Method and system for flood drainage prediction and crop output reduction calculation based on crop model

Abstract

The invention relates to the technical field of agricultural crop drainage and output reduction calculation, and discloses a crop model-based drainage prediction and crop output reduction calculation method and system, and the method comprises the steps: obtaining meteorological data, farming data and soil data; calculating water and soil characteristic data according to the soil data; wherein the water and soil characteristic data comprises saturated water content, wilting points, field moisture capacity and saturated hydraulic conductivity; calculating farmland drainage days according to the water and soil characteristic data; calculating the crop root death rate according to the farmland drainage days; according to the meteorological data, the farming data, the water and soil characteristic data and the crop root death rate, the crop yield reduction percentage is obtained. According to the invention, the number of days of natural drainage and whether artificial drainage is needed can be accurately measured and calculated, and the yield reduction percentage of crop production caused by flood disasters is calculated, so that agricultural decision and management are assisted.

Description

Technical Field

[0001] The present invention relates to the technical field of agricultural crop waterlogging drainage and yield reduction calculation, and in particular to a method and system for waterlogging drainage prediction and crop yield reduction calculation based on a crop model. Background Art

[0002] Predicting the impact of floods and waterlogging on crop production is an important part of agricultural risk management. It helps to build a more scientific and reasonable agricultural management system, helps farmers and farms to prepare for flood control and drainage in advance, and conduct scientific production reduction calculations afterwards.

[0003] Existing technologies usually use satellite remote sensing to obtain the percentage of crop yield reduction caused by flood disasters. However, satellite remote sensing can only monitor crop growth in real time and cannot directly predict future crop yield reductions. In addition, optical remote sensing is greatly restricted by weather conditions. Clouds and fog will hinder data collection. At the same time, crop canopies will also affect remote sensing satellites' judgment of farmland water layers, reducing data availability and continuity. Existing satellite remote sensing methods are even more unable to make decisions and manage flood disasters in advance, and there is a lag.

[0004] Therefore, there is an urgent need for a drainage prediction and crop yield reduction calculation method and system based on crop models, which can accurately measure the number of days for natural drainage and whether artificial drainage is needed, and calculate the percentage of yield reduction caused by flood disasters on crop production, so as to assist in agricultural decision-making and management. Summary of the invention

[0005] In order to solve the above technical problems, the present invention provides a method and system for drainage prediction and crop yield reduction calculation based on a crop model, which can accurately measure the number of days of natural drainage and whether artificial drainage is needed, and calculate the percentage of yield reduction caused by flood disasters on crop production, thereby assisting agricultural decision-making and management.

[0006] The present invention provides a method for predicting waterlogging drainage and calculating crop yield reduction based on a crop model, comprising the following steps: S1. Obtain meteorological data, agricultural data and soil data; S2. Calculate soil and water characteristic data based on soil data; wherein the soil and water characteristic data include saturated water content, wilting point, field holding capacity and saturated hydraulic conductivity; S3. Calculate the number of days for farmland drainage based on water and soil characteristic data; S4. Calculate crop root mortality based on the number of days the farmland is drained; S5. Obtain the percentage of crop yield reduction based on meteorological data, farming data, water and soil characteristic data and crop root mortality rate.

[0007] Furthermore, in S1, meteorological data include temperature, wind speed, water surface evaporation rate, precipitation, runoff, and solar radiation; Agricultural data include farmland area, planting varieties, sowing date, sowing amount, irrigation date, irrigation amount, fertilization date, fertilization amount and fertilizer type; Soil data include the percentage of sand, loam, clay, soil porosity, soil bulk density and organic matter content in the soil.

