Method and device for calculating potential evapotranspiration parameters of target area

Abstract

The invention provides a method and a device for calculating potential evapotranspiration parameters of a target area, belongs to the technical field of data processing, and aims to solve the bottlenecks of low planar precision and spatial resolution and the like of an existing actual measurement method and a model method. Comprising the steps that a first potential evapotranspiration calculation model and a second potential evapotranspiration calculation model are used for calculating a first estimated value and a second estimated value of a target area respectively; calculating a difference value between the first estimation value and the second estimation value; establishing a multi-source potential evapotranspiration initial model according to a function relationship between the difference value and the temperature and the atmospheric precipitable water amount; performing model calculation on the multi-source potential evapotranspiration initial model to obtain a multi-source potential evapotranspiration calculation model; obtaining a planar potential evapotranspiration estimation model according to the multi-source potential evapotranspiration calculation model and the first potential evapotranspiration calculation model; and estimating potential evapotranspiration parameters of the target region by using the planar potential evapotranspiration estimation model. According to the method, the evapotranspiration condition of the moisture in the target area can be evaluated more accurately.

Description

Background Art

[0002] In the broad context of hydrology and climatology, potential evapotranspiration (PET) is a key parameter for measuring total surface evaporation and plant transpiration potential when the soil is fully watered under specific meteorological conditions. It is indispensable for understanding the hydrological cycle and energy balance. It works with precipitation to depict the humidity conditions in related areas. Especially under the trend of global warming, the growth of PET has become a significant driving factor in accelerating global drought. The importance of PET is also reflected in its role as a core component in the calculation of the standardized precipitation potential evapotranspiration index. Studies have shown that drought indicators that incorporate PET can more accurately reflect the severity of drought.

[0003] In recent years, the Global Navigation Satellite System (GNSS) has emerged as a cutting-edge technology for monitoring tropospheric water vapor content with its high precision, superior temporal and spatial resolution, cost-effectiveness, and almost no restrictions on meteorological conditions. Although existing remote sensing technology can provide a wide range of PET estimates, its accuracy is still limited. As a key factor affecting extreme weather events and regional ecological balance, accurate measurement of water vapor is particularly important. With the rapid development of GNSS technology, new paths have been opened up for the accurate measurement of water vapor content. As a core variable for drought monitoring, climate prediction, and agricultural irrigation management, the demand for accurate acquisition of PET is becoming increasingly urgent. The current challenges include: traditional PET models rely on many meteorological parameters that are difficult to obtain comprehensively, and are limited to high-precision measurements at meteorological stations, which is difficult to meet the needs of regional drought index calculations. Summary of the invention

[0004] In order to overcome the problems existing in the related art, the present invention provides a method and device for calculating the potential evapotranspiration parameters of a target area.

[0005] According to a first aspect of an embodiment of the present invention, a method for calculating potential evapotranspiration parameters of a target area is provided, and the method for calculating potential evapotranspiration parameters includes: Calculate a first estimated value and a second estimated value of the target area using a first potential evapotranspiration calculation model and a second potential evapotranspiration calculation model respectively; calculating a difference between the first estimate and the second estimate; According to the functional relationship between the difference and the temperature and atmospheric precipitable water, an initial model of multi-source potential evapotranspiration is established; Solving the multi-source potential evapotranspiration initial model to obtain a multi-source potential evapotranspiration calculation model; Obtaining a planar potential evapotranspiration estimation model according to the multi-source potential evapotranspiration calculation model and the first potential evapotranspiration calculation model; The potential evapotranspiration parameters of the target area are estimated using the areal potential evapotranspiration estimation model.

[0006] In some example embodiments of the present invention, based on the above solution, calculating the first estimated value of the target area using the first potential evapotranspiration calculation model includes: Calculating a heat index for the target area based on the monthly average temperature of the target area; Calculating a thermal index coefficient according to the thermal index; Calculating a correction factor for the target region based on the latitude of the target region and the solar declination; Obtaining a first potential evapotranspiration calculation model according to the thermal index, the thermal index coefficient and the correction coefficient; A first estimated value is obtained based on the temperature data of the target area in that month and the first potential evapotranspiration calculation model.

[0007] In some example embodiments of the present invention, based on the above scheme, obtaining a first potential evapotranspiration calculation model according to the thermal index, the thermal index coefficient and the correction coefficient includes: In the formula, is the PET calculated using the first potential evapotranspiration calculation model, T is the temperature data for the month, I is the heat index, m is the thermal index coefficient, is the correction factor.

[0008] In some example embodiments of the present invention, based on the above solution, calculating the second estimated value of the target area using the second potential evapotranspiration calculation model includes: Taking the hypothetical crop canopy of the target area as a standard and considering the influence of multiple influencing factors on the potential evapotranspiration process, a second potential evapotranspiration calculation model is established; wherein the multiple influencing factors include radiation, temperature, water vapor pressure and wind speed; A second estimated value is obtained according to the air pressure of the target area, the temperature data of the current month, the temperature data of the previous month and the second potential evapotranspiration calculation model.

[0009] In some exemplary embodiments of the present invention, based on the above scheme, taking the assumed crop canopy of the target area as a standard, considering the influence of multiple influencing factors on the potential evapotranspiration process, establishing a second potential evapotranspiration calculation model includes: In the formula, is the net radiation on the crop surface; is the soil heat flux; is the humidity constant; and Respectively represent the average temperature and wind speed within the preset range of the target area; is the saturated water vapor pressure; is the actual water vapor pressure; is the slope of the vapor pressure curve; the constants 900 and 0.34 are the standard crop coefficient and the standard crop wind coefficient, respectively.

