A method for monitoring agricultural drought in humid and semi-humid areas

Abstract

The present invention discloses a method for monitoring agricultural drought in humid and semi-humid regions, comprising: obtaining a daily historical time series of soil moisture conditions in drought-affected years at a research site; estimating the field holding capacity and wilting water content of various soil textures based on the daily historical time series of soil moisture conditions at the research site, and calculating the effective soil water content of various soil textures; obtaining the soil water content of dry crops when they are experiencing water stress based on the crop irrigation water volume and actual monitored soil water content during the critical growth period of the dry crops; calculating an agricultural drought monitoring index for dry crops in humid and semi-humid regions based on the soil water content when the dry crops are experiencing water stress and the effective soil water content of the corresponding soil texture; determining an agricultural drought severity classification based on the STAD value, and using the STAD value to characterize the agricultural drought grade in the research area, thereby achieving drought monitoring. The present invention can overcome the problem that other indicators fail to function in drought monitoring in humid or semi-humid regions, and has high universality.

Description

Technical Field

[0001] The present invention relates to a flood and drought disaster monitoring, early warning and forecasting method, and in particular to a method for monitoring agricultural drought in humid and semi-humid areas. Background Art

[0002] Among existing agricultural drought monitoring indices, the Soil Water Deficit Index (SWD) is considered a highly promising indicator for agricultural drought monitoring. Based on soil moisture, the SWD index considers the relationship between plant physiological status and soil moisture and has proven its usefulness. However, existing research indicates that the SWD index, while highly effective in arid and semi-arid regions, performs poorly in humid regions, such as lake basins. This suggests that the SWD index's assumption that crops experience water stress whenever soil moisture falls below field capacity may not be fully adequate under the complex soil textures of humid regions. Therefore, research on agricultural drought monitoring methods in humid regions is urgently needed. This not only holds important theoretical significance for enriching and developing agricultural drought disaster prevention and control theories and agro-ecohydrology, but also has significant practical value in supporting the development of smart agriculture in humid and semi-humid regions, enhancing food security, and ensuring sustainable socioeconomic development. Summary of the Invention

[0003] Purpose of the invention: In response to the above problems, the present invention proposes a method for monitoring agricultural drought in humid or semi-humid areas. This monitoring method can overcome the problem that other indicators are ineffective in drought monitoring in humid or semi-humid areas. It 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 areas, comprising:

[0005] Obtain the historical time series of daily soil moisture conditions in drought-affected years at the research site;

[0006] The field capacity and wilting water content of various soil textures were estimated based on the daily soil moisture historical time series at the study sites;

[0007] Calculate the soil available water content of various soil textures based on their field holding capacity and wilting water content;

[0008] Based on the actual monitoring values ​​of crop irrigation water and soil moisture content during the key growth period of dryland crops, the soil moisture content when dryland crops experience water stress is obtained;

[0009] Based on the soil moisture content when dryland crops experience water stress and the soil effective moisture content of the corresponding soil texture, the agricultural drought monitoring index of dryland crops in humid and semi-humid areas is calculated. The calculation formula is:

[0010] ;

[0011] Among them, STAD is an indicator for monitoring agricultural drought in dryland crops in humid and semi-humid areas. is the actual soil moisture content, is the soil moisture content when dryland crops experience water stress. Indicates the effective water content of soil corresponding to soil texture;

[0012] The agricultural drought severity classification is determined according to the STAD value, which is used to characterize the agricultural drought level in the study area and realize drought monitoring.

[0013] The field capacity and wilting water content of various soil textures were estimated using the quantile values ​​of the annual soil moisture time series.

[0014] Calculate the effective soil water content of various soil textures, including: subtracting the field water holding capacity of each soil texture from the wilting water content to obtain the effective soil water content of the soil texture.

[0015] Starting from sufficient water supply to gradually reducing irrigation water, the crop evaporation and soil moisture content of different soil textures are monitored and recorded daily to obtain the actual monitoring values ​​of crop irrigation water and soil moisture content during the critical growth period of dryland crops.

