A crop layout analysis optimization method based on water footprint

Abstract

This invention relates to a crop layout analysis and optimization method based on water footprint. It can acquire relevant calculation data for a preset area in a preset year; perform crop planting structure evolution analysis to obtain the rate of change of crop area in the preset year; perform center of gravity trajectory analysis to obtain the center of gravity trajectory analysis results; establish an objective function relating unit water footprint to crop planting area; and use the objective function to obtain the crop layout optimization results based on water footprint. By collecting and analyzing relevant data, the method accurately calculates crop water requirements and water footprint, and then establishes a scientific objective function to optimize crop layout, providing effective decision support for agricultural production.

Description

Technical Field

[0001] This invention relates to the field of crop planting technology, specifically to a crop layout analysis and optimization method based on water footprint. Background Technology

[0002] In the field of agricultural production, the rational utilization of water resources and the optimization of crop layout have always been crucial research topics. With global population growth and economic development, the demand for agricultural products is constantly increasing, while the limited and uneven distribution of water resources has become one of the key factors restricting the sustainable development of agriculture.

[0003] In many agricultural regions, such as cotton-growing areas in China, the long-standing problems of inefficient water use and irrational crop layout have been severe. On the one hand, traditional agricultural production methods often lack precise quantification and scientific analysis of crop water requirements, leading to significant water waste during irrigation. For example, in some areas, a uniform irrigation model is used regardless of the actual water needs of crops, resulting in the ineffective use of some water resources and even causing environmental problems such as secondary soil salinization. On the other hand, crop layout is usually based on historical planting habits and short-term economic interests, without fully considering the differences in water resource endowments across different regions. This has led to the cultivation of large quantities of water-intensive crops in some water-scarce areas, further exacerbating the water supply and demand imbalance, while also affecting crop yield and quality, and reducing the overall efficiency of agricultural production.

[0004] Furthermore, previous research methods have certain limitations in assessing crop water use and optimizing its distribution. Most studies focus only on single crops or local areas, lacking systematic analysis of multiple major crops over larger regions. Summary of the Invention

[0005] In view of this, the purpose of this invention is to provide a crop layout analysis and optimization method based on water footprint, so as to solve the problem that there are certain limitations in the existing technology in assessing crop water use and layout optimization.

[0006] According to a first aspect of the present invention, a method for optimizing crop layout based on water footprint is provided, comprising: Obtain calculation-related data for a preset year and preset region. The calculation-related data includes meteorological data, crop production data, crop growth stage data, and growth coefficients. Based on the production data of each crop, an analysis of the evolution of crop planting structure was conducted to obtain the rate of change of crop area in the preset years; Based on the relevant calculation data, calculate the crop water requirement for each crop throughout its entire growth period at a preset time point; Based on the crop water requirement calculation results, the center of gravity trajectory analysis of crop water requirement between preset time points is performed to obtain the center of gravity trajectory analysis results. Based on the aforementioned calculation data, the water footprint of crop production is calculated, and the unit water footprint is calculated based on the water footprint of crop production. To minimize the total water footprint of crop planting, an objective function is established that relates unit water footprint to crop planting area. The objective function is used to obtain the crop layout optimization results based on water footprint; Output the rate of change of crop area, the center of gravity trajectory analysis results, and the crop layout optimization results for the preset years.

[0007] Preferably, crop planting structure evolution analysis is performed to obtain the rate of change of crop area in preset years, including: The migration rate of each crop can be calculated using the following formula:

[0008] In the formula, CM represents crop migration rate; CPA before The area planted with crops before the change; CPA after The changed crop planting area; Based on the overall crop migration rate, the rate of change in crop area for the preset years is obtained.

