Method for monitoring agricultural drought in humid and semi-humid area

Abstract

The invention discloses an agricultural drought monitoring method for a humid and semi-humid area. The method comprises the following steps: acquiring a day-by-day soil moisture content historical time sequence of a drought generation year of a research site; according to the day-by-day soil moisture content historical time sequence of the research site, estimating the field moisture capacity and the wilting moisture content of various soil textures, and calculating the soil effective moisture content of the various soil textures; according to the crop irrigation water amount and the actual monitoring value of the soil water content in the key growth period of the dry crops, obtaining the soil water content when the dry crops are subjected to water stress; calculating agricultural drought monitoring indexes of the dry crops in the humid and semi-humid areas according to the soil water content when the dry crops are subjected to water stress and the soil effective water content of the corresponding soil texture, and determining agricultural drought severity grade division according to the STAD value for representing the agricultural drought grade of the research area so as to realize drought monitoring. According to the method, the problem that other indexes fail in drought monitoring of a wet or semi-wet area can be solved, and the method has relatively high universality.

Description

Technical Field

[0001] The present invention relates to a method for monitoring, warning and forecasting floods and droughts, and particularly to a method for monitoring agricultural drought in humid and semi-humid regions. Background Art

[0002] Among the existing agricultural drought monitoring indices, the soil water deficit index is considered to be a very potential agricultural drought monitoring indicator. The soil water deficit index based on soil moisture conditions takes into account the relationship between plant physiological status and soil moisture, and its practicality has been proven. However, the research carried out so far shows that the soil water deficit index, which performs well in arid and semi-arid regions, performs poorly in agricultural drought monitoring in humid regions such as lake basins. This indicates that the assumption in this agricultural drought monitoring index that as long as the soil water content is lower than the field capacity, the crop will experience water stress may not be fully sufficient under the complex soil texture conditions in humid regions. Therefore, it is urgent to carry out research on agricultural drought monitoring methods in humid regions. It is of great theoretical significance in enriching and developing the theory of preventing and controlling agricultural drought disasters and agricultural eco-hydrology, and also has important practical value in supporting the construction of smart agriculture in humid and semi-humid regions, improving the food security guarantee ability, and ensuring the sustainable development of social economy. Summary of the Invention

[0003] Object of the Invention: Aiming at the above problems, the present invention proposes a method for monitoring agricultural drought in humid and semi-humid regions, which can overcome the problem of the failure of other indicators in drought monitoring in humid or semi-humid regions, and not only has good practical value, but also has high universality.

[0004] Technical Solution: The technical solution adopted by the present invention is a method for monitoring agricultural drought in humid and semi-humid regions, including: Obtaining the daily historical time series of soil moisture conditions in the study site in the drought years; Estimating the field capacity and wilting water content of various soil textures according to the daily historical time series of soil moisture conditions in the study site; Calculating the available soil water content of various soil textures according to the field capacity and wilting water content of various soil textures; Obtaining the soil water content when the dry crop is under water stress according to the crop irrigation water volume and the actual monitored value of soil water content during the critical growth period of the dry crop; Calculating the agricultural drought monitoring index for dry crops in humid and semi-humid regions according to the soil water content when the dry crop is under water stress and the available soil water content of the corresponding soil texture, and the calculation formula is: ; where STAD is the agricultural drought monitoring index for dry crops in humid and semi-humid regions, is the actual soil water content, It is the soil water content when water stress occurs in dry crops. It represents the available soil water content corresponding to the soil texture. Based on the STAD value, the severity level of agricultural drought is determined, which is used to characterize the agricultural drought level in the study area and realize drought monitoring.

[0005] Through the quantile values of the annual soil water content time series, the field capacity and wilting water content of various soil textures are estimated.

[0006] Calculate the available soil water content of various soil textures, including: subtracting the wilting water content from the field capacity of each soil texture as the available soil water content of this soil texture.

[0007] Starting from sufficient water supply and gradually reducing the irrigation water volume, the crop transpiration and soil water content of different soil textures are monitored and recorded daily to obtain the actual monitored values of crop irrigation water volume and soil water content during the critical growth period of dry crops.