[0016] The soil moisture content of the dryland crop when water stress occurs is obtained based on the actual monitored values ​​of crop irrigation water and soil moisture content during the critical growth period of the dryland crop, including: calculating crop transpiration based on the daily monitored crop irrigation water and soil moisture content during the critical growth period of the dryland crop; calculating crop potential evapotranspiration using the Penman formula based on meteorological factor data; calculating the ratio of crop transpiration to potential evapotranspiration; fitting a change curve of the ratio of crop transpiration to potential evapotranspiration and soil moisture content based on the ratio of crop transpiration to potential evapotranspiration and the corresponding soil moisture content, wherein the soil moisture coordinate corresponding to the inflection point of the change curve is the soil moisture content at the point where water stress occurs to the dryland crop. .

[0017] The measured soil moisture content and the soil moisture content at the point where dry crops begin to experience water stress from sufficient water supply under this soil texture are used to calculate the soil moisture content. The effective soil water content of this soil texture is substituted into the agricultural drought monitoring index formula for dryland crops in humid and semi-humid areas to obtain the STAD value sequence of different soil textures; and the standard for dividing the severity level of agricultural drought is obtained according to the STAD value sequence.

[0018] The standards for the classification of agricultural drought severity levels are:

[0019] If STAD is less than or equal to -10, it is a severe agricultural drought;

[0020] If STAD falls between (-10, -5), it indicates severe agricultural drought;

[0021] If STAD falls between [-5, -2], it is a moderate agricultural drought;

[0022] If STAD falls between (-2,0), it is a mild agricultural drought;

[0023] If STAD is greater than or equal to 0, there is no agricultural drought.

[0024] The present invention proposes a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the method for monitoring agricultural drought in humid and semi-humid areas is implemented.

[0025] The present invention provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the method for monitoring agricultural drought in humid and semi-humid areas is implemented.

[0026] The present invention provides a computer program product, comprising a computer program and / or instructions, which implement the method for monitoring agricultural drought in humid and semi-humid areas when executed by a processor.

[0027] Beneficial effects: In the existing technology, the soil moisture deficit index used in arid and semi-arid areas shows a high deviation in agricultural drought monitoring in humid areas such as lake basins. After in-depth research, we found that the soil texture properties have a very significant impact on the deviation. Further research found that the same crop has different effective water amounts that can be absorbed by crops when it begins to experience drought stress in different climatic zones. This threshold is not only related to the total effective water content of the soil, but is also a function of soil texture. Soil texture not only directly affects the amount of water available to crops, but also has a direct impact on crop growth, root nutrient absorption, crop yield, etc. Therefore, the assumption that crops will experience water stress as long as the soil moisture content is lower than the field holding capacity may not be completely sufficient in humid areas. The point at which drought-stricken crops begin to experience water stress from sufficient water supply is not the field holding capacity, but a soil moisture content that is smaller than the field holding capacity (denoted as ). It is not only related to the crop type, but also to the soil texture. Based on research findings, the present invention proposes a method for monitoring agricultural drought in humid and semi-humid areas, which can solve the problem that other indicators are ineffective in drought monitoring in humid or semi-humid areas. The present invention is the first to propose agricultural drought monitoring indicators and specific operating methods that take into account the influence of soil texture in humid areas. At the same time, it proposes a new agricultural drought indicator that is more rigorous in physical mechanism and determines the classification of drought severity. This invention enriches the relevant research on the agricultural drought evaluation system. The indicators have clear physical meanings, strong operability, relatively less data required, and are highly practical and generalizable. This invention provides an important reference for precision agriculture drought resistance, smart agriculture construction, etc. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 is a flow chart of the method for monitoring agricultural drought in humid and semi-humid areas according to the present invention;

[0029] Figure 2 It is the ratio of evaporation of dry crops to potential evapotranspiration ~ soil moisture change curve. DETAILED DESCRIPTION

[0030] The technical solution of the present invention will be further described below with reference to the accompanying drawings and embodiments.

[0031] Example 1:

[0032] The method for monitoring agricultural drought in humid and semi-humid areas of the present invention is as follows: Figure 1 The specific implementation steps are as follows:

[0033] The present invention is described using a watershed A as an example. Flowering soybeans are a typical dryland crop in humid regions and are very sensitive to water demand. Therefore, the flowering period was selected to conduct potted plant (sealed bottom) experiments.