[0010] In some exemplary embodiments of the present invention, based on the above scheme, establishing the multi-source potential evapotranspiration initial model according to the functional relationship between the difference and the temperature and the atmospheric precipitable water content includes: According to the functional relationship between the difference and the temperature and the atmospheric precipitable water, a piecewise function model is established at multiple meteorological stations in the target area; Fit the piecewise function model coefficients to the grid points to obtain the corresponding coefficients of the grid points; Based on the coefficients corresponding to the grid points, combined with the temperature data and the atmospheric precipitable water data, the difference data at each grid point is calculated; Calculating the potential evapotranspiration at each grid point according to the difference data at each grid point and the first estimated value; Based on the potential evapotranspiration at all grid points, determine the potential evapotranspiration expression; The multi-source potential evapotranspiration initial model is established based on the potential evapotranspiration expression.

[0011] In some exemplary embodiments of the present invention, based on the above-mentioned solution, the multi-source potential evapotranspiration initial model is solved to obtain the multi-source potential evapotranspiration calculation model, which includes: Calculate the first residual between the predicted value and the actual observed value at the meteorological station, and the second residual between the predicted value and the actual observed value at the grid point; Based on the first residual and the second residual, respectively calculating the variance, weight, and number of stations or the number of grid points of the meteorological stations and grid points; Calculating the fused variance of the potential evapotranspiration difference between the meteorological station and the grid point according to the variance, weight and number of stations or the number of grid points of the meteorological station and the grid point; Based on the fused variance, the optimal weights of the meteorological stations and the optimal weights of the grid points are determined using the Bartlett test to obtain the final coefficients of the multi-source potential evapotranspiration calculation model; According to the final coefficients, the multi-source potential evapotranspiration calculation model is obtained.

[0012] According to a second aspect of an embodiment of the present invention, there is provided a device for calculating potential evapotranspiration parameters of a target area, comprising: a calculation module, the calculation module being used to calculate a first estimated value and a second estimated value of a target area using a first potential evapotranspiration calculation model and a second potential evapotranspiration calculation model, respectively; calculate a difference between the first estimated value and the second estimated value; and calculate potential evapotranspiration parameters of the target area using a multi-source potential evapotranspiration calculation model; A model building module is used to establish an initial model of multi-source potential evapotranspiration according to the functional relationship between the difference and the temperature and the atmospheric precipitable water; and to solve the initial model of multi-source potential evapotranspiration to obtain a multi-source potential evapotranspiration calculation model.

[0013] According to a third aspect of an embodiment of the present invention, there is provided an electronic device, comprising: a processor; and a memory, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the method for calculating potential evapotranspiration parameters of a target area as described in the first aspect is implemented.

[0014] According to a fourth aspect of an embodiment of the present invention, there is provided a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the method for calculating potential evapotranspiration parameters of a target area in the first aspect is implemented.

[0015] The technical solution provided by the embodiments of the present invention may have the following beneficial effects: In the embodiment of the present invention, by using two different potential evapotranspiration calculation models (a first potential evapotranspiration calculation model and a second potential evapotranspiration calculation model), the potential evapotranspiration of the target area can be estimated respectively, which helps to reduce the error that may be caused by a single model, thereby improving the accuracy of the estimated value; by calculating the difference between the estimated values ​​of the two models, and combining the functional relationship between temperature and atmospheric precipitable water, a multi-source potential evapotranspiration initial model is established, and the differences between different models and environmental factors are fully considered, so that the multi-source potential evapotranspiration initial model can better adapt to the potential evapotranspiration changes under different environmental conditions, and improve the applicability and accuracy of the model; through the solution process, the model can more accurately reflect the dynamic changes of the potential evapotranspiration parameters, and improve the accuracy and practicality of the model; finally, the potential evapotranspiration parameters of the target area are calculated by integrating the optimized multi-source potential evapotranspiration calculation model and the first potential evapotranspiration calculation model, which means that the calculation data of the present invention is richer, so that the evaporation and evaporation of water in a specific geographical area can be more accurately evaluated, which is of great significance to water resources management, agricultural planning, climate research, ecological assessment and other fields.

[0016] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0018] Figure 1 A schematic diagram showing a system architecture of an exemplary application environment of a method and device for calculating potential evapotranspiration parameters of a target area to which an embodiment of the present invention can be applied; Figure 2 A schematic diagram schematically shows a flow chart of a method for calculating potential evapotranspiration parameters of a target area according to some embodiments of the present invention; Figure 3 A schematic diagram schematically illustrates a device for calculating potential evapotranspiration parameters of a target area according to some embodiments of the present invention; Figure 4 A schematic diagram schematically shows a structure of a computer system of an electronic device according to some embodiments of the present invention; Figure 5 A schematic diagram of a computer-readable storage medium according to some embodiments of the present invention is schematically shown. DETAILED DESCRIPTION

[0019] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Instead, they are merely examples of devices and methods consistent with some aspects of the present invention as detailed in the appended claims.

[0020] The terms used in the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The singular forms "a", "the" and "the" used in the present invention and the appended claims are also intended to include plural forms unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0021] It should be understood that although the terms first, second, third, etc. may be used in the present invention to describe various information, these information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of the present invention, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0022] Figure 1 A schematic diagram of a system architecture of an exemplary application environment of a method and apparatus for calculating potential evapotranspiration parameters of a target area to which an embodiment of the present invention can be applied is shown.

