A comprehensive assessment method for drought events based on physical mechanisms

Abstract

The present invention discloses a comprehensive evaluation method for drought events based on physical mechanisms, comprising: S100: extracting drought events using a daily-scale drought event recognition method; S200: obtaining daily drought intensity and corresponding time length of drought events, arranging them in descending order according to daily drought intensity and drawing a relationship curve between average drought intensity in the time domain and time length; obtaining a time coefficient based on the relationship curve; S300: obtaining grid point drought intensity and corresponding coverage area of ​​drought events, arranging them in descending order according to grid point drought intensity and drawing a relationship curve between average drought intensity in the space domain and coverage area; obtaining a space coefficient based on the relationship curve; S400: evaluating the comprehensive intensity of the extracted drought events according to the time coefficient and the space coefficient.

Description

Technical Field

[0001] The present application belongs to the technical field of drought event identification and assessment, and specifically relates to a comprehensive drought event assessment method based on physical mechanisms. Background Art

[0002] At a certain time and space boundary, water deficit characteristics continue to accumulate slowly, gradually forming drought phenomena. When drought phenomena develop to a certain extent, they may cause losses to economic and social development. In terms of time and space scales, drought intensity is generally used to quantify the severity of drought events. The distribution characteristics of drought intensity in a drought event are closely related to the economic and social losses it causes. Therefore, it is of great significance to study the spatiotemporal distribution function of drought intensity.

[0003] At present, most of the research on the intensity of drought events focuses on the distribution function analysis in the time domain, ignoring the dual distribution function analysis of drought intensity in the time and space domains, making it difficult to construct a universal distribution function equation for drought intensity in the time and space domains. Secondly, most of the existing overall evaluation methods for drought events are based on statistics, and indicators are constructed by weighted summation, specific function structure, etc. to conduct a comparative analysis of drought events as a whole. This method does not consider the nonlinear functional relationship of related characteristic variables, and does not construct an overall evaluation indicator of drought events containing physical mechanisms based on the theoretical statistical distribution of characteristic variables. In short, the current drought event evaluation methods generally have shortcomings such as incompleteness, lack of system, and lack of physical mechanisms. Summary of the invention

[0004] The purpose of this application is to provide a comprehensive drought event assessment method based on physical mechanisms to address the deficiencies mentioned in the background technology.

[0005] This application provides a comprehensive drought event assessment method based on physical mechanisms, including:

[0006] S100: Extracting drought events using daily-scale drought event identification method;

[0007] S200: Obtain the daily drought intensity and the corresponding time length of the drought event, arrange them in descending order according to the daily drought intensity and draw a relationship curve between the average drought intensity in the time domain and the time length; based on the relationship curve, obtain the scatter distribution of the natural logarithm of the average drought intensity in the time domain and the corresponding time length, perform linear regression fitting on the scatter distribution, and take the opposite of the slope of the linear regression line as the time coefficient a , take the intercept of the linear regression line as , It represents the theoretical average drought intensity in the time domain when the time length is equal to 1;

[0008] S300: Obtain the grid drought intensity and the corresponding coverage area of ​​the drought event, arrange them in descending order according to the grid drought intensity and draw a relationship curve between the average drought intensity in the spatial domain and the coverage area; based on the relationship curve, obtain the scattered distribution of the natural logarithm of the average drought intensity in the spatial domain and the corresponding coverage area, perform a univariate linear regression fitting on the scattered distribution, and take the opposite number of the univariate linear regression fitting line as the spatial coefficient b , take the intercept of the univariate linear regression fitting line as , It represents the average drought intensity in the theoretical spatial domain when the coverage area is 1;

[0009] S400: Based on time coefficient a and the spatial coefficient b ,use Evaluate the comprehensive intensity of the extracted drought events F ( n , s ),in, n represents the duration of the drought event, s represents the area covered by the drought event, Represents the average drought intensity in the spatiotemporal domain;

[0010] The calculation method is as follows: the drought event period n The grid points are arranged in descending order of daily drought intensity and the coverage area is taken s The average daily drought intensity of all grid points in the region, that is, the average drought intensity in the spatial and temporal domain.