[0008] Based on the actual monitored values of crop irrigation water volume and soil water content during the critical growth period of dry crops, obtain the soil water content when water stress occurs in dry crops, including: calculating the crop transpiration based on the daily monitored crop irrigation water volume and soil water content during the critical growth period of dry crops; calculating the potential evapotranspiration of crops using the Penman formula based on meteorological factor data; calculating the ratio of crop transpiration to potential evapotranspiration; fitting the change curve of the ratio of crop transpiration / potential evapotranspiration ~ soil water content according to the ratio of crop transpiration / potential evapotranspiration and the corresponding soil water content, and the soil water content coordinate corresponding to the inflection point of the change curve is the soil water content at the point where water stress occurs in dry crops. 。

[0009] Substitute the measured soil water content, the soil water content at the point where water stress starts from sufficient water supply for dry crops under this soil texture , and the available soil water content of this soil texture into the agricultural drought monitoring index formula for dry crops in humid and semi-humid areas to obtain the STAD value sequence of different soil textures; obtain the standard for the severity level division of agricultural drought based on the STAD value sequence.

[0010] The standard for the severity level division of agricultural drought is as follows: If STAD is less than or equal to -10, it is an extremely severe agricultural drought; If STAD falls within (-10, -5), it is a severe agricultural drought; If STAD falls within [-5, -2], it is a moderate agricultural drought; If STAD falls within (-2, 0), it is a mild agricultural drought; If STAD is greater than or equal to 0, then there is no agricultural drought.

[0011] The present invention provides a computer device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the agricultural drought monitoring method for humid and semi-humid regions as described is implemented.

[0012] The present invention provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the agricultural drought monitoring method for humid and semi-humid regions as described is implemented.

[0013] The present invention provides a computer program product, including a computer program and / or instructions. When the computer program and / or instructions are executed by a processor, the agricultural drought monitoring method for humid and semi-humid regions as described is implemented.

[0014] Advantageous effects: In the prior art, the soil water deficit index used in arid and semi-arid regions shows a high deviation in agricultural drought monitoring in humid regions such as lake basins. After in-depth research, we found that the soil texture attribute has a very significant impact on this deviation. Further research found that for the same crop, the available water that can be easily absorbed by the crop when drought stress begins in different climate regions is different. This threshold is not only related to the total available soil water, but is also a function of the soil texture. The soil texture not only directly affects the water available to crops, but also has a direct impact on crop growth, root nutrient uptake, crop yield, etc. Therefore, the assumption that as long as the soil water content is lower than the field capacity, the crop will experience water stress may not be completely sufficient in humid regions. The point at which dry crops begin to experience water stress from sufficient water supply is not the field capacity, but a soil water content smaller than the field capacity (denoted as ). It is related not only to the crop type, but also to the soil texture. Based on the research findings, the present invention provides an agricultural drought monitoring method for humid and semi-humid regions, which can solve the problem that other indicators fail in drought monitoring in humid or semi-humid regions. The present invention first proposes an agricultural drought monitoring index and specific operation method considering the influence of soil texture in humid regions, and at the same time proposes a new and more rigorous agricultural drought index in terms of physical mechanism and determines the classification of drought severity levels. The invention enriches the related research on the agricultural drought evaluation system, with clear physical meaning of the index, strong operability, relatively less required data, and high practicality and popularizability. The invention provides an important reference for precision agriculture drought resistance, smart agriculture construction, etc. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 is a flowchart of the agricultural drought monitoring method for humid and semi-humid regions according to the present invention; Figure 2 is a curve of the ratio of evapotranspiration of dry crops to potential evapotranspiration ~ soil water content change. Detailed implementation manners

[0016] The technical solutions of the present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0017] Embodiment 1: For the agricultural drought monitoring method in humid and semi-humid regions described in the present invention, the flowchart is as Figure 1 shown, and the specific implementation steps are as follows: This embodiment of the present invention is described by taking a certain Basin A as an example. Soybeans in the flowering stage are typical dry crops in the humid region, and the flowering stage is a period when soybeans are very sensitive to water demand. Therefore, a pot experiment (sealed bottom) is carried out during the soybean flowering stage.

[0018] Step 1: Obtain the daily soil moisture historical time series of the research site.

[0019] Taking Basin A as the research object, long-term daily soil moisture data from 2011 to 2023 at different sites are obtained.

[0020] Step 2: Estimate the field water holding capacity and wilting water content of various soil textures according to the daily soil moisture historical time series of the research site.