[0008] Furthermore, in S2, calculating the water and soil characteristic data based on the soil data includes: S21. Based on soil survey data, the soil is divided into n layers according to depth; S22. Calculate the initial value of the saturated water content of each layer of soil according to the soil data; The calculation formula is as follows: Sm n 1=-0.251sand+0.195clay+0.011som+0.006(sand×som)-0.027(clay×som)+0.452(sand×clay)+0.299; Among them, clay represents the percentage of clay, sand represents the percentage of sand, som represents the organic matter content, Sm n 1 represents the initial value of the first saturated water content of the nth layer of soil; Sm n 1'=(Sm n 1)+[1.283×(Sm n 1)²-0.374×(Sm n 1)-0.015]; Among them, Sm n 1' represents the first saturated moisture content correction value of the nth layer of soil; Sm n 2=0.287sand+0.034clay+0.022som-0.018(sand×som)-0.027(clay×som)-0.584(sand×clay)+0.078; Among them, Sm n 2 represents the initial value of the second saturated water content of the nth layer of soil; Sm n 2'= (Sm n 2)+(0.636×(Sm n 2)-0.107); Among them, Sm n 2' represents the second saturated moisture content correction value of the nth layer of soil; Smn =Sm n 1'+Sm n 2'-0.097sand+0.043; Among them, Sm n represents the initial value of the saturated water content of the nth layer of soil; S23, calculating a soil compaction correction coefficient according to the soil compaction degree and soil compaction ratio of each soil layer; The calculation formula is as follows: dfi n =c1v×cw1+c2v×cw2; Among them, dfi n represents the initial density of the soil in the nth layer, c1v represents the compactness value of the soil with the highest compactness in the nth layer, c2v represents the compactness value of the soil with the second highest compactness in the nth layer, cw1 represents the proportion of the soil with the highest compactness in the nth layer, and cw2 represents the proportion of the soil with the second highest compactness in the nth layer; Df n =dfi n ×[0.9+(Day-agro_date+T rain ×10)0.1×(1 / 365)]; Among them, Df n represents the soil compactness correction coefficient of the nth layer of soil, Day represents the current date, T rain represents the number of rainfalls, and agro_date represents the planting date, i.e. the last time the soil was disturbed; S24, calculating the saturated water content correction value of each layer of soil according to the soil compaction correction coefficient and the initial value of saturated water content; The calculation formula is as follows: Sm n 0=1-((1-Sm n )×Df n ); Among them, Sm n 0 represents the corrected value of the saturated moisture content of the nth layer of soil; S25, calculating the field water holding capacity and saturated hydraulic conductivity of each layer of soil according to the initial value of the saturated water content and the corrected value of the saturated water content of each layer of soil; The calculation formula is as follows: Sm n f=Sm n 1'-0.2(Sm n -Sm n 0); Among them, Sm n f represents the field water holding capacity of the nth layer of soil; K n 0=1930(Sm n 0-Sm n 2') (3-BL) ; Among them, K n 0 represents the saturated hydraulic conductivity of the nth layer of soil, and BL represents the slope of the logarithmic curve of soil water tension; S26. calculating the wilting point of each layer of soil according to the soil data; The calculation formula is as follows: ; Among them, θ r represents the wilting point and Ø represents the soil porosity.

[0009] Further, in S21, the soil is divided into n layers according to depth, where n is 8; dividing the soil into 8 layers according to depth includes: L1=4.5cm, L2=9.1cm, L3=16.6cm, L4=28.9cm, L5=49.3cm, L6=82.9cm, L7=138.3cm, and L8=229.6cm.

[0010] Furthermore, in S3, the calculation of farmland drainage days based on water and soil characteristic data includes: S31. Calculate the amount of water retained in farmland based on precipitation and runoff. If there is continuous or intermittent precipitation for several days, (C-Sm10×L1-…-Sm n 0×L n ) is equal to zero for a precipitation cycle; In (Sm10×L1-…-Sm n 0×L n )>0, the water storage C needs to be added with the accumulated precipitation; The number of drainage days needs to be added to the previous natural days, that is, the first precipitation time before the surface water is drained is used as the initial time for calculation.