[0011] In some specific embodiments, the method for extracting drought events using a daily-scale drought event identification method includes:

[0012] The following rules are used to identify drought events on a daily scale:

[0013] Rule 1: On the time scale, the thresholds for the beginning and end of drought events are set to -1;

[0014] Rule 2: In terms of time scale, if the time interval between two adjacent drought events is only one day and the SPEI value on that day is less than 0, the two adjacent drought events are merged, and the duration of the merged drought event is the sum of the duration of the two drought events, and the drought intensity is the sum of the drought intensity of the two drought events; otherwise, they are considered to be two independent drought events;

[0015] Rule 3: On a spatial scale, if 5% or more of the grid points in the study area have a drought index less than -1 on a certain day, and the grid point overlap rate between 15 consecutive drought days is ≥50%, it is judged as a spatiotemporally continuous drought event.

[0016] Furthermore, the comprehensive strength F( n , s ) includes:

[0017] (I) The relationship between the daily drought intensity and the duration of the drought event is obtained by arranging the daily drought intensity in descending order. Based on this relationship, a nonlinear function relationship of the average drought intensity in the time domain is constructed, as shown in equations (1) to (2). A differential equation is used to construct a distribution function relationship between the average drought intensity in the time domain and the duration, that is, a time domain model, as shown in equation (3).

[0018] (ii) Arrange the grid drought intensity in descending order to obtain the relationship between the grid drought intensity and the coverage area of ​​the drought event, and construct the nonlinear function relationship of the average drought intensity in the spatial domain based on this relationship, as shown in equations (4) to (5); use differential equations to construct the distribution function relationship between the average drought intensity in the spatial domain and the coverage area, that is, the spatial domain model, as shown in equation (6);

[0019] 3. Combining the temporal and spatial domain models, constructing a distribution function model of time length, coverage area and average drought intensity in time and space , recorded as the spatiotemporal domain model; among them, Indicates the length of time n , Coverage Area s The average drought intensity of drought events in the temporal and spatial domains under the condition of It represents the average drought intensity in theoretical time and space domain when the time length is 1 and the coverage area is 1;

[0020] (iv) Taking the inverse of the spatiotemporal model, the right side of the equation is the comprehensive intensity;

[0021] (1)

[0022] (2)

[0023] (3)

[0024] In formulas (1) to (3), represents the average drought intensity over time, represents the change in average drought intensity; T represents the length of time corresponding to the average drought intensity, Represents the change in time length, n Indicates the length of time; I e ( n ) indicates from 0 to time n Average drought intensity over time domain; I e (1) represents the theoretical average drought intensity in the time domain when the time length is equal to 1;

[0025] (4)

[0026] (5)

[0027] (6)

[0028] In formula (4)~(5): represents the average drought intensity in the spatial domain, Represents the average drought intensity change in the spatial domain; S Indicates the coverage area, Represents the change in coverage area; The coverage area is s The average drought intensity in the spatial domain at the time of Represents the theoretical spatial domain average drought intensity when the coverage area is 1.

[0029] Compared with the prior art, this application has the following characteristics and beneficial effects:

[0030] Starting from the overall drought event, this application establishes a dual distribution function of drought intensity in the spatiotemporal domain, and derives a comprehensive drought event assessment method with a physical mechanism based on the dual distribution function in the spatiotemporal domain. This application avoids direct comparison of different dimensional elements of time, space, and intensity, and realizes the spatiotemporal comparative analysis of the drought event situation, which facilitates a more comprehensive and systematic assessment of the overall characteristics of the drought event situation.

[0031] This application uses the derived comprehensive intensity to evaluate drought events, which does not require numerical normalization. After unifying the dimensions, quantitative comparisons can be made directly between different events and between different time and space of the same event, eliminating the misjudgment of drought conditions caused by comparisons of single drought characteristic quantities, laying the foundation for the stage division, spatial zoning, and spatiotemporal migration of drought conditions of drought events, which is beneficial to the diagnosis and early warning of drought events, and is of great significance for ensuring the smooth development of the social economy and strengthening drought relief and disaster reduction work. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 A schematic diagram of a process flow of an embodiment of the present application;

[0033] Figure 2 The figure is a schematic diagram of the relationship between the daily drought intensity and the duration of the drought event, wherein figure (a) shows the relationship between the daily drought intensity and the duration under the normal time series; figure (b) shows the relationship between the daily drought intensity and the duration under the new time series;

[0034] Figure 3Schematic diagram of grid drought intensity of drought events, where (a) is the schematic diagram of initial grid drought intensity, and (b) is the schematic diagram of reordered grid drought intensity;

[0035] Figure 4 The relationship curve between the average drought intensity and duration of drought events in the time domain in the embodiment

