Agricultural cultivation water source scheduling method based on data processing

Abstract

The invention relates to the technical field of data processing, in particular to an agricultural cultivation water source scheduling method based on data processing, and the method comprises the steps: collecting farmland data at each time point through various sensors, and obtaining the water evaporation potential of each farmland at each time point according to the air temperature and humidity; obtaining a crop development water shortage index of each farmland at each time point according to the accumulated water depth and the soil humidity of each farmland at each time point; according to the water evaporation potential, the crop development water shortage index and the rainfall intensity, the pheromone volatilization coefficient on the water supply path between the farmlands is obtained; a real-time water supply optimization path is obtained according to the pheromone volatilization coefficient, and reasonable scheduling of water resources is completed. Therefore, reasonable scheduling of water resources is realized, the accuracy of a water supply optimization path is improved, and the timeliness of farmland irrigation is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data processing, in particular to an agricultural cultivation water source scheduling method based on data processing. BACKGROUND

[0002] Nowadays, the planting of farmland tends to be large-area intelligent management, among which, the accuracy and efficiency of the irrigation system are necessary conditions to ensure timely irrigation of crops and normal growth of crops. Different crops planted in different farmlands have different irrigation times, in addition, the environment and weather of farmland will also affect the water supply demand of farmland, and the staff can judge whether the farmland needs water supply irrigation through the collected information data of different farmlands. In order to ensure that crops are irrigated in time and avoid waste of water resources, we need a scientific and reasonable water resource scheduling scheme, and a good real-time farmland water supply optimization path is particularly necessary for the rational scheduling of water resources.

[0003] The ant colony algorithm in the path optimization algorithm has the advantages of strong global optimization ability and good adaptability to different problems, but the pheromone evaporation coefficient in the traditional ant colony algorithm is single, and the next node is inclined to be randomly selected, which although increases the ant colony exploration space, but the positive feedback time also increases, resulting in slow convergence speed.

[0004] In summary, the present application provides an agricultural cultivation water source scheduling method based on data processing, which obtains farmland environment data through various environment data acquisition devices, obtains the evaporation coefficient of each water supply path according to the farmland environment data, calculates the optimized path according to the evaporation coefficient of each water supply path, increases the probability that the water supply route passes through the farmland with high irrigation demand first, and irrigates according to the optimized path, so as to realize the rational scheduling of water resources. SUMMARY

[0005] In order to solve the above technical problems, the present application provides an agricultural cultivation water source scheduling method based on data processing to solve the existing problems.

[0006] The agricultural cultivation water source scheduling method based on data processing of the present application adopts the following technical scheme:

[0007] An embodiment of the present application provides an agricultural cultivation water source scheduling method based on data processing, which comprises the following steps:

[0008] Various sensors are used to collect farmland environment data at each time point;

[0009] The water evaporation potential of each farmland at each time point is obtained according to the environmental temperature and the air relative humidity of each farmland at each time point; the relative waterlogging depth of each farmland at each time point is obtained according to the waterlogging depth of each farmland at each time point; the relative soil humidity of each farmland at each time point is obtained according to the soil humidity of each farmland at each time point; and the crop development water deficiency index of each farmland at each time point is obtained according to the relative waterlogging depth and the relative soil humidity of each farmland at each time point.

[0010] The rainfall intensity of each farmland at each time point is obtained; and the relative water use comparative advantage degree of each farmland at each time point is obtained according to the water evaporation potential, the crop development water deficiency index and the rainfall intensity of each farmland at each time point.

[0011] The neighboring farmland set of each farmland is obtained according to the water supply path of each farmland; the pheromone volatilization coefficient on each water supply path is obtained according to the relative water use comparative advantage degree of each farmland at each time point and the neighboring farmland set of each farmland; the water supply optimization path is obtained according to the pheromone volatilization coefficient on each water supply path; and the water source is dispatched according to the water supply optimization path.

[0012] Preferably, the environmental data of each farmland at each time point is collected by using various sensors, and specifically, the environmental data of each farmland at each time point is collected by using the following sensors:

[0013] The environmental temperature data of each farmland is obtained by using a temperature sensor; the air relative humidity data and the soil humidity data of each farmland are obtained by using a humidity sensor; and the land surface water depth data of each farmland is obtained by using a water level sensor.

