Winter wheat rotten field rain disaster identification method based on intensity-area-duration

Abstract

The invention discloses a winter wheat rotten field rain disaster identification method based on intensity-area-duration time, and the method comprises the steps: collecting historical and forecast meteorological data of a target region, and rapidly identifying a station scale rotten field rain event; then, on the regional scale, the number of regional rotten field rain stations, the number of continuous days, the average cumulative precipitation and the average sunshine duration are extracted for representation, normalization processing is conducted on the four indexes corresponding to historical regional rotten field rain events, and finally a rotten field rain event comprehensive strength evaluation model is constructed by means of the normalized indexes. And obtaining the comprehensive intensity of the regional rotten rain event in the target region, and obtaining an evaluation result of the comprehensive intensity of the historical and forecast regional rotten rain event. According to the method, the principle of rotten field rain identification is improved, indexes for evaluating rotten field rain events are perfected, occurrence and comprehensive strength of winter wheat rotten field rain disasters can be rapidly identified, and meteorological service effectiveness in the critical period of winter wheat harvesting is improved.

Description

Technical Field

[0001] The invention relates to the technical field of agricultural meteorology, and in particular to a method for identifying winter wheat rot rain disasters based on intensity-area-duration. Background Art

[0002] Winter wheat rot rain disaster refers to continuous rainy weather during the wheat harvest, which farmers call "rot rain". This weather condition will cause wheat to fall over and be flooded, mildew and sprout, thus affecting the yield and quality of wheat. If only 1 mm of rain falls every day for 5 consecutive days, the wheat will sprout in the field. Even if the harvested wheat is not threshed in time, it will sprout in the warehouse. This weather condition has brought great trouble to the summer harvest.

[0003] In order to deal with this situation, farmers rushed to harvest wheat and dry it in the sun, including timely draining water from the fields, scientifically dispatching machinery to harvest, drying and drying wheat, and handling germinated and moldy wheat. Therefore, the meteorological department needs to effectively and timely identify rotten field rain events, issue rotten field rain disaster risk warnings in a timely manner, and guide various places to actively carry out "one spray and three preventions" and micro-sprinkler irrigation.

[0004] To screen for bad rain events, many studies have adopted the following traditional methods:

[0005] (1) The precipitation period is concentrated from late May to mid-June;

[0006] (2) Single-day precipitation is greater than or equal to 0.1 mm;

[0007] (3) The duration is greater than or equal to 3 days, and the cumulative precipitation during the process is greater than or equal to 40 mm.

[0008] On the basis of this study, attempts were made to improve the event identification method from the aspects of winter wheat growth period, meteorological influencing factors and thresholds. First, based on the winter wheat phenology dataset and taking into account the growth and development characteristics of wheat, the maturity period of winter wheat is 5.21-6.10, which is the main time period for rotten rain. In view of the differences in wheat maturity in different years, the period of rotten rain is considered to be extended to 5.15-6.15. Secondly, the threshold of 40mm cumulative precipitation in the process is too high. Based on the historical records of rotten rain events, the cumulative precipitation in some areas did not reach 40mm, but the wheat in the area still showed the phenomenon of wheat germination and mildew. Therefore, the threshold of cumulative precipitation was optimized and adjusted. In addition, there are deficiencies in the extraction of feature quantities of regional rotten rain events in previous studies.

[0009] In response to the above problems, it is necessary to develop a method to quickly identify winter wheat rot rain disasters. Through the coordination and linkage of the agricultural and meteorological departments, the government and farmers can take timely response measures to ensure that the yield and quality of wheat are not seriously affected by rot rain. Summary of the invention

[0010] The problem to be solved by the present invention is to provide a method for identifying winter wheat rot rain disasters based on intensity-area-duration, which is used to solve the problems of inaccurate identification of wheat maturity period, overly high requirements for meteorological indicators, and imperfect indicators for evaluating rot rain events in existing rot rain identification methods.

