Vegetation and ecological drought response relation and influence factor action path determination method thereof

Abstract

The invention discloses a vegetation and ecological drought response relationship and an influence factor action path determination method thereof. The response relationship determination method comprises the following steps: determining an ecological water demand sequence according to meteorological data, vegetation data and soil data of a research area; determining an ecological drought index sequence according to the ecological water demand sequence; and according to the ecological drought index sequence, determining a response relationship between the vegetation and the ecological drought, wherein the response relationship between the vegetation and the ecological drought comprises the sensitivity of the vegetation to the ecological drought, a loss probability sequence of the characteristics of the vegetation under different drought levels and an ecological drought threshold. According to the method, the ecological drought index is constructed by integrating meteorological, soil and vegetation data, so that the monitoring accuracy of vegetation drought is improved, and the problems of research uncertainty of a single ecological index and difficulty in quantification of ecological system loss are solved by incorporating a crop planting mode and quantifying ecological system response differences; and the accuracy and efficiency of ecological drought monitoring, evaluation and management are improved.

Description

Technical Field

[0001] The present invention belongs to the field of hydrological events and disaster risk assessment, and in particular relates to a method for determining the relationship between vegetation and ecological drought response and the action path of its influencing factors. Background Art

[0002] Drought, as a complex and frequent natural disaster, poses a serious threat to natural ecosystems and human society. Under drought conditions, the physiological processes of vegetation (such as photosynthesis and transpiration) are significantly inhibited, resulting in a reduction in species and quantity, which in turn affects the stability of the entire agricultural ecosystem and natural ecosystem.

[0003] At present, constructing an ecological drought index is often considered to be an effective means to identify drought events and thus study the complex response relationship between vegetation and ecological drought.

[0004] However, the ecological drought indices that are widely used currently mostly focus on monitoring meteorological factors (such as precipitation and temperature) or hydrological conditions (such as soil moisture and runoff). Although these indicators provide important perspectives for understanding drought, they often ignore the importance of vegetation, a key component of the ecosystem. Summary of the invention

[0005] In order to solve the above problems, the present invention discloses a method for determining the relationship between vegetation and ecological drought response and the action path of its influencing factors.

[0006] The present invention discloses a method for determining the relationship between vegetation and ecological drought response, comprising the following steps: Determine the ecological water demand sequence based on the meteorological data, vegetation data and soil data of the study area; Determining an ecological drought index sequence according to the ecological water demand sequence; The response relationship between vegetation and ecological drought is determined according to the ecological drought index sequence, and the response relationship between vegetation and ecological drought includes: the sensitivity of vegetation to ecological drought and the loss probability sequence of vegetation characteristics under different drought levels and the ecological drought threshold.

[0007] Preferably, the ecological water demand sequence is determined according to the meteorological data, vegetation data and soil data, specifically: Determine a crop coefficient sequence according to the vegetation data and the soil data; determining a soil moisture coefficient based on the soil data; An ecological water requirement sequence is determined according to the crop coefficient sequence, the soil moisture coefficient and the meteorological data.

[0008] Preferably, the crop coefficient sequence is determined according to the vegetation data and the soil data, specifically: Determine a first coefficient sequence according to a quadratic difference method and the vegetation data; determining a second coefficient sequence based on the soil data; A crop coefficient sequence is determined from the first coefficient sequence and the second coefficient sequence according to the vegetation type of the study area.

[0009] Preferably, the first coefficient sequence is determined according to the quadratic difference method and the vegetation data, specifically: Determine the crop planting pattern of the study area based on the quadratic difference method and the vegetation data; A first coefficient sequence is determined based on the crop planting pattern.

[0010] Preferably, the ecological drought index sequence is determined according to the ecological water demand sequence, specifically: Determining a vegetation water deficit sequence based on the ecological water demand sequence; determining a cumulative distribution sequence based on the vegetation water deficit sequence; An ecological drought index sequence is determined according to the cumulative distribution sequence.

