A quantitative assessment method and system for soil secondary salinization risk

Abstract

The present application discloses a method and system for quantitatively assessing the risk of secondary soil salinization, which relates to the field of soil risk assessment. The method includes: obtaining long-sequence monitoring data of groundwater depth in each sub-area; conducting water migration monitoring tests for groundwater depth control to determine the critical depth of secondary soil salinization; determining a set of characteristic values ​​based on the long-sequence monitoring data of groundwater depth and the critical depth of secondary soil salinization; determining the empirical frequency of each characteristic value based on the long-sequence monitoring data of groundwater depth, and drawing a frequency distribution curve; conducting tests on the occurrence and development process of soil salinization, and determining the control duration of secondary soil salinization in combination with the critical depth of secondary soil salinization; determining the probability of secondary soil salinization risk in the sub-area based on the frequency distribution curve and the control duration of secondary soil salinization, and then determining the risk of secondary soil salinization in the area to be assessed. The present application improves the theoretical and scientific nature of the risk assessment of secondary soil salinization.

Description

Technical Field

[0001] The present application relates to the field of soil risk assessment, and in particular to a method and system for quantitatively assessing soil secondary salinization risk based on frequency analysis. Background Art

[0002] Land resources are the most precious material resources for human survival and development. Soil salinization leads to a decline in soil fertility, inability to grow crops, and significantly reduces food production. It has become one of the most common environmental problems causing the reduction of global land resources. In recent years, with the gradual advancement of climate change and groundwater pressure extraction, the depth of groundwater has gradually increased, and the phenomenon of secondary soil salinization has gradually emerged. Therefore, there is an urgent need for a method that can scientifically and quantitatively assess the risk of secondary soil salinization, so as to provide basic support for salinization early warning and targeted governance, high-quality development of regional agriculture, efficient use of land resources, and conservation and protection of water resources. Summary of the invention

[0003] The purpose of this application is to provide a method and system for quantitative assessment of soil secondary salinization risk, which can improve the scientificity and theoretical nature of soil secondary salinization risk assessment, and thus improve the assessment accuracy of soil secondary salinization risk.

[0004] To achieve the above objectives, this application provides the following solutions:

[0005] In a first aspect, the present application provides a method for quantitatively assessing the risk of secondary soil salinization, comprising:

[0006] Divide the area to be assessed into different zones and obtain long-sequence monitoring data of groundwater depth in each zone;

[0007] For any sub-area, carry out water migration monitoring test for groundwater depth control in the sub-area, and determine the critical depth of soil secondary salinization in the sub-area;

[0008] Determine a set of soil secondary salinization risk characteristic values ​​for the sub-district based on the long-sequence monitoring data of groundwater depth and the critical depth of soil secondary salinization in the sub-district;

[0009] Determine the empirical frequency of the secondary salinization risk characteristic value of each soil in the sub-district based on the long-series monitoring data of the groundwater depth in the sub-district;

[0010] According to the empirical frequency of each soil secondary salinization risk characteristic value of the sub-region, a frequency distribution curve of the sub-region is drawn;

[0011] Conducting experiments on the occurrence and development process of soil salinization in the sub-region, and determining the control duration of soil secondary salinization in the sub-region in combination with the critical burial depth of soil secondary salinization in the sub-region;

[0012] According to the frequency distribution curve of the sub-area and the duration of soil secondary salinization control, the frequency corresponding to the duration of soil secondary salinization control in the sub-area is determined to obtain the soil secondary salinization risk probability in the sub-area;

[0013] The degree of secondary soil salinization in the area to be assessed is determined based on the risk probability of secondary soil salinization in each sub-area of ​​the area to be assessed.

[0014] In the second aspect, the present application provides a soil secondary salinization risk quantitative assessment system, comprising:

[0015] The groundwater monitoring module is used to divide the area to be assessed into zones and obtain the long-sequence monitoring data of groundwater depth in each zone;

[0016] A critical burial depth determination module is connected to the groundwater monitoring module and is used to carry out a water migration monitoring test for groundwater burial depth control in any sub-area to determine the critical burial depth of soil secondary salinization in the sub-area;

[0017] A characteristic value determination module, connected to the critical burial depth determination module, is used to determine the risk characteristic value set of soil secondary salinization in the sub-zone according to the long-sequence monitoring data of groundwater burial depth in the sub-zone and the critical burial depth of soil secondary salinization;

[0018] A characteristic frequency determination module, connected to the characteristic value determination module, for determining the empirical frequency of each soil secondary salinization risk characteristic value of the sub-zone according to the long-sequence monitoring data of the groundwater depth of the sub-zone;