[0034] Step 1: Obtain the daily soil moisture historical time series of the study site.

[0035] Taking the A basin as the research object, a long series of daily soil moisture data from 2011 to 2023 were obtained at different stations.

[0036] Step 2: Estimate the field capacity and wilting water content of various soil textures based on the historical time series of daily soil moisture conditions at the study site.

[0037] The five typical soil textures of dryland in Basin A are clay, loam, sand, sandy loam, and loamy sand. Based on the long series of daily soil moisture data from different stations from 2011 to 2023 Estimate field capacity and wilting water content for different soil textures. Field capacity estimation methods vary for different soil textures. For clay and loam soils, the recommended best estimate of field capacity is the 95th percentile of the total soil water content time series. For sandy soils, sandy loam, and loamy sand, the best estimate of field capacity is the multi-year minimum value in the series of annual maximum soil water content during the crop growth period. This method for estimating field capacity, based on field data, is more accurate than traditional calculation methods and has been published in the Journal of Hydrology.

[0038] The wilting water content for different soil textures is calculated using the last 5% quantile of the daily soil water content series. This is an internationally accepted calculation method in the absence of measured wilting water content data.

[0039] Step 3: Calculate the soil available water content of various soil textures based on their field capacity and wilting water content.

[0040] Calculate the effective soil water content of each soil texture. Subtract the field water holding capacity of each soil texture from the wilting water content to get the effective soil water content of that soil texture. The calculation formula for effective soil water content is: ;

[0041] Where, is the effective water content of soil of a certain soil texture, is the field water holding capacity of the soil texture, is the wilting water content of the soil texture;

[0042] The effective water content of clay, loam, sand, sandy loam and loamy sand is recorded as 、 、 、 、 .

[0043] Step 4: Based on the actual monitoring values ​​of crop irrigation water and soil moisture content during the critical growth period of dryland crops, obtain the soil moisture content when dryland crops experience water stress.

[0044] Obtain crop transpiration and soil moisture content during the critical growth period of dryland crops: starting from sufficient water supply to gradually reducing irrigation water, monitor and record crop transpiration and soil moisture content of different soil textures on a daily basis.

[0045] Calculate crop transpiration based on daily monitored crop irrigation water and soil moisture during the critical growth period of each dryland crop. Calculate potential evapotranspiration using the Penman formula based on meteorological factors such as temperature and relative humidity. Calculate the ratio of crop transpiration to potential evapotranspiration. Plot a curve of the ratio of crop transpiration to potential evapotranspiration versus soil moisture content. The x-axis coordinate corresponding to the inflection point of the curve is the soil moisture content at the point where the dryland crop begins to experience water stress after sufficient water supply. The inflection point is the point where the curve changes in concavity. Evaporation and soil moisture content, plot the ratio of crop evaporation / potential evapotranspiration ~ soil moisture change curve is as follows Figure 2 Soil water content at the point where water stress occurs in different soil textures , respectively 、 、 、 、 .

[0046] Step 5: Based on the soil moisture content when dryland crops experience water stress and the soil effective moisture content of the corresponding soil texture, calculate the STAD value of the agricultural drought monitoring indicator for dryland crops in humid and semi-humid areas.

[0047] The STAD value is calculated as: .

[0048] The field capacity, wilting water content and Substitute into the formula , calculate the STAD values ​​of different soil texture and soil moisture conditions, respectively, 、 、 、 、 ,in i For date.

[0049] Step 6: Determine the agricultural drought severity level based on the STAD value to characterize the agricultural drought level in the study area and implement drought monitoring. The STAD agricultural drought severity level classification standards are as follows:

[0050] Table 1 STAD agricultural drought severity classification standards

[0051]

[0052] Example 2:

[0053] In one embodiment, a computer device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned soil moisture prediction method based on deep learning when executing the computer program.

[0054] Example 3:

[0055] 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 computer program implements the above-mentioned soil moisture prediction method based on deep learning.

