A refined forecast method and system for winter wheat agricultural weather suitability

Abstract

The present invention relates to the technical field of agricultural weather forecasting, and in particular to a refined winter wheat agricultural weather suitability forecasting method and system, including: obtaining basic data, predicted meteorological data and soil moisture data of winter wheat in the annual growth period; calculating the initial accumulated temperature index of each growth period based on the basic data of winter wheat in the annual growth period, and predicting the next growth period in combination with the initial accumulated temperature index and the daily average temperature; constructing a growth and development suitability forecasting model in the current growth period; constructing a key agricultural activity suitability forecasting model; obtaining the predicted growth and development suitability and judging the growth and development suitability level, obtaining the predicted sowing and harvesting suitability and judging the sowing and harvesting suitability level; obtaining the defense measures for improving agricultural activities for winter wheat based on the growth and development suitability level, and obtaining the sowing and harvesting activities based on the sowing and harvesting suitability level. The ability to cope with meteorological changes is enhanced, and the precision and automation level of agricultural meteorological services are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of agricultural weather forecasting, and in particular to a refined method and system for forecasting agricultural weather suitability of winter wheat. Background Art

[0002] Winter wheat has a long growth cycle, which is divided into six growth stages, including sowing and germination, tillering, overwintering, greening, jointing - tasseling, milky maturity - maturity. Winter wheat has different specific requirements for meteorological conditions at different growth stages.

[0003] During the growing stage of winter wheat, meteorological disasters such as late spring cold, low temperature damage, drought, and dry hot winds seriously affect the yield of winter wheat. In order to ensure the yield of winter wheat, producers often obtain meteorological information through weather forecasts to take targeted measures to reduce the impact of meteorological disasters.

[0004] Traditional weather forecasts mainly focus on conventional meteorological elements and weather phenomena, and rarely provide targeted information on the growth characteristics of crops such as winter wheat and the special requirements for meteorological conditions at different growth stages, resulting in producers being unable to take targeted measures in a timely and accurate manner. Summary of the invention

[0005] In view of the above-mentioned deficiencies in the prior art, the present invention provides a refined winter wheat agricultural weather suitability forecasting method and system to solve the above-mentioned technical problems.

[0006] In a first aspect, an embodiment of the present application provides a refined method for forecasting winter wheat agricultural weather suitability, comprising:

[0007] S1, obtain basic data of winter wheat growth period, forecast meteorological data and soil moisture data, including data related to farming activities;

[0008] S2, based on the basic data of winter wheat growth period, calculate the initial accumulated temperature index of each growth period, and predict the next growth period based on the starting date of the growth period of the year combined with the initial accumulated temperature index and the daily average temperature;

[0009] S3, based on the meteorological data and soil moisture data of winter wheat during its normal growth period, a growth and development suitability prediction model is constructed;

[0010] A forecast model for suitability of key agricultural activities was constructed based on basic data of winter wheat's annual growth period and meteorological data;

[0011] S4, obtaining predicted growth and development suitability based on the predicted current development period combined with the growth and development suitability prediction model, and judging the growth and development suitability level based on the first judgment rule, obtaining predicted sowing and harvesting suitability based on the key farming activity suitability prediction model, and judging the sowing and harvesting suitability level based on the second judgment rule;

[0012] S5, determining defense measures based on the growth and development suitability level and the sowing and harvesting suitability level, and pushing the defense measures.

[0013] As an embodiment of the present invention, in step S3, the temperature suitability index and the light temperature suitability index are calculated based on the meteorological data of the perennial growth period of winter wheat, the soil moisture suitability index is calculated based on the soil moisture data, and the growth and development suitability forecast model is constructed based on the temperature suitability index, the light temperature suitability index and the soil moisture suitability index combined with the disastrous weather index, which is specifically constructed as follows:

[0014]

[0015] in, is the growth and development suitability, a, b, c are weight coefficients, is the temperature suitability index, is the soil moisture suitability index, is the light suitability index, is the severe weather index;

[0016] When severe weather occurs, The value is 0, when no disastrous weather occurs. The value is 1.

[0017] As an embodiment of the present invention, the temperature suitability index is specifically calculated as:

[0018]

[0019] in, is the average temperature on the forecast day, is the lower temperature required for the growth stage, is the upper limit temperature required for the growth stage, The optimum temperature for the growth stage. is the temperature coefficient, which is calculated by the following formula:

[0020]

[0021] As an embodiment of the present invention, the soil moisture suitability index is specifically calculated as:

[0022]

[0023] in, The upper limit of soil relative humidity is The lower limit of soil relative humidity is: is the predicted value of soil relative humidity on the forecast day;

[0024] The predicted soil relative humidity on the forecast day is calculated by combining the soil moisture storage of the previous day, the precipitation on the forecast day and the water requirement of winter wheat. The specific calculation is:

[0025]

[0026] in, is the predicted precipitation value on the forecast day, is the soil moisture content of the i-th layer one day before the forecast date, is the soil bulk density of the i-th layer, is the thickness of the i-th soil layer, To forecast daily winter wheat water requirement, is the field water holding capacity of the i-th layer of soil, is the total number of soil layers involved in the calculation.

[0027] As an embodiment of the present invention, the light suitability index is specifically calculated as:

[0028]

[0029] in, is the sunshine hours required to reach the appropriate state at different development stages, and S is the sunshine hours on the forecast day.