[0023] like Figure 1 As shown, the system architecture 100 may include one or more terminal devices such as a desktop computer 101, a portable computer 102, a smart phone 103, a network 104, and a server 105. The network 104 is used to provide a medium for a communication link between the terminal device and the server 105. The network 104 may include various connection types, such as wired or wireless communication links or optical fiber cables, etc. The terminal device may be any electronic device with data processing capabilities, which has a display screen for displaying the calculation results of the potential evapotranspiration parameters of the target area to the user, including but not limited to the above-mentioned desktop computers, portable computers, smart phones, etc. It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is only for illustration. According to the implementation requirements, there may be any number of terminal devices, networks and servers. For example, the server 105 may be a sub-server cluster composed of multiple sub-servers.

[0024] The method for calculating the potential evapotranspiration parameters of the target area provided in the embodiment of the present invention can generally be executed by the terminal device, and accordingly, the calculation device for the potential evapotranspiration parameters of the target area is generally set in the terminal device. However, it is easy for those skilled in the art to understand that the method for calculating the potential evapotranspiration parameters of the target area provided in the embodiment of the present invention can also be executed by the server 105, and accordingly, the calculation device for the potential evapotranspiration parameters of the target area can also be set in the server 105, which is not particularly limited in this exemplary embodiment.

[0025] In addition, it should be understood that the calculation method of the potential evapotranspiration parameters of the target area of ​​the embodiment of the present invention can be configured as a software module. In some implementation scenarios, the calculation scheme of the potential evapotranspiration parameters of the target area of ​​the present invention can be deployed separately to achieve accurate calculation of the potential evapotranspiration parameters of the target area. In other implementation scenarios, the calculation scheme of the potential evapotranspiration parameters of the target area of ​​the present invention can be deployed in other software as a functional module of the software, such as deployed in the calculation and analysis software of the potential evapotranspiration parameters of the target area. The present invention does not place any particular restrictions on the application of the calculation method of the potential evapotranspiration parameters of the target area.

[0026] Next, the embodiments of the present invention are described in detail.

[0027] like Figure 1 As shown, Figure 1 The present invention is a flow chart showing a method for calculating potential evapotranspiration parameters of a target area according to an exemplary embodiment of the present invention, comprising the following steps: According to a first aspect of an embodiment of the present invention, a method for calculating potential evapotranspiration parameters of a target area is provided, and the method for calculating potential evapotranspiration parameters includes: S201: Calculating a first estimated value and a second estimated value of a target area using a first potential evapotranspiration calculation model and a second potential evapotranspiration calculation model respectively; S202: Calculate the difference between the first estimated value and the second estimated value; S203: establishing an initial model of multi-source potential evapotranspiration according to the functional relationship between the difference and the temperature and atmospheric precipitable water; S204: performing model solving on the multi-source potential evapotranspiration initial model to obtain a multi-source potential evapotranspiration calculation model; S205: Obtaining a planar potential evapotranspiration estimation model according to the multi-source potential evapotranspiration calculation model and the first potential evapotranspiration calculation model; S206: Estimate potential evapotranspiration parameters of the target area using the surface potential evapotranspiration estimation model.

[0028] The technical solution provided by the embodiments of the present invention may have the following beneficial effects: In the embodiment of the present invention, by using two different potential evapotranspiration calculation models (a first potential evapotranspiration calculation model and a second potential evapotranspiration calculation model), the potential evapotranspiration of the target area can be estimated respectively, which helps to reduce the error that may be caused by a single model, thereby improving the accuracy of the estimated value; by calculating the difference between the estimated values ​​of the two models, and combining the functional relationship between temperature and atmospheric precipitable water, a multi-source potential evapotranspiration initial model is established, and the differences between different models and environmental factors are fully considered, so that the multi-source potential evapotranspiration initial model can better adapt to the potential evapotranspiration changes under different environmental conditions, and improve the applicability and accuracy of the model; through the solution process, the model can more accurately reflect the dynamic changes of the potential evapotranspiration parameters, and improve the accuracy and practicality of the model; finally, the potential evapotranspiration parameters of the target area are calculated by integrating the optimized multi-source potential evapotranspiration calculation model and the first potential evapotranspiration calculation model, which means that the calculation data of the present invention is richer, so that the evaporation and evaporation of water in a specific geographical area can be more accurately evaluated, which is of great significance to water resources management, agricultural planning, climate research, ecological assessment and other fields.

[0029] In S201 , a first estimated value and a second estimated value of a target area are calculated using a first potential evapotranspiration calculation model and a second potential evapotranspiration calculation model, respectively.

[0030] The present invention does not specifically limit the first potential evapotranspiration calculation model and the second potential evapotranspiration calculation model. In some embodiments, the first potential evapotranspiration calculation model may be one of the Penman-Monteith Model, the Horton Model, the FAO-56 Two-Source Model, and the Blaney-Criddle Model. The second potential evapotranspiration calculation model may be the same as the first potential evapotranspiration calculation model, or may be different from the first potential evapotranspiration calculation model. Of course, in different cases, the second potential evapotranspiration calculation model may also be one of the above models. The specific choice of model depends on the availability of data, computing resources, required accuracy, and specific requirements of the application scenario. In practice, it may also be necessary to calibrate and verify the model based on actual monitoring data to ensure the accuracy of the prediction.

[0031] On this basis, the present invention fully considers the monthly average temperature and location of the target area to form a heat index, a heat index coefficient and a correction coefficient, thereby determining a first potential evapotranspiration calculation model, and then obtaining a first estimated value based on the first potential evapotranspiration calculation model, specifically, including: Calculating a heat index for the target area based on the monthly average temperature of the target area; Calculating a thermal index coefficient according to the thermal index; Calculating a correction factor for the target region based on the latitude of the target region and the solar declination; Obtaining a first potential evapotranspiration calculation model according to the thermal index, the thermal index coefficient and the correction coefficient; A first estimated value is obtained based on the temperature data of the target area in that month and the first potential evapotranspiration calculation model.