[0056] Example 4:

[0057] In one embodiment, a computer program product is provided, comprising a computer program / instruction, which, when executed by a processor, implements the soil moisture prediction method based on deep learning.

[0058] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0059] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0060] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0061] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

Claims

1. A method for monitoring agricultural drought in humid and semi-humid areas, characterized in that: include: Obtain the historical time series of daily soil moisture conditions in drought-affected years at the research site; The field capacity and wilting water content of various soil textures were estimated based on the daily soil moisture historical time series at the study sites; Calculate the soil available water content of various soil textures based on their field holding capacity and wilting water content; Based on the actual monitoring values ​​of crop irrigation water and soil moisture content during the key growth period of dryland crops, the soil moisture content when dryland crops experience water stress is obtained; Based on the soil moisture content when dryland crops experience water stress and the soil effective moisture content of the corresponding soil texture, the agricultural drought monitoring index of dryland crops in humid and semi-humid areas is calculated. The calculation formula is: ； Among them, STAD is an indicator for monitoring agricultural drought in dryland crops in humid and semi-humid areas. is the actual soil moisture content, is the soil moisture content when dryland crops experience water stress. Indicates the effective water content of soil corresponding to soil texture; The agricultural drought severity classification is determined according to the STAD value, which is used to characterize the agricultural drought level in the study area and realize drought monitoring.

2. The method for monitoring agricultural drought in humid and semi-humid areas according to claim 1, wherein: The field capacity and wilting water content of various soil textures were estimated using the quantile values ​​of the daily soil moisture time series.

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

4. The method for monitoring agricultural drought in humid and semi-humid areas according to claim 1, wherein: Starting from sufficient water supply to gradually reducing irrigation water, the crop evaporation and soil moisture content of different soil textures are monitored and recorded daily to obtain the actual monitoring values ​​of crop irrigation water and soil moisture content during the critical growth period of dryland crops.

5. The method for monitoring agricultural drought in humid and semi-humid areas according to claim 1, wherein: The soil moisture content of the dryland crop when water stress occurs is obtained based on the actual monitored values ​​of crop irrigation water and soil moisture content during the critical growth period of the dryland crop, including: calculating crop transpiration based on the daily monitored crop irrigation water and soil moisture content during the critical growth period of the dryland crop; calculating crop potential evapotranspiration using the Penman formula based on meteorological factor data; calculating the ratio of crop transpiration to potential evapotranspiration; fitting a change curve of the ratio of crop transpiration to potential evapotranspiration and soil moisture content based on the ratio of crop transpiration to potential evapotranspiration and the corresponding soil moisture content, wherein the soil moisture coordinate corresponding to the inflection point of the change curve is the soil moisture content at the point where water stress occurs to the dryland crop. .

6. The method for monitoring agricultural drought in humid and semi-humid areas according to claim 4, characterized in that: The measured soil moisture content and the soil moisture content at the point where dry crops begin to experience water stress from sufficient water supply under this soil texture are used to calculate the soil moisture content. , the effective soil water content of the soil texture is respectively substituted into the calculation formula of the agricultural drought monitoring index of dryland crops in humid and semi-humid areas to obtain the STAD value sequence of different soil textures; The standard for agricultural drought severity classification is obtained based on the STAD value series.

7. The method for monitoring agricultural drought in humid and semi-humid areas according to claim 6, characterized in that: The standards for the classification of agricultural drought severity levels are: If STAD is less than or equal to -10, it is a severe agricultural drought; If STAD falls between (-10, -5), it indicates severe agricultural drought; If STAD falls between [-5, -2], it is a moderate agricultural drought; If STAD falls between (-2,0), it is a mild agricultural drought; If STAD is greater than or equal to 0, there is no agricultural drought.

8. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the method for monitoring agricultural drought in humid and sub-humid areas according to any one of claims 1 to 7 is implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for monitoring agricultural drought in humid and sub-humid areas according to any one of claims 1 to 7 is implemented.

10. A computer program product comprising a computer program and / or instructions, characterized in that When the computer program and / or instructions are executed by a processor, the method for monitoring agricultural drought in humid and sub-humid areas according to any one of claims 1 to 7 is implemented.

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