[0014] Preferably, the water evaporation potential of each farmland at each time point is obtained according to the environmental temperature and the air relative humidity of each farmland at each time point, and specifically, the product of the air relative humidity and the environmental temperature of each farmland at each time point is taken as the water evaporation potential of each farmland at each time point.

[0015] Preferably, the relative waterlogging depth of each farmland at each time point is obtained according to the waterlogging depth of each farmland at each time point, and specifically, for each farmland requiring surface waterlogging for growing crops, the ratio of the waterlogging depth of the farmland at each time point to the optimal waterlogging depth is taken as the relative waterlogging depth of the farmland at each time point; and for each farmland not requiring surface waterlogging for growing crops, the relative waterlogging depth of the farmland at each time point is obtained by using a preset value.

[0016] Preferably, the relative soil humidity of each farmland at each time point is obtained according to the soil humidity of each farmland at each time point, and specifically, the ratio of the soil humidity of each farmland to the optimal soil humidity is taken as the relative soil humidity of the farmland at each time point.

[0017] Preferably, the crop development water deficiency index of each farmland at each time point is obtained according to the relative waterlogging depth and the relative soil humidity of each farmland at each time point, and the expression is as follows:

[0018] For each farmland at each time point, taking the relative waterlogging depth of the farmland as the index of an exponential function with the natural constant e as the base, taking the relative soil humidity of the farmland as the index of an exponential function with the natural constant e as the base, taking the reciprocal of the product of the two exponential functions as the crop development water deficiency index of the farmland at each time point.

[0019] Preferably, the relative water use comparative advantage degree of each farmland at each time point is obtained according to the water evaporation potential, the crop development water deficiency index and the rainfall intensity of each farmland at each time point, and specifically comprises: calculating the sum value of the water evaporation potential and the crop development water deficiency index of each farmland at each time point, and taking the ratio of the sum value to the rainfall intensity of each farmland at each time point as the relative water use comparative advantage degree of each farmland at each time point.

[0020] Preferably, the set of neighboring farmlands of each farmland is obtained according to the water supply path of each farmland, and specifically comprises: for each farmland, counting the farmlands directly connected with the water supply path of the farmland, and taking each farmland directly connected with the water supply path of the farmland as the set of neighboring farmlands.

[0021] Preferably, the pheromone volatilization coefficient on each water supply path is obtained according to the relative water use comparative advantage degree of each farmland at each time point and the set of neighboring farmlands of each farmland, and specifically comprises:

[0022]

[0023] In the formula, ρ ij (t) is the volatilization coefficient on the water supply path between the i th farmland and the j th farmland, CAW j (t) is the relative water use comparative advantage degree of the j th farmland at the t th time point, allowed j is the set of neighboring farmlands of the j th farmland.

[0024] Preferably, the water supply optimization path is obtained according to the pheromone volatilization coefficient on each water supply path, and specifically comprises: taking the volatilization coefficient on each water supply path as the pheromone volatilization factor in the ant colony algorithm, inputting the pheromone volatilization factor into the probability calculation formula of the ant colony algorithm to obtain the probability of water flow passing through each path, and calculating the water supply optimization path by using the ant colony algorithm according to the probability of each water supply path.

[0025] The present application has at least the following beneficial effects:

[0026] The application obtains an optimized water supply path of farmland by combining the data processing technology with the environmental characteristics of farmland, and realizes the reasonable scheduling of water resources in farmland irrigation according to the optimized path. The evaporation coefficient of each water supply path is obtained through self-adaptation, which solves the problem of slow convergence speed caused by single evaporation coefficient in the traditional ant colony algorithm, increases the probability of the water supply route passing through the farmland with high irrigation demand, increases the accuracy of the water supply optimization path, and further improves the timeliness of farmland irrigation.

[0027] In order to solve the problem that single evaporation coefficient cannot combine the irrigation demand of each farmland, the relative water use comparative advantage degree of each farmland at each time point is obtained by combining the environmental factors of each farmland, so as to obtain the evaporation coefficient of each water supply path, and the optimized water supply path is obtained according to the evaporation coefficient, and the intelligent irrigation of farmland is completed according to the optimized water supply path, which has high rationality of farmland water resource scheduling. BRIEF DESCRIPTION OF DRAWINGS

[0028] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiment or prior art description. Obviously, the drawings in the following description are only some embodiments of the present application, and those skilled in the art can obtain other drawings according to these drawings without creative labor.