[0030] As an embodiment of the present invention, in step S4, obtaining the predicted growth and development suitability based on the predicted current development period combined with the growth and development suitability prediction model, and judging the growth and development suitability level based on the first judgment rule specifically includes:

[0031] Determining a weight coefficient based on the predicted current developmental stage;

[0032] Calculate the growth and development fitness at the same site in the same period in consecutive years;

[0033] The first judgment rule includes winter wheat growth suitability evaluation indexes F1 and F2, which are calculated as:

[0034]

[0035]

[0036] in, is the maximum value, is the average value, is the minimum value;

[0037] When the growth and development suitability is greater than or equal to F1, it is judged to be suitable; when the growth and development suitability is less than or equal to F2, it is judged to be unsuitable; when it is greater than F2 and less than F1, it is judged to be relatively suitable.

[0038] As an embodiment of the present invention, the specific construction process of the key farming activity suitability prediction model includes:

[0039] Determine the sowing suitability judgment index and harvest suitability judgment index;

[0040] Set different threshold ranges for the discrimination indicators under different farming activities;

[0041] Each discrimination index is scored based on meteorological data. When it is below the minimum value of the threshold range, it is scored as 2; when it is above the maximum value of the threshold range, it is scored as 0; and when it is within the threshold range, it is scored as 1;

[0042] According to the sowing and harvesting suitability judgment indicators, each judgment indicator is scored according to the degree to which future weather conditions are met. If it is met, it is scored as 2, if it is not met, it is scored as 0, and otherwise, it is scored as 1.

[0043] As an embodiment of the present invention, in step S4, obtaining predicted suitability of sowing and harvesting based on the key farming activity suitability forecasting model, and judging the suitability level of sowing and harvesting based on the second judgment rule specifically include:

[0044] Obtain the scores of various identification indicators of agricultural activities;

[0045] Calculate the product of the scores of each discriminant index:

[0046]

[0047] Among them, A is the product of the scores of each discrimination index, For the The score of the discrimination index is n, and n is the total number of differential conditions for a certain agricultural activity.

[0048] like If is 0, the suitability of the agricultural activity is judged to be unsuitable. If it is not 0, the suitability of the agricultural activity is further determined according to the following formula:

[0049]

[0050] Where B is the total value of the scores of each discrimination index, For the The score of the discrimination index, n is the total number of differential conditions of a certain agricultural activity;

[0051] like If the value of is twice the total number of difference conditions of a certain agricultural activity, the suitability of the agricultural activity is judged to be suitable, otherwise the suitability of the agricultural activity is judged to be relatively suitable.

[0052] As an embodiment of the present invention, step S2 specifically includes:

[0053]

[0054] Among them, D is the accumulated temperature index on the forecast day, is the initial accumulated temperature index of the development day of the year, t is the average temperature of the forecast day, In order to complete the effective accumulated temperature required for this development stage, is the biological lower temperature limit for this development stage;

[0055] Based on the accumulated temperature index on the forecast day and the initial accumulated temperature index of the next growth period, it is determined whether the forecast day will enter the next growth period;

[0056] After calculating and judging multiple forecast days, the predicted next development period is obtained.

[0057] In a second aspect, the present application also provides a refined winter wheat agricultural weather suitability forecasting system, comprising:

[0058] Data collection module, which obtains basic data of winter wheat growth period, forecast meteorological data and soil moisture data. Basic data include data related to farming activities;

[0059] The growth period prediction module calculates the initial accumulated temperature index of each growth period based on the basic data of winter wheat growth period throughout the year, and predicts the next growth period based on the start date of the growth period of the year combined with the initial accumulated temperature index and the daily average temperature;

[0060] The module for constructing a fitness forecast model is used to build a fitness forecast model for growth and development during the winter wheat growth period based on the meteorological data and soil moisture data during the winter wheat growth period. The module also builds a fitness forecast model for key farming activities based on the basic data and meteorological data during the winter wheat growth period.

[0061] A suitability level judgment module, which obtains predicted growth and development suitability based on the predicted current development period combined with a growth and development suitability prediction model, and judges the growth and development suitability level based on a first judgment rule, obtains predicted sowing and harvesting suitability based on a key farming activity suitability prediction model, and judges the sowing and harvesting suitability level based on a second judgment rule;

[0062] The defense measures push module determines the defense measures based on the growth and development suitability level and the sowing and harvesting suitability level, and pushes the defense measures.

[0063] It can be seen from the above technical solutions that the present invention has the following advantages:

[0064] The present application provides a refined winter wheat agricultural weather suitability forecast method and system, which obtains multi-faceted data, can accurately calculate the accumulated temperature index and accurately predict the development period, and provide an accurate time reference for the arrangement of agricultural activities; the constructed growth and development and key agricultural activity suitability forecast model can scientifically evaluate the impact of meteorological conditions on winter wheat growth and agricultural activities in combination with actual data, and can clarify the suitability level based on judgment rules, helping farmers to know in advance the pros and cons of meteorological conditions on winter wheat growth and agricultural operations, so as to take timely measures to improve agricultural activity defense (such as reasonable irrigation, fertilization, etc.) to optimize the growth environment, and at the same time can reasonably arrange sowing and harvesting activities according to the sowing and harvesting suitability level, thereby improving the yield and quality of winter wheat, enhancing the ability of agricultural production to respond to meteorological changes, and improving the precision and automation level of agricultural meteorological services, to ensure the stable and efficient progress of agricultural production. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] In order to more clearly illustrate the technical solution of the present invention, the drawings required for use in the description will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0066] Figure 1 The present invention is a schematic flow chart of a refined method for forecasting winter wheat agricultural weather suitability according to an embodiment of the present invention.

