classical infiltration model as a basic framework based on the measured data;

[0031] The ratio calculation module is used to calculate the ratio between the cumulative infiltration of the straw-covered slope and the corresponding bare slope using the straw-covered measure as the infiltration factor;

[0032] A straw mulching measure model construction module is used to construct a straw mulching infiltration model based on the proportional relationship and the bare soil infiltration prediction model;

[0033] The straw mulching infiltration prediction module is used to input the measured data to be detected into the straw mulching infiltration model to predict the cumulative infiltration amount of the straw mulching slope.

[0034] Compared with the prior art, the present invention has the following beneficial effects:

[0035] This paper proposes, for the first time, an infiltration prediction model for straw-mulched slopes based on the infiltration factor of straw mulching practices and, using an appropriate bare soil infiltration model, establishes a model for predicting infiltration on straw-mulched slopes. This method has a wider applicability than traditional methods, combining soil characteristics to determine appropriate infiltration models for different soils and using a multiplication formula to predict cumulative infiltration on covered slopes. This method is of great value in evaluating the infiltration benefits of straw-mulching tillage practices. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solution of the present invention, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0037] Figure 1 A flow chart of a method for calculating infiltration of a straw-covered slope according to an embodiment of the present invention;

[0038] Figure 2 This is a diagram of an artificial simulated rainfall test according to an embodiment of the present invention;

[0039] Figure 3 Schematic diagram of the simulation results of the verification model according to the embodiment of the present invention. DETAILED DESCRIPTION

[0040] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0041] Example 1

[0042] A method for calculating infiltration on straw-covered slopes, such as Figure 1 As shown, the method includes:

[0043] Step S1: obtaining test samples based on an indoor artificial simulated rainfall test, and obtaining sample indicators based on the test samples.

[0044] Through indoor artificial simulated rainfall tests, the rainfall infiltration process data of slopes with different rainfall intensities, slopes, initial soil moisture contents and straw burial amounts, as well as the corresponding bare slopes, were observed, including infiltration rate and time step, etc.; the artificial simulated rainfall test was carried out using a trough-type downspout rainfall machine and a soil water tank. The rainfall machine simulated rainfall intensity in the range of 20-120 mm / h, which was simulated by controlling the swing frequency of the sprinkler head. The experimental object was a variable slope soil water tank with specifications of 2m×1m×0.5m (length×width×depth). The bottom of the water tank had wheels for easy movement, and a triangular confluence was provided in the front to facilitate the smooth discharge of runoff and sediment. According to the coverage area of the rainfall machine and the size of the soil water tank, a combination of 3 rainfall machines and 2 water tanks (such as Figure 2shown).

[0045] The filling depth of the soil trough is 0.35m. Before each rainfall, the soil is first sieved with a 1cm sieve and fully dried in the sun and air. The soil is loaded by weighing and filling in layers to ensure that the soil bulk density is consistent. The runoff time is recorded after the start of the test. After the start of runoff, runoff and sediment samples are taken every 5 minutes, and the rainfall lasts for 1 hour. The runoff volume is measured immediately after the end of the test. The indicator obtained from the rainfall test sampling is the runoff volume (L), which needs to be converted into runoff and sediment data indicators, including the runoff depth per rainfall (mm) and the infiltration volume per rainfall (mm).

[0046] (1) The runoff depth of a rainfall event is:

[0047] R=(V1+V2+V3+…+V N ) / S q

[0048] Where R is the runoff depth of a single rainfall, in mm, V1 to V N is the total runoff in each rainfall period, in L, N is the number of rainfall runoff periods, in times, Sq is the slope area, in m 2 .

[0049] (2) Rainfall infiltration: The test is an indoor simulated rainfall test, without considering water evaporation. According to the water balance principle, the infiltration amount is:

[0050] I=PR

[0051] Where I is the rainfall infiltration per time, in mm; P is the rainfall amount per time, in mm; and R is the rainfall runoff per time, in mm.

[0052] Step S2: Based on the sample indicators, the classic infiltration model is used as a basic framework, and a bare soil infiltration prediction model suitable for bare soil is constructed based on the measured data.

[0053] Based on classic infiltration models, including the empirical model Kostiakov (1932) model, Horton (1941) model, and the physical model Philip (1957) formula and Green-Ampt (1911) model, an appropriate infiltration prediction model for bare soil is determined by fitting and testing measured data. The infiltration prediction model is introduced using the Philip (1957) infiltration formula as an example. The formula is:

[0054] i(t)=0.5St -0.5 +i c

[0055] Where i(t) is the infiltration rate, S is the imbibition rate, i c is the steady permeability rate.