[0019] A distribution curve drawing module, connected to the characteristic frequency determination module, is used to draw the frequency distribution curve of the partition according to the empirical frequency of each soil secondary salinization risk characteristic value of the partition;

[0020] The salinization process test module is connected to the critical burial depth determination module, and is used to carry out the soil salinization occurrence and development process test of the sub-zone, and determine the control time of the soil secondary salinization of the sub-zone in combination with the critical burial depth of the soil secondary salinization of the sub-zone;

[0021] A risk probability determination module is connected to the distribution curve drawing module and the salinization process test module, respectively, and is used to determine the frequency corresponding to the soil secondary salinization control duration of the partition according to the frequency distribution curve of the partition and the soil secondary salinization control duration, so as to obtain the soil secondary salinization risk probability of the partition;

[0022] The risk assessment module is connected to the risk probability determination module and is used to determine the degree of secondary salinization of soil in the area to be assessed according to the risk probability of secondary salinization of soil in each sub-area of ​​the area to be assessed.

[0023] According to the specific embodiments provided in this application, this application discloses the following technical effects:

[0024] The present application provides a method and system for quantitative assessment of soil secondary salinization risk, which calculates the soil secondary salinization risk probability for each sub-area in the assessment area, and can accurately assess the degree of salinization in large and small areas. In the process of calculating the probability of soil secondary salinization risk, the characteristic value of soil secondary salinization risk with hydrological statistical characteristics is determined according to the depth of groundwater, which can reflect the risk of soil secondary salinization, and further determine the empirical frequency of the characteristic value of soil secondary salinization risk and the frequency of soil secondary salinization control time, breaking the drawbacks of previous risk assessment methods that can only reflect the salt state, rather than quantitative assessment and calculation in the sense of probability theory, and realizing the quantitative assessment of soil secondary salinization risk in the sense of disaster science and probability theory, improving the scientificity and theoretical nature of soil secondary salinization risk assessment, and thus improving the theoretical nature and scientificity of soil secondary salinization risk assessment. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0026] Figure 1 A schematic flow chart of a method for quantitatively assessing the risk of secondary soil salinization provided in one embodiment of the present application.

[0027] Figure 2 Schematic diagram of the probability density function and probability distribution function of a random variable.

[0028] Figure 3 This is the frequency distribution curve of zone 1 in a certain region.

[0029] Figure 4 This is the frequency distribution curve of zone 2 in a certain region.

[0030] Figure 5 This is a frequency distribution curve of zone 3 in a certain region.

[0031] Figure 6 This is a frequency distribution curve of zone 4 in a certain area.

[0032] Figure 7 This is a frequency distribution curve of zone 5 in a certain region.

[0033] Figure 8This is a frequency distribution curve of zone 6 in a certain region.

[0034] Fig. 9 This is a frequency distribution curve of zone 7 in a certain region.

[0035] Fig.10 This is a frequency distribution curve of zone 8 in a certain area.

[0036] Fig.11 A schematic diagram of the functional modules of a soil secondary salinization risk quantitative assessment system provided in one embodiment of the present application.

[0037] Fig.12 A schematic diagram of the structure of a computer device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0038] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0039] At present, the main methods for assessing the risk of secondary soil salinization are: comprehensive index method, numerical simulation method, and remote sensing interpretation method. Among them, the comprehensive index method evaluates the risk of salinization by comprehensively considering many factors that affect secondary soil salinization. It requires the installation of multiple types of monitoring equipment, which is costly and has low resolution. The numerical simulation method simulates the migration law of soil salt on the basis of experiments to achieve risk assessment. This method has high requirements for hydrogeological and soil characteristic parameters, and it is difficult to accurately assess large areas. The remote sensing interpretation method is based on remote sensing images of the surface where salinization has occurred. It evaluates the degree of salinization through supervised classification remote sensing interpretation methods. Due to the limitations of remote sensing interpretation methods, it is difficult to accurately assess the risk of salinization in a small area.

[0040] In addition, the evaluation results of previous methods often only reflect a certain salt state, rather than the risk rate from the perspective of the possibility of risk events in the sense of risk. There is a lack of predictive evaluation and calculation of the risk of secondary soil salinization in terms of uncertainty and frequency, which makes the evaluation method lack theoretical basis. Many previous studies have shown that for land with given underlying surface and soil conditions, the depth of groundwater is the main hazard factor for secondary soil salinization. However, few studies have evaluated the risk of secondary soil salinization from the perspective of the hazard factor, and there is a lack of relevant theories and methods.

[0041] Therefore, the embodiment of the present application provides a soil secondary salinization risk assessment method based on hydrological frequency analysis, which uses groundwater depth as the soil secondary salinization risk characteristic value, thereby expressing the risk probability of soil secondary salinization from a new perspective that is more theoretical and scientific, and can provide support for high-quality development of regional agriculture, efficient use of land resources, and conservation and protection of water resources.