[0032] Obviously, the first potential evapotranspiration calculation model provided by the present invention considers in detail the comprehensive impact of temperature, geographical latitude and seasonality on potential evapotranspiration, thereby being able to more accurately quantify and estimate the potential evapotranspiration of the target area.

[0033] On this basis, those skilled in the art can calculate the thermal index of the target area in any manner based on the average temperature of the target area, and the present invention does not make specific limitations. In some embodiments, the average temperature can be made proportional to the thermal index or a thermal pressure index can be designed to determine the calculation method of the thermal index.

[0034] In some exemplary embodiments of the present invention, the heat index of the target area may be calculated in the following manner: In the formula, For the i Monthly mean temperature for the month, in °C; The heat index for the 12 months.

[0035] On this basis, the thermal index coefficient is calculated as follows: In the formula, is the thermal index coefficient.

[0036] In addition, in some embodiments, the latitude and solar declination of the target area can be directly obtained through data, or calculated in some way. On this basis, the correction coefficient of the target area can be calculated directly based on the latitude and solar declination of the target area, or the maximum sunshine hours can be calculated based on the latitude and solar declination of the target area, and then the correction coefficient is calculated by the maximum sunshine hours and the number of days in a month. As an example embodiment of the present invention, optionally, the correction coefficient of latitude and month is calculated in the following way: In the formula, represents the correction factor, represents the maximum sunshine hours in the target area and , represents pi, represents the angle of the sun rising every hour and , represents the arccosine function, represents the tangent function, Indicates the latitude of the target area, represents the solar declination of the target area and , represents the sine function, represents the mean Julian day of the month, Indicates the number of days in a month.

[0037] Based on this, according to the thermal index, the thermal index coefficient and the correction coefficient, the first potential evapotranspiration calculation model can be expressed as: In the formula, is the potential evapotranspiration calculated using the first potential evapotranspiration calculation model (i.e., the first estimate, PET), T is the monthly temperature data within the preset range of the target area, I is the heat index, m is the thermal index coefficient, is the correction coefficient. Since the aerodynamic term is ignored when calculating PET using the first potential evapotranspiration calculation model, and only the influence of the thermal factor on PET is considered, but PET is determined by a variety of meteorological factors, the first potential evapotranspiration calculation model cannot obtain high-precision PET in the region.

[0038] Therefore, in the exemplary embodiment provided by the present invention, the second potential evapotranspiration calculation model can be established in the following manner: That is, taking the hypothetical crop canopy of the target area as the standard and considering the influence of various influencing factors on the potential evapotranspiration process, a second potential evapotranspiration calculation model is established; wherein the various influencing factors include radiation, temperature, water vapor pressure and wind speed.

[0039] On this basis, a second estimated value is obtained according to the air pressure of the target area, the temperature data of the current month, the temperature data of the previous month and the second potential evapotranspiration calculation model.

[0040] The second potential evapotranspiration calculation model takes the assumed crop canopy as the standard and fully considers the influence of multiple factors such as radiation, temperature, water vapor pressure and wind speed on the potential evapotranspiration process. The calculation process is relatively complex. Therefore, the specific calculation formula of the second potential evapotranspiration calculation model is as follows: In the formula, is the potential evapotranspiration (i.e., the second estimated value, PET) calculated using the second potential evapotranspiration calculation model. is the net radiation on the crop surface; is the soil heat flux; is the humidity constant; and Respectively represent the monthly average temperature and wind speed within the preset range of the target area; is the saturated water vapor pressure; is the actual water vapor pressure; is the slope of the vapor pressure curve; the constants 900 and 0.34 are the standard crop coefficient and the standard crop wind coefficient, respectively.

[0041] The saturated water vapor pressure The specific calculation method is: The actual water vapor pressure is calculated as follows: and Represent the maximum temperature and the minimum temperature respectively; is the dew point temperature.

[0042] Humidity constant Through air pressure Calculation, the calculation formula is as follows: Soil heat flux It can be calculated by the average temperature of the target month and the previous month. The specific calculation formula is as follows: and Respectively refer to i month and the previous month ( i -1) of the monthly average temperature.

[0043] In S202, a difference between the first estimated value and the second estimated value is calculated; That is, the difference for: In S203, the atmospheric precipitable water PWV can be obtained based on experience, calculated based on some data, or obtained by inverting data obtained using GNSS or GPS (Global Positioning System, GPS).

[0044] Temperature data can also be obtained based on experience, or collected from data, or obtained through measurement. Of course, in order to ensure the accuracy of the data, the atmospheric precipitable water content PWV of the present invention is obtained through GNSS, and the temperature data is obtained through collection and measurement at a meteorological station.

[0045] On this basis, according to the functional relationship between the difference and the temperature and atmospheric precipitable water, the initial model of multi-source potential evapotranspiration is further established, including: According to the functional relationship between the difference and the temperature and the atmospheric precipitable water, a piecewise function model is established at multiple meteorological stations in the target area; Fit the piecewise function model coefficients to the grid points to obtain the corresponding coefficients of the grid points; Based on the coefficients corresponding to the grid points, combined with the temperature data and the atmospheric precipitable water data, the difference data at each grid point is calculated; Calculating the potential evapotranspiration at each grid point according to the difference data at each grid point and the first estimated value; Based on the potential evapotranspiration at all grid points, determine the potential evapotranspiration expression; The multi-source potential evapotranspiration initial model is established based on the potential evapotranspiration expression.

