A method, device and medium for determining a rice drought index equivalent to the number of days of water interruption

Abstract

The application discloses a kind of equivalent water-off days rice drought index determination method, comprising: S1.Calculation daily crop evapotranspiration data;S2.APSIS-Oryza model is constructed, and the model is parameter calibrated and model verified;S3.In the model, the phenophase of crop under full irrigation and no irrigation scenario, yield are simulated dynamically, and long sequence dynamic simulation results are output;S4.Calculation crop specified time period's yield reduction rate;S5.Statistics rice ear differentiation after original water-off days, fitting calculation rice yield and yield reduction rate and the mathematical relationship of original water-off days;S6.Based on the linear mapping of daily evapotranspiration data standardization processing value, obtain drought action coefficient, to calculate the equivalent water-off days of rice drought;S7.Calculation obtains the rice drought index of equivalent water-off days.The application couples crop evapotranspiration and water-off days, proposes equivalent water-off days index, can represent the degree of rice drought.

Description

Technical Field

[0001] The present invention relates to the technical field of rice drought monitoring and drought disaster assessment, and in particular to a method, device and storage medium for determining a rice drought index based on equivalent water shortage days. Background Art

[0002] Agricultural drought is one of the most common natural disasters. Its essence is the phenomenon that insufficient soil moisture supply leads to the stunted growth and development of crops and affects their normal physiological activities. In order to further evaluate and predict the impact of drought on crop production, a large number of scholars have constructed different drought indices to monitor and quantify the intensity of agricultural drought, but most of them are aimed at dryland crops. Rice is my country's main food crop and high-water-consuming crop. Under the same conditions, the impact of drought on rice yield is far greater than that on dryland crops.

[0003] Although a large number of studies have constructed different drought indicators based on temperature, rainfall, and soil moisture data to characterize the relationship between agricultural drought and crop production, rice is a water-loving crop. Its traditional cultivation model is aquifer farming, and soil moisture fluctuates greatly over the long term. Low soil moisture does not necessarily lead to a reduction in yield, but mainly depends on the duration of water shortage and drought. In addition, it is difficult for farmers to grasp the changes in soil moisture or soil water potential, making it difficult to apply.

[0004] To this end, this application specifically proposes a method for determining rice drought indicators based on equivalent water shortage days to solve the above technical problems. Summary of the Invention

[0005] The main purpose of the present invention is to provide a method for determining a rice drought index based on an equivalent number of water-free days, further using the number of water-free days to quantitatively characterize the degree of rice drought (wherein the number of water-free days refers to the number of consecutive days without visible water surface in the field during the rice growing season), coupling crop evapotranspiration with the number of water-free days, and proposing an equivalent number of water-free days index to characterize the degree of rice drought, thereby solving the technical problems raised in the background technology.

[0006] The present invention adopts the following technical solutions to solve the above technical problems:

[0007] A method for determining a rice drought index based on equivalent water shortage days, comprising:

[0008] S1. Collect daily historical meteorological data and calculate daily crop evapotranspiration data during the rice growth stage according to the Penman-Monteith formula;

[0009] S2. Collect historical rice growth test data, construct the APSIM-Oryza model, and use the historical rice growth test data to calibrate and validate the APSIM-Oryza model.

[0010] S3. Input historical meteorological data into the calibrated APSIM-Oryza model to dynamically simulate crop phenology and yield under both fully irrigated and no-irrigation scenarios, and output long-sequence dynamic simulation results.

[0011] S4. Calculate the yield reduction rate of the crop in a specified time period based on the crop yield in the specified time period under the full irrigation and no irrigation scenarios;

[0012] S5. Calculate the original number of days without water after rice panicle differentiation, and calculate the mathematical relationship between rice yield and yield reduction rate and the original number of days without water;

[0013] S6. Based on the daily evapotranspiration data during the rice growth stage, normalize the data and linearly map the normalized values ​​to the drought effect coefficient to construct the equivalent number of days of water shortage for rice drought.

[0014] S7. Calculate the correlation between the yield reduction rate and the original water-outage days and the equivalent water-outage days, respectively, and use the equivalent water-outage days as the rice drought indicator, and analyze its performance in rice drought monitoring and early warning.