[0042] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0043] In an exemplary embodiment, Figure 1 As shown, a method for quantitatively assessing the risk of secondary soil salinization is provided, comprising the following steps 101 to 108.

[0044] Step 101, divide the area to be assessed into zones, and obtain long-sequence monitoring data of groundwater depth in each zone.

[0045] In a specific example, the area to be assessed is first divided into zones according to regional conditions, and then a groundwater depth monitoring well is set in each zone, and the groundwater depth of the corresponding zone is monitored through the groundwater depth monitoring well to obtain long-sequence monitoring data of the groundwater depth of each zone.

[0046] The regional conditions include soil properties, soil layering structure, vegetation cover type, meteorological conditions, hydrological conditions, etc. The groundwater depth monitoring well is a well capable of daily monitoring of groundwater depth.

[0047] The groundwater depth long sequence monitoring data includes the groundwater depth every day for many years. In this example, the groundwater depth long sequence monitoring data includes no less than 30 years of groundwater depth daily data.

[0048] Step 102: for any sub-area, a water migration monitoring test for groundwater depth control of the sub-area is carried out to determine the critical depth of secondary salinization of soil in the sub-area.

[0049] The depth of groundwater is the driving factor for the occurrence of secondary soil salinization. The shallower the groundwater depth, the more serious the soil salinization. However, there is a maximum groundwater depth that can move groundwater to the soil surface. To determine this critical depth, a soil water migration test is required. By controlling different groundwater levels, tracers are added to the groundwater, and the maximum groundwater depth at which the tracers can be monitored in the soil surface is measured. The critical depth of secondary soil salinization is the maximum groundwater depth corresponding to the migration of water to the soil surface under the action of capillary force, as determined by the water migration monitoring test.

[0050] In a specific example, tracers are added to groundwater at different depths in the sub-area, and the moisture in the soil surface is measured in real time to determine the maximum groundwater depth at which the tracer is monitored in the soil surface, and the maximum groundwater depth is used as the critical depth of soil secondary salinization in the sub-area. The critical depth of soil secondary salinization is used as the triggering threshold of soil secondary salinization.

[0051] Step 103, determining a set of risk characteristic values ​​of secondary soil salinization in the sub-zone according to the long-sequence monitoring data of groundwater depth in the sub-zone and the critical depth of secondary soil salinization.

[0052] The soil secondary salinization risk characteristic value set includes the soil secondary salinization risk characteristic value of each year, wherein the soil secondary salinization risk characteristic value of any year is the maximum duration of the groundwater depth being less than the critical depth of soil secondary salinization in that year.

[0053] Specifically, based on the correlation between groundwater depth and soil salinization, the annual maximum duration (unit: day) that the groundwater depth is less than the critical depth of soil secondary salinization is determined as the characteristic value of soil secondary salinization risk.

[0054] The occurrence and development of secondary soil salinization is a relatively slow process. The soil salinization event will not occur until the groundwater depth is less than the critical depth of secondary soil salinization and this state is maintained for a period of time. The longer the time, the more serious the salinization. In addition, the groundwater depth changes on an annual basis. Therefore, the characteristic value of the risk of secondary soil salinization is the maximum annual duration (unit: day) when the groundwater depth is less than the critical depth of secondary soil salinization.

[0055] Step 104, determining the empirical frequency of the secondary salinization risk characteristic value of each soil in the sub-zone according to the long-sequence monitoring data of the groundwater depth in the sub-zone.

[0056] In a specific example, the soil secondary salinization risk characteristic values ​​of the sub-areas are arranged from large to small. Assuming that the sub-areas have n The soil secondary salinization risk characteristic values ​​are arranged from large to small as follows: , , …, , …, The following formula is used to calculate the first m Empirical frequencies of characteristic values ​​of soil secondary salinization risk.

[0057] .

[0058] in, The partition m The empirical frequency of the soil secondary salinization risk characteristic value is greater than or equal to The empirical frequency of n is the number of soil secondary salinization risk characteristic values ​​for the sub-region, m is the serial number of the soil secondary salinization risk characteristic value, that is, greater than and equal to The number of eigenvalues.

[0059] Step 105: draw a frequency distribution curve of the partition according to the empirical frequency of each soil secondary salinization risk characteristic value of the partition.

[0060] Specifically, the empirical frequencies of the characteristic values ​​of secondary salinization risk of each soil were fitted to obtain the probability distribution line type, and the frequency distribution curve was drawn.