[0036] Figure 5 The relationship curve of the product value of the average drought intensity and the duration of drought in the embodiment changes with the duration;

[0037] Figure 6 is the scattered distribution of the natural logarithm of the average drought intensity of the drought event in the time domain and the natural logarithm of its duration in the embodiment;

[0038] Figure 7 is a relationship curve between the average drought intensity in the spatial domain and its corresponding coverage area in the embodiment;

[0039] Figure 8 is a relationship curve between the product value of spatial average drought intensity and coverage area of ​​drought events in the embodiment and the coverage area;

[0040] Fig. 9 Graph 1 is the scattered distribution of the natural logarithm of the spatial average drought intensity of drought events in the embodiment and the natural logarithm of their coverage area. DETAILED DESCRIPTION

[0041] The technical solution of this application and its specific implementation methods are described clearly and completely below. Obviously, the specific implementation methods described are only some of the specific implementation methods of this application and are not used to limit the scope of protection of this application. Based on the specific implementation methods in this application, all other specific implementation methods obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0042] In the comprehensive assessment method of drought events in this application, a self-defined comprehensive intensity is used to comprehensively assess drought events. The derivation process of comprehensive intensity is summarized as follows: construct the time domain model and space domain model of drought events respectively, the time domain model is the distribution function relationship between the average drought intensity and the time length in the time domain of drought events, and the space domain model is the distribution function relationship between the average drought intensity and the coverage area in the space domain of drought events; combine the time domain model and the space domain model to further construct a distribution function model of the time length, coverage area and the average drought intensity in time and space, recorded as the space-time domain model; define the comprehensive intensity based on the space-time domain model.

[0043] The derivation process of comprehensive strength will be described in detail below.

[0044] (i) Construct a nonlinear functional relationship of the average drought intensity in the time domain of drought events, and use differential equations to construct the distribution function relationship between the average drought intensity and the duration in the time domain, which is recorded as the time domain model;

[0045] See also Figure 2 (a) shows the relationship between the daily drought intensity and duration of drought events under normal time series. It can be seen from the figure that the daily drought intensity is scattered over time and has no strong regularity. Figure 2 (a) Arrange in descending order of daily drought intensity, and we get Figure 2 (b) shows the new time series relationship. Under the new time series, starting from the maximum daily drought intensity, as the time length increases, the daily drought intensity gradually decreases, and the average value of the daily drought intensity, that is, the average drought intensity in the time domain, decreases successively. Therefore, the average drought intensity in the latter period is less than that in the previous period. When the average drought intensity in the latter period is subtracted from the average drought intensity in the previous period, the result is less than 0, that is, the change in the average drought intensity in the latter period relative to the previous period is less than 0, while the change in time length is greater than 0. Therefore, the quotient of the change in average drought intensity and the change in time length is less than 0, that is, formula (1). At the same time, as the time length increases, the product value of the average drought intensity in the time domain and the time length also increases synchronously, and the quotient of the change in the product value and the change in time length is greater than 0, resulting in formula (2).

[0046] (1)

[0047] (2)

[0048] In formula (1)~(2): represents the average drought intensity over time, represents the change in average drought intensity; T represents the length of time corresponding to the average drought intensity, Represents the change in time length.

[0049] Formula (1) and Formula (2) are the nonlinear functional relationships of the average drought intensity in the time domain of the constructed drought events.

[0050] The combined equations (1) and (2) are derived into inequality (5). The derivation process is as follows:

[0051] (3)

[0052] (4)

[0053] (5)

[0054] Introducing the time factor a (0<a <1) Establish a differential equation that characterizes the functional relationship between the average drought intensity in the time domain and the duration, solve the differential equation, and finally obtain the functional relationship between the average drought intensity in the time domain and its duration. The specific process is as follows:

[0055] Introducing the time factor a ,make ,right Transform it and get:

[0056] (6)

[0057] Adjust the variable position in equation (6) to obtain:

[0058] (7)

[0059] Integrating both sides of equation (7) simultaneously gives:

[0060] (8)

[0061] (9)

[0062] According to formula (8)~(9), we can get:

[0063] (10)

[0064] In formulas (7) to (9): represents the natural logarithm; n Indicates the length of time in a certain state under the new time series; I e ( n ) indicates from 0 to time n Average drought intensity over time domain; I e (1) is a constant, which is greater than or equal to 1, representing the theoretical time domain average drought intensity when the time length is equal to 1.