[0067] Figure 2 This is a comparison chart between the actual value and the predicted value of soil relative humidity according to an embodiment of the present invention.

[0068] Figure 3 This is a comparison chart between the actual value and the predicted value of sunshine hours according to an embodiment of the present invention.

[0069] Figure 4 The suitability grade and relative meteorological yield of a representative site during the entire growth period of an embodiment of the present invention.

[0070] Figure 5 The present invention is a schematic block diagram of a refined winter wheat agricultural weather suitability forecasting method system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0071] In the detailed description below, various embodiments of the present disclosure will be described more fully. The present disclosure may have various embodiments, and adjustments and changes may be made therein. However, it should be understood that there is no intention to limit the various embodiments of the present disclosure to the specific embodiments disclosed herein, but rather the present disclosure should be understood to cover all adjustments, equivalents and / or alternatives that fall within the spirit and scope of the various embodiments of the present disclosure.

[0072] 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 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 are within the scope of protection of the present invention.

[0073] See also Figure 1 The figure is a flow chart of a method for fine-tuning winter wheat agricultural weather suitability forecasting in a specific embodiment, the method comprising:

[0074] S1, obtain basic data of winter wheat growth period, forecast meteorological data and soil moisture data, including data related to farming activities;

[0075] Data related to agricultural activities can help us gain a deeper understanding of the historical laws and actual needs of different agricultural operations. Forecasting meteorological data can predict future weather trends in advance, and soil moisture data can directly reflect soil moisture conditions. The combination of these data lays a solid foundation for building an accurate forecast model, enabling the entire agricultural weather forecast method to comprehensively consider the impact of various factors on winter wheat growth from multiple dimensions, improve the accuracy and reliability of the forecast, and provide strong data support for the scientific and reasonable arrangement of agricultural activities.

[0076] S2, based on the basic data of winter wheat growth period, calculate the initial accumulated temperature index of each growth period, and predict the next growth period based on the starting date of the growth period of the year combined with the initial accumulated temperature index and the daily average temperature;

[0077] Accurate calculation of the accumulated temperature index can effectively predict the transition time of winter wheat at different development stages, so that farmers can make corresponding agricultural preparations in advance, such as fertilizing, irrigation, and pest control at the right time. This precise prediction helps to arrange agricultural production activities reasonably and avoid improper agricultural operations caused by misjudgment of the development stage, thereby ensuring that winter wheat can be in a more suitable environmental condition at each growth stage, improving growth efficiency and final yield, and also helping to optimize agricultural resource allocation and improve the economic benefits of agricultural production.

[0078] S3, based on the meteorological data and soil moisture data of winter wheat during its normal growth period, a growth and development suitability prediction model is constructed;

[0079] A forecast model for suitability of key agricultural activities was constructed based on basic data of winter wheat's annual growth period and meteorological data;

[0080] The growth and development suitability forecast model can comprehensively consider the impact of meteorological factors such as temperature, soil moisture, light, and soil moisture conditions on the growth and development of winter wheat, accurately assess the growth suitability of winter wheat under different meteorological conditions, and help farmers promptly identify adverse meteorological factors that may affect growth and take corresponding measures. The key agricultural activity suitability forecast model focuses on the relationship between agricultural activities and meteorological conditions, and provides a clear basis for judging meteorological suitability for key agricultural activities such as sowing and harvesting, so that farmers can choose the best time for agricultural operations based on the model prediction results, improve the efficiency of agricultural activities, reduce losses caused by unsuitable meteorological conditions, and ensure the smooth progress of agricultural activities, which is of great significance to improving the yield and quality of winter wheat.

[0081] S4, obtaining predicted growth and development suitability based on the predicted current development period combined with the growth and development suitability prediction model, and judging the growth and development suitability level based on the first judgment rule, obtaining predicted sowing and harvesting suitability based on the key farming activity suitability prediction model, and judging the sowing and harvesting suitability level based on the second judgment rule;

[0082] Through clear grade judgment, farmers can quickly and accurately grasp the impact of meteorological conditions on the growth and development of winter wheat, as well as the pros and cons of agricultural activities such as sowing and harvesting. The judgment of the suitability grade of growth and development helps to timely discover potential growth problems and possible agricultural meteorological disasters, so as to take targeted improvement measures, such as adjusting irrigation volume, spraying foliar fertilizer, etc., to promote the healthy growth of winter wheat. The judgment of the suitability grade of sowing and harvesting can guide farmers to reasonably arrange the sowing and harvesting time, avoid the inability to carry out agricultural machinery work due to precipitation, strong winds and other weather conditions, or the lodging of wheat in the later period due to strong winds, which affects the progress of sowing and harvesting or wheat yield, thereby ensuring the stability and efficiency of winter wheat production.

[0083] S5, determining defense measures based on the growth and development suitability level and the sowing and harvesting suitability level, and pushing the defense measures.