[0009] Preferably, the calculation of crop water requirements throughout the entire growth period for each crop includes: The crop reference evapotranspiration is calculated using the following formula:

[0010] Among them, ET O The reference evapotranspiration for crops is given; Δ is the slope of the saturated vapor pressure versus temperature curve; R n G represents net radiation from the crop surface; G represents soil heat flux. γ This is the constant of the hygrometer; T The average temperature; e a e is the saturated vapor pressure; s u1 is the actual water vapor pressure; u2 is the average daily wind speed at a height of 2m. The actual evapotranspiration of the crop is calculated based on the crop reference evapotranspiration and the crop coefficient:

[0011] Among them, ET C K represents the actual evapotranspiration of the crop. C For the corresponding crop coefficient; The actual evapotranspiration of crops is taken as the crop water requirement.

[0012] Preferably, calculating the crop water requirement for each crop throughout its entire growth period also includes: The blue water requirement of crops can be calculated using the following formula:

[0013] Among them, ET blue The average daily evapotranspiration of blue water; CWU blue The water requirement for blue water; The crop's green water requirement can be calculated using the following formula: Among them, ET green The average daily evapotranspiration of green water; CWU green Water demand for green water; The sum of the blue water requirement and the green water requirement of crops is taken as the crop water requirement.

[0014] Preferably, the center-of-gravity trajectory analysis is performed on the crop water requirement between preset time points to obtain the center-of-gravity trajectory analysis results, including: Based on the crop water requirement calculation results, the centroid coordinates of water storage at all preset time points are obtained; Based on the centroid coordinates of the water storage volume at all preset time points, the distance the centroid of the water storage volume moves between different preset time points is calculated. The centroid coordinates of the water storage volume at all preset time points and the distance the centroid of the water storage volume moves between different preset time points are integrated into the centroid trajectory analysis results.

[0015] Preferably, calculating the water footprint of crop production includes: The green water footprint, blue water footprint, and gray water footprint are calculated using the following formulas:

[0016]

[0017]

[0018] Among them, WF green For the green footprint, WF blue For Blue Water Footprint, WF grey For greywater footprints, ET blue For the average daily evapotranspiration of blue water, ET green For the average daily evapotranspiration of green water, l α The surface runoff fraction of nitrogen fertilizer, l β C represents the infiltration fraction of nitrogen fertilizer. max C represents the maximum acceptable concentration of nitrogen fertilizer in a specific water body. nat Y represents the natural concentration of nitrogen fertilizer in a specific water body, and Y represents crop yield. The sum of the green water footprint, blue water footprint, and gray water footprint is taken as the water footprint of crop production.

[0019] Preferably, the daily average evapotranspiration of green water and the daily average evapotranspiration of blue water are calculated using the following formulas:

[0020]

[0021]

[0022] Among them, P eff ET represents the effective precipitation during the crop growing season, P represents the total precipitation over a 10-day period, and ET represents the total precipitation over a 10-day period. C This refers to the actual evapotranspiration of the crop.

[0023] Preferably, with the goal of minimizing the total water footprint of crop cultivation, an objective function is established for the relationship between unit water footprint and crop planting area, including: The objective function is:

[0024] Where f(1) is the minimum total water footprint in the region, W ij X is the unit water footprint of crop j in region i. ij is the planting area of ​​crop j in region i, n is the total area of ​​the region, and m is the total number of crop types.

[0025] The technical solutions provided by the embodiments of the present invention may include the following beneficial effects: It is understood that the technical solution presented in this invention can acquire relevant calculation data for a preset year and preset region; perform crop planting structure evolution analysis to obtain the rate of change of crop area in the preset year; perform center of gravity trajectory analysis to obtain the center of gravity trajectory analysis results; establish an objective function for the relationship between unit water footprint and crop planting area; and use the objective function to obtain crop layout optimization results based on water footprint. By collecting and analyzing relevant data, the water requirement and water footprint of crops can be accurately calculated, thereby establishing a scientific objective function to optimize crop layout and providing effective decision support for agricultural production.

[0026] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit the invention. Attached Figure Description

[0027] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0028] Figure 1This is a schematic diagram illustrating the steps of a crop layout analysis and optimization method based on water footprint, according to an exemplary embodiment. Detailed Implementation

[0029] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of apparatuses and methods consistent with some aspects of the invention as detailed in the appended claims.