[0065] (ii) Construct a nonlinear functional relationship of the average drought intensity in the spatial domain of drought events, and use differential equations to construct the distribution functional relationship between the average drought intensity and the coverage area in the spatial domain, which is recorded as the spatial domain model;

[0066] See also Figure 3 (a) shows a schematic diagram of the grid drought intensity of a drought event. As the drought intensity contour changes, the drought coverage area occupied by the contour also changes synchronously. In a specified spatial domain, within the range of days when drought occurs, the cumulative value of the drought intensity of a single grid point is called the grid drought intensity. The union of the drought occurrence area (i.e., the number of grid points) on a single day is called the coverage area. After the spatial position is disrupted, the grid drought intensity is arranged in descending order, see Figure 3 (b) As shown. Starting from the maximum grid drought intensity, as the coverage area increases, the grid drought intensity decreases, and the mean of the grid drought intensity corresponding to the coverage area, that is, the average drought intensity in the spatial domain, also decreases successively. Therefore, the average drought intensity corresponding to the latter coverage area is less than the previous one, and the average drought intensity of the latter coverage area minus the previous one is less than 0, that is, the change in the average drought intensity is less than 0, the change in the latter coverage area relative to the previous one is greater than 0, and the quotient of the change in the spatial domain average drought intensity and the change in the coverage area is less than 0, so equation (11) is obtained. At the same time, as the coverage area increases, the product value of the spatial domain average drought intensity and the coverage area also increases synchronously, and the quotient of the change in the product value and the change in the coverage area is greater than 0, so equation (12) is obtained.

[0067] (11)

[0068] (12)

[0069] In formula (11)~(12): represents the average drought intensity in the spatial domain, Represents the average drought intensity change in the spatial domain; S Indicates the coverage area, Represents the change in coverage area.

[0070] Equations (11) and (12) are the nonlinear functional relationships of the average drought intensity in the spatial domain of drought events.

[0071] By combining the nonlinear function relationship (11) and (12), we can derive the inequality (15). The derivation process is as follows:

[0072] (13)

[0073] (14)

[0074] (15)

[0075] Introducing the spatial coefficient b (0< b <1) Establish a differential equation that characterizes the functional relationship between the average drought intensity in the spatial domain and the coverage area, solve the differential equation, and finally obtain the functional relationship between the average drought intensity in the spatial domain and the coverage area. The specific process is as follows:

[0076] Introducing the spatial coefficient b ,make ,right Transform it and get:

[0077] (16)

[0078] (17)

[0079] Integrate both sides of equation (17):

[0080] (18)

[0081] (19)

[0082] (20)

[0083] In formulas (18) to (20): The coverage area is s The average drought intensity in the spatial domain at the time of Greater than or equal to 1, representing the theoretical spatial domain average drought intensity when the coverage area is 1.

[0084] (iii) Combining the temporal domain model and the spatial domain model, a distribution function model of time length, coverage area and spatiotemporal average drought intensity was constructed, which was recorded as the spatiotemporal domain model;

[0085] Two sets of theoretical differential equations are used to characterize the functional relationship between the average drought intensity in the time domain and the time length, and the functional relationship between the average drought intensity in the space domain and the coverage area. From equation (10), we can get equation (21), and from equation (20), we can get equation (22):

[0086] (twenty one)

[0087] (twenty two)

[0088] Solving the two sets of theoretical differential equations (21) to (22), we obtain the theoretical equation (26) for the relationship between time length, coverage area and average drought intensity in the spatiotemporal domain. The specific derivation process is as follows:

[0089] Take the values ​​of formula (21) and formula (22) respectively:

[0090] (twenty three)

[0091] (twenty four)

[0092] In formula (23)~(24): n The duration of drought events T The value of s represents the value of the drought event coverage area S; a represents the time coefficient; b Represents the spatial coefficient.

[0093] For formula (24), let s =1, we get:

[0094] (25)

[0095] Substituting formula (25) into formula (23) yields the spatiotemporal model:

[0096] (26)

[0097] In formulas (25) to (26): Indicates the length of time n , Coverage Area s The average drought intensity of drought events in the temporal and spatial domains under the condition of is a constant, representing the theoretical average drought intensity in spatiotemporal domain when the time length is 1 and the coverage area is 1.

[0098] 4. Define comprehensive intensity based on spatiotemporal domain model.

[0099] Specifically, take the inverse of equation (26) and let the right side of the equation be the comprehensive strength F ( n , s ):

[0100] (27)

[0101] In formula (27): Represents the average drought intensity in time and space; the unit of comprehensive intensity is day * km 2 .