[0084] The defensive measures for improving agricultural activities determined according to the suitability level of growth and development can enable farmers to take precise and effective measures to optimize the growth environment according to the specific meteorological conditions and growth conditions during the growth of winter wheat, such as taking insulation measures when the temperature suitability is low, and carrying out reasonable irrigation or drainage when the soil moisture is not suitable, which will help improve the growth quality and stress resistance of winter wheat. The defensive measures for sowing and harvesting activities determined according to the suitability level of sowing and harvesting can ensure that agricultural activities are carried out under the most suitable meteorological conditions, improve the efficiency of sowing operations, germination rate and survival rate, ensure the yield and quality at harvest, reduce losses caused by meteorological factors, and ultimately achieve an increase in winter wheat yield and maximization of agricultural production benefits, and improve the scientific and refined level of agricultural production.

[0085] In an exemplary embodiment, in step S1, the sources of data are: daily meteorological data such as temperature, precipitation, sunshine, cloud cover, wind speed, etc. from 2014 to 2019 are derived from ground observation data of the automatic weather station of the Meteorological Bureau; data such as 10cm and 20cm soil relative humidity, soil bulk density, field water holding capacity, etc. are derived from observation data of the soil moisture automatic station of the Meteorological Bureau, which are used for the construction, grade determination and verification of the winter wheat agricultural weather forecast model; the sowing and harvesting progress in typical periods are derived from the scheduling information of the agricultural department, which is used for the division and verification of sowing and harvesting suitability grades; the yield data are derived from observations of the winter wheat agricultural meteorological basic station, which are used to verify the suitability grade of meteorological conditions for the growth and development of winter wheat.

[0086] The TianQing data interface is used to automatically read the required element values ​​for building the winter wheat agricultural weather forecast model. For the preliminary monitoring data such as soil relative humidity that have no grid data, the inverse distance interpolation method is used to grid the station data with an accuracy of 1 km*1 km.

[0087] In an exemplary embodiment, according to the requirements of winter wheat for meteorological conditions at different development stages, the 24-hour average temperature, soil relative humidity, sunshine hours and elements involved in major disastrous weather are selected as forecasting factors to construct a growth and development suitability forecasting model:

[0088]

[0089] in, is the growth and development suitability, a, b, c are weight coefficients, is the temperature suitability index, is the soil moisture suitability index, is the light suitability index, is the severe weather index;

[0090] When severe weather occurs, The value is 0, when no disastrous weather occurs. The value is 1.

[0091] In an exemplary embodiment, the temperature suitability index is specifically calculated as:

[0092]

[0093] in, is the average temperature on the forecast day, is the lower temperature required for the growth stage, is the upper limit temperature required for the growth stage, The optimum temperature for the growth stage. is the temperature coefficient, which is calculated by the following formula:

[0094]

[0095] In an exemplary embodiment, the soil moisture suitability index is specifically calculated as:

[0096]

[0097] in, The upper limit of soil relative humidity is The lower limit of soil relative humidity is: is the predicted value of soil relative humidity on the forecast day;

[0098] The predicted soil relative humidity on the forecast day is calculated by combining the soil moisture storage of the previous day, the precipitation on the forecast day and the water requirement of winter wheat. The specific calculation is:

[0099]

[0100] in, is the predicted precipitation value on the forecast day, is the soil moisture content of the i-th layer one day before the forecast date, is the soil bulk density of the i-th layer, is the thickness of the i-th soil layer, To forecast daily winter wheat water requirement, is the field water holding capacity of the i-th layer of soil, is the total number of soil layers involved in the calculation.

[0101] In an exemplary embodiment, the light suitability index is specifically calculated as:

[0102]

[0103] in, is the sunshine hours required to reach the suitable state at different growth stages, S is the sunshine hours of the forecast day;

[0104] Since the grid forecast does not have a forecast of sunshine hours, but only a forecast of cloud cover, there is a literature showing that there is a very significant correlation between cloud cover and sunshine hours. Therefore, the sunshine hours are calculated according to the grid forecast cloud cover data using the following formula:

[0105]

[0106] in: For the available hours, is the cloud cover forecast value.

[0107] In an exemplary embodiment, in step S4, obtaining the predicted growth and development suitability based on the predicted current development period combined with the growth and development suitability prediction model, and judging the growth and development suitability level based on the first judgment rule specifically includes:

[0108] Determining a weight coefficient based on the predicted current developmental stage;

[0109] Calculate the growth and development fitness at the same site in the same period in consecutive years;

[0110] The first judgment rule includes winter wheat growth suitability evaluation indexes F1 and F2, which are calculated as:

[0111]

[0112]

[0113] in, is the maximum value, is the average value, is the minimum value;

[0114] When the growth and development suitability is greater than or equal to F1, it is judged to be suitable; when the growth and development suitability is less than or equal to F2, it is judged to be unsuitable; when it is greater than F2 and less than F1, it is judged to be relatively suitable.

[0115] In an exemplary embodiment, the development of sowing and harvesting agricultural activities is closely related to soil relative humidity, temperature, wind force and other conditions. According to the sowing and harvesting suitability discrimination index, each discrimination index is scored according to the degree of satisfaction of future weather conditions, with a score of 2 when satisfied, 0 when not satisfied, and 1 for the rest.

[0116] In an exemplary embodiment, in step S4, obtaining predicted suitability of sowing and harvesting based on the key farming activity suitability forecasting model, and judging the suitability level of sowing and harvesting based on the second judgment rule specifically include:

[0117] Obtain the scores of various identification indicators of agricultural activities;

[0118] Calculate the product of the scores of each discriminant index:

[0119]

[0120] Among them, A is the product of the scores of each discrimination index, For the The score of the discrimination index is n, and n is the total number of differential conditions for a certain agricultural activity.

