CN116911070B - Soil-based material water storage capacity assessment method, device, equipment and storage medium - Google Patents
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Abstract
The invention relates to the technical field of water storage capacity evaluation, and discloses a soil-based material water storage capacity evaluation method, a device, equipment and a storage medium, wherein the method comprises the steps of obtaining synthetic soil parameters and constructing a synthetic soil infiltration model based on the synthetic soil parameters; acquiring environmental parameters of a target desert area, and constructing a desert sand infiltration model based on the environmental parameters of the target desert area; acquiring water infiltration experimental data, and performing parameter inversion on the synthetic soil infiltration model and the desert sand infiltration model by using the water infiltration experimental data to generate a soil-based material water storage capacity assessment model; generating synthetic soil water storage capacity by using a soil-based material water storage capacity evaluation model; the water storage capacity of the soil-based material was evaluated based on the water storage capacity of the synthetic soil. According to the invention, through accurately describing the water migration process in the synthetic soil, the water storage capacity of different soil-based materials is evaluated, and further, the evaluation result is utilized to provide technical support for desert control and reasonable development and utilization.
Description
Technical Field
The invention relates to the technical field of water storage capacity evaluation, in particular to a method, a device, equipment and a storage medium for evaluating the water storage capacity of a soil-based material.
Background
Drought and water shortage are the most main reasons for the ecological weakness of desertification in the area, and the soil-based material is a potential alternative method for improving the water storage capacity of the surface of the desert by changing the loose structure of sand into cohesive soil. The soil-based material is prepared by adding water-soluble substances with proper viscosity into sand particles to obtain synthetic soil, so that the sand is 'earthed', and the retention and storage capacity of the sand to water is enhanced, so that the water storage capacity of the soil-based material is an important performance index. Classical moisture infiltration Richards equations have difficulty describing this process due to the retention effect of moisture migration in earth-based materials, which exhibit unusual non-boltzmann scale characteristics. Therefore, how to accurately describe the water migration process in the synthetic soil to evaluate the water storage capacity of different soil-based materials, and provide technical support for regional desert control and reasonable development and utilization becomes a technical problem to be solved urgently.
Disclosure of Invention
In view of the above, the invention provides a method, a device, equipment and a storage medium for evaluating the water storage capacity of soil-based materials, so as to solve the technical problems of accurately describing the water migration process in synthetic soil to evaluate the water storage capacity of different soil-based materials and provide technical support for desert control and reasonable development and utilization in areas.
In a first aspect, the present invention provides a method for evaluating water storage capacity of a soil-based material, comprising: acquiring environmental parameters of a target desert area, and constructing a desert sand infiltration model based on the environmental parameters of the target desert area; the environment parameters of the target desert area comprise the volume water content of the desert sand, the water conductivity of the desert sand, the permeability coefficient of the desert sand, the environment temperature, the environment humidity, the wind speed and the rainfall parameters; acquiring synthetic soil parameters, and constructing a synthetic soil infiltration model based on the synthetic soil parameters; the synthetic soil parameters comprise synthetic soil volume water content, synthetic soil water conductivity and synthetic soil sand permeability coefficient; acquiring water infiltration experimental data, and performing parameter inversion on the synthetic soil infiltration model and the desert sand infiltration model by using the water infiltration experimental data to generate a soil-based material water storage capacity assessment model; generating synthetic soil water storage capacity by using a soil-based material water storage capacity evaluation model; and evaluating the water storage capacity of the soil base material based on the water storage capacity of the synthetic soil, and generating an evaluation result of the water storage capacity of the soil base material.
According to the soil-based material water storage capacity assessment method, the synthetic soil infiltration model and the desert sand infiltration model are constructed to efficiently simulate the synthetic soil water infiltration process, the synthetic soil water migration process is accurately described, assessment of the water storage capacities of different soil-based materials is achieved, and further technical support is provided for desert control and reasonable development and utilization by means of assessment results.
In an alternative embodiment, constructing a synthetic soil infiltration model based on synthetic soil parameters includes:
constructing a synthetic soil infiltration model based on the synthetic soil volume water content, the synthetic soil water conductivity and the synthetic soil sand infiltration coefficient, wherein the expression of the synthetic soil infiltration model is as follows:
wherein,，/>respectively representing the vertical space position and the current time, < +.>Representing the earth's surface position of the target desert area->Indicating the contact position of the synthetic soil and the desert sand, +.>Represents the volume water content of the synthetic soil, +.>Representing the time fractional derivative, wherein +.>Representing fractional derivative, ++>Representing the time fractional order, +.>Indicating the water conductivity of the synthetic soil, < >>Representing the synthetic soil permeability coefficient.
In an alternative embodiment, constructing a desert sand infiltration model based on environmental parameters of a target desert area includes:
Constructing a desert sand infiltration model based on the volume water content of the desert sand, the water conductivity of the desert sand and the permeability coefficient of the desert sand; the expression of the desert sand infiltration model is as follows:
wherein,，/>respectively representing the vertical space position and the current time, < +.>Indicating the contact position of the synthetic soil and the desert sand, +.>Lower boundary of desert sand area of target desert area, +.>Represents the volume water content of desert sand and is->Representing the derivative of haustorium->Representing the order of the haustorium derivative, ++>Indicates the water conductivity of desert sand>Representing the permeability coefficient of desert sand.
In an alternative embodiment, before obtaining the water infiltration experimental data, performing parameter inversion on the synthetic soil infiltration model and the desert sand infiltration model by using the water infiltration experimental data to generate the soil-based material water storage capacity assessment model, the method further comprises: obtaining a synthetic soil proportion, a synthetic soil thickness and a soil base material type, and adjusting rainfall parameters, the synthetic soil proportion, the synthetic soil thickness and the soil base material type; and carrying out multiple water infiltration experiments by utilizing the environmental parameters, the synthetic soil parameters and the adjusted rainfall parameters, the synthetic soil proportion, the synthetic soil thickness and the soil-based material types of the target desert area to generate multiple sets of water infiltration experiment data.