[0011] Preferably, the response relationship between vegetation and ecological drought is determined according to the ecological drought index sequence, specifically: Obtain multiple preset vegetation index sequences and ecological drought index sequences of different time scales; Based on multiple vegetation indicator sequences and ecological drought index sequences at different time scales, the response relationship between vegetation and ecological drought is determined.

[0012] Preferably, the response relationship between vegetation and ecological drought is determined based on multiple vegetation indicator sequences and ecological drought index sequences of different time scales, specifically: From the ecological drought index sequences of different time scales, the optimal ecological drought index sequence corresponding to each vegetation index sequence is obtained; According to each vegetation indicator sequence and its corresponding optimal ecological drought index sequence, the response relationship between vegetation and ecological drought is determined.

[0013] Preferably, when the response relationship between vegetation and ecological drought is: the loss probability sequence of vegetation characteristics under different drought levels and the ecological drought threshold, the response relationship between vegetation and ecological drought is determined according to each vegetation indicator sequence and its corresponding optimal ecological drought index sequence, specifically: Determine a first edge distribution, a second edge distribution and a plurality of joint distributions according to each vegetation indicator sequence and its corresponding optimal ecological drought index sequence; Obtain drought grade series for the study area; Determine the loss probability sequence and ecological drought threshold of vegetation characteristics at different drought levels according to the first edge distribution, the second edge distribution, multiple joint distributions and drought level sequence; The first marginal distribution is the marginal distribution of each vegetation index sequence, the second marginal distribution is the marginal distribution of the optimal ecological drought index sequence, and the multiple joint distributions are the joint distributions of each vegetation index sequence and the optimal ecological drought index sequence.

[0014] Preferably, the loss probability sequence and ecological drought threshold of vegetation characteristics at different drought levels are determined according to the first edge distribution, the second edge distribution, multiple joint distributions and the drought level sequence, specifically: Determine the loss probability sequence of vegetation characteristics at different drought levels and its corresponding confidence sequence according to the first marginal distribution, the second marginal distribution, multiple joint distributions, the drought level sequence and the conditional probability formula; The ecological drought index corresponding to the confidence level greater than the preset value in the confidence level sequence is used as the ecological drought threshold value under the corresponding drought level.

[0015] The present invention also discloses a method for determining the action path of factors affecting the relationship between vegetation and ecological drought response, comprising the following steps: Determine the ecological drought threshold of vegetation characteristics under different drought levels by using the method for determining the relationship between vegetation and ecological drought response; Constructing a path analysis model according to a plurality of preset influencing factors and the ecological drought threshold, wherein the plurality of preset influencing factors include meteorological factors, soil factors and vegetation factors; The action paths of the influencing factors of the relationship between vegetation and ecological drought response are determined according to the path analysis model.

[0016] Compared with the prior art, the present invention has the following beneficial effects: (1) The present invention integrates meteorological, soil and vegetation data to construct an ecological drought index, which not only improves the monitoring accuracy of vegetation drought, but also solves the research uncertainty of a single ecological indicator and the difficulty in quantifying ecosystem losses by incorporating crop planting patterns and quantifying differences in ecosystem responses, thereby improving the accuracy and efficiency of ecological drought monitoring, assessment and management; (2) Based on the marginal distribution and joint distribution, this paper calculates the ecological drought threshold and the loss probability of vegetation characteristics, and quantifies the specific impact of drought events on vegetation in a specific ecosystem, including the loss risk of key characteristics such as vegetation growth status, biomass reduction, and coverage change. This method not only provides an accurate estimate of the probability of drought, but also deeply reveals the complex relationship between drought and changes in vegetation characteristics. It can more intuitively assess the potential impact of drought disasters on ecosystems, thereby more effectively carrying out disaster prevention and mitigation work. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a flow chart of the method for determining the relationship between vegetation and ecological drought response of the present invention; Figure 2 It is a flow chart of the method for determining the action paths of the influencing factors of the relationship between vegetation and ecological drought response of the present invention. DETAILED DESCRIPTION

[0018] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present invention. However, it should be clear to those skilled in the art that the present invention may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present invention.