[0046] By establishing a piecewise function model based on the functional relationship between the difference and temperature and atmospheric precipitable water at multiple meteorological stations in the target area, it is possible to more accurately reflect the changing pattern of potential evapotranspiration under different geographical locations and environmental conditions, thereby improving the model's adaptability to complex geographical and climatic characteristics and its estimation accuracy.

[0047] Those skilled in the art can establish piecewise function models at multiple meteorological stations in any manner, as long as the established piecewise function model satisfies the functional relationship between the difference and the temperature and the atmospheric precipitable water content. In the embodiment provided by the present invention, the piecewise function model can be established as: In the formula, – and – They are and , the coefficients of the piecewise linear model; is the atmospheric precipitable water, Monthly temperature data within a preset range for the target area.

[0048] In addition, the present invention uses a polynomial method to fit the piecewise function model coefficients to the grid points to obtain the corresponding coefficients of the grid points. , the expression is as follows: In the formula, n is the number of meteorological stations, is the model coefficient of the first meteorological station, It is n Model coefficients for each meteorological station; – are the model coefficients of the meteorological stations - The polynomial fitting coefficients of ; , and are the longitude, latitude and altitude of the meteorological station, respectively.

[0049] , as well as - The expression of The expression of is similar to that of , and the present invention will not be described in detail here. – and – By calculating and solving , we can get the coefficients at the corresponding grid points.

[0050] By substituting the coefficients at the grid points into the piecewise function model, we can obtain the difference data at each grid point (i.e. DPET value).

[0051] Then, the potential evapotranspiration at each grid point is determined based on the difference data at each grid point and the first estimated value: In the formula, is calculated on the grid points PET .

[0052] Based on this, we can PET The expression of is determined as: Furthermore, the initial model of multi-source potential evapotranspiration is: In the formula, is the fusion coefficient matrix of the initial model of multi-source potential evapotranspiration and , yes PET The fitted coefficients of the expression, is the number of meteorological stations or grid points.

[0053] In S204, since different data sources have different precisions and information contents, it is crucial to determine the optimal weight ratio of multi-source data for model solution. When integrating multiple data sources into one model, it is necessary to consider the contribution and influence of each data source to determine the optimal data weight ratio and optimize the model performance. Therefore, the present invention solves the multi-source potential evapotranspiration initial model and obtains the multi-source potential evapotranspiration calculation model according to the solution result.

[0054] The present invention does not specifically limit the method for solving the multi-source potential evapotranspiration initial model. In some embodiments, the multi-source potential evapotranspiration initial model can be solved by using data fusion technology, uncertainty analysis method, or machine learning and artificial intelligence algorithm.

[0055] However, considering the complexity of the use environment of multi-source potential evapotranspiration and the requirements of the present invention for model accuracy and prediction accuracy. In some exemplary embodiments of the present invention, based on the above scheme, the multi-source potential evapotranspiration initial model is solved to obtain a multi-source potential evapotranspiration calculation model including: Calculate the first residual between the predicted value and the actual observed value at the meteorological station, and the second residual between the predicted value and the actual observed value at the grid point; Based on the first residual and the second residual, respectively calculating the variance, weight, and number of stations or the number of grid points of the meteorological stations and grid points; Calculating the fused variance of the potential evapotranspiration difference between the meteorological station and the grid point according to the variance, weight and number of stations or the number of grid points of the meteorological station and the grid point; Based on the fused variance, the optimal weights of the meteorological stations and the optimal weights of the grid points are determined using the Bartlett test to obtain the final coefficients of the multi-source potential evapotranspiration calculation model; According to the final coefficients, the multi-source potential evapotranspiration calculation model is obtained.

[0056] The model is quantified by the deviation between the predicted value and the actual observed value, and the contribution of different data sources in the model is tailored by analyzing the weights assigned to each prediction error to improve the accuracy of the model. After that, the fusion variance is calculated to reduce the single point error and improve the overall adaptability of the model and the robustness of the prediction. Then, the Bartlett test is used to determine the optimal weight to ensure the scientific nature of the model and the reliability of the optimization results.

[0057] Here, the first residual between the predicted value and the actual observed value at the meteorological station and the second residual between the predicted value and the actual observed value at the grid point can be calculated as follows: In the formula, and They refer to the first residual of the meteorological station and the second residual of the grid point, respectively. and Refers to the parameter input matrices of the meteorological station and grid points, including the longitude, latitude, altitude, PWV and T of the meteorological station and grid points, respectively. and They refer to the weather stations PET and the grid points PET .

[0058] Based on the first residual and the second residual, the variance, weight, and number of meteorological stations and grid points, respectively, may be calculated in the following manner: In the formula, / , / ,and / are the posterior unit weight variance, weight and number of grid points / stations, respectively. is the rank of the correlation matrix, is the inverse matrix of the N matrix, and the N matrix is and The sum of matrices, / They are the adjustment criterion matrices of grid points / meteorological stations respectively.

[0059] According to the variance, weight and number of stations or grid points of the meteorological station and the grid point, the fused variance of the difference between the potential evapotranspiration of the meteorological station and the grid point can be expressed as: In the formula, represents a grid point, When is the weather station, and are the number of grid points and stations, is the fused variance of the station and grid points.

[0060] Based on the fusion variance, the optimal weights of the meteorological stations and the optimal weights of the grid points are determined using the Bartlett test, and the final coefficients of the multi-source potential evapotranspiration calculation model are obtained, including: According to the chi-square test, the significance level is set to 0.1. When the degree of freedom is 2, is 0.02; if , it is considered that the unit weight variances of the two types of data are statistically equal, and the loop is broken.

[0061] In the formula, j is the number of iterations. According to the optimal weights of the grid points and station data determined by the present invention, the final coefficients of the MPF model can be obtained: In the formula, for The transposed matrix of for and The fusion matrix is ; is the weight after fusion and , and are the weights determined for grid points and station data, respectively; for and The combination matrix of .