[0011] S32, calculating the time required for each layer of soil to absorb water saturatedly according to the saturated water content and saturated hydraulic conductivity of each layer of soil; The calculation formula is as follows: T n =(Sm n 0-S n 0)×L n / min(D1,…,D n ); Among them, T n It represents the time required for the nth layer of soil to absorb water to saturation, S n 0 represents the current moisture content of the nth layer of soil, L nrepresents the thickness of the nth layer of soil, D1 represents the saturated hydraulic conductivity of the first layer of soil, and D n represents the saturated hydraulic conductivity of the nth layer of soil; S33, calculating the water retention layer according to the saturated hydraulic conductivity of each layer of soil; When D n >D n+1 , then D n The corresponding nth layer of soil is recorded as the water retention layer; S34, calculating the number of days for drainage of each retention layer; The calculation formula is as follows: P n =(T1+…+T n )+{(C-Sm10×L1-…-Sm n 0×L n ) / [min(D1,…,D n )+E×(1-lai)+ET]}; Among them, P n represents the number of days of drainage of the nth retention layer, C represents the amount of water retained in the farmland, E represents the evaporation rate of the water surface, lai represents the leaf area index and the maximum value of lai is 1, and ET represents the canopy evaporation rate; S35. Calculate the drainage days for farmland based on the drainage days for each retention layer.

[0012] Furthermore, in S4, the calculation of crop root mortality based on the number of days of farmland drainage includes: S41, determining a crop flood resistance index; wherein the flood resistance index i ranges from 1 to 9, 1 being the crop not tolerant to floods, and 9 being the crop tolerant to floods; S42. Calculate the root mortality of crops based on the number of days of farmland drainage; The calculation formula is as follows: ; Where RD represents the crop root mortality rate, t represents the tth day after the disaster, and m represents the total number of days after the disaster.

[0013] Furthermore, in S5, based on meteorological data, farming data, water and soil characteristic data and crop root mortality rate, the crop yield reduction percentage is obtained, including: S51, inputting meteorological data, farming data, water and soil characteristic data and crop root mortality rate into the wofost model to obtain the actual crop yield; S52, setting the crop root mortality rate to 0, and then inputting the meteorological data, farming data, water and soil characteristic data and the crop root mortality rate into the wofost model to obtain the crop comparative yield; S53. Calculate the crop yield reduction percentage based on the actual crop yield and the comparative crop yield.

[0014] The present invention also provides a drainage prediction and crop yield reduction calculation system based on a crop model, which is used to execute any of the above-mentioned drainage prediction and crop yield reduction calculation methods based on a crop model, and the system includes the following modules: Data acquisition module, used to obtain meteorological data, agricultural data and soil data; A water and soil characteristic calculation module, connected to the data acquisition module, is used to calculate water and soil characteristic data based on soil data; wherein the water and soil characteristic data include saturated water content, wilting point, field water holding capacity and saturated hydraulic conductivity; The drainage days calculation module is connected to the water and soil characteristics calculation module and is used to calculate the farmland drainage days based on the water and soil characteristics data; The mortality rate calculation module is connected to the drainage days calculation module and is used to calculate the crop root mortality rate according to the farmland drainage days; The output module is connected with the data acquisition module, the water and soil characteristic calculation module and the mortality calculation module, and is used to obtain the crop yield reduction percentage according to the meteorological data, farming data, water and soil characteristic data and crop root mortality rate.

[0015] The embodiments of the present invention have the following technical effects: The present invention ensures the comprehensiveness and accuracy of input information by integrating meteorological data, agricultural data and soil data, divides the soil into multiple layers according to depth for detailed analysis, takes into account the influence of soil characteristics at different layers on water retention and drainage capacity, improves the authenticity of simulation, and not only pays attention to the flood inundation situation visible on the surface, but also goes deep into the level of crop root health. By calculating the root mortality rate, it more accurately reflects the actual damage of floods to crops, can accurately calculate the number of days for natural drainage, and judge whether manual intervention is needed, providing farmers and managers with a clear operating guide; this solution can accurately calculate the number of days for natural drainage and whether manual drainage is needed, calculate the percentage of crop production reduction caused by floods, and thus assist in agricultural decision-making and management. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0017] Figure 1 It is a flow chart of a method for predicting waterlogging drainage and calculating crop yield reduction based on a crop model provided by an embodiment of the present invention; Figure 2It is a structural schematic diagram of a drainage prediction and crop yield reduction calculation system based on a crop model provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be described clearly and completely below. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work belong to the scope of protection of the present invention.