[0015] Preferably, the daily historical meteorological data in step S1 include the highest temperature, the lowest temperature, rainfall, sunshine hours, wind speed, and humidity. Since evapotranspiration is a key parameter for characterizing the soil moisture status of the SPAC system and its transfer to the atmosphere, the daily crop evapotranspiration is calculated step by step according to the Penman-Monteith formula. The Penman-Monteith formula comprehensively considers the influence of meteorological factors such as solar radiation, wind speed, and humidity to estimate the daily reference crop evapotranspiration. The calculation formula is:

[0016]

[0017] Where ET0 is the daily crop evapotranspiration data during the rice growth stage, Δ is the slope of the temperature-saturation vapor pressure curve at T; R n is the net radiation, G is the soil heat flux, γ is the latent heat of vaporization, T is the average temperature, u2 is the wind speed, e s and e a are the saturated vapor pressure and the actual vapor pressure, respectively.

[0018] Preferably, in step S2, rice cultivation management data, meteorological data and soil data for three or more seasons are collected, and based on the test data of the first two seasons, the parameters of the APSIM-Oryza model are calibrated using a genetic algorithm or a trial-and-error method, and the model is verified using data from the remaining years.

[0019] Preferably, the cultivation management data include key phenological periods of crops (ear differentiation period, flowering period, maturity period), yield, irrigation time, irrigation depth, fertilization time, fertilization amount and sowing density; the soil data include the wilting coefficient, field water holding capacity, saturated water content, bulk density, pH and organic matter content of stratified soil.

[0020] Preferably, in step S4, the yield reduction rate is calculated based on the yield of rice under sufficient irrigation, and the calculation formula is:

[0021]

[0022] Among them, Y reduce Yield is the rice yield reduction rate, f and Yield r are the simulated yields under full irrigation and no irrigation scenarios, respectively.

[0023] Preferably, in the step S5, the duration of drought caused by rice being without water is taken into account, and the number of water-free days T0 (also referred to as the original water-free days for comparison) after rice panicle differentiation over many years under a no-irrigation scenario is counted, and the correlation coefficient between rice yield and yield reduction rate and the number of water-free days is calculated, and a fitting relationship analysis is performed, wherein the number of water-free days refers to the number of consecutive days when the flooded layer of the paddy field is 0 mm and the water requirement of the rice is provided by the water stored in the soil.

[0024] Preferably, the method for constructing the equivalent number of days of water shortage for rice drought in step S6 comprises:

[0025] S61. Based on the normalization of daily evapotranspiration data during the rice growth stage, the calculation formula is:

[0026]

[0027] Among them, ET scalei is the standardized value of the rice growth stage on day i; ET i is the crop evapotranspiration data of the i-th day of rice growth stage, is the average value of historical data of evapotranspiration during the rice growth stage; σ is the standard deviation of evapotranspiration during the rice growth stage;

[0028] S62. Linearly map the standardized value to the specified interval and calculate the drought effect coefficient α i , drought effect coefficient α i The calculation formula is:

[0029]

[0030] Among them, ET scalei,j is the standardized value of the i-th day of the rice growth stage in year j;

[0031] S63. Through drought effect coefficient α i Calculate the equivalent number of days of water shortage T for rice drought e , the calculation formula is:

[0032] T e =∑α i ×T0

[0033] Among them, α i is the effect coefficient of the i-th day of rice growth stage, and T0 is the original number of days of water shortage when rice is affected by drought.

[0034] Preferably, in the specific operation process of step S7, the Pearson correlation coefficient r and the determination coefficient R of rice yield and yield reduction rate and water shortage days are calculated and compared. 2 , as a rice drought indicator of equivalent water-cutoff days, to characterize the quantification and monitoring performance of equivalent water-cutoff days and original water-cutoff days on rice drought, as well as the accuracy of equivalent water-cutoff days in depicting the degree of rice drought compared with original water-cutoff days.

[0035] In another aspect, the present invention further discloses a computer-readable storage medium storing a computer program, wherein when the computer program is executed by a processor, the processor executes the steps of the above method.