[0061] In the hydrological frequency analysis, the Pearson-III type is proved to be the most consistent with the hydrological characteristics. At the same time, the groundwater level is closely related to the changes in hydrological characteristics. Therefore, the frequency distribution curve of this application adopts the Pearson III curve.

[0062] Step 106, conducting an experiment on the occurrence and development process of soil salinization in the sub-zone, and determining the control time of the secondary salinization of the soil in the sub-zone in combination with the critical burial depth of the secondary salinization of the soil in the sub-zone.

[0063] In a specific example, within the range where the groundwater depth in the partition is less than the critical depth of secondary soil salinization in the partition, groundwater with different salt concentrations is set, and the salinity of the surface soil in the partition is monitored in real time under natural evaporation conditions. The timing starts when the salinity of the surface soil is greater than 0 and stops when the salinity of the surface soil is greater than the set salinization threshold. The timing time is used as the control duration of secondary soil salinization in the partition.

[0064] Specifically, the groundwater depth is set to be less than the critical depth of soil secondary salinization to ensure that groundwater can reach the surface continuously under the action of capillary force. Groundwater with different salt concentrations is set to match the groundwater mineralization in different regions. Under natural evaporation conditions, the surface soil salinity is monitored to see how long it takes to reach the salinization threshold of 0.5g / kg. The control duration of soil secondary salinization is the duration of the occurrence and development of soil secondary salinization from scratch.

[0065] Step 107, determining the frequency corresponding to the duration of control of secondary soil salinization of the partition according to the frequency distribution curve of the partition and the duration of control of secondary soil salinization of the partition, so as to obtain the risk probability of secondary soil salinization of the partition.

[0066] In a specific example, the probability density function of the secondary salinization risk characteristic value of each soil in the sub-area is first determined based on the frequency distribution curve using the following formula.

[0067] .

[0068] Then, according to the probability density function of the characteristic value of the risk of secondary salinization of soil in each partition, the frequency corresponding to the control duration of secondary salinization of soil in the partition is determined by the following formula.

[0069] .

[0070] The following formula is then used to determine the risk probability of secondary soil salinization in the sub-area.

[0071] .

[0072] in, for The probability density function of is the risk characteristic value of secondary salinization of any soil in the sub-region, is the shape parameter of the Pearson type III distribution, , is the scale parameter of the Pearson type III distribution, , is the location parameter of the Pearson type III distribution, for The gamma function of P is the frequency corresponding to the duration of soil secondary salinization control in the sub-area, indicating Greater than D 0 The probability of R is the risk probability of secondary soil salinization in the sub-zone, D 0 The duration of controlling secondary salinization of soil in the sub-zone, and Both said The probability distribution function of when x = D 0 The function value at .

[0073] The principle of the frequency calculation formula corresponding to the control duration of soil secondary salinization is introduced in detail below.

[0074] The important basic concepts of probability theory include events, probabilities and random variables. X express, X Different values ​​are taken according to different test results. Although it is impossible to know which value will appear in a test, there is a certain probability of obtaining a certain value. X is called a random variable.

[0075] Random variables can be classified into discrete and continuous types.

[0076] (1) Discrete random variable: If a random variable can only take a finite or infinite number of discrete values, then this random variable is called a discrete random variable.

[0077] (2) Continuous random variable: If a random variable can take any value in a finite interval, it is called a continuous random variable. Most hydrological phenomena are continuous random variables. For example, the flow rate at a station can vary between 0 and the limit value, so it can take any value between 0 and the limit flow rate.

[0078] Random variables are usually represented by capital letters, and their possible values ​​are represented by corresponding lowercase letters. X , and its possible values ​​are recorded as x If you take j value, then X = x 1, X = x 2, ..., X = x j . Generally x 1, x 2, ..., x j The value of a random variable corresponds to its probability one-to-one, and this correspondence is generally called the probability distribution of the random variable.

[0079] For discrete random variables, their probability distribution is generally expressed as a distribution column, as shown in Table 1.

[0080] Table 1 Probability distribution of discrete random variables

[0081]

[0082] in, p k is a random variable X Value x k The probability that it satisfies two conditions: p k ≥0; the sum of all probabilities equals 1.

[0083] For continuous random variables, since all its possible values ​​completely fill a certain interval, it is impossible to list all possible values ​​of the variable in a table. In addition, discrete random variables can have the probability of taking individual values; while the probability of a continuous random variable taking any individual value is zero, so it is impossible to study the probability of individual values ​​but only the probability of a certain interval.