[0019] The present invention proposes a method for predicting waterlogging drainage and calculating crop yield reduction based on a crop model. Figure 1 is a flow chart of a method for predicting waterlogging drainage and calculating crop yield reduction based on a crop model provided by an embodiment of the present invention, see Figure 1 , including: S1. Obtain meteorological data, agricultural data and soil data.

[0020] In some embodiments, weather data may be obtained through a weather center; Soil data can be obtained through the "China Land Surface Simulated Soil Properties Dataset".

[0021] In some embodiments, the meteorological data includes temperature, wind speed, water surface evaporation rate, precipitation, runoff, and solar radiation; Agricultural data include farmland area, planting varieties, sowing date, sowing amount, irrigation date, irrigation amount, fertilization date, fertilization amount and fertilizer type, etc.; Among them, farmland area: the farmland area circled by the user; Planting variety: the variety that the user needs to calculate; Planting date: The planting date corresponding to the growing season that the user needs to calculate; Seeding quantity: The user needs to calculate the seeding quantity corresponding to the growing season; Irrigation date: The date of each irrigation during the growing season that the user needs to calculate; Irrigation volume: The user needs to calculate the water layer thickness for each irrigation during the growing season; Fertilization date: The date of each fertilization during the growing season that the user needs to calculate; Fertilizer amount: The amount of fertilizer that the user needs to calculate for the growing season; Soil data includes the percentage of sand, loam, clay, soil porosity, soil bulk density and organic matter content in the soil; among them, soil data refers to the data of the soil at the location of the farmland circled by the user.

[0022] S2. Calculate water and soil characteristic data based on soil data.

[0023] Specifically include: S21. Based on soil survey data, the soil is divided into n layers according to depth.

[0024] In some embodiments, the soil may be divided into n layers according to depth, where n is 8; dividing the soil into 8 layers according to depth includes: L1=4.5cm, L2=9.1cm, L3=16.6cm, L4=28.9cm, L5=49.3cm, L6=82.9cm, L7=138.3cm, and L8=229.6cm.

[0025] S22. Calculate the initial value of the saturated water content of each layer of soil according to the soil data; The calculation formula is as follows: Sm n 1=-0.251sand+0.195clay+0.011som+0.006(sand×som)-0.027(clay×som)+0.452(sand×clay)+0.299; Among them, clay represents the percentage of clay, sand represents the percentage of sand, som represents the organic matter content, Sm n 1 represents the initial value of the first saturated water content of the nth layer of soil; Sm n 1'=(Sm n 1)+[1.283×(Sm n 1)²-0.374×(Sm n 1)-0.015]; Among them, Sm n 1' represents the first saturated moisture content correction value of the nth layer of soil; Sm n 2=0.287sand+0.034clay+0.022som-0.018(sand×som)-0.027(clay×som)-0.584(sand×clay)+0.078; Among them, Sm n 2 represents the initial value of the second saturated water content of the nth layer of soil; Sm n 2'=(Sm n 2)+(0.636×(Sm n 2)-0.107); Among them, Sm n 2' represents the second saturated moisture content correction value of the nth layer of soil; Sm n =Smn 1'+Sm n 2'-0.097sand+0.043; Among them, Sm n represents the initial value of the saturated water content of the nth layer of soil; S23, calculating a soil compaction correction coefficient according to the soil compaction degree and soil compaction ratio of each soil layer; Table 1 Soil compactness assignment table