[0056] Classical physical process models are commonly used in infiltration models. These are generally based on the law of conservation of energy and Darcy's law, and they consider multiple complex factors, such as the dynamic saturated hydraulic conductivity, initial water content, and initial and other boundary conditions. These models primarily include Green-Ampt (1911), Philip (1957), and Smith-Parlange (1978). Model parameters have practical physical meanings and clearly characterize their corresponding physical implications. The Green-Ampt infiltration model is suitable for soils with low initial water content, particularly coarse textures and soils with a distinct wetting front. The Philip infiltration model is generally applicable to one-dimensional vertical infiltration in mean soils and requires further improvement for infiltration prediction in heterogeneous soils.

[0057] Step S3: Using the straw covering measure as the infiltration factor, the proportional relationship between the cumulative infiltration amount of the straw-covered slope and the corresponding bare slope is calculated.

[0058] The straw mulch infiltration factor (abbreviated as I c ), that is, the ratio of the infiltration of the slope with straw mulching and burial to the infiltration of the corresponding bare soil slope. It is believed that there is a ratio relationship between the cumulative infiltration of the slope with different straw burial amounts and the corresponding bare slope, that is,

[0059] I c =CI r / CI b

[0060] Where, CI r and CI b They represent the cumulative infiltration of covered slopes (mm) and the corresponding cumulative infiltration of bare soil slopes (mm), respectively.

[0061] Step S4: constructing a straw mulching infiltration model based on the proportional relationship and the bare soil infiltration prediction model.

[0062] Based on the ratio relationship between the cumulative infiltration of slopes with different straw burial amounts and the corresponding bare slopes, combined with the established suitable bare soil infiltration model, the product form of different straw coverage and bare soil infiltration model was established, namely the straw coverage infiltration model, which is expressed as:

[0063] I(t) c =I c ×I(t) b

[0064] Where, I(t) c is the infiltration rate of the straw-covered slope, I c is the infiltration factor, I(t) bis the infiltration rate of bare soil slope.

[0065] Step S5: inputting the measured data to be detected into the straw mulching infiltration model to predict the cumulative infiltration amount of the straw mulching slope.

[0066] The deviation between the simulated data and the measured data of the straw mulching infiltration model was tested by T test and 1:1 line test method to clarify its prediction accuracy. Taking the bare black soil slope and the corn straw buried black soil slope as examples, a black soil straw mulching infiltration prediction model was established, and the model simulation results were tested based on the T test and 1:1 line test method. The example results are shown in Figure 2. Figure 3 shown.

[0067] Example 2

[0068] A system for calculating infiltration of a straw-covered slope, the system comprising:

[0069] The index acquisition module is used to obtain test samples based on an indoor artificial simulated rainfall test, and obtain sample indicators based on the test samples.

[0070] Through indoor artificial simulated rainfall tests, the rainfall infiltration process data of slopes with different rainfall intensities, slopes, initial soil moisture contents and straw burial amounts, as well as the corresponding bare slopes, were observed, including infiltration rate and time step, etc.; the artificial simulated rainfall test was carried out using a trough-type downspout rainfall machine and a soil water tank. The rainfall machine simulated rainfall intensity in the range of 20-120 mm / h, which was simulated by controlling the swing frequency of the sprinkler head. The experimental object was a variable slope soil water tank with specifications of 2m×1m×0.5m (length×width×depth). The bottom of the water tank had wheels for easy movement, and a triangular confluence was provided in the front to facilitate the smooth discharge of runoff and sediment. According to the coverage area of the rainfall machine and the size of the soil water tank, a combination of 3 rainfall machines and 2 water tanks (such as Figure 2 shown).

[0071] The filling depth of the soil trough is 0.35m. Before each rainfall, the soil is first sieved with a 1cm sieve and fully dried in the sun and air. The soil is loaded by weighing and filling in layers to ensure that the soil bulk density is consistent. The runoff time is recorded after the start of the test. After the start of runoff, runoff and sediment samples are taken every 5 minutes, and the rainfall lasts for 1 hour. The runoff volume is measured immediately after the end of the test. The indicator obtained from the rainfall test sampling is the runoff volume (L), which needs to be converted into runoff and sediment data indicators, including the runoff depth per rainfall (mm) and the infiltration volume per rainfall (mm).