[0030] In one embodiment, Figure 1 This is a schematic diagram illustrating the steps of a crop layout analysis and optimization method based on water footprint, according to an exemplary embodiment. See also... Figure 1 This paper provides a method for crop layout analysis and optimization based on water footprint, including: Step S11: Obtain calculation-related data for a preset year and preset area. The calculation-related data includes meteorological data, crop production data, crop growth stage data, and growth coefficient. Step S12: Based on the production data of each crop, conduct an evolution analysis of crop planting structure to obtain the rate of change of crop area in the preset years; Step S13: Based on the calculated relevant data, calculate the crop water requirement for each crop throughout its entire growth period at a preset time point; Step S14: Based on the crop water requirement calculation results, perform a center of gravity trajectory analysis on the crop water requirement between preset time points to obtain the center of gravity trajectory analysis results; Step S15: Calculate the crop production water footprint based on the relevant calculation data, and calculate the unit water footprint based on the crop production water footprint; Step S16: With the goal of minimizing the total water footprint of crop planting, establish an objective function relating unit water footprint to crop planting area; Step S17: Use the objective function to obtain the crop layout optimization results based on water footprint; Step S18: Output the rate of change of crop area in the preset years, the center of gravity trajectory analysis results, and the crop layout optimization results.

[0031] It is understood that the technical solution presented in this invention can acquire relevant calculation data for a preset year and preset region; perform crop planting structure evolution analysis to obtain the rate of change of crop area in the preset year; perform center of gravity trajectory analysis to obtain the center of gravity trajectory analysis results; establish an objective function for the relationship between unit water footprint and crop planting area; and use the objective function to obtain crop layout optimization results based on water footprint. By collecting and analyzing relevant data, the water requirement and water footprint of crops can be accurately calculated, thereby establishing a scientific objective function to optimize crop layout and providing effective decision support for agricultural production.

[0032] In step S11, relevant calculation data for a preset year and preset region are obtained. For example, meteorological data for 13 cotton-growing provinces in China from 1980 to 2019 (Hubei, Hunan, Jiangsu, Jiangxi, and Anhui in the Yangtze River Basin; Tianjin, Hebei, Shandong, Henan, Shanxi, and Shaanxi in the Yellow River Basin; and Xinjiang and Gansu in the Northwest Inland Cotton-Growing Region) are obtained, including maximum temperature, minimum temperature, relative humidity, sunshine duration, average wind speed at 2m, and daily precipitation. Production data for various crops in the cotton-growing region (cotton, corn, wheat, rice, rapeseed, potato, and peanut) are collected, such as yield data, sown area, and gross production value, and verified and corrected. Crop growth stage data and growth coefficient (KC) are collected.

[0033] It should be noted that in step S12, crop planting structure evolution analysis is performed to obtain the rate of change of crop area in the preset years, including: The migration rate of each crop can be calculated using the following formula:

[0034] In the formula, CM represents crop migration rate; CPA before The area planted with crops before the change; CPA after The changed crop planting area; based on the overall crop migration rate, the change rate of crop area for the preset years is obtained.

[0035] In practice, taking the data obtained above as an example, crop migration is achieved by calculating the average total area of ​​various crops from 2015 to 2019 and from 1980 to 1984, then calculating the difference, and finally comparing it with that from 1980 to 1984 to obtain the rate of change of crop area in China's cotton-growing areas over the past forty years.

[0036] It should be noted that in step S13, the CropWat 8.0 model recommended by the Food and Agriculture Organization of the United Nations (FAO) can be used for calculation. The crop water requirement for each crop throughout its entire growth period includes: The crop reference evapotranspiration is calculated using the following formula:

[0037] Among them, ET O The reference evapotranspiration for crops is given; Δ is the slope of the saturated vapor pressure versus temperature curve; R n G represents net radiation from the crop surface; G represents soil heat flux. γ This is the constant of the hygrometer; T The average temperature; e a e is the saturated vapor pressure; s u1 is the actual water vapor pressure; u2 is the average daily wind speed at a height of 2m. The actual evapotranspiration of the crop is calculated based on the crop reference evapotranspiration and the crop coefficient:

[0038] Among them, ET C K represents the actual evapotranspiration of the crop. C For the corresponding crop coefficient; Assuming the crop grows under optimal conditions, the actual evapotranspiration of the crop can be taken as the crop's water requirement.