[0036] On the other hand, the present invention further discloses a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the above method.

[0037] As can be seen from the above technical solution, the present invention provides a method for determining rice drought index based on the equivalent number of days of water shortage. Compared with the existing technology, the present invention has the following advantages:

[0038] 1. The present invention uses a crop model to dynamically simulate rice phenology, yield, and paddy field depth over a historical period. It determines the drought effect coefficient based on daily evapotranspiration changes during the rice growing season and calculates the equivalent number of water-cut days. This number of water-cut days can be used to quantitatively characterize the extent of rice drought. By coupling crop evapotranspiration with the number of water-cut days, an equivalent water-cut days index is proposed to characterize the extent of rice drought. A method for constructing and applying the equivalent water-cut days index is presented, providing a theoretical basis and technical support for improving regional drought risk management capabilities and ensuring food production security.

[0039] 2. During periods of water shortage, the present invention quantifies the impact of drought on rice production based on evapotranspiration demand, which can more accurately reflect changes in rice yield. Therefore, by considering the influence of multiple climate factors and using correlation coefficient calculation and relationship fitting, it can more accurately describe and analyze the ability of equivalent water shortage days to characterize the degree of rice drought.

[0040] 3. The calibrated and verified crop model of the present invention can simulate different crop physiological and ecological processes and the dynamic balance of soil moisture and nutrients on a daily scale, realizing the dynamic response of crop production to environmental changes such as soil, climate, and management measures. At the same time, the model can also be applied to simulate different crops at large regional and even global scales, and combined with crop growth models and rice drought indicators, it is conducive to improving the breadth of drought quantification and assessment.

[0041] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present invention, nor is it intended to limit the scope of the present invention. Other features of the present invention will become easy to understand through the following description. Of course, it is not necessary to achieve all of the above-mentioned advantages simultaneously in order to implement any product of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The accompanying drawings, which constitute part of this application, are intended to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are intended to explain the present invention and do not constitute an undue limitation of the present invention. In the accompanying drawings:

[0043] Figure 1 A flow chart of a method for determining equivalent water outage days according to an embodiment of the present invention;

[0044] Figure 2 This is a regression fitting diagram of the crop yield, the original water-cut days, and the equivalent water-cut days according to an embodiment of the present invention;

[0045] Figure 3 Schematic diagram of regression analysis of crop yield reduction rate, original water outage days, and equivalent water outage days according to an embodiment of the present invention. DETAILED DESCRIPTION

[0046] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. In the absence of conflict, the embodiments in this application and the features in the embodiments can be combined with each other. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0047] In the embodiment, see Figures 1 to 3 .

[0048] There are few studies on quantifying the severity of rice drought by the number of water outage days in existing technologies, and the research is still in its infancy. During the rice water outage period, under the same number of water outage days, climate factors also largely determine the severity of crop drought. It is difficult to effectively characterize the severity of rice drought by considering only the number of water outage days.

[0049] Therefore, Figure 1 The method for determining the rice drought index based on the equivalent number of water shortage days proposed in the embodiment of the present invention can construct a characterization index for rice drought analysis by combining crop evapotranspiration, and includes the following steps:

[0050] S1. Collect daily historical meteorological data and calculate daily crop evapotranspiration according to the Penman-Monteith formula. The Penman-Monteith formula comprehensively considers the influence of meteorological factors such as solar radiation, wind speed, and humidity to estimate the reference crop evapotranspiration on a daily scale.

[0051] Specifically, the daily historical meteorological data of the study area include the highest temperature, lowest temperature, rainfall, sunshine hours, wind speed, and humidity. Since evapotranspiration is a key parameter to characterize the soil moisture status of the SPAC system and its transfer to the atmosphere, the daily crop evapotranspiration is calculated step by step according to the Penman-Monteith formula. The calculation formula is:

[0052]

[0053] Where ET0 is the daily crop evapotranspiration data during the rice growth stage, Δ is the slope of the temperature-saturation vapor pressure curve at T; R n is the net radiation, G is the soil heat flux, γ is the latent heat of vaporization, T is the average temperature, u2 is the wind speed, e s and e a are the saturated vapor pressure and the actual vapor pressure, respectively.