[0084] Suppose there is a continuous random variable X , the value is x ,because X=x The probability of is zero, so events are generally not used when analyzing probability distribution. X=x The probability of an event X ≥ x The probability of P ( X ≥ x ) represents. We can also study the probability P ( X < x ). Obviously, the event X ≥ x Probability P ( X ≥ x ) is the value of the random variable x And change, so P ( X ≥ x )yes x A function of X The distribution function of F ( x ),Right now , which represents the random variable X Greater than or equal to a value x The probability of . Its geometric figure is as follows Figure 2 As shown in the figure, the probability distribution function is called a distribution curve in mathematics, and is usually called the cumulative frequency curve of a random variable in hydrology, or simply the frequency curve. x = x p When F ( x )= P ( X ≥ x p )= P , indicating that the random variable is greater than x p The possibility is P %.

[0085] The negative value of the derivative of the distribution function is called the density function, denoted by ,Right now The geometric curve of the density function is called the density curve. In hydrology, it is customary to express variables with the ordinate. x , the horizontal axis represents the probability density value ,like Figure 2 As shown. In fact, the relationship between the distribution function and the density function is the relationship between differentiation and integration. Therefore, if it is known that , we can find out by integration ,Right now The corresponding relationship is as follows Figure 2 shown.

[0086] Step 108: Determine the degree of secondary soil salinization in the area to be assessed based on the risk probability of secondary soil salinization in each sub-area of ​​the area to be assessed.

[0087] Furthermore, according to the risk level of secondary salinization of the soil in the area to be assessed, salinization warning and targeted governance are carried out in the area to be assessed to ensure high-quality agricultural development, efficient use of land resources, and conservation and protection of water resources in the area to be assessed. Specifically, if the risk probability of secondary salinization of the soil in any sub-area in the area to be assessed is greater than the set probability threshold, then alkalinization warning information for the corresponding sub-area is generated, prompting relevant personnel to carry out targeted governance of this sub-area. In addition, if the percentage of sub-areas in which the risk probability of secondary salinization of the soil in the area to be assessed is greater than the set probability threshold exceeds a certain percentage, then alkalinization warning information for the entire area to be assessed is generated, prompting relevant personnel to govern the entire area to be assessed, so as to improve the land resource utilization rate and agricultural development quality of the area to be assessed.

[0088] This application breaks the drawback that previous risk assessment methods can only reflect the salt status, but not quantitative assessment and calculation in the sense of probability theory. It determines that the groundwater depth can reflect the risk of soil secondary salinization as a hydrological statistical characteristic value. It derives the theoretical calculation formula for soil secondary salinization risk based on uncertainty theory, and proposes a quantitative assessment method for soil secondary salinization risk based on the frequency distribution of groundwater depth. It realizes the quantitative assessment of soil secondary salinization risk in the sense of disaster science and probability theory, improves the scientificity and theoretical nature of soil secondary salinization risk assessment, and thus improves the accuracy of soil secondary salinization risk assessment.

[0089] The following introduces the quantitative assessment process of soil secondary salinization risk in a certain area.

[0090] The area is located in the plain area along the river. The river perennially seeps into the groundwater, and the groundwater level has been running at a high level for a long time. At the same time, the area has a temperate continental climate with four distinct seasons. In spring and autumn, there are more winds and less rain, and the evaporation is strong, which makes the area a severely affected area of ​​secondary soil salinization. With the rapid development of the economy and society, water consumption has increased sharply, and groundwater extraction has increased year by year, resulting in a sharp drop in the groundwater level. The problem of soil salinization has been effectively curbed, but with the gradual advancement of groundwater over-exploitation management, the groundwater level has stopped falling and rebounded, and the problem of soil salinization has reappeared.

[0091] There are currently 8 groundwater monitoring wells with long-sequence daily monitoring frequency in the region, distributed in 8 sub-areas, and the length of the groundwater depth monitoring sequence is 32 years from 1990 to 2021. In addition, two monitoring points in the region were tested in an observation and research station, with a monitoring frequency of salinity of 1 month and a monitoring frequency of groundwater depth of 10 days, from May 1, 2018 to December 31, 2021. In order to understand the change process of groundwater depth and salinity in more detail, the soil surface salinity and groundwater depth data are linearly interpolated to the daily scale.

[0092] The quantitative assessment process of soil secondary salinization risk in the region includes the following steps (1) to (8).

[0093] (1) According to the location of monitoring wells in the area, the area was divided into 8 sub-areas using the Thiessen polygon method.

[0094] (2) Carry out water migration monitoring tests controlled by groundwater depth in each sub-district to determine the critical depth of soil secondary salinization in each sub-district. In one example, the critical depth of soil secondary salinization in a sub-district is 400 cm. Therefore, the characteristic value of soil secondary salinization risk is the maximum number of days per year when the groundwater depth is less than 400 cm.

[0095] (3) The characteristic values ​​of soil secondary salinization risk in each sub-region were statistically analyzed. The results are shown in Table 2.