[0026] Table 2 Soil compaction correspondence table

[0027] See Table 1 and Table 2, the calculation formula is as follows: dfi n =c1v×cw1+c2v×cw2; Among them, dfi n represents the initial density of the soil in the nth layer, c1v represents the compactness value of the soil with the highest compactness in the nth layer, c2v represents the compactness value of the soil with the second highest compactness in the nth layer, cw1 represents the proportion of the soil with the highest compactness in the nth layer, and cw2 represents the proportion of the soil with the second highest compactness in the nth layer; Df n =dfi n ×[0.9+(Day-agro_date+T rain ×10)0.1×(1 / 365)]; Among them, Df n represents the soil compactness correction coefficient of the nth layer of soil, Day represents the current date, T rain represents the number of rainfalls, and agro_date represents the planting date, i.e. the last time the soil was disturbed; S24, calculating the saturated water content correction value of each layer of soil according to the soil compaction correction coefficient and the initial value of saturated water content; The calculation formula is as follows: Sm n 0=1-((1-Sm n )×Df n ); Among them, Sm n 0 represents the corrected value of the saturated moisture content of the nth layer of soil; S25, calculating the field water holding capacity and saturated hydraulic conductivity of each layer of soil according to the initial value of the saturated water content and the corrected value of the saturated water content of each layer of soil; The calculation formula is as follows: Smn f=Sm n 1'-0.2(Sm n -Sm n 0); Among them, Sm n f represents the field water holding capacity of the nth layer of soil; K n 0=1930(Sm n 0-Sm n 2') (3-BL) ; Among them, K n 0 represents the saturated hydraulic conductivity of the nth layer of soil, and BL represents the slope of the logarithmic curve of soil water tension; S26. calculating the wilting point of each layer of soil according to the soil data; The calculation formula is as follows: ; Among them, θ r represents the wilting point, Ø represents the soil porosity; Saturated moisture content refers to the moisture content when all soil pores are filled with water under natural conditions; Field water holding capacity refers to the relatively stable soil water content that can be maintained in the soil profile after sufficient irrigation or precipitation on land with deep groundwater and good drainage, allowing water to fully infiltrate and preventing its evaporation over a certain period of time; Saturated hydraulic conductivity refers to the ability of water to pass through soil when the soil is fully saturated, that is, all pores are filled with water, expressed in cm / day.

[0028] S3. Calculate the number of days for farmland drainage based on water and soil characteristic data.

[0029] Specifically include: S31. Calculate the amount of water retained in farmland based on precipitation and runoff.

[0030] In some embodiments, the amount of water retained in farmland C = precipitation - runoff.

[0031] S32. Calculate the time required for each layer of soil to absorb water to saturation based on the saturated water content and saturated hydraulic conductivity of each layer of soil.

[0032] The calculation formula is as follows: T n =(Sm n 0-S n 0)×L n / min(D1,…,D n ); Among them, T n It represents the time required for the nth layer of soil to absorb water to saturation, S n0 represents the current moisture content of the nth layer of soil, L n represents the thickness of the nth layer of soil, D1 represents the saturated hydraulic conductivity of the first layer of soil, and D n It represents the saturated hydraulic conductivity of the nth layer of soil. The saturated water content of each layer of soil is multiplied by the thickness of the soil layer to get the moisture content of the soil layer. The moisture content of the soil layer is divided by the minimum saturated hydraulic conductivity above the soil layer to get the time required for each layer of soil to absorb water to saturation.

[0033] S33. Calculate the water retention layer based on the saturated hydraulic conductivity of each layer of soil.

[0034] In some embodiments, when D n >D n+1 , it will cause water retention, D n The corresponding nth layer of soil is recorded as the water retention layer.

[0035] S34. Calculate the number of days for drainage of each retention layer.

[0036] The calculation formula is as follows: P n =(T1+…+T n )+{(C-Sm10×L1-…-Sm n 0×L n ) / [min(D1,…,D n )+E×(1-lai)+ET]}; Establishment conditions: (C-Sm10×L1-…-Sm n 0×L n )>0; Among them, P n represents the number of days of drainage of the nth retention layer, C represents the amount of water retained in the farmland, E represents the evaporation rate of the water surface, lai represents the leaf area index and the maximum value of lai is 1, and ET represents the canopy evaporation rate.

[0037] Data on water surface evaporation rate come from meteorological data; The canopy evaporation rate is the intermediate data calculated by the wofost model. Since the flood disaster calculation is not a one-time calculation, but a daily calculation, the current canopy evaporation data can be replaced by the canopy evaporation data under non-flood conditions. The canopy evaporation rate is the historical data of the previous day or the latest historical data obtained in the database.

[0038] The leaf area index is calculated by the wofost model or obtained by remote sensing inversion. The leaf area index is the historical data of the previous day or the latest historical data obtained in the database.

[0039] S35. Calculate the drainage days for farmland based on the drainage days for each retention layer.

[0040] When (C-Sm10×L1-…-Sm n 0×L n )>0, the maximum value of drainage days for all retention layers is max(P n ) is the number of days for farmland drainage.