[0102] See also Figure 1 , which is a schematic diagram of the process of the present application, will be referred to below Figure 1 The method of this application is described in detail.

[0103] S100: Extracting drought events using daily-scale drought event identification method;

[0104] Specifically, drought events are identified and extracted based on the run theory under the constraints of relevant rules. In order to exclude the interference of non-drought conditions such as rainless days, the following three rules are used to identify drought events on a daily scale:

[0105] Rule 1: On the time scale, the thresholds for the beginning and end of drought events are set to -1;

[0106] Rule 2: In terms of time scale, if the time interval between two adjacent drought events is only 1 day and the SPEI value on that day is less than 0, the two adjacent drought events are merged, and the duration of the merged drought event is the sum of the duration of the two drought events, and the drought intensity is the sum of the drought intensity of the two drought events; otherwise, they are considered to be two independent drought events;

[0107] Rule 3: On a spatial scale, if 5% or more of the grid points in the study area have a drought index less than -1 on a certain day, and the grid point overlap rate between 15 consecutive drought days is ≥50%, it is judged as a spatiotemporally continuous drought event.

[0108] The above SPEI value represents the Standardized Precipitation Evapotranspiration Index; the duration of a drought event is defined as the number of days from the time of occurrence to the time of end when the SPEI value is continuously less than the threshold; the drought intensity is defined as the absolute value of the difference between the SPEI value and the fixed threshold. In specific implementation, the fixed threshold is generally taken as the -0.5 threshold used in the SPEI index.

[0109] The calculation of the SPEI value is a conventional technique in the industry, and the specific calculation process will not be described in detail.

[0110] S200: Obtain the daily drought intensity and the corresponding time length of the drought event, arrange them in descending order according to the daily drought intensity and draw a relationship curve between the average drought intensity in the time domain and the time length; based on the relationship curve, obtain the scatter distribution of the natural logarithm of the average drought intensity in the time domain and the corresponding time length, perform linear regression fitting on the scatter distribution, and take the opposite number of the slope of the linear regression line as the time coefficient a , take the intercept of the linear regression line as , Represents the theoretical time domain average drought intensity when the time length is equal to 1.

[0111] S300: Obtain the grid drought intensity and the corresponding coverage area of ​​the drought event, arrange them in descending order according to the grid drought intensity and draw a relationship curve between the average drought intensity in the spatial domain and the coverage area; obtain the scattered point distribution of the natural logarithm of the average drought intensity in the spatial domain and the corresponding coverage area based on the relationship curve, perform linear regression fitting on the scattered point distribution, and take the opposite number of the linear regression fitting line as the spatial coefficient b , take the intercept of the linear regression fitting line as , Represents the theoretical spatial domain average drought intensity when the coverage area is 1.

[0112] S400: Based on time coefficient a and the spatial coefficient b ,use Evaluate the comprehensive intensity of extracted drought events F ( n ,s ),in, n represents the duration of the drought event, s represents the area covered by the drought event, Represents the average drought intensity in the spatiotemporal domain;

[0113] The calculation method is as follows: the drought event period n The grid points are arranged in descending order of daily drought intensity and the coverage area is taken s The average daily drought intensity of all grid points in the region, that is, the average drought intensity in the spatial and temporal domain.

[0114] The following will take the drought event that occurred in North China in July 1978 as a case to demonstrate the feasibility of this application.

[0115] Arrange the daily drought intensity of each drought event in descending order, and draw a curve of the relationship between the average drought intensity and the duration of the arranged time domain, see Figure 4 Each curve in the figure represents a drought event. It can be seen from the figure that with the increase of time length, the average drought intensity of all drought events gradually decreases, which verifies the correctness of formula (1). At the same time, the relationship curve between the product of average drought intensity and time length and the change of time length is plotted, see Figure 5 ,From the figure, it can be seen that as the time length increases, the product of the average drought intensity and ,the time length of all drought events gradually increases, verifying the correctness of formula (2).

[0116] Explain the physical meaning of the theoretical distribution function equation. The scattered distribution of the average drought intensity in the time domain and the natural logarithm of its duration is shown in Figure 6 As shown in the figure, the dotted line is the linear regression of the average drought intensity and the length of time in the same period, and the inverse of the dotted line slope represents the time coefficient a The intercept value of the regression equation is . It is proved that there is a linear negative correlation between the average drought intensity in the time domain and the natural logarithm of the time length on the time scale.