[0072] (1) The runoff depth of a rainfall event is:

[0073] R=(V1+V2+V3+…+V N ) / S q

[0074] Where R is the runoff depth of a single rainfall, in mm, V1 to V N is the total runoff in each rainfall period, in L, N is the number of rainfall runoff periods, in times, Sq is the slope area, in m 2 .

[0075] (2) Rainfall infiltration: The test is an indoor simulated rainfall test, without considering water evaporation. According to the water balance principle, the infiltration amount is:

[0076] I=PR

[0077] Where I is the rainfall infiltration per time, in mm; P is the rainfall amount per time, in mm; and R is the rainfall runoff per time, in mm.

[0078] The prediction initial model construction module is used to construct a bare soil infiltration prediction model suitable for bare soil based on the sample indicators, using the classic infiltration model as a basic framework and measured data.

[0079] Based on classic infiltration models, including the empirical model Kostiakov (1932) model, Horton (1941) model, and the physical model Philip (1957) formula and Green-Ampt (1911) model, an appropriate infiltration prediction model for bare soil is determined by fitting and testing measured data. The infiltration prediction model is introduced using the Philip (1957) infiltration formula as an example. The formula is:

[0080] i(t)=0.5St -0.5 +i c

[0081] Where i(t) is the infiltration rate, S is the imbibition rate, i c is the steady permeability rate.

[0082] Classical physical process models are commonly used in infiltration models. These are generally based on the law of conservation of energy and Darcy's law, and they consider multiple complex factors, such as the dynamic saturated hydraulic conductivity, initial water content, and initial and other boundary conditions. These models primarily include Green-Ampt (1911), Philip (1957), and Smith-Parlange (1978). Model parameters have practical physical meanings and clearly characterize their corresponding physical implications. The Green-Ampt infiltration model is suitable for soils with low initial water content, particularly coarse textures and soils with a distinct wetting front. The Philip infiltration model is generally applicable to one-dimensional vertical infiltration in mean soils and requires further improvement for infiltration prediction in heterogeneous soils.

[0083] The proportion calculation module is used to take the straw mulching measure as the infiltration factor and calculate the proportional relationship between the cumulative infiltration amount of the straw-covered slope and the corresponding bare slope.

[0084] The straw mulch infiltration factor (abbreviated as I c ), that is, the ratio of the infiltration of the slope with straw mulching and burial to the infiltration of the corresponding bare soil slope. It is believed that there is a ratio relationship between the cumulative infiltration of the slope with different straw burial amounts and the corresponding bare slope, that is,

[0085] I c =CI r / CI b

[0086] Where, CI r and CI b They represent the cumulative infiltration of covered slopes (mm) and the corresponding cumulative infiltration of bare soil slopes (mm), respectively.

[0087] The straw mulching measure model construction module is used to construct a straw mulching infiltration model based on the proportional relationship and the bare soil infiltration prediction model.

[0088] Based on the ratio relationship between the cumulative infiltration of slopes with different straw burial amounts and the corresponding bare slopes, combined with the established suitable bare soil infiltration model, the product form of different straw coverage and bare soil infiltration model was established, namely the straw coverage infiltration model, which is expressed as:

[0089] I(t) c =I c ×I(t) b

[0090] Where, I(t) c is the infiltration rate of the straw-covered slope, I c is the infiltration factor, I(t) b is the infiltration rate of bare soil slope.

[0091] The straw mulching infiltration prediction module is used to input the measured data to be detected into the straw mulching infiltration model to predict the cumulative infiltration amount of the straw mulching slope.

[0092] The deviation between the simulated data and the measured data of the straw mulching infiltration model was tested by T test and 1:1 line test method to clarify its prediction accuracy. Taking the bare black soil slope and the corn straw buried black soil slope as examples, a black soil straw mulching infiltration prediction model was established, and the model simulation results were tested based on the T test and 1:1 line test method. The example results are shown in Figure 2. Figure 3 shown.

[0093] The embodiments described above are merely descriptions of preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Without departing from the spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by persons skilled in the art should fall within the scope of protection defined by the claims of the present invention.