[0054] The historical meteorological data include daily maximum temperature, minimum temperature, rainfall, sunshine hours, wind speed, humidity, etc.

[0055] S2. Conduct field experiments for three or more seasons, collect rice crop cultivation management data, meteorological data, and soil data for three or more seasons in the study area, and calibrate the parameters of the APSIM-Oryza model using genetic algorithms or trial-and-error methods based on the experimental data from the first two seasons. Use data from the remaining years to verify the model. At this time, the output variables of the APSIM-Oryza model include the main crop phenological periods (panicle differentiation period, flowering period, and maturity period), crop yield, field water surface depth during the growing season, and stratified soil moisture content.

[0056] Among them, the cultivation management data include key phenological periods of crops (ear differentiation period, flowering period, maturity period), yield, irrigation time, irrigation depth, fertilization time, fertilization amount and sowing density; the soil data include the wilting coefficient, field water holding capacity, saturated water content, bulk density, pH and organic matter content of stratified soil.

[0057] Specifically, during the actual experiment, half of the experimental observation data were used to calibrate the parameters of the crop model, and the observation data of the remaining years were used for model verification, ensuring the accuracy and reliability of the crop model simulation process. The calibrated and verified crop model can dynamically simulate the response of crops in different regions to different environmental changes by setting meteorological conditions, soil characteristics and management measures in different regions, thereby improving the breadth and applicability of the technical method.

[0058] S3. Based on the crop variety parameters calibrated and verified in S2, use them as genetic trait parameters of representative varieties in the region, input multiple years of historical meteorological data, and drive the calibrated APSIM-Oryza model to dynamically simulate key phenological periods and yield changes of rice under no irrigation and full irrigation scenarios.

[0059] At this time, the calibrated and verified crop model can simulate the physiological and ecological processes of different crops and the dynamic balance of soil moisture and nutrients on a daily scale, and realize the dynamic response of crop production to environmental changes such as soil, climate and management measures.

[0060] It can also be further explained that calibrated and verified crop models can be widely used to simulate different crops at regional and even global scales. Therefore, this method, combined with crop growth models and rice drought indicators, is conducive to improving the breadth of drought quantification and assessment.

[0061] S4. Calculate the rice yield reduction rate over many years based on the rice yield under full irrigation.

[0062] The rice yield reduction rate is defined as the ratio of the yield difference between the full irrigation and no irrigation scenarios to the crop yield under the full irrigation scenario, which is:

[0063]

[0064] Among them, Y reduce Yield is the rice yield reduction rate for that year. f and Yield r are the simulated yields under full irrigation and no irrigation scenarios in the same year, respectively;

[0065] S5. Based on the long-series dynamic simulation results output by APSIM-Oryza, and considering the duration of rice drought after water shortage, we calculated the number of water shortage days (T0) after rice panicle differentiation (also referred to as the original water shortage days for comparison) over multiple years under a no-irrigation scenario. We then fitted and calculated the correlation coefficients between rice yield and yield reduction rate and the original water shortage days, and conducted a fitting relationship analysis. The water shortage days refer to the number of days in which the flooded layer of the paddy field reaches 0 mm, and the rice water requirement is met by soil water storage.

[0066] Furthermore, rice planting habits and intermittent irrigation technology are also taken into consideration. Therefore, the number of days without water for rice (original water-cut days) T0 under the no-irrigation scenario over many years is counted, and the mathematical relationship between rice yield and yield reduction rate and the original water-cut days is fitted to quantify the impact of drought on rice production.

[0067] Among them, combined with the many years of experiments at the experimental station, rice drought mainly occurs during the high temperature period from July to August. The water cut-off days in this technical solution are the continuous water cut-off days after the rice panicle differentiation.