[0011] To solve the above problems, the present invention adopts the following technical solutions:

[0012] In a first aspect, the present invention provides a method for identifying winter wheat rot rain disaster based on intensity-area-duration, comprising the following steps:

[0013] S1. Collect historical and forecast meteorological data of the target area, including precipitation, sunshine duration, and number of meteorological stations in the target area;

[0014] S2. Based on the collected target area data, the site-scale rotten field rain event method is used to quickly identify the rotten field rain event;

[0015] S3. On a regional scale, quickly identify regional rain events, extract and characterize regional rain events in the target area, and normalize them with the indicators corresponding to historical regional rain events;

[0016] S4. Construct an intensity-area-duration comprehensive intensity assessment model for rainstorm events to obtain the comprehensive intensity of regional rainstorm events in the target area;

[0017] S5. Compare the comprehensive intensity of regional rain events in the target area with the comprehensive intensity of historical regional rain events to obtain the comprehensive intensity assessment result of regional rain events.

[0018] Preferably, in step S2, based on the historical and forecast meteorological data of the target area, the site-scale rain event identification method is as follows:

[0019] S2.1. Determine the concentrated time of precipitation in the target area;

[0020] S2.2. The site-scale rain event includes meteorological elements: precipitation p, sunshine hours s, duration d, site-scale rain event E sta is a function of three meteorological elements, expressed as follows:

[0021] E sta =f(p,s,d)#(1)

[0022] S2.3, when the duration is d = 3 days, the judgment condition of the rain event is:

[0023]

[0024] Among them, i represents a day during the rainy season, p i is the precipitation on the i-th day.

[0025] S2.4, when the duration d>3 days, cloudy and rainy with little sunshine will also cause bad rain, and sunshine will be included in the judgment conditions:

[0026]

[0027] Among them, k is a day without rain, h k is the sunshine hours on the kth day, p i is the precipitation on the i-th day.

[0028] Specifically, in step S2.1, the precipitation period in the target area is concentrated from May 15 to June 15 every year;

[0029] Specifically, in step S3, the regional scale rain event is a rain event in the target area, where the number of rain events affecting sites exceeds a preset threshold value in the same time period, and is recorded as a regional rain event E in the target area. reg , the method is as follows:

[0030]

[0031] Where N is the total number of meteorological stations in the main winter wheat production areas, n affect (t) represents the total number of meteorological stations where rainstorms occur in time period t, T is the time set of the period when rainstorms occur, and the preset threshold is 8%.

[0032] Preferably, in step S3, the regional rain event index includes four meteorological elements: the number of sites S, the duration of days D, the average cumulative precipitation P and the average sunshine hours H, and the four indexes of the regional rain event are extracted.

[0033] Specifically, in step S3, the extracted target area rain event index is normalized with the four indicators of historical rain events to obtain the normalized station number Norm S , Normalized duration Norm D , Normalized precipitation Norm P , Normalized sunshine duration Norm H , the normalization formula is as follows:

[0034]

[0035] Among them, Norm r Extract the normalized value of the index value for the target area rain event r, X r is the extraction index value of the rain event r in the target area, Xmin X is the minimum value of the index value extracted from all the bad rain events in history. max The maximum value of the indicator value extracted from all historical bad rain events.

[0036] Specifically, in step S4, a comprehensive intensity assessment model of intensity-area-duration rainstorm events is constructed;

[0037] The intensity, during the winter wheat maturity period, both sunshine and precipitation affect the quality of wheat. The more precipitation and the shorter the sunshine duration, the more severe the winter wheat is affected. The calculation formula of the intensity index I of the regional field rot rain event is:

[0038] I=Norm P -Norm H #(6)

[0039] In the formula, Norm P 、Norm H are the normalized values ​​of the average cumulative precipitation P and the average sunshine hours H respectively;