Claims

1. A method for calculating infiltration of straw-covered slopes, characterized in that: The method comprises: Step S1: obtaining test samples based on an indoor artificial simulated rainfall test, and obtaining sample indicators based on the test samples; Step S2: Based on the sample indicators, the classical infiltration model is used as a basic framework, and a bare soil infiltration prediction model suitable for bare soil is constructed based on the measured data; Step S3: using the straw mulching measure as an infiltration factor, calculating the proportional relationship between the cumulative infiltration amount of the straw-covered slope and the corresponding bare slope; Step S4: constructing a straw mulching infiltration model based on the proportional relationship and the bare soil infiltration prediction model; Step S5: inputting the measured data to be detected into the straw mulching infiltration model to predict the cumulative infiltration amount of the straw mulching measure.

2. The method for calculating the infiltration of a straw-covered slope according to claim 1, characterized in that: The indoor artificial simulated rainfall test was carried out using a trough-type down-spraying rainfall machine and a soil water tank. The rainfall intensity simulated by the rainfall machine was in the range of 20-120 mm / h, which was simulated by controlling the swing frequency of the sprinkler nozzle. The experimental object was a variable slope soil water tank with a specification of 2m×1m×0.5m. There were wheels at the bottom of the tank for easy movement, and a triangular confluence was provided in the front to facilitate the smooth discharge of runoff and sediment.

3. The method for calculating the infiltration of a straw-covered slope according to claim 2, characterized in that: The process of obtaining the test samples includes: before each rainfall, the soil is sieved through a 1 cm sieve, fully air-dried, and filled by weighing and layering to ensure that the soil bulk density is consistent. After the test begins, the runoff time is recorded. After the runoff begins, runoff and sediment samples are taken every 5 minutes. The rainfall lasts for 1 hour. After the test ends, the runoff volume is measured to obtain the test samples.

4. The method for calculating infiltration of a straw-covered slope according to claim 1, wherein: The sample indicators include the sub-rainfall runoff volume and the sub-rainfall infiltration volume.

5. The method for calculating infiltration of a straw-covered slope according to claim 4, characterized in that: The specific contents of the rainfall runoff depth include: R=(V1+V2+V3+…+V N ) / S q Among them, R is the runoff depth of the rainfall, in mm, V1 to V N is the total runoff of each rainfall period, in L, N is the number of rainfall periods, in times, S q is the slope area, in m 2 .

6. The method for calculating infiltration of a straw-covered slope according to claim 4, characterized in that: The content of the rainfall infiltration volume specifically includes: I=PR Among them, I is the rainfall infiltration, unit is mm, P is the rainfall, unit is mm, R is the rainfall runoff, unit is mm.

7. The method for calculating the infiltration of a straw-covered slope according to claim 1, characterized in that In step S2, the content of the infiltration prediction model specifically includes: i(t)=0.5St -0.5 +i c Where i(t) is the infiltration rate, S is the imbibition rate, i c is the steady infiltration rate, and t is the rainfall duration.

8. The method for calculating the infiltration of a straw-covered slope according to claim 1, characterized in that In step S3, the content of the proportional relationship specifically includes: AND c =CI r / CI b Among them, CI r 、CI b are the cumulative infiltration of the covered slope and the corresponding bare soil slope, respectively.

9. The method for calculating infiltration of a straw-covered slope according to claim 1, characterized in that: In step S4, the straw mulching infiltration model specifically includes: I(t) c =I c ×I(t) b Where, I(t) c is the infiltration amount of the slope with straw mulching, I c is the infiltration factor, I(t) b is the infiltration rate of bare soil slope.

10. A system for calculating infiltration of straw-covered slopes, wherein the system applies the infiltration method according to any one of claims 1 to 9, characterized in that include: An index acquisition module is used to obtain test samples based on an indoor artificial simulated rainfall test, and obtain sample indicators based on the test samples; A prediction initial model construction module is used to construct a bare soil infiltration prediction model suitable for bare soil based on the sample indicators and the classical infiltration model as a basic framework based on the measured data; The proportion calculation module is used to take the straw mulching measure as the infiltration factor and calculate the proportional relationship between the cumulative infiltration of the straw-covered slope and the corresponding bare slope; A straw mulching measure model construction module is used to construct a straw mulching infiltration model based on the proportional relationship and the bare soil infiltration prediction model; The straw mulching infiltration prediction module is used to input the measured data to be detected into the straw mulching infiltration model to predict the cumulative infiltration amount of the straw mulching slope.

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