[0121] like If is 0, the suitability of the agricultural activity is judged to be unsuitable. If it is not 0, the suitability of the agricultural activity is further determined according to the following formula:

[0122]

[0123] Where B is the total value of the scores of each discrimination index, For the The score of the discrimination index, n is the total number of differential conditions of a certain agricultural activity;

[0124] like If the value of is twice the total number of difference conditions of a certain agricultural activity, the suitability of the agricultural activity is judged to be suitable, otherwise the suitability of the agricultural activity is judged to be relatively suitable.

[0125] In an exemplary embodiment, the winter wheat overwintering period is predicted based on the day when the temperature passes 0°C; the other growth periods are predicted using the accumulated temperature method for future growth periods, that is, the accumulated temperature of each growth period is calculated as the accumulated temperature index for growth period forecast based on the perennial growth period of winter wheat as the basic database, and whether to enter the next growth period is predicted based on the start date of the growth period of the year and the accumulated temperature index. The growth period accumulated temperature forecasting method equation is expressed as:

[0126]

[0127] Among them, D is the accumulated temperature index on the forecast day, is the initial accumulated temperature index of the development day of the year, t is the average temperature of the forecast day, In order to complete the effective accumulated temperature required for this development stage, It is the biological lower limit temperature for this development stage.

[0128] In an exemplary embodiment, the growth of winter wheat is divided into six stages: sowing and germination, tillering, overwintering, greening, jointing-tasseling, milky maturity-maturity. By consulting literature, experimental observation, expert consultation and other methods, the parameters of the fitness function of each factor in the main development stages of winter wheat are determined as shown in the following table:

[0129]

[0130] The temperature, water and light conditions in different growth stages of winter wheat have different effects on its growth and development. Combined with the main growth stages and development observation data of winter wheat, the average temperature, water and light suitability at different development stages are used to correlate with meteorological yield. The ratio of each suitability correlation coefficient to the sum of the correlation coefficients of the three factors is used as the weight coefficient of each factor as shown in the following table:

[0131]

[0132] When forecasting agricultural weather, high-impact weather is the most concerned factor. In order to better predict the impact of extreme weather on winter wheat growth, the comprehensive suitability model is established by fully considering the influence of light, temperature and water conditions, and also taking into account disastrous weather. In order to realize the automatic identification of disastrous weather, the main agricultural meteorological disasters such as frost, dry hot wind, continuous cloudy days and strong wind disasters are selected in combination with standards, literature and disaster investigation data, and their phenomenon identification indicators are determined as shown in the following table:

[0133]

[0134] In an exemplary embodiment, winter wheat sowing and harvesting are important agricultural activities. The suitability of forecasted meteorological conditions for agricultural activities is not only related to the efficiency and cost of agricultural operations, but also has an important impact on crop yields. The development of sowing and harvesting agricultural activities is closely related to soil relative humidity, temperature, wind speed and other conditions. According to the sowing and harvesting suitability level indicators shown in the following table, the suitability level discrimination model is used to predict the suitability level:

[0135]

[0136] Note: T is the average daily temperature in the next 24 hours, in °C; SW 10 is the relative humidity of soil at 10 cm, unit is %; R 24 It is the precipitation in the next 24 hours, in mm.

[0137] In an exemplary embodiment, a specific example of step S5 is:

[0138] If the predicted growth and development suitability level for a certain period of time shows that the temperature suitability is low, for example, during the jointing period of winter wheat, the temperature continues to be low (below the lower limit of the suitable temperature range), based on the judgment results of the growth and development suitability level, the defensive measures that can be taken to improve agricultural activities are: choose sunny and windless daytime for irrigation, and use the large specific heat capacity of water to slowly release heat at night, which plays a certain role in heat preservation.

[0139] On the contrary, if the temperature suitability is high (higher than the upper limit of the suitable temperature range), such as before wintering, if the temperature continues to be high, it will easily cause vigorous growth of seedlings before winter and affect the ability to resist cold. Appropriate suppression measures can be taken to control vigorous growth.

[0140] In addition, if the suitability is 0, it can be judged that disastrous weather will occur. According to the disastrous weather such as frost, frost, dry hot wind, etc., the disaster type can be further determined according to the disaster indicators, and irrigation, foliar fertilizer spraying or growth regulators can be adopted to improve the resistance of winter wheat and prevent disastrous weather.

[0141] If in early June, the harvest suitability level in a certain area is suitable, that is, the relative humidity of the 10cm soil is less than 70%, the precipitation in the next 24 hours is less than 0.1mm, and the wind speed in the next 24 hours is less than 3m / s. At this time, farmers can choose suitable harvesting machinery, such as combine harvesters, to harvest in time to ensure harvest efficiency and quality and reduce harvest losses; after harvesting, they should be dried in time or dried with drying equipment so that the moisture content of wheat reaches the safe storage standard before storage.

[0142] In an exemplary embodiment, the results of the meteorological conditions suitability for growth and development are tested, such as Figure 2 As shown in the figure, the accuracy of the soil moisture prediction value directly affects the accuracy of the moisture suitability model. The actual 20cm soil relative humidity observation data of 115 soil moisture automatic stations in October 2018 were compared with the prediction data. The results showed that the average absolute error between the predicted and actual soil relative humidity values ​​was 2.8, and the relative error was 5.4%. Among them, 73% of the absolute errors were within 3, 87% were within 5, and 93% were within 10; 76% of the relative errors were within 5%, 86% were within 10%, and 90% were within 15%. The soil moisture prediction model can meet business needs.