[0062] Substitute this coefficient into the initial model of multi-source potential evapotranspiration In the above, the multi-source potential evapotranspiration calculation model can be obtained.

[0063] In S205, in order to enrich the data sources of the areal potential evapotranspiration estimation model so as to make the estimation data of the areal potential evapotranspiration estimation model more accurate, after the multi-source potential evapotranspiration calculation model MPF is established, it is combined with the first potential evapotranspiration calculation model to obtain the areal potential evapotranspiration estimation model.

[0064] Here, those skilled in the art may combine the multi-source potential evapotranspiration calculation model and the first potential evapotranspiration calculation model in any manner, such as by addition, product, or by setting certain coefficients for both and then performing addition or product, and the present invention does not make any specific limitation.

[0065] In the specific implementation manner provided by the present invention, the expression of the surface potential evapotranspiration estimation model is: In the formula, represents a matrix consisting of longitude, latitude, altitude, T, and PWV. PET estimated at any location for the first potential evapotranspiration calculation model.

[0066] On this basis, the PET of the target area can be calculated by simply obtaining the longitude, latitude, elevation, PWV and T of the target area.

[0067] According to a second aspect of an embodiment of the present invention, a device 300 for calculating potential evapotranspiration parameters of a target area is also provided. Figure 3 As shown, the calculation device 300 for the potential evapotranspiration parameter of the target area includes: A calculation module 310, the calculation module 310 is used to calculate a first estimated value and a second estimated value of a target area using a first potential evapotranspiration calculation model and a second potential evapotranspiration calculation model respectively; calculate a difference between the first estimated value and the second estimated value; and calculate a potential evapotranspiration parameter of the target area using a multi-source potential evapotranspiration calculation model; The model building module 320 is used to establish an initial model of multi-source potential evapotranspiration according to the functional relationship between the difference and the temperature and the atmospheric precipitable water; and to solve the initial model of multi-source potential evapotranspiration to obtain a multi-source potential evapotranspiration calculation model.

[0068] In an exemplary embodiment of the present invention, based on the above solution, the calculation module 310 may further include an estimation submodule, a difference calculation submodule and a parameter calculation submodule. The estimation submodule is used to calculate a first estimation value and a second estimation value of the target area using a first potential evapotranspiration calculation model and a second potential evapotranspiration calculation model; The difference calculation submodule is used to calculate the difference between the first estimated value and the second estimated value; The parameter calculation submodule is used to calculate the potential evapotranspiration parameters of the target area using a multi-source potential evapotranspiration calculation model.

[0069] In an exemplary embodiment of the present invention, based on the above solution, the model building module 320 may further include an initial model building submodule and a model building submodule. The initial model establishment submodule is used to establish an initial model of multi-source potential evapotranspiration based on the functional relationship between the difference and the temperature and atmospheric precipitable water; The model building submodule is used to solve the multi-source potential evapotranspiration initial model to obtain a multi-source potential evapotranspiration calculation model.

[0070] In an exemplary embodiment of the present invention, based on the aforementioned scheme, the estimation submodule may further include a first estimation unit, the first estimation unit being used to calculate a thermal index of the target area based on the monthly average temperature of the target area; to calculate a thermal index coefficient based on the thermal index; to calculate a correction coefficient of the target area based on the latitude and solar declination of the target area; to obtain a first potential evapotranspiration calculation model based on the thermal index, the thermal index coefficient and the correction coefficient; and to obtain a first estimated value based on the temperature data of the target area in that month and the first potential evapotranspiration calculation model.

[0071] In an exemplary embodiment of the present invention, based on the aforementioned scheme, the estimation submodule may further include a second estimation unit, which is used to establish a second potential evaporation calculation model based on the assumed crop canopy of the target area and considering the influence of multiple influencing factors on the potential evaporation process; wherein the multiple influencing factors include radiation, temperature, water vapor pressure and wind speed; and a second estimated value is obtained based on the air pressure of the target area, the temperature data of the current month, the temperature data of the previous month and the second potential evaporation calculation model.

[0072] In an exemplary embodiment of the present invention, based on the above scheme, the initial model building submodule may further include a piecewise function model building unit, a fitting unit, a difference data calculation unit, a potential evapotranspiration calculation unit, an expression generation unit and a model building unit; The piecewise function model building unit is used to build piecewise function models at multiple meteorological stations in the target area according to the functional relationship between the difference and the temperature and the atmospheric precipitable water content; The fitting unit is used to fit the piecewise function model coefficients to the grid points to obtain the corresponding coefficients of the grid points; The difference data calculation unit is used to calculate the difference data at each grid point based on the coefficients corresponding to the grid points, combined with the temperature data and the atmospheric precipitable water data; The potential evapotranspiration calculation unit is used to calculate the potential evapotranspiration at each grid point according to the difference data at each grid point and the first estimated value; The expression generation unit is used to determine the potential evapotranspiration expression based on the potential evapotranspiration at all grid points; The model building unit is used to build the multi-source potential evapotranspiration initial model based on the potential evapotranspiration expression.