[0019] like Figure 1 As shown, the present invention discloses a method for determining the relationship between vegetation and ecological drought response, comprising the following steps: S1. Determine the ecological water demand sequence based on the meteorological data, vegetation data and soil data of the study area; in Example 1, the meteorological data, vegetation data and soil data of each grid in the Yangtze River Basin from 1982 to 2018 are collected; the meteorological data include actual evapotranspiration sequence and potential evapotranspiration sequence; the vegetation data include NDVI (normalized vegetation index) sequence; the soil texture data include soil particle size composition data of different grids and LUCC (land use) data of different grids.

[0020] Preferably, S1 is specifically: S11, determining a crop coefficient sequence according to vegetation data and soil data; Preferably, S11 is specifically: S111, determining a first coefficient sequence according to a quadratic difference method and vegetation data; Preferably, S111 is specifically: S1111. Determine the crop planting pattern in the study area based on the quadratic difference method and vegetation data; The specific S1111 is: using the quadratic difference method and the NDVI sequence to identify the crop planting pattern of each grid point:

[0021] Where: S Represents the long series data of NDVI monthly scale of a certain grid; i Indicates i months; S 1 i It represents the difference of NDVI between adjacent months; S 2 i Based on S 1 i Determined value; S 3 i Indicates peak value.

[0022] In each grid, the study period is calculated one by one in three adjacent months to obtain multiple peaks. In order to eliminate the interference of abnormal fluctuations and weed growth, the obtained peaks are screened according to the following three preset conditions, that is, only the peaks that meet the following three conditions at the same time can be retained: (1) The peak should be in the middle growth period of the main crops (wheat, corn, rice or soybeans); (2) The peak NDVI should be greater than the average NDVI of multiple years in the grid; (3) The interval between two adjacent peaks is at least two months.

[0023] The number of peak values ​​after screening in each grid is obtained, and the crop growth pattern of each grid, that is, the number of harvests per year, is determined according to the number of peak values ​​after screening.

[0024] S1112. Determine a first coefficient sequence according to a crop planting pattern.

[0025] According to the crop planting pattern of each grid, relevant materials such as the "FAO-56 Crop Water Requirements Calculation Guide (Chinese Version)" are consulted to obtain the first coefficient sequence of each grid. The first coefficient sequence corresponds to the crop coefficient sequence.

[0026] S112, determining a second coefficient sequence according to soil data; In Example 1, based on LUCC (land use) data and combined with Section 2.2.2.2 of the document "Liu Yuting, Xu Jijun, Liu Simin, et al. Research on changes in ecological water demand in the upper reaches of the Yangtze River [J]. Water Resources and Hydropower Technology (Chinese and English), 2021, 52(08):120-131.DOI:10.13928 / j.cnki.wrahe.2021.08.012.", the second coefficient sequence of each grid is obtained; the second coefficient sequence corresponds to the crop coefficient sequence of the natural ecosystem (such as grassland, forest and shrubs).

[0027] S113. Determine a crop coefficient sequence from the first coefficient sequence and the second coefficient sequence according to the vegetation type in the study area.

[0028] In Example 1, the vegetation types in the study area include crops and natural ecosystems; the crop coefficient sequence of each grid is selected from the first coefficient sequence of each grid and the second coefficient sequence of each grid according to the vegetation type.

[0029] S12, determining soil moisture coefficient according to soil data; In Example 1, the soil moisture coefficient of each grid is obtained based on the soil particle size composition data of each grid in the study area and combined with Table 1 in the document "Wang Gailing, Wang Qingchu, Shi Shengxin. Study on the ecological water demand of forest and grass vegetation in the Yongding River Basin of Shanxi Province [J]. Journal of Natural Resources, 2013, 28(10): 1743-1753."

[0030] S13. Determine the ecological water demand sequence of each grid according to the crop coefficient sequence, soil moisture coefficient and meteorological data of each grid.

[0031] In Example 1, taking a certain grid as an example, the Penman-Monteith crop model is used to calculate the ecological water requirement series (EWR) of the grid:

[0032] Where: k c is the crop coefficient sequence of the grid, k s is the soil moisture coefficient of the grid, and ET0 is the potential evapotranspiration sequence of the grid.