According to the soil-based material water storage capacity evaluation method provided by the embodiment, a plurality of groups of water infiltration experimental data are generated by adjusting rainfall parameters, synthetic soil proportions, synthetic soil thickness and types of soil-based materials; inversion is carried out on parameters in the water infiltration control model through abundant experimental data, so that generalization of inversion parameters is improved.
In an alternative embodiment, the parameter inversion is performed on the synthetic soil infiltration model and the desert sand infiltration model by using the water infiltration experimental data to generate a soil-based material water storage capacity assessment model, which comprises the following steps: performing parameter inversion on the synthetic soil infiltration model and the desert sand infiltration model by utilizing a plurality of groups of water infiltration experimental data to generate a time fractional order, a time derivative order, a soil base material infiltration coefficient and a desert sand infiltration coefficient; and respectively inputting the time fractional order, the time derivative order, the soil base material permeability coefficient and the desert sand permeability coefficient into a synthetic soil permeability model and a desert sand permeability model to generate a soil base material water storage capacity assessment model.
According to the soil base material water storage capacity assessment method, parameter inversion is carried out on the synthetic soil infiltration model and the desert sand infiltration model through multiple sets of water infiltration experimental data, the environment parameters are corresponding to the soil base material water storage capacity assessment model, the constructed soil base material water storage capacity assessment model can be adjusted in a self-adaptive mode according to the environment parameters, and the application range of the soil base material water storage capacity assessment model is widened.
In an alternative embodiment, the synthetic soil water storage capacity is generated using a soil based material water storage capacity assessment model, comprising: collecting the current rainfall of a target desert area, and solving a soil-based material water storage capacity evaluation model by using a finite difference method based on the current rainfall of the target desert area to generate vertical water content distribution; determining the water content at the lower boundary of the desert sand based on the vertical water content distribution; and acquiring the synthetic soil area, and determining the synthetic soil water storage capacity based on the current rainfall of the target desert area, the synthetic soil area and the water content at the lower boundary of the desert sand.
According to the soil-based material water storage capacity assessment method, based on real-time monitoring of environmental parameters, the soil-based material water storage capacity assessment model is utilized to simulate synthetic soil water storage capacity, objective and reliable data are obtained, and technical support can be provided for regional groundwater resource assessment and reasonable development and utilization.
In an alternative embodiment, the method further comprises:
and predicting the groundwater supply quantity of the target desert area based on the synthetic soil water storage quantity to generate a groundwater supply quantity prediction result.
According to the soil-based material water storage capacity assessment method, the objective data of the soil water storage capacity is synthesized, the groundwater supply quantity of the target desert area is predicted, and the groundwater supply quantity prediction result is generated, so that technical support is provided for regional groundwater resource assessment and reasonable development and utilization.
In a second aspect, the present invention provides a soil base material water storage capacity evaluation device, comprising: the first construction module is used for acquiring the environmental parameters of the target desert area and constructing a desert sand infiltration model based on the environmental parameters of the target desert area; the environment parameters of the target desert area comprise the volume water content of the desert sand, the water conductivity of the desert sand, the permeability coefficient of the desert sand, the environment temperature, the environment humidity, the wind speed and the rainfall parameters; the second construction module is used for acquiring synthetic soil parameters and constructing a synthetic soil infiltration model based on the synthetic soil parameters; the synthetic soil parameters comprise synthetic soil volume water content, synthetic soil water conductivity and synthetic soil sand permeability coefficient; the inversion module is used for acquiring water infiltration experimental data, carrying out parameter inversion on the synthetic soil infiltration model and the desert sand infiltration model by utilizing the water infiltration experimental data, and generating a soil-based material water storage capacity assessment model; the first generation module is used for generating synthetic soil water storage capacity by utilizing the soil base material water storage capacity evaluation model; and the second generation module is used for evaluating the water storage capacity of the soil base material based on the water storage capacity of the synthetic soil and generating a water storage capacity evaluation result of the soil base material.
In a third aspect, the present invention provides a computer device comprising: the storage device comprises a storage device and a processor, wherein the storage device and the processor are in communication connection, the storage device stores computer instructions, and the processor executes the computer instructions, so that the soil base material water storage capacity assessment method of the first aspect or any corresponding embodiment of the first aspect is executed.
In a fourth aspect, the present invention provides a computer-readable storage medium having stored thereon computer instructions for causing a computer to execute the soil base material water storage capacity assessment method of the first aspect or any one of the embodiments corresponding thereto.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic block diagram of a schematic water infiltration in synthetic soil according to an embodiment of the present invention;
FIG. 2 is a flow chart of a method for evaluating the water storage capacity of a soil base material according to an embodiment of the present invention;
FIG. 3 is a flow chart of a method for evaluating the water storage capacity of a soil base material according to an embodiment of the present invention;
FIG. 4 is a block diagram showing the construction of a soil base material water storage capacity evaluation device according to an embodiment of the present invention;
fig. 5 is a schematic diagram of a hardware structure of a computer device according to an embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The soil-based material water storage capacity evaluation method provided by the specification can be applied to the simulation of a water infiltration schematic structure diagram of synthetic soil shown in figure 1 (whereinzRepresenting a vertical spatial position). The electronic device may include, but is not limited to, a notebook, desktop, mobile terminal, such as a cell phone, tablet, etc.; of course, the soil-based material water storage capacity evaluation method provided in the present specification may also be applied to an application program running in the above-mentioned electronic device.
The embodiment of the invention provides a soil-based material water storage capacity assessment method, which is used for assessing the water storage capacities of different soil-based materials by constructing a synthetic soil infiltration model and a desert sand infiltration model and generating the soil-based material water storage capacity assessment model through parameter inversion so as to accurately describe the water migration process in synthetic soil, and provides technical effects of technical support for regional desert control and reasonable development and utilization.