[0040] The duration of the regional rainstorm is defined as the first day that meets the regional rainstorm determination conditions as the starting day of the regional rainstorm. After the regional rainstorm starts, the day before the regional rainstorm determination conditions are not met in the target area is defined as the ending day of the regional rainstorm. The number of days from the starting day of the regional rainstorm to the ending day is the duration of the regional rainstorm process. The duration index of the regional rainstorm is expressed by the normalized duration days Norm. D express;

[0041] The area, under the condition of meeting the judgment of regional rainstorm, during the duration of regional rainstorm, shall be the number of stations meeting the regional rainstorm as the impact range of regional rainstorm, and the regional rainstorm area index shall be normalized by the number of stations Norm S express;

[0042] The comprehensive intensity assessment model calculates the comprehensive intensity C of the regional rainstorm event in the target area. S , the method is as follows:

[0043] Cs=Norm S +Norm D +I#(7)

[0044] In the formula, Norm S 、Norm D , I are the area, duration and intensity indicators of regional rainstorms respectively.

[0045] Preferably, in step S5, the obtained comprehensive intensity of regional rotten rain events in the target area is normalized with the comprehensive intensity of historical regional rotten rain events to obtain the comprehensive intensity ranking of regional rotten rain events in the target area in historical regional rotten rain events, the regional rotten rain intensity in the target area is evaluated, and rotten rain disaster warning and response are guided.

[0046] In a second aspect, the present invention provides an electronic device for a method for identifying winter wheat rot rain disasters based on intensity-area-duration, characterized in that it includes: one or more processors; a storage device on which machine-readable instructions executable by the processor are stored; and a bus. When the electronic device is running, the processor communicates with the storage device via the bus, and the processor executes the machine-readable instructions to perform any step of the method for identifying winter wheat rot rain disasters based on intensity-area-duration as described in the first aspect.

[0047] In a third aspect, the present invention further provides a computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method for identifying winter wheat rot rain disasters based on intensity-area-duration as described in any one of the first aspects.

[0048] Compared with the prior art, the present invention adopts the above technical solution and has the following technical effects:

[0049] The present invention is based on the intensity-area-duration method for identifying winter wheat rot rain disasters, improves the existing principle of identifying rot rain events, solves the problems of inaccurate identification of wheat maturity period and excessively high requirements for meteorological indicators in the existing rot rain identification methods, and improves the indicators for evaluating rot rain events. The present invention allows meteorological service personnel to quickly identify winter wheat rot rain disasters and evaluate their intensity based on forecast data such as precipitation and sunshine duration, thereby uniting relevant departments such as agriculture and the government to guide farmers to take countermeasures in a timely manner to ensure that wheat yield and quality are not seriously affected. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 This is a flow chart of a method for identifying rain disasters that may cause winter wheat rot based on intensity-area-duration according to an embodiment of the present invention;

[0051] Figure 2 Flow chart of the site-scale and regional-scale rotten rain event discrimination criteria in an embodiment of the present invention;

[0052] Figure 3 This is a diagram showing the identification result of a regional field rot rain event in a major winter wheat producing area according to an embodiment of the present invention;

[0053] Figure 4A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0054] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the application is further elaborated in detail below in conjunction with the accompanying drawings. The described embodiments are only a part of the embodiments involved in the present invention. All non-innovative embodiments of other researchers in the field on this embodiment belong to the protection scope of the present invention. At the same time, for the step numbering in the embodiment of the present invention, it is only set for the convenience of explanation, and the order between the steps is not limited in any way. The execution order of each step in the embodiment can be adaptively adjusted according to the understanding of those skilled in the art.

[0055] The present invention provides a method for identifying winter wheat rot rain disaster based on intensity-area-duration. Figure 1 As shown, the following steps are included:

[0056] Step 101, collecting historical and forecast meteorological data of the target area, including precipitation, sunshine duration, and number of meteorological stations in the target area;

[0057] Step 102: Based on the collected target area data, quickly identify the rotten field rain event according to the site-scale rotten field rain event method;

[0058] Step 103: quickly identify regional rain events that cause landslides at a regional scale, extract and characterize regional rain events that cause landslides in the target area, and perform normalization processing on the indicators corresponding to historical regional rain events.