[0068] S6. Crop evapotranspiration is a key parameter for characterizing soil moisture status and its transfer to the atmosphere in a SPAC system. It is also an effective indicator for quantifying the severity of crop drought. Considering the water consumption process during rice water shortage, we normalize the daily evapotranspiration during the rice growth stage. Based on the normalized data distribution, we linearly map the normalized values ​​to action coefficients in the interval [0, 2] to quantify the severity of rice drought, thereby constructing the equivalent number of days of water shortage T for rice drought. e .

[0069] Among them, considering that during the water outage period, rice relies on root soil moisture to maintain physiological and ecological activities, evapotranspiration comprehensively considers the influence of multiple meteorological factors and can effectively reflect the degree of rice drought under water shortage conditions. The greater the daily evapotranspiration, the more severe the rice drought. Therefore, based on the daily evapotranspiration and the duration of rice drought, the effect coefficient is determined on the basis of the original water outage days to construct the equivalent water outage days of rice drought. The calculation formula is:

[0070]

[0071]

[0072] T e =∑α i ×T0

[0073] Among them, ET scalei is the standardized value of the rice growth stage on day i; ET i is the crop evapotranspiration data of the i-th day of rice growth stage, is the average value of historical data of evapotranspiration during the rice growth stage; σ is the standard deviation of evapotranspiration during the rice growth stage, ET scalei,j is the standardized value of the i-th day of the rice growth stage in the j-th year, α i is the effect coefficient of the i-th day of rice growth stage, and T0 is the original number of days of water shortage when rice is affected by drought.

[0074] S7. Calculate the Pearson correlation coefficient r and the coefficient of determination R for comparing the production reduction rate with the original water outage days and the equivalent water outage days. 2 , used to characterize the equivalent water outage days T eThe quantification and monitoring performance of rice drought by the original water shortage days T0 and the equivalent water shortage days T e Compared with the original water shortage days T0, the accuracy of describing the degree of rice drought is improved.

[0075] The fitting calculation is as follows:

[0076] The results of fitting analysis of rice yield over many years with original water shortage days and equivalent water shortage days are shown in the table below:

[0077] Statistical indicators Relationship between production and water outage days Relationship between output and equivalent water outage days Correlation coefficient -0.695 -0.779 Coefficient of determination 0.484 0.606 Significance *** *** Linear regression equation y=-140.38*x+9529.43 y=-236.5*x+9677.34

[0078] refer to Figure 2 As shown in the table above, by analyzing the correlation between rice yield and the original water-outage days and the equivalent water-outage days, as well as the determination coefficient of linear fitting, it can be seen that the correlation coefficient between rice yield and the original water-outage days is -0.695. After equivalently quantifying the impact of drought, the correlation coefficient between yield and the equivalent water-outage days is -0.779, and the determination coefficient of the fitting regression of rice yield and water-outage days increases from 0.484 to 0.606. The results show that during the rice water-out period, quantifying the impact of drought on rice production based on evapotranspiration demand can more accurately reflect the changes in rice yield.

[0079] The results of the fitting analysis of the rice yield reduction rate over the years, the original water shortage days and the equivalent water shortage days are shown in the table below:

[0080]

[0081] refer to Figure 3 As shown in the table above, the correlation between rice yield reduction rate and the original and equivalent water shortage days, as well as the determination coefficient of the S-shaped curve fitting, was further analyzed. Compared with the original water shortage days, after the equivalent quantitative drought impact, the correlation coefficient between rice yield reduction rate and water shortage days increased from 0.772 to 0.827, and the determination coefficient of the fitting regression increased from 0.647 to 0.711.

[0082] At this time, based on the comprehensive consideration of crop evapotranspiration changes due to multiple meteorological factors, a drought effect coefficient was introduced to quantify the severity of rice drought. This can facilitate the further construction of the equivalent number of water-out days for rice drought, make it easier for farmers to master and practice, and is conducive to its promotion and application on a large regional scale.