According to an embodiment of the present invention, there is provided an embodiment of a soil base material water storage capacity assessment method, it being noted that the steps shown in the flowchart of the drawings may be performed in a computer system such as a set of computer executable instructions, and that although a logical order is shown in the flowchart, in some cases the steps shown or described may be performed in an order different from that herein.
In this embodiment, a method for evaluating the water storage capacity of a soil-based material is provided, which can be used in the above-mentioned notebook, desktop computer, mobile terminal, such as mobile phone, tablet computer, etc., fig. 2 is a flowchart of the method for evaluating the water storage capacity of a soil-based material according to an embodiment of the present invention, as shown in fig. 2, the flowchart includes the following steps:
Step S201, obtaining synthetic soil parameters, and constructing a synthetic soil infiltration model based on the synthetic soil parameters; wherein the synthetic soil parameters comprise synthetic soil volume moisture content, synthetic soil water conductivity and synthetic soil sand permeability coefficient.
Specifically, the synthetic soil is formed by mixing soil base materials, desert sand and water, wherein A groups of soil base materials are selected, each soil base material is divided into B groups according to the proportion of the soil base materials to the desert sand and the water, and meanwhile, the soil base materials are divided into 2cm, 5cm, 15cm and 25cm according to the thickness of the synthetic soil, so that the synthetic soil is composed of 4 XA and B types, and the synthetic soil parameters comprise the volume moisture content of the synthetic soil, the water conductivity of the synthetic soil and the permeability coefficient of the synthetic soil sand, and the volume moisture content of the synthetic soil, the water conductivity of the synthetic soil and the permeability coefficient of the synthetic soil sand can be measured through measuring equipment.
Further, a synthetic soil infiltration model is constructed based on the synthetic soil volume water content, the synthetic soil water conductivity and the synthetic soil sand infiltration coefficient, and the expression of the synthetic soil infiltration model is shown as the following formula (1):
（1）
wherein,，/>respectively representing the vertical space position and the current time, < +.>Representing the earth's surface position of the target desert area->Indicating the contact position of the synthetic soil and the desert sand, +. >Represents the volume water content of the synthetic soil, +.>Time fractional derivative representing the type of Caputo (fractional differential equation), wherein +.>Indicating that the derivative of this type is a fractional derivative of the category Caputo (fractional differential equation), 0 indicates the initial moment, ++>Represents the time fractional order, represents the retention degree of the synthetic material to the moisture,，/>the lower the value, the stronger the retention effect, and the +.>Indicating the water conductivity of the synthetic soil, < >>Representing the synthetic soil permeability coefficient.
Step S202, acquiring environmental parameters of a target desert area, and constructing a desert sand infiltration model based on the environmental parameters of the target desert area; the environment parameters of the target desert area comprise the volume water content of the desert sand, the water conductivity of the desert sand, the permeability coefficient of the desert sand, the environment temperature, the environment humidity, the wind speed and the rainfall parameters.
Specifically, the environmental parameters may be obtained, but not limited to, by collecting historical parameters or actually measured by a monitoring device, and those skilled in the art can determine according to actual situations, which is not limited herein; if the wind measuring tower is arranged, the ambient temperature, the ambient humidity and the wind speed of the near-earth side of the target desert area can be monitored; the method comprises the steps of collecting a desert sand sample of a target desert area, analyzing the grain size composition of the desert sand sample, measuring the water conductivity of the desert sand and the permeability coefficient of the desert sand, arranging a measuring station in the area, and monitoring the volumetric water content value of the vertical desert sand, wherein the distribution of the volumetric water content value can form a function of the vertical position and the water content; the rainfall parameters may include the rainfall season and the rainfall intensity.
Further, constructing a desert sand infiltration model based on the volume water content of the desert sand, the water conductivity of the desert sand and the permeability coefficient of the desert sand; the expression of the desert sand infiltration model is shown in formula (2):
（2）
wherein,，/>respectively representing the vertical space position and the current time, < +.>Indicating the contact position of the synthetic soil and the desert sand, +.>Lower boundary of desert sand area of target desert area, +.>Represents the volume water content of desert sand and is->Representing the derivative of haustorium->Indicating the order of the derivative of Haoskov, where ++>，/>Indicates the water conductivity of desert sand>Representing the permeability coefficient of desert sand.
Further, desert sand is formed by long-time weathering and abrasion of rocks and stones, is usually thin, dry and loose, and is characterized by loose particle arrangement, large spacing, contact constraint among particles, no viscosity and excellent vertical permeability; the method is influenced by the fractal characteristics of heterogeneous mediums of desert sand, the permeation process of moisture in the fractal characteristics shows abnormal non-Boltzmann scale characteristics, the Hausdroff fractal derivative has scale transformation characteristics, and the description of the structure of the split mediums is realized through time scale transformation; in order to describe the moisture infiltration process in desert sand, a space-time Hausdroff fractal Richards equation is established here, as shown in formula (2).
Further, synthetic soil is formed by adding a water-based material with proper viscosity into desert sand, so that the sand is 'earthed', the earth-based material has a detention effect on water migration therein, the abnormal non-boltzmann scale characteristic is shown, meanwhile, the water in the desert sand has the characteristic of migrating along a matrix with fractal structural characteristics, although Hausdroff fractal derivative can describe the non-boltzmann scale characteristic, the Hausdroff fractal derivative is realized based on scale change, and a fractional derivative model describes the detention phenomenon through a memory operator; thus, to describe this process, the present embodiment establishes a coupling model in which a two-stage time fractional order Richards equation is shown in equation (1) and a Hausdroff fractal Richards equation is shown in equation (2). In general, hausdroff fractal Richards equation is used as the exact lower boundary of time fractional order Richards equation, which guarantees @ whenn-m）=（m-l) if there is a further analysis of the groundwater feed at this point, at this pointzThe value is the junction position of the desert sand and the underground diving.