[0059] Step 104, constructing an intensity-area-duration comprehensive intensity assessment model for rainstorm events, and obtaining the comprehensive intensity of regional rainstorm events in the target area;

[0060] Step 105: Compare the comprehensive intensity of regional rain events in the target area with the comprehensive intensity of historical regional rain events to obtain a comprehensive intensity assessment result of regional rain events.

[0061] Among them, the criteria for judging the bad rain events at the station scale and regional scale are as follows: Figure 2 shown.

[0062] Step 201, determine that the concentrated precipitation period in the target area is from May 15 to June 15 every year;

[0063] Step 202: The site-scale rain event includes meteorological elements: precipitation p, sunshine hours s, duration d, site-scale rain event E sta is a function of three meteorological elements, expressed as follows:

[0064] Esta =f(p,s,d)#(1)

[0065] Step 203: When the duration d=3 days, the judgment condition of the rainstorm event is:

[0066]

[0067] Among them, i represents a day during the rainy season, p i is the precipitation on the i-th day;

[0068] Step 204: When the duration d>3 days, cloudy and rainy weather with little sunshine will also cause bad rain, and sunshine is included in the judgment conditions:

[0069]

[0070] Among them, k is a day without rain, h k is the sunshine hours on the kth day, p i is the precipitation on the i-th day;

[0071] Step 205: In the same time period, the number of sites affected by the rainstorm event exceeds the preset threshold, which is recorded as a regional rainstorm event E in the target area. reg , the method is as follows:

[0072]

[0073] Where N is the total number of meteorological stations in the main winter wheat production areas, n affect (t) represents the total number of meteorological stations where rainstorms occur in time period t, T is the time set of the period when rainstorms occur, and the preset threshold is 8%.

[0074] In one embodiment of the present invention, based on the meteorological data of China's main winter wheat producing areas from May 15 to June 15, 1961 to 2024, specifically the daily precipitation data and daily sunshine duration data of 589 meteorological stations, the station rotten rain events are quickly identified, and based on the station rotten rain events, regional rotten rain events are identified on a regional scale.

[0075] The results are as follows Figure 3 As shown, there were 36 regional field rot rain events in the main winter wheat producing area. The four sub-graphs represent the number of stations, average cumulative precipitation and average sunshine hours, duration days, and comprehensive intensity.

[0076] Taking 2023 as an example, from May 25 to May 31, 2023, a large-scale continuous rainy weather event occurred in China's main winter wheat producing areas, which highly overlapped with the maturity period of winter wheat, meeting the criteria for the occurrence of rotten rain. Through calculation, the average precipitation of the regional rotten rain event in 2023 was 59.21mm, the average sunshine duration was 4.76h, and the duration was 7 days. The number of meteorological stations involved in the rotten rain was 139, and the affected areas involved provinces such as Hebei, Henan, Shandong, Jiangsu, and Anhui. The area affected by the rotten rain reached 27.9 million mu. Through the results of the regional rotten rain event in 2023, the average cumulative precipitation, average sunshine hours, number of stations, duration and other indicators of the rotten rain event were extracted, and normalized with the historical rotten rain event indicators to obtain normalized indicators, which were input into the comprehensive intensity assessment model of the rotten rain event, and the comprehensive intensity of the rotten rain event in 2023 was obtained to be 0.61. Figure 3 It can be seen that the 2023 rainstorm event was the most serious in the past decade, which is consistent with historical records.

[0077] Since the 1980s, the regional wheat rot rain events in 1983, 1985, 1986, 1987, 1991, 1992, 1998, 2002, 2010, 2013, 2018, 2021 and 2023 screened out by the intensity-area-duration based winter wheat rot rain disaster identification method are consistent with the records of authoritative materials such as "China Meteorological Disaster Encyclopedia", "China Meteorological Disaster Yearbook" and "China Meteorological News", that is, the intensity-area-duration based winter wheat rot rain disaster identification method can accurately identify regional wheat rot rain events in historical records.

