An Ecosystem Cycle Regulation Method and System Based on the VIC Hydrological Model

Abstract

This application proposes an ecosystem cycle regulation method and system based on the VIC hydrological model, relating to the field of photovoltaic agricultural water resource regulation technology. First, a first VIC hydrological model is established, consisting of a water balance equation and an energy balance equation. Then, the relationship between energy and water cycle in the first VIC hydrological model is modified according to the photovoltaic panel installation, so that the obtained parameters are more consistent with actual conditions. Next, with the optimization objectives of maximizing net radiation and minimizing photovoltaic panel height, the optimal photovoltaic panel installation information for power generation efficiency is determined from multiple sets of photovoltaic panel installation parameters. Furthermore, the first plant planting information and the first dynamic water resource regulation information are determined. Through the technical solution of this application, the VIC hydrological model is modified according to the photovoltaic panel installation, thereby determining photovoltaic panel installation information, plant planting information, and dynamic water resource regulation information that better meet actual needs.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of agricultural photovoltaic ecological system optimization, and particularly relates to an ecological system circulation regulation method and system based on a VIC hydrological model. BACKGROUND

[0002] The traditional agricultural photovoltaic project has the following problems: the energy-water cycle coupling mechanism is not clear; the influence of photovoltaic panel shading and cleaning water consumption on the local ecology lacks quantitative analysis; multi-objective conflict: power generation efficiency, water resource utilization and crop yield are difficult to optimize; strong experience dependence: the design parameters (such as photovoltaic panel inclination, cleaning frequency) lack scientific basis. SUMMARY

[0003] The purpose of the present application is to provide an ecological system circulation regulation method and system based on a VIC hydrological model, to solve the technical problem of inaccurate quantitative analysis in the prior art of agricultural photovoltaic ecological system.

[0004] The present application provides an ecological system circulation regulation method based on a VIC hydrological model, which comprises the following steps:

[0005] S1: establishing a first VIC hydrological model, and outputting a first evapotranspiration, a first net radiation value and a first surface runoff through the first VIC hydrological model;

[0006] S2: performing first photovoltaic energy redistribution processing on the first net radiation value to obtain a second net radiation value and a first radiation shading rate;

[0007] S3: performing first water cycle disturbance processing on the first surface runoff and the first evapotranspiration to obtain a target soil moisture content and a target evapotranspiration;

[0008] S4: determining first photovoltaic panel setting information with the optimization objectives of maximum net radiation value and minimum photovoltaic panel height;

[0009] S5: determining first plant planting information according to the first photovoltaic panel setting information, first soil nutrient information and first meteorological data;

[0010] S6: determining first water resource dynamic regulation information according to the target soil moisture content, the target evapotranspiration, the first plant planting information and the first meteorological data.

[0011] Preferably, the S1 comprises the following sub-steps:

[0012] S11: establishing a first water balance equation according to soil moisture content, precipitation, evapotranspiration, surface runoff and groundwater runoff;

[0013] S12: establishing a first energy balance equation according to net radiation, sensible heat flux, latent heat flux and soil heat flux;

[0014] S13: establishing the first VIC hydrological model according to the first water balance equation and the first energy balance equation, and obtaining a first evapotranspiration, a first net radiation value and a first surface runoff.

[0015] Preferably, the first water balance equation is:

[0016] ;

[0017] wherein W is soil water content; P is precipitation; ET is evapotranspiration; R surf is surface runoff; R sub is underground runoff.

[0018] Preferably, the first energy balance equation has the following specific form:

[0019] ;

[0020] wherein R n is the first net radiation, H is sensible heat flux, LE is latent heat flux, and G is soil heat flux.