[0033] S2. Determine an ecological drought index sequence according to the ecological water demand sequence. In the present invention, the ecological drought index is recorded as SEWSI; Preferably, S2 is specifically: S21. Determine the vegetation water deficit sequence based on the ecological water demand sequence; Example 1 Based on the water balance theory, the standardized vegetation water deficit index (SEWSI) of the grid is constructed: EWS=EWC-EWR Where: EWS is the vegetation water deficit sequence of the grid, EWC is the actual evapotranspiration sequence of the grid, and EWR is the vegetation water requirement sequence of the grid.

[0034] S22, in each grid, determining a cumulative distribution sequence based on the vegetation water deficit sequence; S22 is specifically: fitting the EWS of the grid through the logarithmic logistic probability distribution to obtain the cumulative distribution function of the grid:

[0035] Where: α is the scale parameter, β is the shape parameter, γ is the original parameter, x For EWS, F(x) is the cumulative distribution function of the raster.

[0036] α , β and γ The calculation formula is as follows:

[0037] Where: Γ is the factorial function, Di It is the difference series of monthly precipitation and evapotranspiration, which has the same meaning as EWS. w 0. w 1 and w 2 is the probability weighted moment of EWS.

[0038] w 0. w 1 and w 2The calculation method is as follows:

[0039] Where: N The number of months to be calculated for participation; Di For EWS.

[0040] S23. Determine the ecological drought index sequence of the grid according to the cumulative distribution sequence of the grid.

[0041] S23 specifically includes: obtaining the inverse function of the cumulative distribution function of the grid, and using the inverse function as the ecological drought index SEWSI.

[0042] In other embodiments, the cumulative distribution function of the grid may also be normalized to obtain the corresponding SEWSI:

[0043] The present invention constructs an ecological drought index and uses the ecological drought index to identify drought events in each grid in the study area. In one embodiment, a situation where SEWSI<-0.5 is considered to be an ecological drought.

[0044] S3. Determine the response relationship between vegetation and ecological drought based on the ecological drought index sequence. The response relationship between vegetation and ecological drought includes: the sensitivity of vegetation to ecological drought and the loss probability sequence of vegetation characteristics under different drought levels and the ecological drought threshold.

[0045] Preferably, S3 is specifically: S31, obtaining multiple preset vegetation index sequences and ecological drought index sequences of different time scales in each grid; In Example 1, S31 is specifically: S311. Collect and process the vegetation sequences in each grid in the Yangtze River Basin from 1982 to 2018. The vegetation sequences include: normalized difference vegetation index NDVI sequence, leaf area index LAI sequence, terrestrial gross primary production GPP sequence and sunlight induced chlorophyll fluorescence SIF sequence, and calculate the kNDVI sequence.

[0046] S312, the vegetation sequences with different spatial resolutions in each grid: NDVI sequence (or kNDVI sequence), LAI sequence, GPP sequence and SIF sequence are cleaned and resampled to 0.1° spatial resolution.

[0047] S313, detrending and deseasonalizing each vegetation sequence in each grid is performed by using the detrend function of Matlab to obtain a standardized vegetation index sequence in each grid.

[0048] The following is an example of how to obtain ecological drought index series at different time scales: In one embodiment, ecological drought index sequences at time scales of 1 to 3 months are obtained respectively: the vegetation water deficit sequence at a time scale of 1 month is obtained by using the aforementioned steps S1 to S21, and the ecological drought index sequence at a time scale of 1 month is determined according to the vegetation water deficit sequence at a time scale of 1 month; When calculating the vegetation water deficit series on a time scale of 2-3 months, the vegetation water deficit series on a time scale of 1 month is multiplied by the time scale multiple (i.e., 2 and 3), and then the corresponding ecological drought index series on a time scale of 2-3 months is obtained.

[0049] In other embodiments, it is also possible to start from step S1, respectively obtain meteorological data, vegetation data and soil data at different time scales, and then respectively calculate the ecological drought index series at different time scales.

