Method and system for identifying asymmetric meteorological drought-flood rapid transition events

Abstract

The embodiment of the application discloses a kind of asymmetric meteorological waterlogging drought acute change event identification method and system.The method is by in time scale to the first precipitation data of target area in preset time is handled to obtain the second precipitation data of decadal time series, and based on asymmetric mode, according to the second precipitation data, generate the first standardized precipitation index of target area in single decadal time series and the second standardized precipitation index in multiple decadal time series, then according to the first standardized precipitation index and the second standardized precipitation index, determine the flood and drought event of target area in preset time in time series, finally, according to the flood and drought event of target area in preset time in time series, the waterlogging drought acute change event of target area in preset time can be accurately identified, it has important theoretical significance and application value to the risk assessment of extreme event, the formulation of disaster prevention and mitigation measures.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of water conservancy engineering, and particularly relates to a method and system for identifying an asymmetric meteorological waterlogging and drought sudden change event. BACKGROUND

[0002] Waterlogging and drought sudden change events are usually defined as the rapid transition of two states of drought and waterlogging, including waterlogging-to-drought events and drought-to-waterlogging events, i.e., meteorological waterlogging and drought sudden change events specifically refer to waterlogging-to-drought events. How to accurately identify waterlogging and drought sudden change events is a prerequisite and basis for studying the spatiotemporal evolution characteristics and influences of waterlogging and drought sudden change events, and has important theoretical significance and application value for risk assessment of extreme events and development of disaster prevention and mitigation measures. SUMMARY

[0003] In view of the deficiencies in the prior art, the present application provides a method and system for identifying an asymmetric meteorological waterlogging and drought sudden change event, aiming to solve the technical problem of low accuracy in identifying waterlogging and drought sudden change events in the prior art.

[0004] In a first aspect, the present application provides a method for identifying an asymmetric meteorological waterlogging and drought sudden change event, which comprises:

[0005] processing first precipitation data of a target region within a preset time to obtain second precipitation data of a ten-day scale time series;

[0006] generating, according to the second precipitation data, a first standardized precipitation index of the target region under a single ten-day scale time series and a second standardized precipitation index of the target region under a multi-ten-day scale time series;

[0007] determining a waterlogging event of the target region on a time series within the preset time according to the first standardized precipitation index, and determining a drought event of the target region on the time series within the preset time according to the second standardized precipitation index;

[0008] identifying a waterlogging and drought sudden change event of the target region within the preset time according to the waterlogging event and the drought event of the target region on the time series within the preset time.

[0009] In a second aspect, the present application provides a device for identifying an asymmetric meteorological waterlogging and drought sudden change event, which comprises:

[0010] a processing unit configured to process first precipitation data of a target region within a preset time to obtain second precipitation data of a ten-day scale time series;

[0011] a generating unit configured to generate, according to the second precipitation data, a first standardized precipitation index of the target region under a single ten-day scale time series and a second standardized precipitation index of the target region under a multi-ten-day scale time series;

[0012] The determining unit is configured to determine a flood event of the target region in a time sequence within a preset time according to a first standardized precipitation index, and determine a drought event of the target region in the time sequence within the preset time according to a second standardized precipitation index.

[0013] The identifying unit is configured to identify a flood-drought abrupt change event of the target region within the preset time according to the flood event and the drought event of the target region in the time sequence within the preset time.

[0014] In a third aspect, an electronic device is provided, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the asymmetric meteorological flood-drought abrupt change event identification method provided in the first aspect is implemented.

[0015] In a fourth aspect, a computer readable storage medium is provided, which stores a computer program, and when the computer program is executed by a processor, the processor executes the asymmetric meteorological flood-drought abrupt change event identification method provided in the first aspect.

[0016] In a fifth aspect, a computer program product is provided, which includes a computer program or instructions, and the computer program or instructions are executed by a processor to implement the asymmetric meteorological flood-drought abrupt change event identification method provided in the first aspect.

[0017] In a sixth aspect, an asymmetric meteorological flood-drought abrupt change event identification system is provided, which is applied to the asymmetric meteorological flood-drought abrupt change event identification method provided in the first aspect.

[0018] The asymmetric meteorological flood-drought abrupt change event identification method and system provided by the embodiments of the present application can accurately identify the flood-drought abrupt change event of the target region within the preset time according to the flood event and the drought event of the target region in the time sequence within the preset time, which has important theoretical significance and application value for the risk assessment of extreme events and the development of disaster prevention and mitigation measures. BRIEF DESCRIPTION OF DRAWINGS

[0019] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0020] Figure 1 A flowchart of the asymmetric meteorological waterlogging and drought sudden change event identification method provided by the embodiment of the present application is shown in the figure.

[0021] Figure 2 A 2022 regional middle and lower reaches ten-scale precipitation sequence diagram provided by the embodiment of the present application is shown in the figure.