[0029] Figure 1 The flowchart of the agricultural cultivation water source scheduling method based on data processing provided by the present application is shown in the figure.

[0030] Figure 2 The schematic diagram of the water supply path of farmland is shown in the figure. DETAILED DESCRIPTION

[0031] In order to further illustrate the technical means and effects adopted by the present application to achieve the predetermined invention purpose, the specific implementation, structure, features and effects of the agricultural cultivation water source scheduling method based on data processing according to the present application are described in detail as follows by combining with the drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0032] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs.

[0033] The specific scheme of the agricultural cultivation water source scheduling method based on data processing provided by the present application is described in detail below in combination with the drawings.

[0034] An embodiment of the present application provides an agricultural cultivation water source scheduling method based on data processing.

[0035] Specifically, the present application provides an agricultural cultivation water source scheduling method based on data processing, which comprises the following steps: Figure 1

[0036] In step S001, the environment data of each farmland needing water supply is obtained.

[0037] The environment temperature data of each farmland is obtained by a temperature sensor, the air relative humidity data and soil humidity data of each farmland are obtained by a humidity sensor, and the land surface water depth data of each farmland is obtained by a water surface height sensor.

[0038] In step S002, the pheromone evaporation coefficient of each water supply path at each time point is obtained according to the environment data of each farmland at each time point.

[0039] In the farmlands needing water supply, the water demand of different farmlands is different, the water demand of some farmlands is relatively large and the situation is relatively urgent, so the water supply should be given priority to; the water demand of some farmlands is relatively small and the situation is relatively relaxed, so the water supply can be appropriately delayed. However, in the traditional ant colony algorithm, the pheromone evaporation coefficients of different paths are the same, and the water supply path selection does not consider the water supply demand of the farmland, and the water supply demand of the farmland changes with time. Therefore, the pheromone evaporation coefficient of each water supply path at each time point is obtained according to the water supply demand of each farmland at each time point, so as to update and optimize the path in real time, so that the farmland with high water supply demand at each time point can be supplied with water as soon as possible. The specific steps are as follows:

[0040] Generally, the higher the farmland environment temperature and the lower the air relative humidity, the faster the water evaporation speed, the more serious the water loss of the farmland crops and soil, and the higher the farmland water demand; on the contrary, when the temperature is low or the air relative humidity is high, the water evaporation is difficult and the water evaporation speed is slow, and the farmland water demand is relatively low; although the atmospheric pressure also affects the water evaporation speed, the atmospheric pressure of each farmland is relatively stable and is normal atmospheric pressure, so the influence of pressure is not considered. Therefore, taking the jth farmland at the t time point as an example, the water evaporation potential of each farmland at each time point is:

[0041] E j (t)=β·m j (t)·(T+273)

[0042] In the formula, E j (t) is the water evaporation potential of the jth farmland at the t time point, β is a limiting factor, m j ​(t) is the relative humidity of the air of the jth farmland at the t time point, and T is the environmental temperature of the jth farmland at the t time point. Wherein T is the temperature in Celsius, and the unit is ℃, and T+273 is the corresponding temperature in Kelvin, and the unit is Kelvin.

[0043] It should be noted that the value of β can be set by the implementer, and in this embodiment, the value of β is set to 0.5. Through the setting of β, the value range of water evaporation potential is limited in the range of (0-1], so as to facilitate subsequent calculation; the higher the water evaporation potential, the faster the water evaporation speed in the farmland, and the higher the demand degree of the farmland for water; the lower the water evaporation potential, the slower the water evaporation speed in the farmland, and the lower the demand degree of the farmland for water.

[0044] In common crops, some crops (such as rice) need to accumulate water on the surface of the soil and the accumulated water depth reaches a certain value to grow normally. For example, when the accumulated water depth on the surface of the soil is less than the optimal accumulated water depth required for the growth of rice, the water supply required by the rice is insufficient, which will affect the yield of the rice, so at this time, the demand degree of the rice for water is higher, and the demand degree of the paddy field for water is higher; when the accumulated water depth on the surface of the soil is greater than the optimal accumulated water depth required for the growth of rice, it indicates that the water in the paddy field is already saturated, and no additional water is needed, so at this time, the demand degree of the paddy field for water is lower. In addition, each crop has a certain requirement for soil humidity, when the soil humidity is less than the optimal soil humidity required for the growth of crops, it will affect the absorption of water by crops, affect the normal growth of crops, and thus affect the yield of crops, so at this time, the demand degree of the farmland for water is higher, and the smaller the soil humidity, the drier the land, and the higher the demand degree of the farmland for water; when the soil humidity is greater than the optimal soil humidity required for the growth of crops, the demand degree of the farmland for water is lower. Therefore, taking the jth farmland at the t time point as an example, the crop development water deficiency index of each farmland at each time point is obtained according to the accumulated water depth and the soil humidity of each farmland at each time point, and the expression is:

[0045]

[0046] In the formula, G j (t) is the crop development water deficiency index of the jth farmland at the t time point, WHR j (t) is the relative accumulated water depth of the jth farmland at the t time point, WCR j (t) is the relative soil humidity of the jth farmland at the t time point, e () is the exponential function with e as the base, and α is the limiting factor; h j (t) is the accumulated water depth of the jth farmland at the t time point, h j (0) is the optimal accumulated water depth of the jth farmland at the t time point; c j (t) is the soil humidity of the jth farmland at the t time point, c j(0) is the optimum soil moisture of the jth farmland at time t. It should be noted that the value of α can be set by the implementer. In this embodiment, the value of α is set to 1-e -1 By setting α, the crop development water shortage index is limited to the range of (0,1] to facilitate subsequent calculations; when the jth farmland needs surface water at time t, WHR j The smaller the value of (t), the greater the demand for water for the farmland. When supplying water, the farmland should be given priority as much as possible. j The larger the (t) value is, the smaller the demand for water for the farmland is, and the water supply to the farmland can be appropriately delayed. When the jth farmland does not need surface water at time t, the WHR j The value of (t) is set to -1, so that when calculating the crop development water shortage index, The result is 1, which avoids the lack of water depth parameters in the farmland, thus affecting the calculation of the crop development water shortage index. j The smaller the value of (t), the drier the soil, and the greater the water demand of the jth farmland at time t; j The larger the value of (t), the smaller the water demand of the farmland. j (t) is the crop development water shortage index of the jth farmland at time t, G j The larger the value of (t), the greater the water demand of the farmland, and the higher the priority of water supply to the farmland should be; j The smaller the value of (t), the smaller the water demand of the farmland, and the water supply priority of the farmland should be relatively lowered.

[0047] The rainfall intensity of each farmland at each time point is obtained based on the rainfall observation system. The specific method is well-known technology and will not be elaborated here. Since rainfall provides additional water supply to farmland, taking the jth farmland at time point t as an example, the relative water use comparative advantage of each farmland at each time point is calculated based on the above two indicators combined with rainfall intensity:

[0048]

[0049] Where, CAW j (t) is the comparative advantage of water use of the jth farmland at time t, E j (t) is the water evaporation potential of the jth farmland at time t, G j (t) is the crop development water shortage index of the jth farmland at time t, R j (t) is the rainfall intensity of the j-th farmland at time point t, exp() is an exponential function with e as the base, and γ is a constant to prevent the denominator from being 0. The value of γ can be selected by the implementer. In this embodiment, the value of γ is set to 1.

[0050] When there is rainfall in the area where the j-th farmland is located at time point t, the amount of water required to be transported by the water supply center will decrease, so the water supply order of the farmland can be appropriately delayed; when there is no rainfall in the farmland at time point t, all the water used for the farmland comes from the water supply center. At this time, the water supply demand level of the farmland remains unchanged, and the water supply order cannot be delayed.

[0051] If the relative water use comparative advantage of a certain farmland is greater, it means that when supplying water, the water supply priority of this farmland is higher, and the water supply path should pass through this farmland first, that is, the pheromone volatility coefficient on the water supply path from other farmlands to this farmland should be smaller, so that more pheromones are retained on the water supply path, thereby increasing the probability of ants choosing the path of this farmland; if the relative water use comparative advantage index value of a certain farmland is smaller, then when supplying water, the water supply to this farmland can be appropriately delayed, that is, the pheromone volatility coefficient on the path from other farmlands to this farmland should be larger, so that less pheromones are retained on the water supply path, thereby reducing the probability of ants choosing the path of this farmland.