And step S203, acquiring water infiltration experimental data, and performing parameter inversion on the synthetic soil infiltration model and the desert sand infiltration model by using the water infiltration experimental data to generate a soil-based material water storage capacity assessment model.
In particular, the acquisition of the moisture infiltration experimental data may be obtained by, but not limited to, collecting historical experimental data, or by indoor soil column experiments; if the desert sand of a target desert area is selected to be filled, adding a soil-based material into the upper layer of the soil column to form synthetic soil with a certain thickness, controlling the upper boundary temperature of the soil column to be consistent with the thickness adopted by an actual plan, laterally placing conductivity meters, arranging the conductivity meters at the positions of the upper boundary of the soil column and the lower boundary of the soil layer, if the soil layer of the soil layer is thicker, if the soil layer is larger than 20cm, increasing the quantity of the conductivity meters, measuring the water content of a plurality of positions, if the water content of a plurality of positions is required by analyzing groundwater supply, placing a fine gauze below the soil column, immersing the surface layer in a container for containing water, and placing a weighing device below the container; those skilled in the art may set the setting according to the actual situation, and the present invention is not limited thereto.
Further, the synthetic soil proportion, the synthetic soil thickness and the types of soil-based materials are obtained, and rainfall parameters, the synthetic soil proportion, the synthetic soil thickness and the types of soil-based materials are adjusted; carrying out multiple water infiltration experiments by utilizing the environmental parameters, the synthetic soil parameters and the adjusted rainfall parameters, the synthetic soil proportion, the synthetic soil thickness and the soil-based material types of the target desert area to generate multiple groups of water infiltration experimental data; as an alternative mode, different rainfall intensities are adopted to combine 4×a×b in step S201 into soil, multiple groups of experiments are repeated, multiple groups of water infiltration experimental data are utilized to perform parameter inversion on a synthetic soil infiltration model and a desert sand infiltration model through a least square method, multiple groups of inversion parameters under multiple rainfall conditions under multiple soil base material types, proportions and thicknesses are generated, and multiple groups of corresponding soil base material water storage capacity assessment models are generated; in practical application, proper types, proportions and thicknesses of soil-based materials are selected to achieve better cost performance.
Further, carrying out parameter inversion on the synthetic soil infiltration model and the desert sand infiltration model by utilizing a plurality of groups of water infiltration experimental data to generate a time fractional order, a time derivative order, a soil base material infiltration coefficient and a desert sand infiltration coefficient; respectively inputting the time fractional order, the time derivative order, the soil base material permeability coefficient and the desert sand permeability coefficient into a synthetic soil permeability model and a desert sand permeability model to generate a soil base material water storage capacity assessment model, wherein the soil base material water storage capacity assessment model is shown in the formulas (1) to (2):
（1）
（2）
wherein,，/>respectively representing the vertical space position and the current time, < +.>Representing the earth's surface position of the target desert area->Indicating the contact position of the synthetic soil and the desert sand, +.>Lower boundary of desert sand area of target desert area, +.>Represents the volume water content of the synthetic soil, +.>Time fractional derivative representing the type of Caputo (fractional differential equation), wherein +.>Indicating that the derivative of this type is a fractional derivative of the category Caputo (fractional differential equation), 0 indicates the initial moment, ++>Representing the time fractional order, representing the degree of retention of moisture by the composite material, +.>，/>The lower the value, the stronger the retention effect, and the +. >Indicating the water conductivity of the synthetic soil, < >>Represents the permeability coefficient of synthetic soil, < >>Representing the derivative of haustorium->Indicating the order of the derivative of Haoskov, where ++>，/>Indicates the water conductivity of desert sand>Representing the permeability coefficient of desert sand.
And S204, generating synthetic soil water storage capacity by using a soil-based material water storage capacity evaluation model.
And step S205, evaluating the water storage capacity of the soil base material based on the water storage capacity of the synthetic soil, and generating a water storage capacity evaluation result of the soil base material.
Specifically, the larger the water storage capacity is, the stronger the capability of the synthetic soil is, and the synthetic soil is formed by mixing soil base materials, desert sand and water, so that the water storage capability of the synthetic soil can indirectly reflect the water storage capability of the soil base materials; the water storage capacity is compared with the preset threshold value, and an evaluation result of the water storage capacity of the soil-based material is generated based on the comparison result; the threshold and water storage capacity level may be set by those skilled in the art according to the actual situation, and are not limited herein.
Further, predicting the groundwater supply quantity of the target desert area based on the synthetic soil water storage quantity, and generating a groundwater supply quantity prediction result; comparing the water storage capacity with a preset threshold value, and predicting the groundwater supply quantity of the target desert area based on the comparison result; if the water storage capacity is larger than a preset threshold value, judging that the groundwater supply quantity of the target desert area is insufficient; if the water storage capacity is smaller than a preset threshold value, judging that the groundwater supply quantity of the target desert area is sufficient; furthermore, the underground water resource of the target desert area can be evaluated.
According to the soil-based material water storage capacity assessment method, a synthetic soil infiltration model and a desert sand infiltration model are built, a double-stage time fractional order Richards equation and a Hausdroff fractal Richards equation coupling model are built, the water infiltration process of synthetic soil is efficiently simulated, the water migration process of the synthetic soil is accurately described, assessment of the water storage capacities of different soil-based materials is achieved, and further technical support is provided for desert control and reasonable development and utilization by means of assessment results.