[0083] In summary, since crop evapotranspiration comprehensively considers the influence of climate factors such as temperature, solar radiation, wind speed, and humidity, it is a key parameter to characterize the soil moisture status of the SPAC system and its transfer to the atmosphere. To address the problem that only considering the number of water-outage days is difficult to effectively characterize the severity of rice drought, this method addresses the problem that only considering the number of water-outage days as an indicator is difficult to effectively characterize. Through the crop growth model, it can realize the dynamic simulation of the entire process of rice growth and development, dry matter accumulation and distribution, and yield formation under different phenological conditions, environmental conditions (including paddy field depth), and different irrigation scenarios in historical periods. The drought effect coefficient is determined based on the daily changes in evapotranspiration during the rice growing season, and an equivalent number of water-outage days is constructed. Crop evapotranspiration is coupled with the number of water-outage days to propose an equivalent water-outage day indicator to characterize the severity of rice drought. The construction method and application approach of the equivalent water-outage day indicator are given. Through correlation coefficient calculation and relationship fitting, the characterization ability of the equivalent water-outage day indicator for the severity of rice drought is analyzed. In the specific implementation process, it can be found that considering the influence of multiple climate factors and more accurately describing the response of rice production to drought is of great significance to improving regional risk management capabilities and ensuring food production security. It provides a theoretical basis and technical support for improving regional drought risk management capabilities and ensuring food production security.

[0084] In another aspect, the present invention further discloses a computer-readable storage medium storing a computer program, wherein when the computer program is executed by a processor, the processor executes the steps of the above method.

[0085] On the other hand, the present invention further discloses a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the above method.

[0086] In another embodiment provided by the present application, a computer program product comprising instructions is further provided, which, when executed on a computer, enables the computer to execute any of the methods for determining rice drought indicators based on equivalent water shortage days in the above embodiments.

[0087] It is understandable that the system provided by the embodiment of the present invention corresponds to the method provided by the embodiment of the present invention, and the explanation, examples and beneficial effects of the relevant contents can refer to the corresponding parts of the above method.

[0088] The embodiment of the present application further provides an electronic device, comprising a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other via the communication bus.

[0089] Memory for storing computer programs;

[0090] The processor is configured to implement the above-mentioned method for determining the rice drought index based on the equivalent number of water-cut-off days when executing the program stored in the memory.

[0091] The communication bus mentioned in the above electronic device can be a peripheral component interconnect standard bus or an extended industry standard architecture bus, etc. The communication bus can be divided into an address bus, a data bus, a control bus, etc.

[0092] The communication interface is used for communication between the above electronic device and other devices.

[0093] The memory may include a random access memory, or a non-volatile memory, such as at least one disk memory. Optionally, the memory may also be at least one storage device located away from the aforementioned processor.

[0094] The above-mentioned processor can be a general-purpose processor, including a central processing unit, a network processor, etc.; it can also be a digital signal processor, an application-specific integrated circuit, a field programmable gate array or other programmable logic device, a discrete gate or transistor logic device, or a discrete hardware component.

[0095] It should also be noted that electronic devices also include terminal devices, which can also be called terminals, user equipment, mobile stations, mobile terminals, etc. Terminal devices can be mobile phones, smart TVs, wearable devices, tablet computers, computers with wireless transceiver functions, virtual reality terminal devices, augmented reality terminal devices, wireless terminals in industrial control, wireless terminals in unmanned driving, wireless terminals in remote surgery, wireless terminals in smart grids, wireless terminals in transportation safety, wireless terminals in smart cities, wireless terminals in smart homes, etc. The embodiments of this application do not limit the specific technology and specific device form used by the terminal devices.

[0096] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When software is used for implementation, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website, computer, server or data center to another website, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrations. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium, or a semiconductor medium (e.g., a solid-state hard disk).

[0097] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

[0098] In addition, it should be noted that if the embodiments of the present invention involve directional indications (such as up, down, left, right, front, back, etc.), the directional indications are only used to explain the relative position relationship, movement status, etc. between the components under a certain specific posture. If the specific posture changes, the directional indications will also change accordingly.