[0039] Crop water requirements consist of two parts: blue water requirements and green water requirements. The sources and acquisition costs of these two parts differ significantly. Green water requirements refer to the water demand for effective rainfall during crop growth; blue water requirements refer to the water demand for water beyond effective rainfall. Calculating the total water requirement for each crop throughout its entire growth cycle also includes: The blue water requirement of crops can be calculated using the following formula:

[0040] Among them, ET blue The average daily evapotranspiration of blue water; CWU blue The water requirement for blue water; The crop's green water requirement can be calculated using the following formula: Among them, ET green The average daily evapotranspiration of green water; CWU green Water demand for green water; The sum of the blue water requirement and the green water requirement of crops is taken as the crop water requirement.

[0041] The total water requirements for blue water and green water of crops throughout their entire growth period are equal to the cumulative daily evapotranspiration of the crops from planting to harvest.

[0042] In step S14, the center-of-gravity migration of crop water requirements is analyzed. The center of gravity, a concept derived from geometry and physics, represents the spatial equilibrium point of regional elements in geography. Center-of-gravity migration is a commonly used method for studying the spatial distribution of regional elements, with wide applicability, aiming to reflect the spatial variation trend of elements between years. In this embodiment, using ArcGIS software and the center-of-gravity model method, the center-of-gravity trajectory of regional crop water requirements at different preset time points (e.g., 1980, 1985, 2015, and 2020) is described.

[0043] It should be noted that the center-of-gravity trajectory analysis of crop water requirements between preset time points yields the following results: Based on the crop water requirement calculation results, the centroid coordinates P(x) of the water storage at all preset time points are obtained. j ,y j );

[0044]

[0045] P(x j ,y j ) represents the geographical coordinates x in year j. j With y j In the formula, x j Let y be the longitude of the centroid P in year j. j Let Q be the latitude of the centroid P in year j. ij To calculate the weight of the centroid, i.e. the crop water requirement value for the i-th region in the j-th year.

[0046] Based on the centroid coordinates of the water storage volume at all preset time points, the distance the centroid of the water storage volume moves between different preset time points is calculated.

[0047] Where xk+m and xk represent the longitude coordinates of the barycenter P in year k+m and year k, respectively, and yk+m and yk represent the latitude coordinates of the barycenter P in year k+m and year k, respectively.

[0048] The centroid coordinates of the water storage volume at all preset time points and the distance the centroid of the water storage volume moves between different preset time points are integrated into the centroid trajectory analysis results.

[0049] In step S15, a regional-scale water footprint assessment is conducted. The crop production water footprint refers to the total amount of water resources consumed per unit yield during crop growth, including the green water footprint, blue water footprint, and grey water footprint. The green water footprint refers to water that enters the atmosphere through transpiration and evaporation, primarily originating from soil water stored on the soil surface and utilized by plants. The blue water footprint refers to surface water and groundwater resources utilized by crops. The grey water footprint refers to the amount of water required to dilute pollutants generated during the production of the target product to the highest acceptable and safe concentration in water bodies. The grey water footprint determines the amount of water required to dilute pollutants to meet water quality standards; this is mainly due to the excessive use of nitrogen fertilizers, while phosphorus and potassium fertilizers are neglected due to their lower pollution levels.