[0021] The 5 typical soil textures in dry land in Basin A are clay, loam, sand, sandy loam, and loamy sand. Based on the long-term daily soil moisture data from different sites from 2011 to 2023 Estimate the field water holding capacity and wilting water content of different soil textures. There are differences in the estimation methods of the field water holding capacity of different soil textures. The best estimated values of the field water holding capacity of clay and loam are recommended as the quantile values of 95% of all soil moisture time series, and the estimated values of the field water holding capacity of sand, sandy loam, and loamy sand should be taken as the multi-year minimum value in the annual maximum value sequence of soil moisture during the crop growth period. This estimation method of the field water holding capacity is a more accurate method obtained based on measured data research compared with the traditional calculation method, and has been published in the journal Journal of Hydrology.

[0022] The wilting water content of different soil textures is the last 5% quantile value of the daily soil moisture content sequence. This is an internationally common calculation method in the case of lack of measured data of wilting water content.

[0023] Step 3: Calculate the available soil water content of various soil textures according to the field water holding capacity and wilting water content of various soil textures.

[0024] Calculate the available soil water content of each soil texture. Subtract the wilting water content from the field water holding capacity of each soil texture, which is the available soil water content of that soil texture. The calculation formula for the available soil water content is: ; In the formula, is the available water content of the soil with a certain soil texture, is the field water holding capacity of this kind of soil texture, is the wilting water content of this kind of soil texture; The available water contents of clay, loam, sand, sandy loam and loamy sand are respectively denoted as , , , , .

[0025] Step 4: According to the crop irrigation water volume and the actual monitored value of the soil water content during the critical growth period of dry crops, obtain the soil water content when the dry crops are under water stress.

[0026] Obtain the crop evapotranspiration and soil water content during the critical growth period of dry crops: Starting from sufficient water supply and gradually reducing the irrigation water volume, daily monitor and record the crop evapotranspiration and soil water content of different soil textures.

[0027] Based on the crop irrigation water volume and soil water content monitored daily for each dry crop during the critical growth period, calculate the crop evapotranspiration; calculate the potential evapotranspiration using the Penman formula based on meteorological factors such as air temperature and relative humidity; calculate the ratio of crop evapotranspiration to potential evapotranspiration; plot the curve of the ratio of crop evapotranspiration to potential evapotranspiration against the change in soil water content. The x-axis coordinate corresponding to the inflection point of the curve is the soil water content at the point where the dry crops start to be under water stress from sufficient water supply . The inflection point is the point where the concavity and convexity of the curve change. For the evapotranspiration and soil water content, plot the curve of the ratio of crop evapotranspiration to potential evapotranspiration against the change in soil water content as Figure 2 shown. The soil water contents at the points where different soil textures are under water stress , are respectively denoted as , , , , .

[0028] Step 5: According to the soil water content when the dry crops are under water stress and the available water content of the corresponding soil texture, calculate the STAD value of the agricultural drought monitoring index for dry crops in the humid and semi-humid regions.

[0029] The STAD value is calculated as: .

[0030] Respectively substitute the field water holding capacity, wilting water content of each soil texture and into the formula , calculate the STAD values of soil moisture stations with different soil textures, and are respectively denoted as , , , , , where i is the date.

[0031] Step 6: Determine the classification of the severity level of agricultural drought based on the STAD value, which is used to characterize the agricultural drought level in the study area and achieve drought monitoring. The classification criteria for the severity level of STAD agricultural drought are as follows: Table 1 Classification Criteria for the Severity Level of STAD Agricultural Drought

[0032] Example 2: In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the above-mentioned soil moisture prediction method based on deep learning is implemented.

[0033] Example 3: In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the above-mentioned soil moisture prediction method based on deep learning is implemented.

[0034] Example 4: In one embodiment, a computer program product is provided, including a computer program / instructions. When the computer program / instructions are executed by a processor, the above-mentioned soil moisture prediction method based on deep learning is implemented.

[0035] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memories, CD-ROMs, optical memories, etc.) containing computer-usable program codes.