[0041] S4. Calculate the root mortality rate of crops based on the number of days the farmland is drained.

[0042] Specifically include: S41. Determine the crop flood resistance index.

[0043] In some embodiments, the flood resistance index i ranges from 1 to 9, where 1 means the crop is not flood resistant and 9 means the crop is flood resistant.

[0044] S42. Calculate the root mortality of crops based on the number of days of farmland drainage; The calculation formula is as follows: ; Among them, RD represents the crop root mortality rate, t represents the tth day after the disaster, and m represents the total number of days after the disaster. m is less than or equal to the number of days for farmland drainage (max(P n ).

[0045] For example, Chinese cabbage is not tolerant to waterlogging, and the flood resistance index is defined as 1. The root mortality rate of crops after the disaster is calculated as follows: Day 1: RD = 9%; The next day: RD = 9% + 18% = 27%; Day 3: RD = 9% + 18% + 27% = 54%; Article 4: RD=9%+18%+27%+36%=90%; Day 5: RD=9%+18%+27%+36%+45%=100%; when the crop root mortality rate is greater than 100%, the final result is equal to 100%.

[0046] S5. Obtain the percentage of crop yield reduction based on meteorological data, farming data, water and soil characteristic data and crop root mortality rate.

[0047] Specifically include: S51. Input meteorological data, agricultural data, water and soil characteristic data and crop root mortality rate into the wofost model to obtain the actual crop yield.

[0048] S52, setting the crop root mortality rate to 0, and then inputting the meteorological data, farming data, water and soil characteristic data and the crop root mortality rate into the wofost model to obtain the crop comparative yield.

[0049] S53. Calculate the crop yield reduction percentage based on the actual crop yield and the comparative crop yield.

[0050] In some embodiments, the crop yield reduction percentage = 1-(actual crop yield / comparative crop yield).

[0051] The present invention ensures the comprehensiveness and accuracy of input information by integrating meteorological data, agricultural data and soil data, divides the soil into multiple layers according to depth for detailed analysis, takes into account the influence of soil characteristics at different layers on water retention and drainage capacity, improves the authenticity of simulation, and not only pays attention to the flood inundation situation visible on the surface, but also goes deep into the level of crop root health. By calculating the root mortality rate, it more accurately reflects the actual damage of floods to crops, can accurately calculate the number of days for natural drainage, and judge whether manual intervention is needed, providing farmers and managers with a clear operating guide; this solution can accurately calculate the number of days for natural drainage and whether manual drainage is needed, calculate the percentage of crop production reduction caused by floods, and thus assist in agricultural decision-making and management.

[0052] Figure 2 is a schematic diagram of a system for waterlogging prediction and crop yield reduction calculation based on a crop model provided by an embodiment of the present invention. The system is used to execute a method for waterlogging prediction and crop yield reduction calculation based on a crop model described in the above embodiment. Figure 2 As shown, the system includes the following modules: Data acquisition module, used to obtain meteorological data, agricultural data and soil data; A water and soil characteristic calculation module, connected to the data acquisition module, is used to calculate water and soil characteristic data based on soil data; wherein the water and soil characteristic data include saturated water content, wilting point, field water holding capacity and saturated hydraulic conductivity; The drainage days calculation module is connected to the water and soil characteristics calculation module and is used to calculate the farmland drainage days based on the water and soil characteristics data; The mortality rate calculation module is connected to the drainage days calculation module and is used to calculate the crop root mortality rate according to the farmland drainage days; The output module is connected with the data acquisition module, the water and soil characteristic calculation module and the mortality calculation module, and is used to obtain the crop yield reduction percentage according to the meteorological data, farming data, water and soil characteristic data and crop root mortality rate.

[0053] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the technical solutions of the embodiments of the present invention.

Claims

1. A method for predicting waterlogging drainage and calculating crop yield reduction based on a crop model, characterized in that: The steps include: S1. Obtain meteorological data, agricultural data and soil data; S2. Calculate soil and water characteristic data based on soil data; wherein the soil and water characteristic data include saturated water content, wilting point, field holding capacity and saturated hydraulic conductivity; S3. Calculate the number of days for farmland drainage based on water and soil characteristic data; S4. Calculate crop root mortality based on the number of days the farmland is drained; S5. Obtain the percentage of crop yield reduction based on meteorological data, farming data, water and soil characteristic data and crop root mortality rate.