[0050]

[0051] It should be noted that calculating the water footprint of crop production includes: The green water footprint, blue water footprint, and gray water footprint are calculated using the following formulas:

[0052]

[0053]

[0054] Among them, WF green For the green footprint, WF blue For Blue Water Footprint, WF grey For greywater footprints, ET blue For the average daily evapotranspiration of blue water, ET green For the average daily evapotranspiration of green water, l α The surface runoff fraction of nitrogen fertilizer, l β C represents the infiltration fraction of nitrogen fertilizer. max C represents the maximum acceptable concentration of nitrogen fertilizer in a specific water body. nat Y represents the natural concentration of nitrogen fertilizer in a specific water body, and Y represents crop yield. The sum of the green water footprint, blue water footprint, and gray water footprint is taken as the water footprint of crop production.

[0055] It should be noted that the average daily evapotranspiration of green water and the average daily evapotranspiration of blue water can be calculated using the following formulas:

[0056]

[0057]

[0058] Among them, P effET represents the effective precipitation during the crop growing season, P represents the total precipitation over a 10-day period, and ET represents the total precipitation over a 10-day period. C This refers to the actual evapotranspiration of the crop.

[0059] In step S17, a linear programming model is constructed. The objective function is a method for finding the optimal solution for each specific objective under various constraints. It is computed using Python's PULP linear programming package. Among numerous intelligent algorithms for solving objective optimization problems, linear programming stands out for its efficiency and simple, clear model building, enabling decision-makers to quickly find the optimal solution. It can be used for various problems, such as resource allocation and production planning, and it provides feasibility and sensitivity analysis, helping to evaluate the model's stability under varying inputs. Furthermore, the quantitative method reduces subjectivity, improves the scientific rigor of decision-making, and provides a visual representation that intuitively presents the feasible solution region and the optimal solution.

[0060] It should be noted that, with the goal of minimizing the total water footprint of crop cultivation, an objective function is established for the relationship between unit water footprint and crop planting area, including: The objective function is:

[0061] Where f(1) is the minimum total water footprint in the region, W ij X is the unit water footprint of crop j in region i. ij is the planting area of ​​crop j in region i, n is the total area of ​​the region, and m is the total number of crop types.

[0062] The objective function described above uses several crops, including cotton, wheat, and corn, from China's cotton-growing regions as representatives in a structural configuration simulation. The planting areas of various crops in 13 provinces, including Xinjiang and Hebei, are summed to determine the decision variables for the planting configuration model of the main crops. Let X... ij (i=1,2,3; j=1,2,3...20) represents the decision variables, where i is the province and j is the crop type.

[0063] The constraints of the above objective function are as follows: Constraint 1: The total planting area of ​​each province remains unchanged. For each province i, the optimized total planting area of ​​crops is equal to the initial total planting area of ​​each crop.

[0064]

[0065] In the formula: A ij This represents the initial planting area of ​​crop j in province i.

[0066] Constraint 2: If the initial planting area of ​​a crop is zero, the optimized planting area must also be zero.

[0067]

[0068] In the formula: X ij Let A be the planting area of ​​crop j in province i, n be the number of provinces, m be the number of crop types, and A be the number of crop varieties. ij This represents the initial planting area of ​​crop j in province i. Constraint 3: The optimized yield cannot be lower than the initial yield. The total optimized yield of each crop j cannot be lower than the initial total yield T. j 0 (The permissible reduction in output is 0, meaning that reduction is not allowed.)

[0069] In the formula: P ij T represents the yield per unit area (yield per hectare) of crop j in province ii. j 0 Represents the initial total yield of crop j. Constraint 4: The crop planting area in the main producing areas must remain unchanged or increase. For each crop j in the main producing areas Mj, the total crop planting area in the main producing areas cannot decrease.

[0070] In the formula: A ij This represents the initial planting area of ​​crop j in province i. Constraint 5: The net profit per unit of crop cultivation in the main production area must remain constant or increase. For each crop j in the main production area Mj, the total net profit per unit of crop cultivation in the main production area cannot decrease.

[0071]

[0072] In the formula: R ij This represents the net profit per unit (profit per hectare) of crop j in province i. Feasible solution space: All decision variables must be non-negative.

[0073] In the formula: X ij is the planting area of ​​crop j in province i, n is the number of provinces, and m is the number of crop types.