[0099] In addition, if there are descriptions involving "first", "second", etc. in the embodiments of the present invention, the descriptions of "first", "second", etc. are only for descriptive purposes and cannot be understood as indicating or suggesting their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of such features. In addition, the meaning of "and / or" appearing throughout the text includes three parallel schemes. Taking "A and / or B" as an example, it includes scheme A, or scheme B, or schemes in which A and B are satisfied at the same time. In addition, in the embodiments of the present invention, "multiple" refers to more than two. In addition, the technical solutions between the various embodiments can be combined with each other, but it must be based on the ability of ordinary technicians in this field to implement. When the combination of technical solutions is mutually contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

Claims

1. A method for determining rice drought index based on equivalent water shortage days, characterized in that: include: S1. Collect historical meteorological data and calculate daily crop evapotranspiration data during the rice growth stage; S2. Construct the APSIM-Oryza model and use historical rice growth test data to calibrate and validate the APSIM-Oryza model. S3. Input historical meteorological data into the calibrated APSIM-Oryza model to dynamically simulate crop phenology and yield under both fully irrigated and no-irrigation scenarios, and output long-sequence dynamic simulation results. S4. Calculate the yield reduction rate of the crop in a specified time period based on the crop yield in the specified time period under the full irrigation and no irrigation scenarios; S5. Calculate the original number of days without water after rice panicle differentiation, and calculate the mathematical relationship between rice yield and yield reduction rate and the original number of days without water; S6. Based on the daily evapotranspiration data during the rice growth stage, normalize the data and linearly map the normalized values ​​to the drought effect coefficient to construct the equivalent number of days of water shortage for rice drought. S7. Calculate the correlation between the yield reduction rate and the original water-cutoff days and the equivalent water-cutoff days, respectively, as the rice drought index of the equivalent water-cutoff days.

2. The method for determining the rice drought index based on the equivalent number of water shortage days according to claim 1, wherein: The calculation formula for daily crop evapotranspiration data in step S1 is: Where ET0 is the daily crop evapotranspiration data during the rice growth stage, Δ is the slope of the temperature-saturation vapor pressure curve at T; R n is the net radiation, G is the soil heat flux, γ is the latent heat of vaporization, T is the average temperature, u2 is the wind speed, e s and e a are the saturated vapor pressure and the actual vapor pressure, respectively.

3. The method for determining the rice drought index of equivalent water shortage days according to claim 1, wherein: The calculation formula for the production reduction rate in step S4 is: Among them, Y reduce Yield is the rice yield reduction rate, f and Yield r are the simulated yields under full irrigation and no irrigation scenarios, respectively.

4. The method for determining rice drought index based on equivalent water shortage days according to claim 1, wherein: The method for constructing the equivalent number of days of water shortage for rice drought in step S6 includes: S61. Based on the normalization of daily evapotranspiration data during the rice growth stage, the calculation formula is: Among them, ET scalei is the standardized value of the rice growth stage on day i; ET i is the crop evapotranspiration data of the i-th day of rice growth stage, is the average value of historical data of evapotranspiration during the rice growth stage; σ is the standard deviation of evapotranspiration during the rice growth stage; S62. Linearly map the standardized value to the specified interval and calculate the drought effect coefficient α i ; S63. Through drought effect coefficient α i Calculate the equivalent number of days of water shortage T for rice drought e , the calculation formula is: T e =∑α i ×T0 Among them, α i is the effect coefficient of the i-th day of rice growth stage, and T0 is the original number of days of water shortage when rice is affected by drought.

5. The method for determining rice drought index based on equivalent water shortage days according to claim 4, wherein: In the step S62, the drought effect coefficient α is linearly mapped to the interval [0, 2] according to the standardized data distribution. i , the drought effect coefficient α i The calculation formula is: Among them, ET scalei,j is the standardized value of the i-th day of the rice growth stage in the j-th year.

6. The method for determining rice drought index based on equivalent water shortage days according to claim 1, wherein: In the specific operation process of step S7, the Pearson correlation coefficient r and the determination coefficient R of rice yield and yield reduction rate and water shortage days are calculated and compared. 2 , as a rice drought index of equivalent water-off days, to characterize the quantification and monitoring performance of equivalent water-off days and original water-off days on rice drought.

7. A computer-readable storage medium, characterized in that A computer program is stored, and when the computer program is executed by a processor, the processor is caused to perform the steps of the method according to any one of claims 1 to 6.

8. A computer device, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the method according to any one of claims 1 to 6.

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