[0073] In an exemplary embodiment of the present invention, based on the aforementioned solution, the model building submodule may further include a residual calculation unit, a weight calculation unit, a fusion variance calculation unit, a weight calculation unit and a model generation unit; The residual calculation unit is used to calculate the first residual between the predicted value and the actual observed value of the meteorological station, and the second residual between the predicted value and the actual observed value of the grid point; The weight calculation unit is used to calculate the variance, weight and number of stations or number of grid points of the meteorological stations and grid points respectively based on the first residual and the second residual; The fused variance calculation unit is used to calculate the fused variance of the potential evapotranspiration difference between the meteorological station and the grid point according to the variance, weight and number of stations or number of grid points of the meteorological station and the grid point; The weight calculation unit is used to determine the optimal weight of the meteorological station and the optimal weight of the grid point based on the fusion variance by using the Bartlett test to obtain the final coefficient of the multi-source potential evapotranspiration calculation model; The model generation unit is used to obtain the multi-source potential evapotranspiration calculation model according to the final coefficients.

[0074] It should be noted that, although several modules and submodules of the calculation device for the potential evapotranspiration parameters of the target area are mentioned in the above detailed description, this division is not mandatory. In fact, according to an embodiment of the present invention, the features and functions of two or more modules or submodules described above can be embodied in one module or unit. Conversely, the features and functions of one module or submodule described above can be further divided into multiple modules or submodules to be embodied.

[0075] In addition, in an exemplary embodiment of the present invention, an electronic device capable of implementing the above-mentioned method for calculating potential evapotranspiration parameters of a target area is also provided.

[0076] Those skilled in the art will appreciate that various aspects of the present invention may be implemented as systems, methods or program products. Therefore, various aspects of the present invention may be specifically implemented in the following forms, namely: complete hardware embodiments, complete software embodiments (including firmware, microcode, etc.), or embodiments combining hardware and software aspects, which may be collectively referred to herein as "circuits", "modules" or "systems".

[0077] Refer to the following Figure 4 An electronic device 400 according to such an embodiment of the present invention is described. Figure 4 The electronic device 400 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0078] like Figure 4 As shown, the electronic device 400 is in the form of a general computing device. The components of the electronic device 400 may include but are not limited to: the at least one processing unit 410, the at least one storage unit 420, a bus 430 connecting different system components (including the storage unit 420 and the processing unit 410), and a display unit 440.

[0079] The storage unit stores program codes, which can be executed by the processing unit 410, so that the processing unit 410 performs the steps of various exemplary embodiments of the present invention described in the above “Exemplary Method” section. For example, the processing unit 410 can perform the following steps: Figure 2In S201 shown in the figure, a first estimated value and a second estimated value of a target area are calculated using a first potential evapotranspiration calculation model and a second potential evapotranspiration calculation model respectively; S202, the difference between the first estimated value and the second estimated value is calculated; S203, a multi-source potential evapotranspiration initial model is established according to the functional relationship between the difference and the temperature and the atmospheric precipitable water; S204, the multi-source potential evapotranspiration initial model is solved to obtain a multi-source potential evapotranspiration calculation model; S205, a planar potential evapotranspiration estimation model is obtained according to the multi-source potential evapotranspiration calculation model and the first potential evapotranspiration calculation model; S206, the potential evapotranspiration parameters of the target area are estimated using the planar potential evapotranspiration estimation model.

[0080] The storage unit 420 may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM) 421 and / or a cache memory unit 422 , and may further include a read-only memory unit (ROM) 423 .

[0081] The storage unit 420 may also include a program / utility 424 having a set (at least one) of program modules 425, such program modules 425 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0082] Bus 430 may represent one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0083] The electronic device 400 may also communicate with one or more external devices 470 (e.g., keyboards, pointing devices, Bluetooth devices, etc.), may also communicate with one or more devices that enable a user to interact with the electronic device 400, and / or communicate with any device that enables the electronic device 400 to communicate with one or more other computing devices (e.g., routers, modems, etc.). This communication may be performed through an input / output (I / O) interface 450. In addition, the electronic device 400 may also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) through a network adapter 460. As shown, the network adapter 460 communicates with other modules of the electronic device 400 through a bus 430. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 400, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, etc.

[0084] Through the description of the above embodiments, it is easy for those skilled in the art to understand that the exemplary embodiments described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the embodiment of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the embodiment of the present invention.

[0085] In an exemplary embodiment of the present invention, a computer-readable storage medium is also provided, on which a program product capable of implementing the above method of the present invention is stored. In some possible embodiments, various aspects of the present invention can also be implemented in the form of a program product, which includes a program code, and when the program product is run on a terminal device, the program code is used to enable the terminal device to perform the steps of various exemplary embodiments of the present invention described in the above "Exemplary Method" section of the present invention.

[0086] refer to Figure 5 As shown, a program product 500 for realizing the calculation method of the potential evapotranspiration parameters of the target area according to an embodiment of the present invention is described, which can adopt a portable compact disk read-only memory (CD-ROM) and include program code, and can be run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited thereto. In the present invention, the readable storage medium can be any tangible medium containing or storing a program, and the program can be used by or in combination with an instruction execution system, an apparatus or a device.

[0087] The program product may use any combination of one or more readable storage media. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0088] Program code for performing the operations of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0089] In addition, the above-mentioned figures are only schematic illustrations of the processes included in the method according to an exemplary embodiment of the present invention, and are not intended to be limiting. It is easy to understand that the processes shown in the above-mentioned figures do not indicate or limit the time sequence of these processes. In addition, it is also easy to understand that these processes can be performed synchronously or asynchronously, for example, in multiple modules.

[0090] Through the description of the above embodiments, it is easy for those skilled in the art to understand that the exemplary embodiments described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the embodiment of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the embodiment of the present invention.

[0091] Other embodiments of the invention will readily occur to those skilled in the art after considering the specification and practicing the invention disclosed herein. The invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of the invention are indicated by the claims.