[0021] Preferably, the S2 comprises:

[0022] S21: obtaining the first radiation shielding rate according to the initial setting information of the photovoltaic panel;

[0023] The specific calculation formula is as follows:

[0024] ;

[0025] wherein θ is the inclination of the photovoltaic panel, H1 is the height of the photovoltaic panel, and D is the spacing of the photovoltaic panel;

[0026] S22: determining the second net radiation value according to the first radiation shielding rate and the first net radiation value;

[0027] The specific calculation formula of the second net radiation value is as follows:

[0028] ;

[0029] wherein the R n is the first net radiation value, the βpv is the reflectivity of the photovoltaic panel, and the R in is incident solar radiation, which represents the total solar radiation energy perpendicularly irradiated to the surface of the ground or the photovoltaic panel within a unit time.

[0030] Preferably, the S3 comprises:

[0031] S31: determining a first permeation loss value according to the first cleaning data of the photovoltaic panel;

[0032] The calculation formula of the first permeation loss value is as follows:

[0033] Q loss =k infil t wash ;

[0034] Wherein, the k infil is the soil permeability coefficient; t wash is the cleaning duration;

[0035] S32: determining a second surface runoff according to the first permeation loss value and the first surface runoff;

[0036] The calculation formula of the second surface runoff is as follows:

[0037] ;

[0038] S33: calculating a target soil water content and a target evapotranspiration according to the second surface runoff and the first VIC hydrological model.

[0039] Preferably, the S4 comprises:

[0040] S41: determining a plurality of second photovoltaic panel setting information;

[0041] S42: iteratively performing the S2 for each set of the second photovoltaic panel setting information, thereby obtaining a plurality of third net radiation values, and determining each set of the second photovoltaic panel setting information and the corresponding third net radiation value as first mapping information;

[0042] S43: selecting target mapping information from the plurality of first mapping information with the maximum net radiation value and the minimum photovoltaic panel height as the target, and determining the first photovoltaic panel setting information according to the target mapping information.

[0043] Preferably, the S5 comprises:

[0044] S51: determining a target radiation shielding rate according to the first photovoltaic panel setting information;

[0045] S52: inputting the target radiation shielding rate, first soil nutrient information and first meteorological data into a plant planting information prediction model to determine first plant planting information.

[0046] Preferably, the S6 comprises:

[0047] S61: determining a first photovoltaic panel flushing strategy according to the first dust accumulation degree and the first meteorological data;

[0048] S62: determining a first irrigation strategy according to the first photovoltaic panel flushing strategy, the target soil water content, the first plant planting information and the target evapotranspiration;

[0049] S63: determining a first water resource dynamic regulation information according to the first photovoltaic panel flushing strategy, the first plant planting information and the first irrigation strategy.

[0050] The application further provides an ecosystem circulation regulation system based on the VIC hydrological model.

[0051] The application provides an ecosystem circulation regulation method and system based on a VIC hydrological model, and relates to the technical field of photovoltaic agricultural water resource regulation. First, a first VIC hydrological model composed of a water balance equation and an energy balance equation is established, then the relationship between energy and water circulation in the first VIC hydrological model is modified according to the setting of photovoltaic panels, so that the relevant parameters obtained are more in line with the actual situation, then the optimal objective of maximum net radiation value and minimum photovoltaic panel height is used to determine the first photovoltaic panel setting information with the best power generation efficiency from a plurality of photovoltaic panel setting parameters, and further determine the first plant planting information and the first water resource dynamic regulation information. Through the technical scheme of the application, the VIC hydrological model is modified according to the influence of the erected photovoltaic panels on the agricultural base, so that the photovoltaic panel setting information, the plant planting information and the water resource dynamic regulation information more in line with the actual needs can be determined. BRIEF DESCRIPTION OF DRAWINGS

[0052] In order to more clearly illustrate the embodiments of the application or the technical solutions in the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description are only exemplary, and for those skilled in the art, other drawings can be obtained without creative labor on the basis of the provided drawings.

[0053] Figure 1 is the execution flowchart of the ecosystem circulation regulation method based on the VIC hydrological model in the application.