In this embodiment, a method for evaluating the water storage capacity of a soil-based material is provided, which can be used in the above notebook, desktop, mobile terminal, such as a mobile phone, tablet computer, etc., and fig. 3 is a flowchart of the method for evaluating the water storage capacity of a soil-based material according to an embodiment of the present invention, as shown in fig. 3, the flowchart includes the following steps:
Step S301, obtaining synthetic soil parameters, and constructing a synthetic soil infiltration model based on the synthetic soil parameters; the synthetic soil parameters comprise synthetic soil volume water content, synthetic soil water conductivity and synthetic soil sand permeability coefficient; please refer to step S201 in the embodiment shown in fig. 2 in detail, which is not described herein.
Step S302, acquiring environmental parameters of a target desert area, and constructing a desert sand infiltration model based on the environmental parameters of the target desert area; the environment parameters of the target desert area comprise the volume water content of the desert sand, the water conductivity of the desert sand, the permeability coefficient of the desert sand, the environment temperature, the environment humidity, the wind speed and the rainfall parameters; please refer to step S202 in the embodiment shown in fig. 2, which is not described herein.
Step S303, acquiring water infiltration experimental data, and performing parameter inversion on the synthetic soil infiltration model and the desert sand infiltration model by using the water infiltration experimental data to generate a soil-based material water storage capacity assessment model; please refer to step S203 in the embodiment shown in fig. 2 in detail, which is not described herein.
Step S304, generating synthetic soil water storage capacity by using a soil-based material water storage capacity evaluation model; please refer to step S204 in the embodiment shown in fig. 2 in detail, which is not described herein.
Specifically, the step S304 includes:
and S3041, collecting the current rainfall of the target desert area, and solving a soil-based material water storage capacity evaluation model by using a finite difference method based on the current rainfall of the target desert area to generate vertical water content distribution.
Specifically, the current rainfall Q of the target desert area Lowering blood pressure Can be obtained through actual measurement and acquisition by monitoring equipment.
And step S3042, determining the water content at the lower boundary of the desert sand based on the vertical water content distribution.
Specifically, the vertical water content distribution represents the relationship between the vertical position of the desert sand and the water content, and the water content at the lower boundary of the desert sand is determined based on the vertical water content distribution of the target desert area.
And step S3043, obtaining a synthetic soil area, and determining the synthetic soil water storage capacity based on the current rainfall of the target desert area, the synthetic soil area and the water content at the lower boundary of the desert sand.
Specifically, the acquisition of the synthetic soil area may be measured directly by the detection device, without limitation. Multiplying the preset time length, the synthetic soil area and the water content at the lower boundary of the desert sand to generate the water loss quantity Q of the synthetic soil Flow of Synthetic soil water storage Q Storage device Equal to the current rainfall Q Lowering blood pressure Water loss amount Q of synthetic soil Flow of The difference of (2), i.eQ Storage device =Q Lowering blood pressure -Q Flow of 。
Step S305, evaluating the water storage capacity of the soil base material based on the water storage capacity of the synthetic soil, and generating a water storage capacity evaluation result of the soil base material; please refer to step S205 in the embodiment shown in fig. 2 in detail, which is not described herein.
According to the soil-based material water storage capacity assessment method, based on real-time monitoring of environmental parameters, the soil-based material water storage capacity assessment model is utilized to simulate synthetic soil water storage capacity, objective and reliable data are obtained, and technical support can be provided for regional groundwater resource assessment and reasonable development and utilization.
The embodiment also provides a soil-based material water storage capacity evaluation device, which is used for realizing the embodiment and the preferred implementation manner, and is not described in detail; as used below, the term "module" may be a combination of software and/or hardware that implements a predetermined function; while the means described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and contemplated.
The present embodiment provides a soil-based material water storage capacity evaluation device, as shown in fig. 4, including:
A first construction module 401, configured to obtain an environmental parameter of a target desert area, and construct a desert sand infiltration model based on the environmental parameter of the target desert area; the environment parameters of the target desert area comprise the volume water content of the desert sand, the water conductivity of the desert sand, the permeability coefficient of the desert sand, the environment temperature, the environment humidity, the wind speed and the rainfall parameters;
a second construction module 402, configured to acquire synthetic soil parameters, and construct a synthetic soil infiltration model based on the synthetic soil parameters; the synthetic soil parameters comprise synthetic soil volume water content, synthetic soil water conductivity and synthetic soil sand permeability coefficient;
the inversion module 403 is configured to obtain water infiltration experimental data, perform parameter inversion on the synthetic soil infiltration model and the desert sand infiltration model by using the water infiltration experimental data, and generate a soil-based material water storage capacity assessment model;
a first generation module 404 for generating a synthetic soil water storage capacity using a soil-based material water storage capacity assessment model;
the second generation module 405 is configured to evaluate the water storage capacity of the soil base material based on the synthetic soil water storage capacity, and generate a result of evaluating the water storage capacity of the soil base material.
In some alternative embodiments, the first construction module 401 is specifically configured to construct a synthetic soil infiltration model based on the synthetic soil volume moisture content, the synthetic soil water conductivity, and the synthetic soil sand infiltration coefficient, where the expression of the synthetic soil infiltration model is shown in formula (1):
（1）
Wherein,，/>respectively representing the vertical space position and the current time, < +.>Representing the earth's surface position of the target desert area->Indicating the contact position of the synthetic soil and the desert sand, +.>Represents the volume water content of the synthetic soil, +.>Time fractional derivative representing the type of Caputo (fractional differential equation), wherein +.>Indicating that the derivative of this type is a fractional derivative of the category Caputo (fractional differential equation), 0 indicates the initial moment, ++>Represents the time fractional order, represents the retention degree of the synthetic material to the moisture,，/>the lower the value, the stronger the retention effect, and the +.>Indicating the water conductivity of the synthetic soil, < >>Representing the synthetic soil permeability coefficient.