[0074] The crop layout analysis and optimization method based on water footprint of the present invention has the following beneficial effects: Improving water resource utilization efficiency: By accurately acquiring meteorological data, crop production data, crop growth stage data, and growth coefficients, and calculating crop water requirements and water footprints, it is possible to precisely grasp the water needs of different crops at different growth stages. This allows for the rational allocation of water resources according to actual needs during agricultural irrigation, avoiding overuse and waste, effectively improving water resource utilization efficiency, and alleviating water resource pressure in agricultural production.

[0075] Analyzing crop water requirements and water footprints using scientific methods helps identify high-water-consuming and low-water-consuming crops, enabling rational allocation based on regional water resource conditions. For example, in areas with relatively scarce water resources, the planting area of ​​high-water-consuming crops can be appropriately reduced while the proportion of low-water-consuming crops can be increased, thereby optimizing water resource allocation and improving overall water resource utilization efficiency.

[0076] Optimizing crop layout: This method, based on the analysis of the evolution of crop planting structure, derives the rate of change in crop area, providing a clear understanding of the dynamic trends in the planting area of ​​different crops over different time periods. Combined with the results of center-of-gravity trajectory analysis, it offers a deeper understanding of the spatial distribution of crop water requirements, thus providing a scientific basis for crop layout.

[0077] By optimizing crop layout using an established objective function, the relationship between unit water footprint and crop planting area is fully considered. This approach enables the rational distribution of crops across different regions while meeting agricultural production needs. This optimized crop layout better adapts to varying natural conditions and water resources in different areas, improving crop adaptability to different growing environments, thereby increasing crop yield and quality and enhancing the economic benefits of agricultural production.

[0078] Promoting sustainable agricultural development: Rational crop layout and efficient water resource utilization help reduce the negative environmental impacts of agricultural production. For example, avoiding soil degradation and water pollution caused by over-irrigation and improper fertilization protects the agricultural ecological environment and lays the foundation for long-term sustainable agricultural development.

[0079] By improving water resource utilization efficiency and optimizing crop layout, we can achieve stable growth in agricultural production under limited water resources, ensure the security of agricultural product supply, meet social demand for agricultural products, promote the coordinated development of agriculture and the ecological environment, and achieve the goal of sustainable agricultural development.

[0080] Providing scientific decision support: The crop area change rate, center of gravity trajectory analysis results, and crop layout optimization results output by this invention provide agricultural producers, managers, and decision-makers with comprehensive and accurate information and scientific decision-making basis. They can formulate reasonable agricultural production plans, water resource management strategies, and regional agricultural development plans based on these results, improving the scientific rigor and rationality of decision-making and promoting the healthy development of the agricultural industry.

[0081] It is understood that the same or similar parts in the above embodiments can be referred to each other, and the contents not described in detail in some embodiments can be referred to the same or similar contents in other embodiments.

[0082] It should be noted that in the description of this invention, the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance. Furthermore, in the description of this invention, unless otherwise stated, "a plurality of" means at least two.

[0083] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing a particular logical function or process, and the scope of the preferred embodiments of the invention includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as will be understood by those skilled in the art to which embodiments of the invention pertain.

[0084] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0085] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0086] Furthermore, the functional units in the various embodiments of the present invention can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0087] The storage media mentioned above can be read-only memory, disk, or optical disk, etc.

[0088] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0089] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A method for crop layout analysis and optimization based on water footprint, characterized in that, include: Obtain calculation-related data for a preset year and preset region. The calculation-related data includes meteorological data, crop production data, crop growth stage data, and growth coefficients. Based on the production data of each crop, an analysis of the evolution of crop planting structure was conducted to obtain the rate of change of crop area in the preset years; Based on the relevant calculation data, calculate the crop water requirement for each crop throughout its entire growth period at a preset time point; Based on the crop water requirement calculation results, the center of gravity trajectory analysis of crop water requirement between preset time points is performed to obtain the center of gravity trajectory analysis results. Based on the aforementioned calculation data, the water footprint of crop production is calculated, and the unit water footprint is calculated based on the water footprint of crop production. To minimize the total water footprint of crop planting, an objective function is established that relates unit water footprint to crop planting area. The objective function is used to obtain the crop layout optimization results based on water footprint; Output the rate of change of crop area, the center of gravity trajectory analysis results, and the crop layout optimization results for the preset years.

