Identification method of winter wheat rot rain disaster based on intensity-area-duration

Abstract

The present invention discloses a winter wheat rot rain disaster identification method based on intensity-area-duration. First, historical and forecast meteorological data for the target area are collected to quickly identify rot rain events at the site scale. Then, at the regional scale, the number of regional rot rain sites, the number of duration days, the average cumulative precipitation, and the average sunshine hours are extracted for characterization. These are then normalized with the four indicators corresponding to historical regional rot rain events. Finally, a comprehensive intensity assessment model for rot rain events is constructed using the normalized index to obtain the comprehensive intensity of regional rot rain events in the target area, and an assessment result of the comprehensive intensity of historical and forecast regional rot rain events is obtained. The present method improves the principle of rot rain identification and improves the indicators for evaluating rot rain events. It can quickly identify the occurrence and comprehensive intensity of winter wheat rot rain disasters, thereby improving the effectiveness of meteorological services during the critical winter wheat harvest period.

Description

Technical Field

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

[0002] Winter wheat rot rain refers to continuous rain during the wheat harvest, which farmers call "rot rain." This weather condition can cause wheat to fall over, become flooded, and cause mildew and sprouting, thus affecting both yield and quality. If even just 1 mm of rain falls daily for five consecutive days, wheat will sprout in the fields. Even harvested wheat can sprout in warehouses if not threshed promptly. This weather condition creates significant challenges for the summer harvest.

[0003] To address this situation, farmers rushed to harvest and dry wheat, including draining water from fields, deploying harvesting machinery, ensuring wheat drying and airing, and handling any germinated or moldy wheat. Therefore, meteorological authorities are required to effectively and promptly identify rotten wheat rain events, issue timely warnings for rotten wheat rain disaster risks, and guide local governments in implementing measures such as "one spray, 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] Based on this research, we attempted to improve the event identification method by considering aspects such as the winter wheat growth period, meteorological factors, and thresholds. First, based on a winter wheat phenology dataset and considering the growth and development characteristics of wheat, the winter wheat maturity period is May 21–June 10, which is the main period for rotten rain. Given the differences in wheat maturity between different years, the rotten rain period was considered to be expanded to May 15–June 15. Second, the threshold of 40 mm of cumulative precipitation was too high. Based on historical records of rotten rain events, some areas did not reach 40 mm of cumulative precipitation, but wheat still experienced sprouting and mildew. Therefore, the threshold of cumulative precipitation was optimized and adjusted. In addition, previous studies have found deficiencies in the extraction of regional rotten rain event characteristics.

[0009] To address the above issues, 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 wheat yield and quality 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 in existing rot rain identification methods of inaccurate identification of wheat maturity period, excessively high requirements for meteorological indicators, and imperfect indicators for evaluating rot rain events.

[0011] In order 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 disasters based on intensity-area-duration, comprising the following steps:

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

[0014] S2. Based on the collected target area data, the bad rain event is quickly identified according to the site-scale bad rain event method;

[0015] S3. Rapidly identify regional rain events at the regional scale, 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 precipitation period in the target area;

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

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

[0022] S2.3. When the duration is d = 3 days, the conditions for judging the rain event are:

[0023]

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

[0025] S2.4. When the duration d is greater than 3 days, cloudy and rainy weather with little sunshine can also cause heavy rain. In this case, sunshine should be included in the judgment criteria:

[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 day i.

[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 which the number of sites affected by the rain event exceeds a preset threshold value within the same time period, and is recorded as a regional rain event E in the target area. reg , as follows:

[0030]

[0031] 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 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 stations S, the duration D, the average cumulative precipitation P and the average sunshine hours H, and the four indicators of the regional rain event are extracted.

[0033] Specifically, in step S3, the extracted target area bad rain event index is normalized with the four indicators of historical bad rain events to obtain the normalized station number Norm S , normalized duration Norm D , Normalized precipitation Norm P , Normalized sunshine hours 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 Extract the minimum value of the index value from all the bad rain events in history, X max The maximum value of the index value is extracted from all historical bad rain events.

[0036] Specifically, in step S4, a comprehensive intensity assessment model of intensity-area-duration rain 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 damage to the winter wheat. 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 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 begins, 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 to the ending day of the regional rainstorm is the duration of the regional rainstorm process. The regional rainstorm duration index is expressed as the normalized duration days Norm. D express;

[0041] The area, under the conditions of regional rainstorm, during the duration of regional rainstorm, the number of stations meeting the conditions of regional rainstorm is regarded as the impact range of regional rainstorm. The regional rainstorm area index is 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 , 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 rainstorm 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, and the regional rotten rain intensity in the target area is evaluated to guide rotten rain disaster warning and response.

[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 and the storage device communicate 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 intensity-area-duration-based winter wheat rot rain disaster identification method as described in any one of the first aspects are executed.