In some alternative embodiments, the second construction module 402 is specifically configured to construct a desert sand infiltration model based on the volume moisture content of the desert sand, the water conductivity of the desert sand, and the permeability coefficient of the desert sand; the expression of the desert sand infiltration model is shown in formula (2):
（2）
wherein,，/>respectively representing the vertical space position and the current time, < +.>Indicating the contact position of the synthetic soil and the desert sand, +.>Lower boundary of desert sand area of target desert area, +.>Represents the volume water content of desert sand and is->Representing the derivative of haustorium->Representing the order of the haustorium derivative, ++ >Indicates the water conductivity of desert sand>Representing the permeability coefficient of desert sand.
In some alternative embodiments, further comprising:
the adjusting module is used for obtaining the synthetic soil proportion, the synthetic soil thickness and the types of the soil base materials, and adjusting rainfall parameters, the synthetic soil proportion, the synthetic soil thickness and the types of the soil base materials;
and the third generation module is used for carrying out multiple water infiltration experiments by utilizing the environmental parameters, the synthetic soil parameters and the adjusted rainfall parameters, the synthetic soil proportion, the synthetic soil thickness and the soil-based material types of the target desert area to generate multiple groups of water infiltration experiment data.
In some alternative embodiments, the inversion module 403 includes:
the inversion submodule is used for carrying out parameter inversion on the synthetic soil infiltration model and the desert sand infiltration model by utilizing a plurality of groups of water infiltration experimental data to generate a time fractional order, a time derivative order, a soil base material infiltration coefficient and a desert sand infiltration coefficient;
the generation submodule is used for respectively inputting the time fractional order, the time derivative order, the soil base material permeability coefficient and the desert sand permeability coefficient into the synthetic soil permeability model and the desert sand permeability model to generate the soil base material water storage capacity assessment model.
In some alternative embodiments, the first generation module 404 includes:
the acquisition submodule is used for acquiring the current rainfall of the target desert area, solving a soil-based material water storage capacity evaluation model by using a finite difference method based on the current rainfall of the target desert area, and generating vertical water content distribution;
the first determining submodule is used for determining the water content at the lower boundary of the desert sand based on the vertical water content distribution;
and the second determination submodule is used for obtaining the synthetic soil area and determining the synthetic soil water storage capacity based on the current rainfall of the target desert area, the synthetic soil area and the water content at the lower boundary of the desert sand.
In some alternative embodiments, further comprising:
and the fourth generation module is used for predicting the groundwater supply quantity of the target desert area based on the synthetic soil water storage quantity and generating a groundwater supply quantity prediction result.
Further functional descriptions of the above respective modules and units are the same as those of the above corresponding embodiments, and are not repeated here.
The soil matrix material water storage capacity assessment device in this embodiment is in the form of a functional unit, where the unit refers to an ASIC (Application Specific Integrated Circuit ) circuit, a processor and memory executing one or more software or fixed programs, and/or other devices that can provide the above functions.
The embodiment of the invention also provides computer equipment, which is provided with the soil-based material water storage capacity evaluation device shown in the figure 4.
Referring to fig. 5, fig. 5 is a schematic structural diagram of a computer device according to an alternative embodiment of the present invention, as shown in fig. 5, the computer device includes: one or more processors 10, memory 20, and interfaces for connecting the various components, including high-speed interfaces and low-speed interfaces. The various components are communicatively coupled to each other using different buses and may be mounted on a common motherboard or in other manners as desired. The processor may process instructions executing within the computer device, including instructions stored in or on memory to display graphical information of the GUI on an external input/output device, such as a display device coupled to the interface. In some alternative embodiments, multiple processors and/or multiple buses may be used, if desired, along with multiple memories and multiple memories. Also, multiple computer devices may be connected, each providing a portion of the necessary operations (e.g., as a server array, a set of blade servers, or a multiprocessor system). One processor 10 is illustrated in fig. 5.
The processor 10 may be a central processor, a network processor, or a combination thereof. The processor 10 may further include a hardware chip, among others. The hardware chip may be an application specific integrated circuit, a programmable logic device, or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general-purpose array logic, or any combination thereof.
Wherein the memory 20 stores instructions executable by the at least one processor 10 to cause the at least one processor 10 to perform a method for implementing the embodiments described above.
The memory 20 may include a storage program area that may store an operating system, at least one application program required for functions, and a storage data area; the storage data area may store data created according to the use of the computer device, etc. In addition, the memory 20 may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, memory 20 may optionally include memory located remotely from processor 10, which may be connected to the computer device via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
Memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk, or solid state disk; the memory 20 may also comprise a combination of the above types of memories.
The computer device further comprises input means 30 and output means 40. The processor 10, memory 20, input device 30, and output device 40 may be connected by a bus or other means, for example in fig. 5.
The input device 30 may receive input numeric or character information and generate key signal inputs related to user settings and function control of the computer apparatus, such as a touch screen, a keypad, a mouse, a trackpad, a touchpad, a pointer stick, one or more mouse buttons, a trackball, a joystick, and the like. The output means 40 may include a display device, auxiliary lighting means (e.g., LEDs), tactile feedback means (e.g., vibration motors), and the like. Such display devices include, but are not limited to, liquid crystal displays, light emitting diodes, displays and plasma displays. In some alternative implementations, the display device may be a touch screen.
The embodiments of the present invention also provide a computer readable storage medium, and the method according to the embodiments of the present invention described above may be implemented in hardware, firmware, or as a computer code which may be recorded on a storage medium, or as original stored in a remote storage medium or a non-transitory machine readable storage medium downloaded through a network and to be stored in a local storage medium, so that the method described herein may be stored on such software process on a storage medium using a general purpose computer, a special purpose processor, or programmable or special purpose hardware. The storage medium can be a magnetic disk, an optical disk, a read-only memory, a random access memory, a flash memory, a hard disk, a solid state disk or the like; further, the storage medium may also comprise a combination of memories of the kind described above. It will be appreciated that a computer, processor, microprocessor controller or programmable hardware includes a storage element that can store or receive software or computer code that, when accessed and executed by the computer, processor or hardware, implements the methods illustrated by the above embodiments.