[0054] Figure 2 is the relationship diagram of the photovoltaic panel setting information in the application. DETAILED DESCRIPTION

[0055] Clearly, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the protection scope of the present application.

[0056] The present application will be described in detail below with reference to the accompanying drawings and specific embodiments, wherein the schematic embodiments and the description are only used to explain the present application, but not to limit the present application.

[0057] A VIC hydrological model-based ecosystem circulation regulation method and system will be described in detail below.

[0058] The present embodiment provides a VIC hydrological model-based ecosystem circulation regulation method, and a specific process is shown in Figure 1 .

[0059] S1: Establish a first VIC hydrological model, and output a first evapotranspiration, a first net radiation value, and a first surface runoff through the first VIC hydrological model.

[0060] The S1 includes the following sub-steps:

[0061] S11: Establish a first water balance equation according to soil moisture content, precipitation, evapotranspiration, surface runoff, and groundwater runoff.

[0062] The specific form of the first water balance equation is as follows:

[0063] ;

[0064] Wherein, W is the soil moisture content (unit: mm); P is the precipitation (unit: mm); ET is the evapotranspiration (unit: mm); R surf is the surface runoff (unit: mm); R sub is the groundwater runoff (unit: mm).

[0065] Wherein, the groundwater runoff is usually not greatly affected by radiation, so the empirical value can be taken, and the soil moisture content at a specific time point can be calculated through the first water balance equation.

[0066] S12: Establish a first energy balance equation according to the net radiation, the sensible heat flux, the latent heat flux, and the soil heat flux.

[0067] The specific form of the first energy balance equation is as follows:

[0068] ;

[0069] wherein R n is the net radiation (unit: W / m2), H is the sensible heat flux (unit: W / m2), LE is the latent heat flux (unit: W / m2), and G is the soil heat flux (unit: W / m2).

[0070] S13: establishing the first VIC hydrological model according to the first water balance equation and the first energy balance equation, and obtaining the first evapotranspiration, the first net radiation value, and the first surface runoff.

[0071] The first VIC hydrological model can comprehensively consider the processes of rainfall, infiltration, runoff, evaporation, and soil moisture migration in the basin by simulating the water and heat exchange among the atmosphere, soil, and vegetation.

[0072] The first evapotranspiration and the first surface runoff can be obtained through the first water balance equation included in the first VIC hydrological model. In the process of obtaining, the measured soil moisture content can be substituted, so as to obtain the first evapotranspiration and the first surface runoff corresponding thereto. Since there is a correlation between the soil moisture content and the evapotranspiration under specific environmental conditions, the soil moisture content and the first evapotranspiration appear in pairs, and when the soil moisture content is determined, the first evapotranspiration can be determined.

[0073] The first net radiation value can be obtained through the first energy balance equation included in the first VIC hydrological model.

[0074] The first net radiation value and the first surface runoff are both parameter values at the first time point.

[0075] S2: performing first photovoltaic energy redistribution processing on the first net radiation value to obtain a second net radiation value and a first radiation shielding rate.

[0076] Since the photovoltaic panel is arranged above the vegetation, it is possible to redistribute the photovoltaic energy of the specified area. Therefore, it is necessary to correct the first net radiation value according to the arrangement mode of the photovoltaic panel to obtain the second net radiation value.

[0077] The S2 includes the following sub-steps:

[0078] S21: obtaining the first radiation shielding rate according to the initial arrangement information of the photovoltaic panel.

[0079] The specific calculation formula is as follows:

[0080] ;

[0081] Wherein, θ is the inclination angle of the photovoltaic panel (unit: degree), H1 is the height of the photovoltaic panel (unit: meter), and D is the spacing of the photovoltaic panel (unit: meter).

[0082] S22: determining the second net radiation value according to the first radiation shielding rate and the first net radiation value.