[0096] Table 2 Statistical table of soil secondary salinization risk characteristic values ​​in each sub-region of a certain region from 1990 to 2022

[0097]

[0098] (4) Calculate the empirical frequency of the characteristic value of secondary salinization risk of each soil in each sub-zone.

[0099] (5) Draw the empirical data, apply the Pearson-Ⅲ curve for fitting, and draw the frequency distribution curve, such as Figures 3 to 10 shown.

[0100] (6) Determine the duration of controlling secondary soil salinization in the area.

[0101] Through the experiment on the occurrence and development process of soil salinization at the two observation and research stations, it can be determined that for the soil type in the area, it takes 35 days for soil salinization to develop from nothing to something. Therefore, the control period of secondary soil salinization is 35 days.

[0102] (7) Based on the frequency distribution curve determined in step (5) and the duration of soil secondary salinization control determined in step (6), calculate the frequency value when the duration of soil secondary salinization control is 35 days.。

[0103] When the groundwater depth of each sub-area is less than 4m and the duration reaches 35 days, the possibility of soil salinization risk events is shown in Table 3. The risk rates of sub-areas 3, 5 and 8 are relatively high, at 45.14%, 64.19% and 47.97% respectively, while the risk rates of sub-areas 1, 4 and 7 are relatively low, at 0.96%, 5.39% and 11.69% respectively. Among them, since sub-area 8 is close to the river, the groundwater is laterally recharged by the river, resulting in a higher water level and a higher risk of secondary soil salinization. The assessment results are consistent with the actual situation.

[0104] Table 3 Probability of soil secondary salinization risk in each sub-region

[0105]

[0106] The present application also provides an application scenario, which applies the above-mentioned soil secondary salinization risk quantitative assessment method. Specifically: The soil secondary salinization risk quantitative assessment method provided in this embodiment can be applied in the ecological restoration scenario of a certain area. In the ecological restoration scenario of a certain area, the soil secondary salinization risk quantitative assessment method provided in this embodiment is used to determine the soil secondary salinization risk probability of each sub-area in the area and the degree of soil secondary salinization in the area, and based on the soil secondary salinization risk probability of each sub-area in the area and the degree of soil secondary salinization in the area, early warning information is generated, and targeted governance of the ecological environment in the area is carried out to improve the land resource utilization rate and agricultural development quality in the area.

[0107] Based on the same inventive concept, the embodiment of the present application also provides a soil secondary salinization risk quantitative assessment system for implementing the soil secondary salinization risk quantitative assessment method involved above. The implementation scheme for solving the problem provided by the system is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more embodiments of the soil secondary salinization risk quantitative assessment system provided below can refer to the limitations of the soil secondary salinization risk quantitative assessment method above, and will not be repeated here.

[0108] In an exemplary embodiment, Fig.11 As shown, a soil secondary salinization risk quantitative assessment system is provided, including: a groundwater monitoring module 201, a critical burial depth determination module 202, a characteristic value determination module 203, a characteristic frequency determination module 204, a distribution curve drawing module 205, a salinization process test module 206, a risk probability determination module 207 and a risk assessment module 208.

[0109] The groundwater monitoring module 201 is used to divide the area to be evaluated into zones and obtain long-sequence monitoring data of the groundwater depth in each zone.

[0110] The critical burial depth determination module 202 is connected to the groundwater monitoring module 201. The critical burial depth determination module 202 is used to carry out a water migration monitoring test for groundwater burial depth control in any sub-area to determine the critical burial depth of soil secondary salinization in the sub-area.

[0111] The characteristic value determination module 203 is connected to the critical burial depth determination module 202, and the characteristic value determination module 203 is used to determine the soil secondary salinization risk characteristic value set of the partition according to the long-sequence monitoring data of the groundwater burial depth of the partition and the critical burial depth of soil secondary salinization.

[0112] The characteristic frequency determination module 204 is connected to the characteristic value determination module 203, and is used to determine the empirical frequency of each soil secondary salinization risk characteristic value of the sub-zone according to the long-sequence monitoring data of the groundwater depth of the sub-zone.

[0113] The distribution curve drawing module 205 is connected to the characteristic frequency determination module 204, and is used to draw the frequency distribution curve of the partition according to the empirical frequency of each soil secondary salinization risk characteristic value of the partition.

[0114] The salinization process test module 206 is connected to the critical burial depth determination module 202. The salinization process test module 206 is used to carry out the soil salinization occurrence and development process test of the partition, and determine the control time of the secondary salinization of the soil in the partition in combination with the critical burial depth of the secondary salinization of the soil in the partition.