2. The method according to claim 1, characterized in that, An analysis of crop planting structure evolution was conducted to obtain the rate of change in crop area for preset years, including: The migration rate of each crop can be calculated using the following formula: wherein CM is the crop mobility; CPA before is the crop planting area before the change; CPA after is the crop planting area after the change; Based on the overall crop migration rate, the rate of change in crop area for the preset years is obtained.

3. The method according to claim 1, characterized in that, Calculate the crop water requirements for each crop throughout its entire growth period, including: The crop reference evapotranspiration is calculated using the following formula: Among them, ET O The reference evapotranspiration for crops is given; Δ is the slope of the saturated vapor pressure versus temperature curve; R n G represents net radiation from the crop surface; G represents soil heat flux. γ This is the constant of the hygrometer; T The average temperature; e a e is the saturated vapor pressure; s u1 is the actual water vapor pressure; u2 is the average daily wind speed at a height of 2m. The actual evapotranspiration of the crop is calculated based on the crop reference evapotranspiration and the crop coefficient: Among them, ET C K represents the actual evapotranspiration of the crop. C For the corresponding crop coefficient; The actual evapotranspiration of crops is taken as the crop's water requirement.

4. The method according to claim 3, characterized in that, Calculating the water requirements of each crop throughout its entire growth period also includes: The blue water requirement of crops can be calculated using the following formula: Among them, ET blue The average daily evapotranspiration of blue water; CWU blue The water requirement for blue water; The crop's green water requirement can be calculated using the following formula: Among them, ET green The average daily evapotranspiration of green water; CWU green Water demand for green water; The sum of the blue water requirement and the green water requirement of crops is taken as the crop water requirement.

5. The method according to claim 4, characterized in that, A centroid trajectory analysis was performed on the crop water requirement between preset time points to obtain the centroid trajectory analysis results, including: Based on the crop water requirement calculation results, the centroid coordinates of water storage at all preset time points are obtained; Based on the centroid coordinates of the water storage volume at all preset time points, the distance the centroid of the water storage volume moves between different preset time points is calculated. The centroid coordinates of the water storage volume at all preset time points and the distance the centroid of the water storage volume moves between different preset time points are integrated into the centroid trajectory analysis results.

6. The method according to claim 1, characterized in that, Calculating the water footprint of crop production includes: The green water footprint, blue water footprint, and gray water footprint are calculated using the following formulas: Among them, WF green For the green footprint, WF blue For Blue Water Footprint, WF grey For greywater footprints, ET blue For the average daily evapotranspiration of blue water, ET green For the average daily evapotranspiration of green water, l α The surface runoff fraction of nitrogen fertilizer, l β C represents the infiltration fraction of nitrogen fertilizer. max C represents the maximum acceptable concentration of nitrogen fertilizer in a specific water body. nat Y represents the natural concentration of nitrogen fertilizer in a specific water body, and Y represents crop yield. The sum of the green water footprint, blue water footprint, and gray water footprint is taken as the water footprint of crop production.

7. The method according to claim 6, characterized in that, The daily average evapotranspiration of green water and the daily average evapotranspiration of blue water are calculated using the following formulas: Among them, P eff ET represents the effective precipitation during the crop growing season, P represents the total precipitation over a ten-day period, and ET represents the total precipitation over a ten-day period. C This refers to the actual evapotranspiration of the crop.

8. The method according to claim 6, characterized in that, To minimize the total water footprint of crop cultivation, an objective function is established for the relationship between unit water footprint and crop planting area, including: The objective function is: in, To achieve the minimum total water footprint in the region, W ij X is the unit water footprint of crop j in region i. ij is the planting area of ​​crop j in region i, n is the total area of ​​the region, and m is the total number of crop types.

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