[0143] To verify the accuracy of the sunshine duration forecast model, Figure 3 As shown in the figure, the actual sunshine duration data of a certain area from October 2018 to June 2019 were selected to test the forecast model. The results show that the average absolute error between the predicted and actual values ​​of sunshine duration is 0.5h, of which 43% are within 1h, 77% are within 2h, and 96% are within 3h. The sunshine duration prediction model can meet business needs.

[0144] A typical disaster in a region was selected to verify the results of the suitability for growth and development. In 2018, winter wheat in the southern, western northwest and most central areas jointly tillered between March 27 and April 2, and in the eastern northwest between April 6 and 8. On April 7, a large-scale cooling process occurred in the region, with temperatures below 0°C in the western, central and southern northwest regions. According to the calculation results of the growth and development suitability model, the meteorological conditions in most parts of the northwest and central regions were not suitable for the growth of winter wheat. An agricultural survey was carried out after the process occurred. Some wheat fields were frozen, and symptoms such as yellowing leaves appeared. The forecast results were consistent with the actual growth of winter wheat.

[0145] From May 15 to 21, 2018, winter wheat in a certain area was in the heading-milky stage. There was less sunshine for more than 3 days in some areas of the southwest and northwest. Insufficient sunlight will delay the time of ear differentiation, which is not conducive to the formation of large ears and the decline of photosynthesis, resulting in an increase in the number of spikelets and florets, affecting the formation of yield; and the relative humidity in some areas is high, accompanied by strong winds, and the risk of lodging of winter wheat is high. According to the calculation of the suitability model, the meteorological conditions in most areas of the region are not suitable for the growth of winter wheat. After the process occurred, an agricultural survey was carried out. Local wheat fields were lodged, and the yield of winter wheat in 2018 was 6089.3kg / ha, which was lower than the average of the previous five years (6099.9kg / ha) and the previous year (6109.7kg / ha). The forecast results are consistent with the actual growth of winter wheat.

[0146] Reference Figure 4 As shown in the figure, 5 representative stations were selected respectively, and the weighted average method was used to obtain the comprehensive suitability of the growth period for the daily winter wheat growth suitability. The relative meteorological yield of winter wheat in 2017 and 2018 at the representative stations was used to verify the suitability level for the entire growth period. The results showed that when the suitability level was suitable, the relative meteorological yield of all samples was above 5%; when the level was relatively suitable, 71% of the samples had a relative meteorological yield between -5% and 5%; when the suitability level was unsuitable, 50% of the relative meteorological yield was below -5%.

[0147] In an exemplary embodiment, a sowing and harvesting suitability model is constructed using actual meteorological elements during the sowing and harvesting of winter wheat in 2019, and the rationality or applicability of the model is tested using actual progress.

[0148] In 2019, winter wheat in one region began to be sown on October 7. Affected by accumulated temperature and other factors, the suitable sowing period in most parts of the northwest and the central and northern regions was October 6, in the south and southwest on October 13, in the southeast on October 11, and in other regions on October 7. From October 8 to 12, 2019, precipitation occurred in many parts of the province, with precipitation in most parts of the south and central regions exceeding 10 mm, which delayed the sowing progress of winter wheat to a certain extent. From October 15 to 18, there was basically no effective precipitation in the province, which was suitable for sowing winter wheat. According to the actual sowing situation, some sub-regions were suitable for sowing later, and some sub-regions had finished sowing on the 18th. In order to exclude the influence of factors such as the suitable sowing period and insufficient unsown area in the later period, the sowing situation in the above five cities was not considered during the verification. In addition, combined with weather conditions, the sowing situation of seven sub-regions from October 10 to 12 and October 14 to 16 was selected to verify the rationality of the sowing suitability level. The sowing suitability level of the representative date was calculated respectively, and the percentage of the average sowing area in the representative day to the actual sowing area of ​​each sub-region was obtained by statistics as the judgment index of the sowing progress. Statistics show that from October 10 to 12, there were 28 days in the sub-region that were not suitable for sowing, accounting for 31% of the total days, 13 days were suitable, accounting for 14%, and 49 days were relatively suitable, accounting for 54%. From October 14 to 16, there were 9 days that were not suitable, accounting for 10% of the total days, and 81 days were relatively suitable, accounting for 90%. At the same time, a comprehensive analysis of the three-day comprehensive sowing suitability conditions was carried out, and the three levels of daily suitable, relatively suitable and suitable were assigned 1, 0.5 and 0 values, and the three-day comprehensive sowing suitability index was calculated. The statistical analysis showed that the comprehensive harvest suitability index from 10 to 12 was 1.25, and the comprehensive suitability index from 14 to 16 was 1.35. The average sowing progress from 10 to 12 was 2.8% lower than the average sowing progress from 14 to 16. The average daily sowing progress corresponding to the comprehensive suitability index was statistically analyzed using 1.5 and 2.5 as the boundary indicators of relatively suitable and suitable grades. When the comprehensive suitability index was not suitable for sowing for three days, the average sowing progress on the sowing day was 4.6%, when it was relatively suitable, it was 5.7%, and when it was suitable, it was 9.7%. The sowing suitability was consistent with the actual sowing situation.

[0149] In summary, the construction of the meteorological condition suitability forecast model for winter wheat growth and development in the present invention fully considers the different contributions of temperature, moisture and sunshine to the growth of winter wheat, and can objectively reflect the degree to which climatic conditions meet the growth and development of crops. At the same time, the introduction of disastrous weather into the suitability model can carry out high-impact weather forecasts, overcome the shortcomings of insensitivity to extreme weather, and give full play to the role of agricultural weather forecasts.