[0078] The statistical results show that after the 1980s, the main winter wheat producing areas suffered from high-intensity rotten rain disasters (comprehensive intensity ≥ 0.5) in 7 years, namely 1983, 1984, 1986, 1991, 2000, 2013, and 2023. The records of 1983, 1986, 1991, 2013, and 2023 are consistent with historical records, while there are no relevant records in 1984 and 2000, so they are recorded as empty reports, and no omissions occur, so the TS score is 0.71. Therefore, it can be concluded that the winter wheat rotten rain disaster identification method based on intensity-area-duration has a high accuracy in identifying regional rotten rain disasters with high comprehensive intensity.

[0079] The present application also provides a structure of an electronic device, such as Figure 4As shown, it includes: a processor 401, a storage medium 402 and a bus 403, the storage medium 402 stores machine-readable instructions executable by the processor 401, when the electronic device runs the winter wheat rot rain disaster identification method based on intensity-area-duration as in the embodiment, the processor 401 communicates with the storage medium 402 through the bus 403, the processor 401 executes the machine-readable instructions, the processor 401 method item preamble part to perform the following steps, including: respectively obtaining historical and forecast meteorological data of the target area, including precipitation, sunshine duration, and the number of meteorological stations in the target area, and responding to regional precipitation, sunshine duration, and the number of meteorological stations that meet the rot rain identification criteria.

[0080] An embodiment of the present application also provides a computer-readable storage medium, on which a computer program is stored. The computer program is executed when a processor is running, and the processor performs the following steps, including: obtaining historical and forecast meteorological data of the target area, including precipitation, sunshine duration, and the number of meteorological stations in the target area, and responding to regional precipitation, sunshine duration, and the number of meteorological stations that meet the criteria for distinguishing bad rain.

[0081] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for identifying winter wheat rot rain disaster based on intensity-area-duration, characterized in that: The steps include: S1. Collect historical and forecast meteorological data of the target area, including precipitation, sunshine duration, and number of meteorological stations in the target area; S2. Based on the collected target area data, the site-scale rotten field rain event method is used to quickly identify the rotten field rain event; S3. On a regional scale, quickly identify regional rain events, extract and characterize regional rain events in the target area, and normalize them with the indicators corresponding to historical regional rain events; S4. Construct an intensity-area-duration comprehensive intensity assessment model for rainstorm events to obtain the comprehensive intensity of regional rainstorm events in the target area; S5. Compare the comprehensive intensity of regional rain events in the target area with the comprehensive intensity of historical regional rain events to obtain the comprehensive intensity assessment result of regional rain events.

2. The method for identifying winter wheat rot rain disaster based on intensity-area-duration according to claim 1 is characterized in that: In step S2, based on the historical and forecast meteorological data of the target area, the site-scale rain event identification method is as follows: S2.

1. Determine the concentrated time of precipitation in the target area; S2.

2. The site-scale rain event includes meteorological elements: precipitation p, sunshine hours s, duration d, site-scale rain event E sta is a function of three meteorological elements, expressed as follows: E sta =f(p,s,d)#(1) S2.3, when the duration d = 3 days, the judgment condition of the rain event is: Among them, i represents a day during the rainy season, p i is the precipitation on the i-th day; S2.4, when the duration d>3 days, cloudy and rainy with little sunshine will also cause bad rain, and sunshine will be included in the judgment conditions: Among them, k is a day without rain, h k is the sunshine hours on the kth day, p i is the precipitation on the i-th day.

3. The method for identifying winter wheat rot rain disaster based on intensity-area-duration according to claim 2 is characterized in that: In step S2.1, the precipitation period in the target area is concentrated from May 15 to June 15 every year.