[0092] It should be understood that the present invention is not limited to the exact construction that has been described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A method for calculating potential evapotranspiration parameters in a target area, characterized in that: The calculation method of the potential evapotranspiration parameter includes: Calculate a first estimated value and a second estimated value of the target area using a first potential evapotranspiration calculation model and a second potential evapotranspiration calculation model respectively; calculating a difference between the first estimate and the second estimate; According to the functional relationship between the difference and the temperature and atmospheric precipitable water, an initial model of multi-source potential evapotranspiration is established; Solving the multi-source potential evapotranspiration initial model to obtain a multi-source potential evapotranspiration calculation model; Obtaining a planar potential evapotranspiration estimation model according to the multi-source potential evapotranspiration calculation model and the first potential evapotranspiration calculation model; The potential evapotranspiration parameters of the target area are estimated using the areal potential evapotranspiration estimation model.

2. The method for calculating the potential evapotranspiration parameters of the target area according to claim 1, characterized in that: The first estimate of the target area calculated using the first potential evapotranspiration calculation model includes: Calculating a heat index for the target area based on the monthly average temperature of the target area; Calculating a thermal index coefficient according to the thermal index; Calculating a correction factor for the target region based on the latitude of the target region and the solar declination; Obtaining a first potential evapotranspiration calculation model according to the thermal index, the thermal index coefficient and the correction coefficient; A first estimated value is obtained based on the temperature data of the target area in that month and the first potential evapotranspiration calculation model.

3. The method for calculating the potential evapotranspiration parameters of the target area according to claim 2, characterized in that: According to the thermal index, the thermal index coefficient and the correction coefficient, obtaining a first potential evapotranspiration calculation model includes: In the formula, is the PET calculated using the first potential evapotranspiration calculation model, T is the temperature data for the month, I is the heat index, m is the thermal index coefficient, is the correction factor.

4. The method for calculating the potential evapotranspiration parameters of the target area according to claim 1, characterized in that: The second estimate for the target area calculated using the second potential evapotranspiration calculation model includes: Taking the hypothetical crop canopy of the target area as a standard and considering the influence of multiple influencing factors on the potential evapotranspiration process, a second potential evapotranspiration calculation model is established; wherein the multiple influencing factors include radiation, temperature, water vapor pressure and wind speed; A second estimated value is obtained according to the air pressure of the target area, the temperature data of the current month, the temperature data of the previous month and the second potential evapotranspiration calculation model.

5. The method for calculating the potential evapotranspiration parameters of the target area according to claim 4, characterized in that: Taking the hypothetical crop canopy in the target area as the standard and considering the influence of various influencing factors on the potential evapotranspiration process, the second potential evapotranspiration calculation model is established, including: In the formula, is the net radiation on the crop surface; is the soil heat flux; is the humidity constant; and They represent the average temperature and wind speed within the preset range of the target area respectively; is the saturated water vapor pressure; is the actual water vapor pressure; is the slope of the vapor pressure curve; the constants 900 and 0.34 are the standard crop coefficient and the standard crop wind coefficient, respectively.

6. The method for calculating the potential evapotranspiration parameters of the target area according to claim 1, characterized in that: According to the functional relationship between the difference and temperature and atmospheric precipitable water, the initial model of multi-source potential evapotranspiration is established, including: According to the functional relationship between the difference and the temperature and the atmospheric precipitable water, a piecewise function model is established at multiple meteorological stations in the target area; Fit the piecewise function model coefficients to the grid points to obtain the corresponding coefficients of the grid points; Based on the coefficients corresponding to the grid points, combined with the temperature data and the atmospheric precipitable water data, the difference data at each grid point is calculated; Calculating the potential evapotranspiration at each grid point according to the difference data at each grid point and the first estimated value; Based on the potential evapotranspiration at all grid points, determine the potential evapotranspiration expression; The multi-source potential evapotranspiration initial model is established based on the potential evapotranspiration expression.

7. The method for calculating the potential evapotranspiration parameters of the target area according to claim 1, characterized in that: The multi-source potential evapotranspiration initial model is solved to obtain a multi-source potential evapotranspiration calculation model including: Calculate the first residual between the predicted value and the actual observed value at the meteorological station, and the second residual between the predicted value and the actual observed value at the grid point; Based on the first residual and the second residual, respectively calculating the variance, weight, and number of stations or the number of grid points of the meteorological stations and grid points; Calculating the fused variance of the potential evapotranspiration difference between the meteorological station and the grid point according to the variance, weight and number of stations or the number of grid points of the meteorological station and the grid point; Based on the fused variance, the optimal weights of the meteorological stations and the optimal weights of the grid points are determined using the Bartlett test to obtain the final coefficients of the multi-source potential evapotranspiration calculation model; According to the final coefficients, the multi-source potential evapotranspiration calculation model is obtained.

8. A device for calculating potential evapotranspiration parameters of a target area, characterized in that: include: A calculation module, the calculation module being used to calculate a first estimated value and a second estimated value of a target area using a first potential evapotranspiration calculation model and a second potential evapotranspiration calculation model respectively; Calculating the difference between the first estimated value and the second estimated value; and calculating the potential evapotranspiration parameters of the target area using a multi-source potential evapotranspiration calculation model; A model building module is used to establish an initial model of multi-source potential evapotranspiration according to the functional relationship between the difference and the temperature and the atmospheric precipitable water; and to solve the initial model of multi-source potential evapotranspiration to obtain a multi-source potential evapotranspiration calculation model.

9. An electronic device, characterized in that: include: processor; as well as A memory having computer-readable instructions stored thereon, wherein the computer-readable instructions, when executed by the processor, implement the method for calculating the potential evapotranspiration parameter of the target area according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for calculating the potential evapotranspiration parameter of the target area according to any one of claims 1 to 7 is implemented.

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