[0117] Arrange the drought intensity of drought events in descending order, and draw the relationship curve between the average drought intensity in the spatial domain and its corresponding coverage area. Figure 7 As shown in the figure, each curve represents a drought event. As the number of grid points increases, the coverage area increases, and the average drought intensity in the spatial domain gradually decreases, which verifies the correctness of formula (11). Calculate the product of the average drought intensity in the spatial domain and the coverage area, and draw a curve of the relationship between the product value and the coverage area, as shown in Figure 8 As shown in the figure, each curve represents a drought event. As the coverage area increases, the product of the spatial average drought intensity and its coverage area increases synchronously, which verifies the correctness of formula (12).

[0118] The scattered distribution of the natural logarithm of the spatial average drought intensity and its coverage area is as follows: Fig. 9 As shown, the dotted line is the univariate linear regression result of the scattered points. Fig. 9 The opposite of the slope of the dashed line is the space coefficient b The intercept value of the regression equation is . It is proved that there is a linear negative correlation between the average drought intensity in the spatial domain and the natural logarithm of the coverage area on a spatial scale. The deviation of some scattered points from the linear regression equation may be related to two errors. First, the error in drought event identification. When using the run theory and corresponding rules to identify and screen drought events, it is difficult to accurately characterize the natural boundaries of drought events due to the setting of thresholds. Second, drought events often show phenomena such as splitting, fusion, and multi-centers in spatial distribution, which often cause related errors in drought event identification.

[0119] Note that the above are only preferred embodiments of the present application and the technical principles used. Those skilled in the art will understand that the present application is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the protection scope of the present application. Therefore, although the present application is described in more detail through the above embodiments, the present application is not limited to the above embodiments, and may also include more other equivalent embodiments without departing from the concept of the present application, all of which belong to the protection scope of the present application.

Claims

1. A comprehensive drought event assessment method based on physical mechanisms, characterized by: include: S100: Extracting drought events using daily-scale drought event identification method; S200: Obtain the daily drought intensity and the corresponding time length of the drought event, arrange them in descending order according to the daily drought intensity and draw a relationship curve between the average drought intensity in the time domain and the time length; based on the relationship curve, obtain the scatter distribution of the natural logarithm of the average drought intensity in the time domain and the corresponding time length, perform linear regression fitting on the scatter distribution, and take the opposite of the slope of the linear regression line as the time coefficient a , take the intercept of the linear regression line as , It represents the theoretical average drought intensity in the time domain when the time length is equal to 1; S300: Obtain the grid drought intensity and the corresponding coverage area of ​​the drought event, arrange them in descending order according to the grid drought intensity and draw a relationship curve between the average drought intensity in the spatial domain and the coverage area; based on the relationship curve, obtain the scattered distribution of the natural logarithm of the average drought intensity in the spatial domain and the corresponding coverage area, perform a univariate linear regression fitting on the scattered distribution, and take the opposite number of the univariate linear regression fitting line as the spatial coefficient b , take the intercept of the univariate linear regression fitting line as , It represents the average drought intensity in the theoretical spatial domain when the coverage area is 1; S4 00: According to the time coefficient a and the spatial coefficient b ,use Evaluate the comprehensive intensity of the extracted drought events F ( n , s ),in, n represents the duration of the drought event, s represents the area covered by the drought event, Represents the average drought intensity in the spatiotemporal domain; The calculation method is as follows: the drought event period n The grid points are arranged in descending order of daily drought intensity and the coverage area is taken s The average daily drought intensity of all grid points in the region, that is, the average drought intensity in the spatial and temporal domain.

2. The method for comprehensive drought assessment based on physical mechanism according to claim 1, characterized in that: The method for extracting drought events using the daily scale drought event identification method includes: The following rules are used to identify drought events on a daily scale: Rule 1: On the time scale, the thresholds for the beginning and end of drought events are set to -1; Rule 2: In terms of time scale, if the time interval between two adjacent drought events is only one day and the SPEI value on that day is less than 0, the two adjacent drought events are merged, and the duration of the merged drought event is the sum of the duration of the two drought events, and the drought intensity is the sum of the drought intensity of the two drought events; otherwise, they are considered to be two independent drought events; Rule 3: On a spatial scale, if 5% or more of the grid points in the study area have a drought index less than -1 on a certain day, and the grid point overlap rate between 15 consecutive drought days is ≥50%, it is judged as a spatiotemporally continuous drought event.

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