[0150] In order to fully consider the impact of previous moisture conditions on winter wheat growth, the winter wheat growth suitability model introduced soil moisture observation data to take into account the previous soil moisture conditions, so the soil moisture automatic station observation data are required to be high.

[0151] Fuzzy mathematics is used to establish the suitability function of meteorological factors for agricultural activities, and its meteorological indicators are determined, and then a comprehensive meteorological suitability model for sowing and harvesting is established. The test shows that the design of the comprehensive suitability model and its indicator selection are reasonable and can be used for local sowing and harvesting meteorological suitability estimation business.

[0152] The present invention is based on grid forecasting, realizing daily agricultural weather forecast for winter wheat in the next 1-7 days on 1 km×1 km grids. The inverse distance interpolation method is used for gridding of non-gridded data, realizing refined agricultural weather forecast in time and space, greatly improving the accuracy and automation level of agricultural meteorological services. However, due to the error of the interpolation method, and the fact that elements such as soil relative humidity and sunshine hours cannot be directly read through grid forecast products, it is necessary to use readable elements for prediction. Through inspection, the moisture and sunshine forecast models are reasonably constructed, and the results can meet business needs, but it also increases the error of the final suitability forecast to a certain extent.

[0153] After obtaining the suitability level, the corresponding countermeasures and suggestions can be read according to the element assignment to obtain the corresponding defense measures. For example, if the temperature is not suitable and the temperature is higher than the suitability temperature, the countermeasures and suggestions of the average temperature being too high are read; if it is lower than the suitable temperature, the countermeasures and suggestions of the average temperature being too low are read; if the moisture is not suitable and the moisture is greater than the upper critical value, the countermeasures and suggestions of the precipitation being too much are read; if the moisture is less than the lower critical value, the countermeasures and suggestions of the precipitation being too little are read; if the light is not suitable, the countermeasures and suggestions of the light being too unsuitable are read; if a disaster occurs, the countermeasures and suggestions corresponding to the disaster are read. The countermeasures and suggestions are shown in the following table:

[0154]

[0155] This method can realize suitability level forecast and defense measures push based on the location's crop growth suitability level and agricultural activities according to the meteorological conditions of different grid points.

[0156] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0157] like Figure 5As shown, the following is an embodiment of the refined winter wheat agricultural weather suitability forecasting system provided by the embodiments of the present disclosure. The system and the refined winter wheat agricultural weather suitability forecasting method of the above-mentioned embodiments belong to the same inventive concept. For details not described in detail in the embodiments of the refined winter wheat agricultural weather suitability forecasting system, reference can be made to the embodiments of the above-mentioned refined winter wheat agricultural weather suitability forecasting method.

[0158] The system includes:

[0159] Data collection module, which obtains basic data of winter wheat growth period, forecast meteorological data and soil moisture data. Basic data include data related to farming activities;

[0160] The growth period prediction module calculates the initial accumulated temperature index of each growth period based on the basic data of winter wheat growth period throughout the year, and predicts the next growth period based on the start date of the growth period of the year combined with the initial accumulated temperature index and the daily average temperature;

[0161] The module for constructing a fitness forecast model is used to build a fitness forecast model for growth and development during the winter wheat growth period based on the meteorological data and soil moisture data during the winter wheat growth period. The module also builds a fitness forecast model for key farming activities based on the basic data and meteorological data during the winter wheat growth period.

[0162] A suitability level judgment module, which obtains predicted growth and development suitability based on the predicted current development period combined with a growth and development suitability prediction model, and judges the growth and development suitability level based on a first judgment rule, obtains predicted sowing and harvesting suitability based on a key farming activity suitability prediction model, and judges the sowing and harvesting suitability level based on a second judgment rule;

[0163] The defense measures push module determines the defense measures based on the growth and development suitability level and the sowing and harvesting suitability level, and pushes the defense measures.

[0164] The winter wheat agricultural weather forecast system obtains comprehensive data through the data collection module, providing an information foundation for the follow-up; the development period prediction module accurately estimates the growth process, helping agricultural planning and resource optimization; the suitability forecast model construction module provides effective evaluation tools from the two aspects of growth and development and key agricultural activities; the suitability level judgment module provides intuitive level information, which is convenient for farmers to grasp the situation and respond in time; the activity acquisition module realizes docking with agricultural operations and optimizes agricultural activities based on the suitability level. The modules work together to comprehensively improve the accuracy and practicality of agricultural weather forecasts, play a key role in improving winter wheat yield and quality, optimizing agricultural production management, and ensuring food security, and promote agricultural production to move towards scientific and refined directions.