[0052] Take the jth farmland as an example, Figure 2 As shown, the big dots are water supply centers, the small dots are farmlands, and the straight lines are water supply paths in the irrigation system. Since there is not a direct water supply path between any two farmlands, the farmlands directly connected to farmland j are farmlands 5, 7, 8, and 9. Therefore, the set of other farmlands directly connected to farmland j through the water supply path is allowed. j ={5,7,8,9}, set allowed j As the set of neighboring farmlands of the jth farmland, the pheromone volatility coefficient on each water supply path is constructed, and the expression is:

[0053]

[0054] Where, ρ ij (t) is the volatility coefficient on the water supply path between the i-th farmland and the j-th farmland, CAW j (t) is the comparative advantage of water use of the jth farmland at time t, allowed j is the set of neighboring farmlands of the jth farmland.

[0055] The greater the relative water use comparative advantage of the j-th farmland, the greater the demand for water in the region, and the more pheromones should be retained on the path from other farmlands to the j-th farmland, that is, the pheromone volatility coefficient on the water supply path connected to the j-th farmland is smaller; the smaller the relative water use comparative advantage of the j-th farmland, the smaller the demand for water in the region, and the fewer pheromones should be retained on the path from other farmlands to the j-th farmland, that is, the pheromone volatility coefficient on the water supply path connected to the j-th farmland is larger.

[0056] In step S003, the real-time optimized path of the farmland water supply is obtained through the ant colony algorithm, and the real-time optimized path is sent to the water supply center to complete the reasonable allocation of water resources.

[0057] The evaporation coefficients of the water supply paths are determined through the above steps, and the evaporation coefficients of the water supply paths are taken as pheromone evaporation factors in the ant colony algorithm, and are input into a probability calculation formula of the ant colony algorithm to calculate the probability of water flow through each path from the water supply center, wherein the probability calculation is a known technology, and will not be described here again. The probabilities of the water supply paths are substituted into the ant colony algorithm for modeling, and finally an optimized path for supplying water to each farmland is obtained. The monitoring center of the local agricultural water conservancy department sends the obtained optimized path of farmland water supply to the water supply center, and the water supply center supplies water resources to each farmland according to the optimized path to ensure the normal operation of agricultural production.

[0058] In summary, the embodiment of the present application obtains the optimized path of farmland water supply by combining the data processing technology with the environmental characteristics of the farmland, and realizes the reasonable scheduling of water resources in farmland irrigation according to the optimized path. The evaporation coefficients of the water supply paths are obtained through self-adaptation, which solves the problem of slow convergence speed caused by a single evaporation coefficient in the traditional ant colony algorithm, increases the probability of the water supply route passing through the farmland with high irrigation demand, increases the accuracy of the water supply optimized path, and further improves the timeliness of farmland irrigation.

[0059] In order to solve the problem that a single evaporation coefficient cannot combine the irrigation demand of each farmland, the embodiment combines the environmental factors of each farmland to obtain the relative water use comparative advantage degree of each farmland at each time point, so as to obtain the evaporation coefficients of each water supply path, obtain the water supply optimized path according to the evaporation coefficients, and complete the intelligent irrigation of the farmland according to the water supply optimized path, which has high rationality of farmland water resource scheduling.

[0060] It should be noted that: the above-mentioned sequence of the embodiments of the present application is only for description, and does not represent the advantages and disadvantages of the embodiments. The above describes the specific embodiments of the present application. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multi-task processing and parallel processing are also possible or can be advantageous.

[0061] Each embodiment in the present specification is described in a progressive manner, and the same or similar parts of each embodiment can be referred to each other. Each embodiment mainly describes the differences from other embodiments.

[0062] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than limit them; the technical solutions recorded in the foregoing embodiments are modified, or some technical features are replaced equivalently, and the essence of the corresponding technical solutions does not deviate from the scope of the technical solutions of the embodiments of the present application, which should be included in the protection scope of the present application.

Claims

1. The agricultural cultivation water source scheduling method based on data processing is characterized by: The method comprises the following steps: Various sensors are used to collect environmental data of each farmland at each time point; The water evaporation potential of each farmland at each time point is obtained based on the ambient temperature and relative air humidity of each farmland at each time point; the relative water depth of each farmland at each time point is obtained based on the water depth of each farmland at each time point; the relative soil moisture of each farmland at each time point is obtained based on the soil moisture of each farmland at each time point; and the crop development water shortage index of each farmland at each time point is obtained based on the relative water depth and relative soil moisture of each farmland at each time point. Obtain the rainfall intensity of each farmland at each time point; obtain the relative water use comparative advantage of each farmland at each time point based on the water evaporation potential, crop development water shortage index and rainfall intensity of each farmland at each time point; Based on the water supply path of each farmland, the set of neighboring farmlands of each farmland is obtained; based on the relative water use comparative advantage of each farmland at each time point and the set of neighboring farmlands of each farmland, the pheromone volatility coefficient on each water supply path is obtained; based on the pheromone volatility coefficient on each water supply path, the optimized water supply path is obtained; and water source scheduling is carried out according to the optimized water supply path.