[0083] The specific calculation formula of the second net radiation value is as follows:

[0084] ;

[0085] Wherein, the R n is the first net radiation value (unit: W / m²), the β pv is the reflectivity of the photovoltaic panel (unit: percent); and the R in is the incident solar radiation (unit: W / m²), which represents the total solar radiation energy perpendicularly irradiated to the ground or the surface of the photovoltaic panel within a unit time.

[0086] The second net radiation value refers to the recalculated net radiation value after considering the influence of the erected photovoltaic panel on the basis of the first VIC hydrological model.

[0087] S3: performing first water cycle disturbance processing on the first surface runoff and the first evapotranspiration to obtain a target soil moisture content and a target evapotranspiration.

[0088] Since the photovoltaic panel is arranged above the plant, not only the net radiation value will be affected, but also the surface runoff and the evapotranspiration will be affected accordingly, because the photovoltaic panel blocks the water evaporation of the plant and the soil.

[0089] In the cleaning process of the photovoltaic panel, part of the cleaning water is not effectively utilized due to infiltration into the soil. It is a key parameter in the water cycle model of the agricultural photovoltaic power station, which directly affects the calculation of the surface runoff, the soil moisture content and the irrigation demand.

[0090] The S3 specifically includes the following sub-steps:

[0091] S31: determining a first infiltration loss value according to first cleaning data of the photovoltaic panel.

[0092] The first cleaning data includes the single cleaning duration of the photovoltaic panel.

[0093] The calculation formula of the first infiltration loss value is as follows:

[0094] Q loss =k infil t wash;

[0095] wherein the k infil is the soil infiltration coefficient (mm / s) related to the soil type and moisture content; t wash is the duration of washing (s).

[0096] S32: determining a second surface runoff according to the first infiltration loss value and the first surface runoff.

[0097] The calculation formula of the second surface runoff is as follows:

[0098] ;

[0099] That is, the second surface runoff is calculated by the first surface runoff and the first infiltration loss value.

[0100] S33: calculating a target soil moisture content and a target evapotranspiration according to the second surface runoff and the first VIC hydrological model.

[0101] In the first water balance equation of the first VIC hydrological model, when the second surface runoff is determined, the target soil moisture content and the target evapotranspiration can be simulated and calculated, wherein the target soil moisture content and the target evapotranspiration are matched in pairs.

[0102] S4: determining first photovoltaic panel setting information with the maximum net radiation value and the minimum photovoltaic panel height as the optimization target.

[0103] On the basis of a specific geographical area and the terrain condition, different photovoltaic panel setting parameters are set for the photovoltaic panel, so as to obtain different photovoltaic panel power generation efficiencies and different influences on crops in the area.

[0104] The S4 can specifically include the following sub-steps:

[0105] S41: determining a plurality of second photovoltaic panel setting information.

[0106] In the S2, the first VIC hydrological model is modified by the initial setting information of the photovoltaic panel to obtain the second net radiation value.

[0107] In order to evaluate the net radiation values corresponding to different photovoltaic panel setting information, a plurality of different second photovoltaic panel setting information is determined in this step, so as to facilitate subsequent calculation of the net radiation values corresponding to different second photovoltaic panel setting information, so that a group of photovoltaic panel setting information with the highest photovoltaic panel power generation efficiency can be selected.

[0108] For example, the S4 can include the following steps: Figure 2As shown, the photovoltaic panel setting information includes: θ is the inclination of the photovoltaic panel, H is the height of the photovoltaic panel, and D is the spacing of the photovoltaic panel. Among them, if the land area and the number of photovoltaic panels to be erected are determined, only the height H of the photovoltaic panel is the independent variable among the above three parameters, and the inclination θ of the photovoltaic panel and the spacing D of the photovoltaic panel are dependent variables that change with H.

[0109] In this step, a plurality of photovoltaic panel height values are determined in a predetermined height range and step size, and corresponding photovoltaic panel inclination and photovoltaic panel spacing are determined according to different photovoltaic panel height values. The same set of photovoltaic panel height, inclination and spacing is taken as a set of the second photovoltaic panel setting information.