2. The method for predicting waterlogging drainage and calculating crop yield reduction based on a crop model according to claim 1, characterized in that: In S1, the meteorological data include temperature, wind speed, water surface evaporation rate, precipitation, runoff and solar radiation; Agricultural data include farmland area, planting varieties, sowing date, sowing amount, irrigation date, irrigation amount, fertilization date, fertilization amount and fertilizer type; Soil data include the percentage of sand, loam, clay, soil porosity, soil bulk density and organic matter content in the soil.

3. The method for predicting waterlogging drainage and calculating crop yield reduction based on crop model according to claim 2, characterized in that: In S2, calculating the water and soil characteristic data according to the soil data includes: S21. Based on soil survey data, the soil is divided into n layers according to depth; S22. Calculate the initial value of the saturated water content of each layer of soil according to the soil data; The calculation formula is as follows: Sm n 1=-0.251sand+0.195clay+0.011som+0.006(sand×som)-0.027(clay×som)+0.452(sand×clay)+0.299; Among them, clay represents the percentage of clay, sand represents the percentage of sand, som represents the organic matter content, Sm n 1 represents the initial value of the first saturated water content of the nth layer of soil; Sm n 1'=(Sm n 1)+[1.283×(Sm n 1)²-0.374×(Sm n 1)-0.015]; Among them, Sm n 1' represents the first saturated moisture content correction value of the nth layer of soil; Sm n 2=0.287sand+0.034clay+0.022som-0.018(sand×som)-0.027(clay×som)-0.584(sand×clay)+0.078; Among them, Sm n 2 represents the initial value of the second saturated water content of the nth layer of soil; Sm n 2'=(Sm n 2)+(0.636×(Sm n 2)-0.107); Among them, Sm n 2' represents the second saturated moisture content correction value of the nth layer of soil; Sm n =Sm n 1'+Sm n 2'-0.097sand+0.043; Among them, Sm n represents the initial value of the saturated water content of the nth layer of soil; S23, calculating a soil compaction correction coefficient according to the soil compaction degree and soil compaction ratio of each soil layer; The calculation formula is as follows: dfi n =c1v×cw1+c2v×cw2; Among them, dfi n represents the initial density of the soil in the nth layer, c1v represents the compactness value of the soil with the highest compactness in the nth layer, c2v represents the compactness value of the soil with the second highest compactness in the nth layer, cw1 represents the proportion of the soil with the highest compactness in the nth layer, and cw2 represents the proportion of the soil with the second highest compactness in the nth layer; Df n =dfi n ×[0.9+(Day-agro_date+T rain ×10)0.1×(1 / 365)]; Among them, Df n represents the soil compactness correction coefficient of the nth layer of soil, Day represents the current date, T rain It indicates the number of rainfalls, and agro_date indicates the planting date; S24, calculating the saturated water content correction value of each layer of soil according to the soil compaction correction coefficient and the initial value of saturated water content; The calculation formula is as follows: Sm n 0=1-((1-Sm n )×Df n ); Among them, Sm n 0 represents the corrected value of the saturated moisture content of the nth layer of soil; S25, calculating the field water holding capacity and saturated hydraulic conductivity of each layer of soil according to the initial value of the saturated water content and the corrected value of the saturated water content of each layer of soil; The calculation formula is as follows: Sm n f=Sm n 1'-0.2(Sm n -Sm n 0); Among them, Sm n f represents the field water holding capacity of the nth layer of soil; K n 0=1930(Sm n 0-Sm n 2') (3-BL) ; Among them, K n 0 represents the saturated hydraulic conductivity of the nth layer of soil, BL represents the slope of the logarithm of soil water tension; S26. calculating the wilting point of each layer of soil according to the soil data; The calculation formula is as follows: ； Among them, θ r represents the wilting point and Ø represents the soil porosity.