[0050] S32. Determine the response relationship between vegetation and ecological drought in each grid based on multiple vegetation indicator sequences and ecological drought index sequences at different time scales in each grid.

[0051] Preferably, S32 is specifically: S321, obtaining the optimal ecological drought index SEWSI sequence corresponding to each vegetation index sequence from the ecological drought index sequences of different time scales; S321 is specifically as follows: Pearson correlation analysis is performed on the vegetation index sequence in each grid and the ecological drought index sequence of different time scales, and the time scale with the largest correlation coefficient is selected as the optimal ecological drought index SEWSI time scale sequence in each grid; S322. Determine the response relationship between vegetation and ecological drought based on each vegetation indicator sequence and its corresponding optimal ecological drought index sequence.

[0052] Preferably, when the response relationship between vegetation and ecological drought is: the sensitivity of vegetation to ecological drought, the optimal SEWSI time scale corresponding to each grid in the study area with different dry and wet conditions and different vegetation types is statistically analyzed. The smaller the time scale, the more sensitive the vegetation is to ecological drought.

[0053] Preferably, when the response relationship between vegetation and ecological drought is: the loss probability sequence of vegetation characteristics under different drought levels and the ecological drought threshold, S322 is specifically (for ease of understanding, the following descriptions of the first edge distribution, the second edge distribution, and multiple joint distributions are all based on a grid in the study area as an example): S3221. Determine the first marginal distribution, the second marginal distribution and multiple joint distributions according to each vegetation indicator sequence and its corresponding optimal ecological drought index sequence; the first marginal distribution is the marginal distribution of each vegetation indicator sequence, the second marginal distribution is the marginal distribution of the optimal ecological drought index sequence, and the multiple joint distributions are the joint distributions of each vegetation indicator sequence and the optimal ecological drought index sequence.

[0054] In Example 1, the marginal distribution of each vegetation index sequence and the optimal drought index sequence in each grid is obtained, and the joint distribution of each vegetation index sequence and the optimal ecological drought index sequence in each grid is constructed through five Copula functions; the optimal Copula function is selected according to the Euclidean square distance, and the corresponding joint distribution is extracted.

[0055] S3222. Obtain the drought grade sequence of the study area. The drought grade sequence can be obtained by looking up the table; S3223, determining a loss probability sequence and an ecological drought threshold of vegetation characteristics at different drought levels according to the first edge distribution, the second edge distribution, the multiple joint distributions, and the drought level sequence; Preferably, S3223 is specifically: S32231. Determine the loss probability sequence of vegetation characteristics at different drought levels and its corresponding confidence sequence according to the first marginal distribution, the second marginal distribution, the multiple joint distributions, the drought level sequence and the conditional probability formula; S32232. The ecological drought index corresponding to the confidence level greater than the preset value in the confidence level sequence is used as the ecological drought threshold value under the corresponding drought level.

[0056] It can be seen from step S3223 that the present invention uses multiple vegetation indicators to characterize corresponding vegetation features.

[0057] Taking the joint distribution of the standardized vegetation index kNDVI (SkNDVI) and the ecological drought index SEWSI in a certain grid as an example, step S3223 is explained: According to the joint distribution, the conditional probability formula is used to determine the probability of vegetation loss characteristics of terrestrial ecosystems under drought stress in the grid, and to evaluate the vulnerability of different types of vegetation. The expression is shown in the following formula:

[0058] Where: is the loss probability sequence of vegetation index kNDVI, skndvi is -1, F kNDVI and F SEWSI are the marginal distributions of SkNDVI and SEWSI, C It is a Copula function.

[0059] In the above formula, while obtaining the loss probability sequence of the vegetation indicator kNDVI in the grid, the corresponding confidence sequence can be obtained. The ecological drought index corresponding to 95% in the confidence sequence is determined as the threshold for ecological drought to trigger vegetation loss.

[0060] Furthermore, the present invention also combines the above-mentioned method for determining the relationship between vegetation and ecological drought response, and statistically analyzes the vulnerability and ecological drought triggering thresholds of different dry and wet conditions and different ecosystems according to land cover types and climate dry and wet zoning.