[0165] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A refined method for forecasting winter wheat agricultural weather suitability, characterized in that: include: S1, obtain basic data of winter wheat growth period, forecast meteorological data and soil moisture data, including data related to farming activities; S2, based on the basic data of winter wheat growth period, calculate the initial accumulated temperature index of each growth period, and predict the next growth period based on the starting date of the growth period of the year combined with the initial accumulated temperature index and the daily average temperature; S3, based on the meteorological data and soil moisture data of winter wheat during its normal growth period, a growth and development suitability prediction model is constructed; A forecast model for suitability of key agricultural activities was constructed based on basic data of winter wheat's annual growth period and meteorological data; The temperature suitability index and light temperature suitability index were calculated based on the meteorological data of winter wheat during its normal growth period. The soil moisture suitability index was calculated based on the soil moisture data. A growth and development suitability forecast model was constructed based on the temperature suitability index, light temperature suitability index and soil moisture suitability index combined with the disastrous weather index. The specific construction is as follows: in, is the growth and development suitability, a, b, c are weight coefficients, is the temperature suitability index, is the soil moisture suitability index, is the light suitability index, is the severe weather index; When severe weather occurs, The value is 0, when no disastrous weather occurs. The value is 1; S4, obtaining predicted growth and development suitability based on the predicted current development period combined with the growth and development suitability prediction model, and judging the growth and development suitability level based on the first judgment rule, obtaining predicted sowing and harvesting suitability based on the key farming activity suitability prediction model, and judging the sowing and harvesting suitability level based on the second judgment rule; S5, determining defense measures based on the growth and development suitability level and the sowing and harvesting suitability level, and pushing the defense measures.

2. The refined winter wheat agricultural weather suitability forecasting method according to claim 1 is characterized in that: The temperature suitability index is calculated as follows: in, is the average temperature on the forecast day, is the lower temperature required for the growth stage, is the upper limit temperature required for the growth stage, The optimum temperature for the growth stage. is the temperature coefficient, which is calculated by the following formula: 。 3. The refined winter wheat agricultural weather suitability forecasting method according to claim 1 is characterized in that: The soil moisture suitability index is calculated as follows: in, The upper limit of soil relative humidity is The lower limit of soil relative humidity is is the predicted value of soil relative humidity on the forecast day; The predicted soil relative humidity on the forecast day is calculated by combining the soil moisture storage of the previous day, the precipitation on the forecast day and the water requirement of winter wheat. The specific calculation is: in, is the predicted precipitation value on the forecast day, is the soil moisture content of the i-th layer one day before the forecast date, is the soil bulk density of the i-th layer, is the thickness of the i-th soil layer, To forecast daily winter wheat water requirement, is the field water holding capacity of the i-th layer of soil, is the total number of soil layers involved in the calculation.

4. The refined winter wheat agricultural weather suitability forecasting method according to claim 1, characterized in that: The specific calculation of light suitability index is: in, is the sunshine hours required to reach the appropriate state at different development stages, and S is the sunshine hours on the forecast day.

5. The refined winter wheat agricultural weather suitability forecasting method according to claim 1, characterized in that: In step S4, the predicted growth and development suitability is obtained based on the predicted current development period combined with the growth and development suitability prediction model, and the growth and development suitability level is judged based on the first judgment rule, specifically including: Determining a weight coefficient based on the predicted current developmental stage; Calculate the growth and development fitness at the same site in the same period in consecutive years; The first judgment rule includes winter wheat growth suitability evaluation indexes F1 and F2, which are calculated as: in, is the maximum value, is the average value, is the minimum value; When the growth and development suitability is greater than or equal to F1, it is judged to be suitable; when the growth and development suitability is less than or equal to F2, it is judged to be unsuitable; when it is greater than F2 and less than F1, it is judged to be relatively suitable.

6. The refined winter wheat agricultural weather suitability forecasting method according to claim 1, characterized in that: The specific construction process of the key agricultural activity suitability prediction model includes: Determine the sowing suitability judgment index and harvest suitability judgment index; Set different threshold ranges for the discrimination indicators under different farming activities; Each discrimination index is scored based on meteorological data. When it is below the minimum value of the threshold range, it is scored as 2; when it is above the maximum value of the threshold range, it is scored as 0; and when it is within the threshold range, it is scored as 1; According to the sowing and harvesting suitability judgment indicators, each judgment indicator is scored according to the degree to which future weather conditions are met. If it is met, it is scored as 2, if it is not met, it is scored as 0, and otherwise, it is scored as 1.

7. The refined winter wheat agricultural weather suitability forecasting method according to claim 6 is characterized in that: In step S4, the predicted suitability of sowing and harvesting is obtained based on the key farming activity suitability forecasting model, and the suitability level of sowing and harvesting is judged based on the second judgment rule, which specifically includes: Obtain the scores of various identification indicators of agricultural activities; Calculate the product of the scores of each discriminant index: Among them, A is the product of the scores of each discrimination index, For the The score of the discrimination index, n is the total number of differential conditions of a certain agricultural activity; like If is 0, the suitability of the agricultural activity is judged to be unsuitable. If it is not 0, the suitability of the agricultural activity is further determined according to the following formula: Where B is the total value of the scores of each discrimination index, For the The score of the discrimination index, n is the total number of differential conditions of a certain agricultural activity; like If the value of is twice the total number of difference conditions of a certain agricultural activity, the suitability of the agricultural activity is judged to be suitable, otherwise the suitability of the agricultural activity is judged to be relatively suitable.

8. The refined winter wheat agricultural weather suitability forecasting method according to claim 7 is characterized in that: Step S2 specifically includes: Among them, D is the accumulated temperature index on the forecast day, is the initial accumulated temperature index of the development day of the year, t is the average temperature of the forecast day, In order to complete the effective accumulated temperature required for this development stage, is the biological lower temperature limit for this development stage; Based on the accumulated temperature index on the forecast day and the initial accumulated temperature index of the next growth period, it is determined whether the forecast day will enter the next growth period; After calculating and judging multiple forecast days, the predicted next development period is obtained.

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