Although embodiments of the present invention have been described in connection with the accompanying drawings, various modifications and variations may be made by those skilled in the art without departing from the spirit and scope of the invention, and such modifications and variations fall within the scope of the invention as defined by the appended claims.
Claims (10)
1. A method for evaluating the water storage capacity of a soil-based material, the method comprising:
acquiring synthetic soil parameters, and constructing a synthetic soil infiltration model based on the synthetic soil parameters; the synthetic soil parameters comprise synthetic soil volume water content, synthetic soil water conductivity and synthetic soil sand permeability coefficient;
acquiring environmental parameters of a target desert area, and constructing a desert sand infiltration model based on the environmental parameters of the target desert area; the environment parameters of the target desert area comprise desert sand volume water content, desert sand water conductivity, desert sand permeability coefficient, environment temperature, environment humidity, wind speed and rainfall parameters;
acquiring water infiltration experimental data, and performing parameter inversion on the synthetic soil infiltration model and the desert sand infiltration model by using the water infiltration experimental data to generate a soil-based material water storage capacity assessment model;
generating synthetic soil water storage capacity by using the soil-based material water storage capacity evaluation model;
evaluating the water storage capacity of the soil base material based on the synthetic soil water storage capacity to generate a soil base material water storage capacity evaluation result;
the construction of the synthetic soil infiltration model based on the synthetic soil parameters comprises the following steps:
Constructing the synthetic soil permeability model based on the synthetic soil volume water content, the synthetic soil water conductivity and the synthetic soil sand permeability coefficient, wherein the expression of the synthetic soil permeability model is as follows:
wherein,，/>respectively represent vertical spacePosition and current time, +.>Representing the earth's surface position of the target desert area->Indicating the contact position of the synthetic soil and the desert sand, +.>Represents the volume water content of the synthetic soil, +.>Representing the time fractional derivative, whereinRepresenting fractional derivative, ++>Representing the time fractional order, +.>Indicating the water conductivity of the synthetic soil, < >>Representing the synthetic soil permeability coefficient;
the construction of the desert sand infiltration model based on the environmental parameters of the target desert area comprises the following steps:
constructing the desert sand infiltration model based on the volume water content of the desert sand, the water conductivity of the desert sand and the permeability coefficient of the desert sand; the expression of the desert sand infiltration model is as follows:
wherein,，/>respectively representing the vertical space position and the current time, < +.>Indicating the contact position of the synthetic soil and the desert sand, +.>Lower boundary of desert sand area of target desert area, +.>Represents the volume water content of desert sand and is->Representing the derivative of haustorium- >Representing the order of the haustorium derivative, ++>Indicates the water conductivity of desert sand>Representing the permeability coefficient of desert sand;
the method for performing parameter inversion on the synthetic soil infiltration model and the desert sand infiltration model by utilizing the water infiltration experimental data to generate a soil-based material water storage capacity assessment model comprises the following steps:
performing parameter inversion on the synthetic soil infiltration model and the desert sand infiltration model by utilizing the multiple sets of water infiltration experimental data to generate a time fractional order, a time derivative order, a soil base material infiltration coefficient and a desert sand infiltration coefficient;
and respectively inputting the time fractional order, the time derivative order, the soil base material permeability coefficient and the desert sand permeability coefficient into the synthetic soil permeability model and the desert sand permeability model to generate the soil base material water storage capacity assessment model.
2. The method of claim 1, further comprising, prior to the obtaining the moisture infiltration experimental data, performing a parametric inversion of the synthetic soil infiltration model and the desert sand infiltration model using the moisture infiltration experimental data to generate a soil-based material water storage capacity assessment model:
Obtaining a synthetic soil proportion, a synthetic soil thickness and a soil base material type, and adjusting the rainfall parameter, the synthetic soil proportion, the synthetic soil thickness and the soil base material type;
and carrying out multiple water infiltration experiments by utilizing the environmental parameters, the synthetic soil parameters, the adjusted rainfall parameters, the synthetic soil proportion, the synthetic soil thickness and the soil-based material types of the target desert area to generate multiple groups of water infiltration experimental data.
3. The method of claim 1, wherein said generating said synthetic soil water storage capacity using said earth-based material water storage capacity assessment model comprises:
collecting the current rainfall of a target desert area, and solving the soil-based material water storage capacity evaluation model by using a finite difference method based on the current rainfall of the target desert area to generate vertical water content distribution;
determining the water content at the lower boundary of the desert sand based on the vertical water content distribution;
and acquiring a synthetic soil area, and determining the synthetic soil water storage capacity based on the current rainfall of the target desert area, the synthetic soil area and the water content at the lower boundary of the desert sand.
4. The method as recited in claim 1, further comprising:
and predicting the groundwater supply quantity of the target desert area based on the synthetic soil water storage quantity to generate a groundwater supply quantity prediction result.