[0115] The risk probability determination module 207 is connected to the distribution curve drawing module 205 and the salinization process test module 206 respectively. The risk probability determination module 207 is used to determine the frequency corresponding to the control duration of secondary salinization of soil in the partition according to the frequency distribution curve of the partition and the control duration of secondary salinization of soil, so as to obtain the risk probability of secondary salinization of soil in the partition.

[0116] The risk assessment module 208 is connected to the risk probability determination module 207, and is used to determine the degree of secondary soil salinization in the area to be assessed according to the risk probability of secondary soil salinization in each sub-area of ​​the area to be assessed.

[0117] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Fig.12As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store relevant data of the area to be evaluated (including long-sequence monitoring data of groundwater depth in each partition and the control time of secondary salinization of soil). The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a quantitative assessment method for the risk of secondary salinization of soil is implemented.

[0118] Those skilled in the art will understand that Fig.12 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components. In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0119] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0120] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0121] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0122] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0123] The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but is not limited thereto.

[0124] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0125] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A method for quantitatively assessing the risk of secondary soil salinization, characterized in that: The quantitative assessment method for soil secondary salinization risk includes: Divide the area to be assessed into different zones and obtain long-sequence monitoring data of groundwater depth in each zone; For any sub-area, carry out water migration monitoring test for groundwater depth control in the sub-area, and determine the critical depth of soil secondary salinization in the sub-area; Determine a set of soil secondary salinization risk characteristic values ​​for the sub-district based on the long-sequence monitoring data of groundwater depth and the critical depth of soil secondary salinization in the sub-district; Determine the empirical frequency of the secondary salinization risk characteristic value of each soil in the sub-district based on the long-series monitoring data of the groundwater depth in the sub-district; According to the empirical frequency of each soil secondary salinization risk characteristic value of the sub-region, a frequency distribution curve of the sub-region is drawn; Conducting experiments on the occurrence and development process of soil salinization in the sub-region, and determining the control duration of soil secondary salinization in the sub-region in combination with the critical burial depth of soil secondary salinization in the sub-region; According to the frequency distribution curve of the sub-area and the duration of soil secondary salinization control, the frequency corresponding to the duration of soil secondary salinization control in the sub-area is determined to obtain the risk probability of soil secondary salinization in the sub-area, specifically including: According to the frequency distribution curve, the probability density function of the secondary salinization risk characteristic value of each soil in the sub-region is determined by the following formula: ； According to the probability density function of the characteristic value of the secondary salinization risk of each soil in the sub-area, the frequency corresponding to the control duration of the secondary salinization of the soil in the sub-area is determined by the following formula: ； The following formula is used to determine the risk probability of secondary soil salinization in the sub-zone: ； in, for The probability density function of is the risk characteristic value of secondary salinization of any soil in the sub-region, is the shape parameter of the Pearson type III distribution, , is the scale parameter of the Pearson type III distribution, , is the location parameter of the Pearson type III distribution, for The gamma function of P is the frequency corresponding to the duration of soil secondary salinization control in the sub-zone, R is the risk probability of secondary soil salinization in the sub-zone, D 0 The duration of controlling secondary salinization of soil in the sub-zone, and Both said The probability distribution function of when x = D 0 The function value when ; The degree of secondary soil salinization in the area to be assessed is determined based on the risk probability of secondary soil salinization in each sub-area of ​​the area to be assessed.

2. The method for quantitative assessment of soil secondary salinization risk according to claim 1, characterized in that: Divide the area to be assessed into different zones and obtain long-sequence monitoring data of groundwater depth in each zone, including: Zoning the area to be assessed according to regional conditions; A groundwater depth monitoring well is set in each sub-area, and the groundwater depth of the corresponding sub-area is monitored through the groundwater depth monitoring well to obtain long-sequence monitoring data of the groundwater depth of each sub-area.

3. The method for quantitative assessment of soil secondary salinization risk according to claim 2, characterized in that: The regional conditions include soil properties, soil layering structure, vegetation cover type, meteorological conditions and hydrological conditions.

4. The method for quantitative assessment of soil secondary salinization risk according to claim 1, characterized in that: Conduct water migration monitoring tests for groundwater depth control in the sub-districts to determine the critical depth of soil secondary salinization in the sub-districts, including: Tracers are added to groundwater at different depths in the sub-zone, and the moisture in the soil surface is measured in real time to determine the maximum groundwater depth at which the tracer is monitored in the soil surface, and the maximum groundwater depth is used as the critical depth of secondary salinization of soil in the sub-zone.

5. The method for quantitative assessment of soil secondary salinization risk according to claim 1, characterized in that: The groundwater depth long-series monitoring data includes the groundwater depth every day for many years; The soil secondary salinization risk characteristic value set includes the soil secondary salinization risk characteristic value for each year; wherein the soil secondary salinization risk characteristic value for any year is the maximum duration of time in which the groundwater depth is less than the critical depth of soil secondary salinization in that year.