[0110] S42: For each set of the second photovoltaic panel setting information, the S2 is iteratively executed, thereby obtaining a plurality of third net radiation values, and each set of the second photovoltaic panel setting information and the corresponding third net radiation value is determined as the first mapping information.

[0111] In the case of determining the photovoltaic panel setting information, the corresponding third net radiation value can be determined, so that the above information can be combined into a set of the first mapping information, and then a plurality of the first mapping information can be evaluated to obtain a set of the first mapping information with the best photovoltaic performance.

[0112] S43: Select the target mapping information from the plurality of the first mapping information with the maximum net radiation value and the minimum photovoltaic panel height as the target, and determine the first photovoltaic panel setting information according to the target mapping information.

[0113] Since the net radiation value is directly related to the power generation efficiency of the photovoltaic panel, and the smaller the photovoltaic panel height is, the less the shading is, and thus the less the impact on crop growth is, the maximum net radiation value and the minimum photovoltaic panel height can be used as the optimization target, so that the target mapping information is selected from the plurality of the first mapping information.

[0114] In the specific optimization process, the net radiation value and the photovoltaic panel height in different the first mapping information can be curve fitted, so that a set of the first mapping information with the best power generation and shading index is obtained according to the fitted curve.

[0115] In other embodiments, the objective function fitting method commonly used in the art can also be used to select the installation cost and other factors as constraint conditions to obtain a set of the first mapping information with the best index with the net radiation value and the photovoltaic panel height as the optimization target.

[0116] S5: Determine the first plant planting information according to the first photovoltaic panel setting information, the first soil nutrient information and the first meteorological data.

[0117] In this step group, the best crop type and planting density need to be matched according to the soil-weather-pv shading dynamic.

[0118] The S5 comprises the following sub-steps:

[0119] S51: determining a target radiation shielding rate according to the first photovoltaic panel setting information.

[0120] In the case where the first photovoltaic panel setting information has been determined, the corresponding target radiation shielding rate can be calculated according to the calculation method in the S21.

[0121] S52: inputting the target radiation shielding rate, first soil nutrient information and first meteorological data into a plant planting information prediction model to determine first plant planting information.

[0122] The first soil nutrient information and the first meteorological data are information obtained after actual measurement of the target land, which can be used to predict the first plant planting information suitable for planting on the target land.

[0123] The first soil nutrient information mainly includes soil pH value, organic matter content, nitrogen, phosphorus and potassium (NPK) content, trace element content, soil physical properties, etc.

[0124] The plant planting information prediction model is obtained by training a convolutional neural network model. When selecting training samples, the plant information most suitable for planting under the combination of photovoltaic panel erection parameters of different radiation shielding rates and different soil nutrient information and meteorological data can be used as training samples. The radiation shielding rate, soil nutrient information and meteorological data in each sample data are used as input, and the plant information most suitable for planting is used as output to train the plant planting information prediction model.

[0125] The meteorological data mainly includes precipitation information and wind speed information.

[0126] S6: determining first water resource dynamic regulation information according to the target soil water content, the target evapotranspiration, the first plant planting information and the first meteorological data.

[0127] After the soil water content, evapotranspiration and meteorological data such as rainfall are determined, the corresponding water resource dynamic regulation information can be determined, which can specifically include photovoltaic panel washing strategy and crop irrigation strategy.

[0128] The S6 comprises the following sub-steps:

[0129] S61: determining a first photovoltaic panel washing strategy according to a first dust accumulation degree and the first meteorological data.

[0130] The dust accumulation degree of the photovoltaic panel directly affects the power generation efficiency of the photovoltaic panel, so when the dust accumulation degree is too high, the photovoltaic panel needs to be cleaned, but the cleaning process includes dry brushing, low-pressure washing, high-pressure washing and other forms. The corresponding cleaning strategy can be selected in combination with the recent rainfall information in the meteorological data.