4. The method for identifying winter wheat rot rain disaster based on intensity-area-duration according to claim 2 is characterized in that: In step S3, a regional scale rainstorm event is a rainstorm event in the target area. The rainstorm event affects the site ratio α exceeding the preset threshold in the same time period, which is recorded as a regional rainstorm event E in the target area. reg , the method is as follows: Where N is the total number of meteorological stations in the main winter wheat producing areas, n affect (t) represents the total number of meteorological stations where rainstorms occur in time period t, T is the time set of the period when rainstorms occur, and the preset threshold is 8%.

5. The method for identifying winter wheat rot rain disaster based on intensity-area-duration according to claim 4 is characterized in that: In step S3, the regional rain event index includes four meteorological elements: the number of sites S, the duration of days D, the average cumulative precipitation P and the average sunshine hours H, and the four indexes of the regional rain event are extracted.

6. The method for identifying winter wheat rot rain disaster based on intensity-area-duration according to claim 5 is characterized in that: In step S3, the extracted regional rain event index is normalized with the four indexes of historical regional rain events to obtain the normalized station number Norm S , Normalized duration Norm D , Normalized precipitation Norm P , Normalized sunshine duration Norm H , the normalization formula is as follows: Among them, Norm r Extract the normalized value of the index value for the target area rain event r, X r is the extraction index value of the rain event r in the target area, X min X is the minimum value of the index value extracted from all the bad rain events in history. max The maximum value of the indicator value extracted from all historical bad rain events.

7. The method for identifying winter wheat rot rain disaster based on intensity-area-duration according to claim 6 is characterized in that: In step S4, a comprehensive intensity assessment model of intensity-area-duration rainstorm events is constructed; The intensity, during the winter wheat maturity period, both sunshine and precipitation affect the quality of wheat. The more precipitation and the shorter the sunshine duration, the more severe the winter wheat is affected. The calculation formula of the intensity index I of the regional field rot rain event is: I=Norm P -Norm H #(6) In the formula, Norm P 、Norm H are the normalized values ​​of the average cumulative precipitation P and the average sunshine hours H respectively; The duration of the regional rainstorm is defined as the first day that meets the regional rainstorm determination conditions as the starting day of the regional rainstorm. After the regional rainstorm starts, the day before the regional rainstorm determination conditions are not met in the target area is defined as the ending day of the regional rainstorm. The number of days from the starting day of the regional rainstorm to the ending day is the duration of the regional rainstorm process. The duration index of the regional rainstorm is expressed by the normalized duration days Norm. D express; The area, under the condition of meeting the judgment of regional rainstorm, during the duration of regional rainstorm, shall be the number of stations meeting the regional rainstorm as the impact range of regional rainstorm, and the regional rainstorm area index shall be normalized by the number of stations Norm S express; The comprehensive intensity assessment model calculates the comprehensive intensity Cs of the regional rainstorm event in the target area as follows: Cs=Norm S +Norm D +I#(7) In the formula, Norm S 、Norm D , I are the area, duration and intensity indicators of regional rainstorms respectively.

8. The method for identifying winter wheat rot rain disaster based on intensity-area-duration according to claim 7 is characterized in that: In step S5, the obtained comprehensive intensity of regional rotten rain events in the target area is normalized with the comprehensive intensity of historical regional rotten rain events to obtain the comprehensive intensity ranking of regional rotten rain events in the target area in the historical regional rotten rain events, and the regional rotten rain intensity in the target area is evaluated to guide rotten rain disaster warning and response.

9. An electronic device, characterized in that: include: one or more processors; a storage device having stored thereon machine-readable instructions executable by the processor; bus, When the electronic device is running, the processor communicates with the storage device through a bus, and the processor executes the machine-readable instructions to perform the steps of the intensity-area-duration-based winter wheat rot rain disaster identification method described in any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that: A computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps in the method for identifying winter wheat rot rain disaster based on intensity-area-duration as described in any one of claims 1 to 8 are executed.

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