4. The method for predicting waterlogging drainage and calculating crop yield reduction based on crop model according to claim 3, characterized in that: In S21, the soil is divided into n layers according to depth, where n is 8; and the soil is divided into 8 layers according to depth includes: L1=4.5cm, L2=9.1cm, L3=16.6cm, L4=28.9cm, L5=49.3cm, L6=82.9cm, L7=138.3cm, and L8=229.6cm.

5. The method for predicting waterlogging drainage and calculating crop yield reduction based on crop model according to claim 3, characterized in that: In S3, calculating the number of days for farmland drainage based on water and soil characteristic data includes: S31. Calculate the amount of water retained in farmland based on precipitation and runoff; S32, calculating the time required for saturated water absorption of each layer of soil according to the saturated water content correction value and saturated hydraulic conductivity of each layer of soil; The calculation formula is as follows: T n =(Sm n 0-S n 0)×L n / min(D1,…,D n ); Among them, T n It represents the time required for the nth layer of soil to absorb water to saturation, S n 0 represents the current moisture content of the nth layer of soil, L n represents the thickness of the nth layer of soil, D1 represents the saturated hydraulic conductivity of the first layer of soil, and D n represents the saturated hydraulic conductivity of the nth layer of soil; S33, calculating the water retention layer according to the saturated hydraulic conductivity of each layer of soil; When D n >D n+1 , then D n The corresponding nth layer of soil is recorded as the water retention layer; S34, calculating the number of days for drainage of each retention layer; The calculation formula is as follows: P n =(T1+…+T n )+{(C-Sm10-…-Sm n 0) / [min(D1,…,D n )+E×(1-lai)+ET]}; Among them, P n represents the number of days of drainage of the nth retention layer, C represents the amount of water retained in the farmland, E represents the evaporation rate of the water surface, lai represents the leaf area index and lai<1, and ET represents the canopy evaporation rate; S35. Calculate the drainage days for farmland based on the drainage days for each retention layer.

6. The method for predicting waterlogging drainage and calculating crop yield reduction based on crop model according to claim 1, characterized in that: In S4, calculating the crop root mortality rate according to the number of days of farmland drainage includes: S41, determining a crop flood resistance index; wherein the flood resistance index i ranges from 1 to 9, 1 being the crop not tolerant to floods, and 9 being the crop tolerant to floods; S42. Calculate the root mortality of crops based on the number of days of farmland drainage; The calculation formula is as follows: ； Where RD represents the crop root mortality rate, t represents the tth day after the disaster, and m represents the total number of days after the disaster.

7. The method for predicting waterlogging drainage and calculating crop yield reduction based on crop model according to claim 1, characterized in that: In S5, the percentage of crop yield reduction is obtained based on meteorological data, farming data, water and soil characteristic data and crop root mortality rate, including: S51, inputting meteorological data, farming data, water and soil characteristic data and crop root mortality rate into the wofost model to obtain the actual crop yield; S52, setting the crop root mortality rate to 0, and then inputting the meteorological data, farming data, water and soil characteristic data and the crop root mortality rate into the wofost model to obtain the crop comparative yield; S53. Calculate the crop yield reduction percentage based on the actual crop yield and the comparative crop yield.

8. A system for waterlogging prediction and crop yield reduction calculation based on a crop model, used to implement a method for waterlogging prediction and crop yield reduction calculation based on a crop model as described in any one of claims 1 to 7, characterized in that: The system includes the following modules: Data acquisition module, used to obtain meteorological data, agricultural data and soil data; A water and soil characteristic calculation module, connected to the data acquisition module, for calculating water and soil characteristic data according to soil data; wherein the water and soil characteristic data include saturated water content, wilting point, field holding capacity and saturated hydraulic conductivity; A drainage days calculation module, connected to the water and soil characteristics calculation module, is used to calculate the farmland drainage days according to the water and soil characteristics data; A mortality rate calculation module, connected to the drainage days calculation module, for calculating the crop root mortality rate according to the farmland drainage days; The output module is connected to the data acquisition module, the water and soil characteristic calculation module and the mortality calculation module, and is used to obtain the crop yield reduction percentage based on meteorological data, farming data, water and soil characteristic data and crop root mortality rate.

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