6. The method for quantitative assessment of soil secondary salinization risk according to claim 5, characterized in that: According to the long-sequence monitoring data of groundwater depth in the sub-district, the empirical frequency of the characteristic value of secondary salinization risk of each soil in the sub-district is determined, specifically including: The soil secondary salinization risk characteristic values ​​of the sub-regions are arranged from large to small, and the second risk characteristic values ​​of the sub-regions are calculated using the following formula: m Empirical frequency of soil secondary salinization risk characteristic values: ； in, The partition m The empirical frequency of the characteristic value of soil secondary salinization risk is n is the number of soil secondary salinization risk characteristic values ​​for the sub-region, m It is the serial number of the characteristic value of soil secondary salinization risk.

7. The method for quantitative assessment of soil secondary salinization risk according to claim 1, characterized in that: Conducting soil salinization occurrence and development process tests in the sub-area, and determining the control duration of soil secondary salinization in the sub-area in combination with the critical burial depth of soil secondary salinization in the sub-area, specifically including: Within the range where the groundwater depth in the subzone is less than the critical depth of secondary soil salinization in the subzone, groundwater with different salt concentrations is set, and the surface soil salinity of the subzone is monitored in real time under natural evaporation conditions. The timing starts when the surface soil salinity is greater than 0 and stops when the surface soil salinity is greater than the set salinization degree threshold. The timing time is used as the control time of secondary soil salinization in the subzone.

8. The method for quantitative assessment of soil secondary salinization risk according to claim 1, characterized in that: The frequency distribution curve adopts a Pearson III type curve.

9. A soil secondary salinization risk quantitative assessment system, applied to the soil secondary salinization risk quantitative assessment method according to any one of claims 1 to 8, characterized in that: The soil secondary salinization risk quantitative assessment system includes: The groundwater monitoring module is used to divide the area to be assessed into zones and obtain the long-sequence monitoring data of groundwater depth in each zone; A critical burial depth determination module is connected to the groundwater monitoring module and is used to carry out a water migration monitoring test for groundwater burial depth control in any sub-area to determine the critical burial depth of soil secondary salinization in the sub-area; A characteristic value determination module, connected to the critical burial depth determination module, is used to determine the risk characteristic value set of soil secondary salinization in the sub-zone according to the long-sequence monitoring data of groundwater burial depth in the sub-zone and the critical burial depth of soil secondary salinization; A characteristic frequency determination module, connected to the characteristic value determination module, for determining the empirical frequency of each soil secondary salinization risk characteristic value of the sub-zone according to the long-sequence monitoring data of the groundwater depth of the sub-zone; A distribution curve drawing module, connected to the characteristic frequency determination module, is used to draw the frequency distribution curve of the partition according to the empirical frequency of each soil secondary salinization risk characteristic value of the partition; The salinization process test module is connected to the critical burial depth determination module, and is used to carry out the soil salinization occurrence and development process test of the sub-zone, and determine the control time of the soil secondary salinization of the sub-zone in combination with the critical burial depth of the soil secondary salinization of the sub-zone; The risk probability determination module is connected to the distribution curve drawing module and the salinization process test module respectively, and is used to determine the frequency corresponding to the soil secondary salinization control duration of the partition according to the frequency distribution curve of the partition and the soil secondary salinization control duration, so as to obtain the soil secondary salinization risk probability of the partition, specifically including: According to the frequency distribution curve, the probability density function of the secondary salinization risk characteristic value of each soil in the sub-region is determined by the following formula: ； According to the probability density function of the characteristic value of the secondary salinization risk of each soil in the sub-area, the frequency corresponding to the control duration of the secondary salinization of the soil in the sub-area is determined by the following formula: ； The following formula is used to determine the risk probability of secondary soil salinization in the sub-zone: ； in, for The probability density function of is the risk characteristic value of secondary salinization of any soil in the sub-region, is the shape parameter of the Pearson type III distribution, , is the scale parameter of the Pearson type III distribution, , is the location parameter of the Pearson type III distribution, for The gamma function of P is the frequency corresponding to the duration of soil secondary salinization control in the sub-zone, R is the risk probability of secondary soil salinization in the sub-zone, D 0 The duration of controlling secondary salinization of soil in the sub-zone, and Both said The probability distribution function of when x = D 0 The function value when ; The risk assessment module is connected to the risk probability determination module and is used to determine the degree of secondary salinization of soil in the area to be assessed according to the risk probability of secondary salinization of soil in each sub-area of ​​the area to be assessed.

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