[0131] Preferably, a washing strategy prediction model can be trained to determine the first photovoltaic panel washing strategy, and the model can be trained using a convolutional neural network. When selecting training samples, different dust accumulation degrees and rainfall probabilities and rainfall amounts within 6 hours can be used as input data, and artificial or historical cleaning strategies can be used as output data, and the washing strategy prediction model can be trained.

[0132] Therefore, one of dry brushing, low-pressure washing or high-pressure washing can be used as the first photovoltaic panel washing strategy.

[0133] S62: According to the first photovoltaic panel washing strategy, the target soil water content, the first plant planting information and the target evapotranspiration, a first irrigation strategy is determined.

[0134] Different first photovoltaic panel washing strategies often correspond to different water consumption, so the corresponding first irrigation strategy can be determined in combination with the target soil water content and the target evapotranspiration.

[0135] When determining the first irrigation strategy, it can be determined by expert experience or by training a machine learning model. Preferably, the first irrigation strategy can be determined by training a machine learning model, so that the determined first irrigation strategy is more scientific and reasonable. When selecting training samples, the photovoltaic panel washing strategy, the soil water content, the plant planting information and the evapotranspiration can be used as input data, and the irrigation water consumption can be used as output data, so as to train an irrigation strategy determination model.

[0136] S63: According to the first photovoltaic panel washing strategy and the first irrigation strategy, a first water resource dynamic regulation information is determined.

[0137] The first water resource dynamic regulation information includes the washing strategy and the irrigation strategy of the photovoltaic panel.

[0138] The application also provides an ecosystem circulation regulation system based on the VIC hydrological model, which is used to execute the ecosystem circulation regulation method based on the VIC hydrological model.

[0139] The application provides an ecosystem circulation regulation method and system based on a VIC hydrological model, and relates to the technical field of photovoltaic agricultural water resource regulation. First, a first VIC hydrological model composed of a water balance equation and an energy balance equation is established, then the relationship between energy and water circulation in the first VIC hydrological model is corrected according to the setting of the photovoltaic panel, so that the relevant parameters obtained are more in line with the actual situation, then the first photovoltaic panel setting information with the best power generation efficiency is determined from a plurality of photovoltaic panel setting parameters, taking the maximum net radiation value and the minimum photovoltaic panel height as the optimization target, and further the first plant planting information and the first water resource dynamic regulation information are determined. Through the technical scheme of the application, the VIC hydrological model is corrected according to the influence of the erected photovoltaic panel on the agricultural base, so that the photovoltaic panel setting information, the plant planting information and the water resource dynamic regulation information more in line with the actual needs can be determined.

[0140] The above description is only the preferred embodiment of the present application, and any equivalent changes or modifications made according to the structure, features and principles described in the patent application scope of the present application are included in the patent application scope of the present application.