[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 an 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 overly high requirements for meteorological indicators in 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 assess their intensity based on forecast data such as precipitation and sunshine duration, thereby uniting relevant departments such as agriculture and government to guide farmers to take timely response measures 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 winter wheat rot rain disasters based on intensity-area-duration according to an embodiment of the present invention;

[0051] Figure 2 Flowchart 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 results of a regional field-rotting rain event in a major winter wheat producing area according to an embodiment of the present invention;

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

[0054] In order to make the purpose, technical solutions and advantages of the present invention clearer, the technical solutions of the application are further elaborated in detail below with reference to 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 this field on this embodiment fall within the scope of protection of the present invention. At the same time, the step numbers in the embodiments of the present invention are only set for the convenience of explanation and description, 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 is based on the intensity-area-duration winter wheat rot rain disaster identification method, such as Figure 1 As shown, the following steps are included:

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

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

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

[0059] Step 104: construct an intensity-area-duration comprehensive intensity assessment model for the rainstorm event to obtain the comprehensive intensity of the regional rainstorm event in the target area;

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

[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 and is expressed as follows:

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

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

[0066]

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

[0068] Step 204: When the duration d is greater than 3 days, cloudy and rainy weather with little sunshine will also cause heavy rain, and sunshine will be 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 day i;

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

[0072]

[0073] 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 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-level rotten rain events are quickly identified, and based on the station-level 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-rotting 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, respectively.

[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 winter wheat maturity period and met 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 was 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. The normalized indicators 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 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 the "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] Statistical results show that after the 1980s, major winter wheat-producing areas experienced high-intensity rotten rain disasters (comprehensive intensity ≥ 0.5) in seven years: 1983, 1984, 1986, 1991, 2000, 2013, and 2023. The records for 1983, 1986, 1991, 2013, and 2023 are consistent with historical records, while no relevant records were found for 1984 and 2000, so they were recorded as false positives. No omissions occurred, resulting in a TS score of 0.71. Therefore, it can be concluded that the winter wheat rotten rain disaster identification method based on intensity, area, and duration has high accuracy in identifying regional rotten rain disasters of 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, and the processor 401 executes the preamble of the method item 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 judgment 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 by a processor when the 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 determining 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 principles 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 disasters based on intensity-area-duration, characterized in that: The steps include: S1. Collect historical and forecast meteorological data for the target area, including precipitation, sunshine duration, and the number of meteorological stations in the target area; S2. Based on the collected target area data, quickly identify the rotten field rain event according to the site scale rotten field rain event, the method is as follows: S2.

1. Determine the concentrated precipitation period in the target area; The concentrated precipitation period in the target area is from May 15 to June 15 each year; S2.

2. The meteorological elements of the site-scale rain event include: precipitation p, sunshine hours s, duration d, site-scale rain event E sta is a function of three meteorological elements and is expressed as follows: E sta =f(p,s,d) (1) S2.

3. When the duration d = 3 days, the conditions for judging the rain event are: Among them, i represents a day during the rainy season, p i is the precipitation on day i; S2.

4. When the duration d is greater than 3 days, cloudy and rainy weather with little sunshine can also cause heavy rain. In this case, sunshine should be included in the judgment criteria: Among them, k is a day without rain, h k is the sunshine hours on the kth day, p i is the precipitation on day i; S3. Rapidly identify regional rain events at the regional scale, extract and characterize regional rain events in the target area, and normalize them with the indicators corresponding to historical regional rain events; A regional scale rainstorm event is a rainstorm event in the target area where the number of rainstorm-affected sites exceeds the preset threshold value 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 turbid rain occurs in period t, T is the time set of the period when turbid rain occurs, and the preset threshold is 8%; 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; 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 damage to the winter wheat. 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 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 begins, 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 to the ending day of the regional rainstorm is the duration of the regional rainstorm process. The regional rainstorm duration index is expressed as the normalized duration days Norm. D express; The area, under the conditions of regional rainstorm, during the duration of regional rainstorm, the number of stations meeting the conditions of regional rainstorm is regarded as the impact range of regional rainstorm. The regional rainstorm area index is normalized by the number of stations Norm S express; A comprehensive intensity assessment model of intensity-area-duration rainstorm events was constructed to calculate the comprehensive intensity Cs of regional rainstorm events in the target area. The method is as follows: Cs=Norm S +Norm D +I (7) In the formula, Norm S 、Norm D , I are the area, duration and intensity index of regional rainstorm respectively; 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 S3, the regional rain event index includes four meteorological elements: the number of stations S, the duration D, the average cumulative precipitation P and the average sunshine hours H, and the four indicators of the regional rain event are extracted.

3. The method for identifying winter wheat rot rain disaster based on intensity-area-duration according to claim 2, characterized in that: In step S3, the extracted regional rain event index is normalized with the four indicators of historical regional rain events to obtain the normalized station number Norm S , normalized duration Norm D , Normalized precipitation Norm P , Normalized sunshine hours 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 Extract the minimum value of the index value from all the bad rain events in history, X max The maximum value of the index value is extracted from all historical bad rain events.

4. The method for identifying winter wheat rot rain disaster based on intensity-area-duration according to claim 1, 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.

5. 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 4.

6. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, which, when executed by a processor, executes the steps of the intensity-area-duration-based winter wheat rot rain disaster identification method according to any one of claims 1 to 4.

Images