[0061] like Figure 2As shown, the present invention also discloses a method for determining the action path of factors affecting the relationship between vegetation and ecological drought response, comprising the following steps: Step 1: Determine the ecological drought threshold of vegetation characteristics under different drought levels by using the relationship determination method between vegetation and ecological drought response; Step 2: construct a path analysis model based on multiple preset influencing factors and ecological drought thresholds, where the multiple preset influencing factors include meteorological factors, soil factors, and vegetation factors; Step 2 is specifically as follows: Collect precipitation, temperature, VPD (vapor pressure deficit), soil moisture data in each grid in the Yangtze River Basin from 1982 to 2018, as well as soil type and altitude data in each grid.

[0062] The data corresponding to the above-mentioned impact factors with different spatial resolutions were resampled to 0.1° resolution using bilinear interpolation.

[0063] The data corresponding to each influencing factor are subjected to principal component analysis to obtain the factors after dimensionality reduction.

[0064] Step 3: Determine the action path of the influencing factors of the relationship between vegetation and ecological drought response based on the path analysis model.

[0065] Step three is as follows: different ecosystems are divided according to different climatic conditions and vegetation types, and the factors of different ecosystems after dimensionality reduction are obtained. The ecological drought triggering thresholds under different drought levels in each ecosystem are calculated using the above method. The factors after dimensionality reduction are used as independent variables, and the ecological drought triggering thresholds under different drought levels are used as dependent variables. The input is into the partial least squares path analysis model of the corresponding ecosystem, and the action path of the influencing factors of the relationship between vegetation and ecological drought response is determined according to the output results of the path analysis model.

[0066] Compared with the prior art, the present invention has the following beneficial effects: (1) The present invention integrates meteorological, soil and vegetation data to construct an ecological drought index, which not only improves the monitoring accuracy of vegetation drought, but also solves the research uncertainty of a single ecological indicator and the difficulty in quantifying ecosystem losses by incorporating crop planting patterns and quantifying differences in ecosystem responses, thereby improving the accuracy and efficiency of ecological drought monitoring, assessment and management; (2) Based on the marginal distribution and joint distribution, this paper calculates the ecological drought threshold and the loss probability of vegetation characteristics, and quantifies the specific impact of drought events on vegetation in a specific ecosystem, including the loss risk of key characteristics such as vegetation growth status, biomass reduction, and coverage change. This method not only provides an accurate estimate of the probability of drought, but also deeply reveals the complex relationship between drought and changes in vegetation characteristics. It can more intuitively assess the potential impact of drought disasters on ecosystems, thereby more effectively carrying out disaster prevention and mitigation work.

[0067] The above are only a few embodiments of the present application and do not constitute any form of limitation to the present application. Although the present application is disclosed as above with preferred embodiments, it is not intended to limit the present application. Any technician familiar with the profession, without departing from the scope of the technical solution of the present application, using the technical content disclosed above to make slight changes or modifications are equivalent to equivalent implementation cases and fall within the scope of the technical solution.

Claims

1. A method for determining the relationship between vegetation and ecological drought response, characterized in that: The following steps are involved: Determine the ecological water demand sequence based on the meteorological data, vegetation data and soil data of the study area; Determining an ecological drought index sequence according to the ecological water demand sequence; The response relationship between vegetation and ecological drought is determined according to the ecological drought index sequence, and the response relationship between vegetation and ecological drought includes: the sensitivity of vegetation to ecological drought and the loss probability sequence of vegetation characteristics under different drought levels and the ecological drought threshold.

2. The method for determining the relationship between vegetation and ecological drought response according to claim 1, characterized in that: The ecological water demand sequence is determined based on the meteorological data, vegetation data and soil data, specifically: Determine a crop coefficient sequence according to the vegetation data and the soil data; determining a soil moisture coefficient based on the soil data; An ecological water requirement sequence is determined according to the crop coefficient sequence, the soil moisture coefficient and the meteorological data.