[0036] The present application is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram can be implemented by computer program instructions, and the combination of the flows and / or blocks in the flowchart and / or block diagram can also be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate for implementation in the process Figure 1One or more processes and / or blocks Figure 1 Apparatus for the functions specified in one or more blocks

[0037] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce a manufacture including an instruction apparatus that implements the functions in the process Figure 1 One or more processes and / or blocks Figure 1 The functions specified in one or more blocks

[0038] These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, whereby the instructions executed on the computer or other programmable apparatus provide steps for implementing the functions in the process Figure 1 One or more processes and / or blocks Figure 1 Steps for the functions specified in one or more blocks

Claims

1. An agricultural drought monitoring method in humid and semi-humid regions, characterized in that, Including: Obtain the daily historical time series of soil moisture content in the drought years at the research site; Estimate the field water holding capacity and wilting water content of various soil textures according to the daily historical time series of soil moisture content at the research site; Calculate the available soil water content of various soil textures according to the field water holding capacity and wilting water content of various soil textures; Obtain the soil moisture content when water stress occurs in dry crops according to the actual monitored values of crop irrigation water volume and soil moisture content during the critical growth period of dry crops; Calculate the agricultural drought monitoring index for dry crops in humid and semi-humid regions according to the soil moisture content when water stress occurs in dry crops and the available soil water content of the corresponding soil texture. The calculation formula is: ； Among them, STAD is the monitoring index for agricultural drought in humid and semi-humid areas for dry crops, is the actual soil water content, is the soil water content when water stress occurs in dry crops, represents the available soil water content corresponding to the soil texture; Determine the classification of the severity level of agricultural drought according to the STAD value, which is used to characterize the agricultural drought level in the research area and realize drought monitoring.

2. The agricultural drought monitoring method in humid and semi-humid regions according to claim 1, wherein: Estimate the field water holding capacity and wilting water content of various soil textures through the quantile values of the daily soil moisture content time series.

3. The agricultural drought monitoring method in the humid and semi-humid regions according to claim 1, wherein: Calculate the available soil water content of various soil textures, including: subtracting the wilting water content from the field water holding capacity of each soil texture as the available soil water content of that soil texture.

4. The agricultural drought monitoring method in the humid and semi-humid regions according to claim 1, wherein: From the start of sufficient water supply to the gradual reduction of irrigation water volume, daily monitor and record the crop evapotranspiration and soil moisture content of different soil textures to obtain the actual monitored values of crop irrigation water volume and soil moisture content during the critical growth period of dry crops.

5. The agricultural drought monitoring method in humid and semi-humid regions according to claim 1, characterized in that, According to the actual monitored values of crop irrigation water volume and soil water content during the critical growth period of dry crops, obtain the soil water content when water stress occurs in dry crops, including: calculating the crop evapotranspiration based on the daily monitored crop irrigation water volume and soil water content during the critical growth period of dry crops; calculating the potential evapotranspiration of crops using the Penman formula based on meteorological factor data; calculating the ratio of crop evapotranspiration to potential evapotranspiration; fitting a change curve of the ratio of crop evapotranspiration / potential evapotranspiration ~ soil water content according to the ratio of crop evapotranspiration / potential evapotranspiration and the corresponding soil water content, and the soil water content coordinate corresponding to the inflection point of the change curve is the soil water content at the point where water stress occurs in dry crops .

6. The agricultural drought monitoring method in humid and semi-humid regions according to claim 4, characterized in that: The measured soil water content and the soil water content at the point where water stress begins for dry crops starting from sufficient water supply under this soil texture are , the available soil water content of this soil texture, are respectively substituted into the calculation formula of the agricultural drought monitoring index for dry crops in the humid and semi-humid regions to obtain the STAD value sequences of different soil textures; Obtain the criteria for the classification of the severity level of agricultural drought according to the STAD value sequence.

7. The agricultural drought monitoring method in humid and semi-humid regions according to claim 6, wherein The criteria for the classification of the severity level of agricultural drought are as follows: If STAD is less than or equal to -10, it is an extremely severe agricultural drought; If STAD falls within (-10, -5), it is a severe agricultural drought; If STAD falls within [-5, -2], it is a moderate agricultural drought; If STAD falls within (-2, 0), it is a mild agricultural drought; If STAD is greater than or equal to 0, then no agricultural drought has occurred.

8. A computer device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the agricultural drought monitoring method for humid and semi-humid regions described in any one of claims 1 to 7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the agricultural drought monitoring method for humid and semi-humid regions described in any one of claims 1 to 7.

10. A computer program product, comprising a computer program and / or instructions, characterized in that, When the computer program and / or instruction is executed by the processor, it implements the agricultural drought monitoring method for humid and semi-humid regions described in any one of claims 1 to 7.

Images