Claims

1. An ecosystem circulation regulation method based on a VIC hydrological model, characterized in that, The method comprises: S1: establishing a first VIC hydrological model, outputting a first evapotranspiration, a first net radiation value and a first surface runoff through the first VIC hydrological model; The S1 comprises the following sub-steps: S11: establishing a first water balance equation according to soil moisture content, precipitation, evapotranspiration, surface runoff and groundwater runoff; S12: establishing a first energy balance equation according to net radiation, sensible heat flux, latent heat flux and soil heat flux; S13: establishing the first VIC hydrological model according to the first water balance equation and the first energy balance equation; S2: performing first photovoltaic energy redistribution processing on the first net radiation value to obtain a second net radiation value and a first radiation shielding rate; S3: performing first water cycle disturbance processing on the first surface runoff and the first evapotranspiration to obtain a target soil moisture content and a target evapotranspiration; S4: determining first photovoltaic panel setting information with the maximum net radiation value and the minimum photovoltaic panel height as the optimization target; The S4 comprises: S41: determining a plurality of second photovoltaic panel setting information; S42: for each set of second photovoltaic panel setting information, iteratively performing the S2 to obtain a plurality of third net radiation values, and determining each set of second photovoltaic panel setting information and the corresponding third net radiation value as first mapping information; S43: selecting target mapping information from the plurality of first mapping information with the maximum net radiation value and the minimum photovoltaic panel height as the target, and determining the first photovoltaic panel setting information according to the target mapping information; S5: determining target radiation shielding rate according to the first photovoltaic panel setting information, and determining first plant planting information according to first soil nutrient information, first meteorological data and the target radiation shielding rate; The first photovoltaic panel setting information comprises the inclination, height and spacing of the photovoltaic panel; S6: determining first water resource dynamic regulation information according to the target soil moisture content, the target evapotranspiration, the first plant planting information and the first meteorological data; The first water resource dynamic regulation information comprises a first photovoltaic panel washing strategy and a first irrigation strategy. 2.The method of claim 1, wherein, The first water balance equation is: ； Wherein, W is soil water content; P is precipitation; ET is evapotranspiration; R surf is surface runoff; R sub is groundwater runoff. 3.The method of claim 1, wherein, The specific form of the first energy balance equation is as follows: ； Wherein, Rn is the first net radiation, H is the sensible heat flux, LE is the latent heat flux, and G is the soil heat flux.

4. The ecosystem circulation regulation method based on the VIC hydrological model according to claim 3, characterized in that, The S2 comprises: S21: obtaining the first radiation shielding rate according to the initial setting information of the photovoltaic panel; The specific calculation formula is as follows: ； Wherein, θ is the inclination of the photovoltaic panel, H1 is the height of the photovoltaic panel, and D is the spacing of the photovoltaic panel; S22: determining the second net radiation value according to the first radiation shielding rate and the first net radiation value; The specific calculation formula of the second net radiation value is as follows: ； wherein said R n is the first net radiation value, said β pv is the photovoltaic panel reflectance; said R in is the incident solar radiation, representing the total solar energy per unit of time that is normally incident on the surface of the ground or of the photovoltaic panel.

5. The ecosystem circulation regulation method based on the VIC hydrological model according to claim 4, characterized in that, The S3 comprises: S31: determining a first penetration loss value according to the first cleaning data of the photovoltaic panel; The calculation formula of the first penetration loss value is as follows: Q loss =k infil t wash ； wherein the k infil is the soil permeability coefficient; t wash is the duration of the washing; S32: determining a second surface runoff according to the first penetration loss value and the first surface runoff; The calculation formula of the second surface runoff is as follows: ； S33: calculating a target soil moisture content and a target evapotranspiration according to the second surface runoff and the first VIC hydrological model.

6. The ecosystem circulation regulation method based on the VIC hydrological model according to claim 5, characterized in that, The S5 further comprises: inputting the target radiation shielding rate, the first soil nutrient information and the first meteorological data into a plant planting information prediction model, the plant planting information prediction model being obtained by training a convolutional neural network model, when selecting training samples, plant information most suitable for planting under different radiation shielding rates of photovoltaic panel erection parameters combined with different soil nutrient information and meteorological data is taken as the training sample, radiation shielding rate, soil nutrient information and meteorological data in each sample data are taken as input, and the plant information most suitable for planting is taken as output, so as to train the plant planting information prediction model to determine the first plant planting information.

7. The method of claim 6, wherein the VIC hydrological model is based on a Variable Infiltration Capacity (VIC) model. The S6 comprises: S61: determining a first photovoltaic panel washing strategy according to the first dust accumulation degree and the first meteorological data; S62: determining a first irrigation strategy according to the first photovoltaic panel washing strategy, the target soil moisture content, the first plant planting information and the target evapotranspiration; S63: determining first water resource dynamic regulation information according to the first photovoltaic panel washing strategy and the first irrigation strategy.

8. An ecosystem circulation regulation system based on a VIC hydrological model, used to implement the ecosystem circulation regulation method based on the VIC hydrological model in any one of claims 1-7.

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