3. The method for determining the relationship between vegetation and ecological drought response according to claim 2, characterized in that: The crop coefficient sequence is determined according to the vegetation data and the soil data, specifically: Determine a first coefficient sequence according to a quadratic difference method and the vegetation data; determining a second coefficient sequence based on the soil data; A crop coefficient sequence is determined from the first coefficient sequence and the second coefficient sequence according to the vegetation type of the study area.

4. The method for determining the relationship between vegetation and ecological drought response according to claim 3, characterized in that: The first coefficient sequence is determined according to the quadratic difference method and the vegetation data, specifically: Determine the crop planting pattern of the study area based on the quadratic difference method and the vegetation data; A first coefficient sequence is determined based on the crop planting pattern.

5. The method for determining the relationship between vegetation and ecological drought response according to claim 1, characterized in that: The ecological drought index sequence is determined according to the ecological water demand sequence, specifically: Determining a vegetation water deficit sequence based on the ecological water demand sequence; determining a cumulative distribution sequence based on the vegetation water deficit sequence; An ecological drought index sequence is determined according to the cumulative distribution sequence.

6. The method for determining the relationship between vegetation and ecological drought response according to claim 1, characterized in that: The response relationship between vegetation and ecological drought is determined according to the ecological drought index sequence, specifically: Obtain multiple preset vegetation index sequences and ecological drought index sequences of different time scales; Based on multiple vegetation indicator sequences and ecological drought index sequences at different time scales, the response relationship between vegetation and ecological drought is determined.

7. The method for determining the relationship between vegetation and ecological drought response according to claim 6, characterized in that: Based on multiple vegetation indicator sequences and ecological drought index sequences at different time scales, the response relationship between vegetation and ecological drought is determined, specifically: From the ecological drought index sequences of different time scales, the optimal ecological drought index sequence corresponding to each vegetation index sequence is obtained; According to each vegetation indicator sequence and its corresponding optimal ecological drought index sequence, the response relationship between vegetation and ecological drought is determined.

8. The method for determining the relationship between vegetation and ecological drought response according to claim 7, characterized in that: When the response relationship between vegetation and ecological drought is: the loss probability sequence of vegetation characteristics under different drought levels and the ecological drought threshold, the response relationship between vegetation and ecological drought is determined according to each vegetation indicator sequence and its corresponding optimal ecological drought index sequence, specifically: Determine a first edge distribution, a second edge distribution and a plurality of joint distributions according to each vegetation indicator sequence and its corresponding optimal ecological drought index sequence; Obtain drought grade series for the study area; Determine the loss probability sequence and ecological drought threshold of vegetation characteristics at different drought levels according to the first edge distribution, the second edge distribution, multiple joint distributions and drought level sequence; The first marginal distribution is the marginal distribution of each vegetation index sequence, the second marginal distribution is the marginal distribution of the optimal ecological drought index sequence, and the multiple joint distributions are the joint distributions of each vegetation index sequence and the optimal ecological drought index sequence.

9. The method for determining the relationship between vegetation and ecological drought response according to claim 8, characterized in that: According to the first edge distribution, the second edge distribution, multiple joint distributions and the drought level sequence, the loss probability sequence and ecological drought threshold of the vegetation characteristics under different drought levels are determined, specifically: Determine the loss probability sequence of vegetation characteristics at different drought levels and its corresponding confidence sequence according to the first marginal distribution, the second marginal distribution, multiple joint distributions, the drought level sequence and the conditional probability formula; The ecological drought index corresponding to the confidence level greater than the preset value in the confidence level sequence is used as the ecological drought threshold value under the corresponding drought level.

10. A method for determining the action path of factors affecting the relationship between vegetation and ecological drought response, characterized in that: The following steps are involved: Determine the ecological drought threshold of vegetation characteristics at different drought levels using the method for determining the relationship between vegetation and ecological drought response according to any one of claims 1 to 9; Constructing a path analysis model according to a plurality of preset influencing factors and the ecological drought threshold, wherein the plurality of preset influencing factors include meteorological factors, soil factors and vegetation factors; The action paths of the influencing factors of the relationship between vegetation and ecological drought response are determined according to the path analysis model.

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