2. The agricultural cultivation water source scheduling method based on data processing according to claim 1, characterized in that: The various sensors are used to collect farmland environmental data at various time points, specifically: The ambient temperature data of each farmland is obtained through the temperature sensor, the relative humidity data of the air and the soil moisture data of each farmland are obtained through the humidity sensor, and the land surface water depth data of each farmland is obtained through the water level sensor.

3. The agricultural cultivation water source scheduling method based on data processing according to claim 1, characterized in that: The method of obtaining the water evaporation potential of each farmland at each time point according to the ambient temperature and relative air humidity of each farmland at each time point includes: taking the product of the relative air humidity and the ambient temperature of each farmland at each time point as the water evaporation potential of each farmland at each time point.

4. The agricultural cultivation water source scheduling method based on data processing according to claim 1, characterized in that: The relative water depth of each farmland at each time point is obtained based on the water depth of each farmland at each time point, specifically including: for each farmland that requires surface water accumulation to grow crops, the ratio of the water depth of the farmland at each time point to the optimal water depth is used as the relative water depth of the farmland at each time point; for each farmland that does not require surface water accumulation to grow crops, the relative water depth of the farmland at each time point is obtained through a preset value.

5. The agricultural cultivation water source scheduling method based on data processing according to claim 1, characterized in that: The obtaining of the relative soil moisture of each farmland at each time point according to the soil moisture of each farmland at each time point specifically includes: taking the ratio of the soil moisture of each farmland to the optimum soil moisture as the relative soil moisture of the farmland at each time point.

6. The agricultural cultivation water source scheduling method based on data processing according to claim 1, characterized in that: The crop development water shortage index of each farmland at each time point is obtained according to the relative water depth and relative soil moisture of each farmland at each time point, and the expression is: For each farmland at each time point, the relative water depth of the farmland is taken as the exponent of an exponential function with the natural constant e as the base, and the relative soil moisture of the farmland is taken as the exponent of an exponential function with the natural constant e as the base; the inverse of the product of the two exponential functions is taken as the crop development water shortage index of each farmland at each time point.

7. The agricultural cultivation water source scheduling method based on data processing according to claim 1, characterized in that: The method of obtaining the relative water use comparative advantage of each farmland at each time point based on the water evaporation potential, crop development water shortage index and rainfall intensity of each farmland at each time point specifically includes: calculating the sum of the water evaporation potential and the crop development water shortage index of each farmland at each time point, and taking the ratio of the sum to the rainfall intensity of each farmland at each time point as the relative water use comparative advantage of each farmland at each time point.

8. The agricultural cultivation water source scheduling method based on data processing according to claim 1, characterized in that: The neighboring farmland set of each farmland is obtained according to the water supply path of each farmland. Specifically, for each farmland, the farmlands directly connected to the farmland water supply path are counted, and the farmlands directly connected to the farmland water supply path are regarded as the neighboring farmland set.

9. The agricultural cultivation water source scheduling method based on data processing according to claim 1, characterized in that: The pheromone volatility coefficient on each water supply path is obtained based on the relative water use comparative advantage of each farmland at each time point and the set of neighboring farmlands of each farmland, specifically including: Where, ρ ij (t) is the volatility coefficient on the water supply path between the i-th farmland and the j-th farmland, CAW j (t) is the comparative advantage of water use of the jth farmland at time t, allowed j is the set of neighboring farmlands of the jth farmland.

10. The agricultural cultivation water source scheduling method based on data processing according to claim 1, characterized in that: The method of obtaining the optimized water supply path according to the pheromone volatility coefficient on each water supply path is as follows: the volatility coefficient on each water supply path is used as the pheromone volatility factor in the ant colony algorithm, and is input into the probability calculation formula of the ant colony algorithm to obtain the probability of water flowing through each path; and the optimized water supply path is calculated using the ant colony algorithm according to the probability of each water supply path.

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