5. A soil-based material water storage capacity evaluation device, characterized in that the device comprises:
the first construction module is used for acquiring synthetic soil parameters and constructing a synthetic soil infiltration model based on the synthetic soil parameters; the synthetic soil parameters comprise synthetic soil volume water content, synthetic soil water conductivity and synthetic soil sand permeability coefficient;
the second construction module is used for acquiring the environmental parameters of the target desert area and constructing a desert sand infiltration model based on the environmental parameters of the target desert area; the environment parameters of the target desert area comprise desert sand volume water content, desert sand water conductivity, desert sand permeability coefficient, environment temperature, environment humidity, wind speed and rainfall parameters;
the inversion module is used for acquiring water infiltration experimental data, carrying out parameter inversion on the synthetic soil infiltration model and the desert sand infiltration model by utilizing the water infiltration experimental data, and generating a soil-based material water storage capacity assessment model;
The first generation module is used for generating synthetic soil water storage capacity by utilizing the soil base material water storage capacity evaluation model;
the second generation module is used for evaluating the water storage capacity of the soil base material based on the water storage capacity of the synthetic soil and generating a water storage capacity evaluation result of the soil base material;
the first construction module is specifically configured to construct the synthetic soil infiltration model based on the synthetic soil volume water content, the synthetic soil water conductivity and the synthetic soil sand infiltration coefficient, where an expression of the synthetic soil infiltration model is as follows:
wherein,，/>respectively representing the vertical space position and the current time, < +.>Representing the earth's surface position of the target desert area->Indicating the contact position of the synthetic soil and the desert sand, +.>Represents the volume water content of the synthetic soil, +.>Representing the time fractional derivative, whereinRepresenting fractional derivative, ++>Representing the time fractional order, +.>Indicating the water conductivity of the synthetic soil, < >>Representing the synthetic soil permeability coefficient;
the second construction module is specifically configured to construct the desert sand infiltration model based on the volume water content of the desert sand, the water conductivity of the desert sand and the permeability coefficient of the desert sand; the expression of the desert sand infiltration model is as follows:
Wherein,，/>respectively representing the vertical space position and the current time, < +.>Indicating the contact position of the synthetic soil and the desert sand, +.>Lower boundary of desert sand area of target desert area, +.>Represents the volume water content of desert sand and is->Representing the derivative of haustorium->Representing the order of the haustorium derivative, ++>Indicates the water conductivity of desert sand>Representing the permeability coefficient of desert sand;
the inversion module comprises:
the inversion submodule is used for carrying out parameter inversion on the synthetic soil infiltration model and the desert sand infiltration model by utilizing the multiple groups of water infiltration experimental data to generate a time fractional order, a time derivative order, a soil base material infiltration coefficient and a desert sand infiltration coefficient;
the generation submodule is used for inputting the time fractional order, the time derivative order, the soil base material permeability coefficient and the desert sand permeability coefficient into the synthetic soil permeability model and the desert sand permeability model respectively to generate the soil base material water storage capacity assessment model.
6. The apparatus of claim 5, wherein prior to the inversion module, further comprising:
the adjusting module is used for obtaining the synthetic soil proportion, the synthetic soil thickness and the types of the soil base materials and adjusting the rainfall parameters, the synthetic soil proportion, the synthetic soil thickness and the types of the soil base materials;
And the third generation module is used for carrying out multiple water infiltration experiments by utilizing the environmental parameters, the synthetic soil parameters and the adjusted rainfall parameters, the synthetic soil proportion, the synthetic soil thickness and the soil-based material types of the target desert area to generate multiple groups of water infiltration experimental data.
7. The apparatus of claim 5, wherein the first generation module comprises:
the acquisition submodule is used for acquiring the current rainfall of the target desert area, and solving the soil-based material water storage capacity evaluation model by utilizing a finite difference method based on the current rainfall of the target desert area to generate vertical water content distribution;
the first determining submodule is used for determining the water content at the lower boundary of the desert sand based on the vertical water content distribution;
and the second determination submodule is used for obtaining the synthetic soil area and determining the synthetic soil water storage capacity based on the current rainfall of the target desert area, the synthetic soil area and the water content at the lower boundary of the desert sand.
8. The apparatus as recited in claim 5, further comprising:
and the fourth generation module is used for predicting the groundwater supply quantity of the target desert area based on the synthetic soil water storage quantity and generating a groundwater supply quantity prediction result.
9. A computer device, comprising:
a memory and a processor, the memory and the processor are in communication connection, the memory stores computer instructions, and the processor executes the computer instructions, thereby executing the soil-based material water storage capacity assessment method according to any one of claims 1 to 4.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon computer instructions for causing a computer to execute the soil-based material water storage capacity evaluation method according to any one of claims 1 to 4.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2017222372A1 (en) * | 2016-06-20 | 2017-12-28 | Fugro N.V. | A method, a system, and a computer program product for determining soil properties |
| CN111273289A (en) * | 2020-01-20 | 2020-06-12 | 中南大学 | Desert parameter inversion method, device, equipment and storage medium |
| CN114894995A (en) * | 2022-03-31 | 2022-08-12 | 神华北电胜利能源有限公司 | Mining area soil moisture inversion method, device and computer readable storage medium |
| CN116127674A (en) * | 2021-11-09 | 2023-05-16 | 中国石油天然气集团有限公司 | Method for monitoring and evaluating wetland ecosystem in oilfield development area |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114397427B (en) * | 2021-12-28 | 2023-08-01 | 中国科学院南京土壤研究所 | Soil hydraulics characteristic prediction method based on ring cutter soil sample infiltration process |
-
2023
- 2023-09-07 CN CN202311147823.2A patent/CN116911070B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2017222372A1 (en) * | 2016-06-20 | 2017-12-28 | Fugro N.V. | A method, a system, and a computer program product for determining soil properties |
| CN111273289A (en) * | 2020-01-20 | 2020-06-12 | 中南大学 | Desert parameter inversion method, device, equipment and storage medium |
| CN116127674A (en) * | 2021-11-09 | 2023-05-16 | 中国石油天然气集团有限公司 | Method for monitoring and evaluating wetland ecosystem in oilfield development area |
| CN114894995A (en) * | 2022-03-31 | 2022-08-12 | 神华北电胜利能源有限公司 | Mining area soil moisture inversion method, device and computer readable storage medium |
Non-Patent Citations (2)
| Title |
|---|
| 半干旱地区半流动沙丘水分深层渗漏量及其对降雨格局的响应;王宇祥;刘廷玺;段利民;童新;王冠丽;李东方;;应用生态学报(第08期);第232-242页 * |
| 土壤水入渗补给数值模拟――以河北栾城为例;吴庆华;王贵玲;张家发;朱国胜;张薇;;长江科学院院报(第04期);第20-25页 * |
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