[0022] Figure 3 A 2022 single ten-scale SPI sequence and flood event marking diagram provided by the embodiment of the present application is shown in the figure.

[0023] Figure 4 A 2022 six ten-scale SPI sequence and drought event marking diagram provided by the embodiment of the present application is shown in the figure.

[0024] Figure 5 A distribution diagram of the identified waterlogging and drought sudden change event provided by the embodiment of the present application is shown in the figure.

[0025] Figure 6 A 2022 typical waterlogging and drought sudden change event development process diagram provided by the embodiment of the present application is shown in the figure.

[0026] Figure 7 A schematic block diagram of the asymmetric meteorological waterlogging and drought sudden change event identification device provided by the embodiment of the present application is shown in the figure.

[0027] Figure 8 A schematic block diagram of the electronic device provided by the embodiment of the present application is shown in the figure. DETAILED DESCRIPTION

[0028] The technical solutions in the embodiments of the present application will be described clearly and completely in the following with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0029] It should be understood that when used in the specification and the appended claims, the terms "comprise" and "include" indicate the presence of described features, integers, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or collections thereof.

[0030] It should also be understood that the terms used in the specification herein are for the purpose of describing particular embodiments and do not intend to limit the application. As used in the specification and the appended claims herein, the singular forms "a," "an" and "the" are intended to include plural forms unless the context clearly dictates otherwise.

[0031] It should be further understood that the term "and / or" used in the specification and the appended claims herein means one or more of the associated listed items as well as all possible combinations of the items and includes these combinations.

[0032] In addition, in this application, unless otherwise explicitly specified or limited in the embodiments, the terms "mounting", "connecting", "connecting" and "fixing" and the like appearing in the embodiments should be understood broadly, for example, the connection can be fixed connection, or detachable connection, or integral, which can be understood, or mechanical connection, electrical connection, etc. Of course, it can also be directly connected, or indirectly connected through an intermediate medium, or the internal communication of two elements, or the interaction relationship of two elements. For those skilled in the art, the specific meaning of the above terms in this application can be understood according to the specific implementation situation.

[0033] In related art, in the process of studying drought and flood sudden alternation events, a continuous drought and flood sudden alternation intensity index time series is first constructed, and then the event is identified based on the sequence. For example, the short-cycle drought and flood sudden alternation index (SDFAI) and the daily-scale drought and flood sudden alternation index (DWAAI) are constructed based on the difference between the two adjacent periods of precipitation and the sum of the absolute values. However, the short-cycle drought and flood sudden alternation index (SDFAI) and the daily-scale drought and flood sudden alternation index (DWAAI) are difficult to avoid misjudgment and omission.

[0034] Based on this, the idea of first determining the drought and flood sudden alternation event and then calculating the event intensity can be used, and then the drought and flood sudden alternation event can be quantified relatively accurately, such as the standardized drought and flood sudden alternation index (SDWAI), which can first identify the existence of drought and flood sudden alternation between two consecutive periods based on the traditional drought index, such as SPI (standardized precipitation index) or SRI (Standardized Runoff Index), and then calculate the drought and flood sudden alternation intensity.

[0035] However, the development process of flood is rapid, and a typical flood process of a relatively large basin generally does not exceed one month, but the development process of drought is slow, and a drought process generally lasts for several months or even more than one year. Although the standardized flood-drought abrupt change index can relatively accurately identify the flood-drought abrupt change process, the time scale of quantifying drought and flood is still symmetrical, such as when the standardized precipitation index of a single month scale is used to identify events, if the standardized precipitation index of the previous month is greater than 1 and the standardized precipitation index of the current month is less than -1, it is determined that there is a flood-drought abrupt change event. However, one month is too long for the time scale of flood events and too short for the time scale of drought events, which leads to low accuracy of the final identified flood-drought abrupt change event.

[0036] Therefore, the application provides a method and system for identifying an asymmetric meteorological flood-drought abrupt change event. The method processes first precipitation data of a target region within a preset time on a time scale to obtain second precipitation data of a ten-day time series, generates a first standardized precipitation index of the target region in a single ten-day time series and a second standardized precipitation index of the target region in a multi-ten-day time series based on an asymmetric manner according to the second precipitation data, determines a flood event and a drought event of the target region within the preset time on a time series according to the first standardized precipitation index and the second standardized precipitation index, and finally accurately identifies a flood-drought abrupt change event of the target region within the preset time according to the flood event and the drought event of the target region within the preset time on the time series. The method has important theoretical significance and application value for risk assessment of extreme events and development of disaster prevention and mitigation measures.

[0037] It can be understood that the method for identifying an asymmetric meteorological flood-drought abrupt change event provided by the embodiments of the application can be applied to a terminal device, and the method is implemented in application software installed in the terminal device to identify the flood-drought abrupt change event. The terminal device can be a desktop computer, a notebook computer, a tablet computer, or a mobile phone.

[0038] It should be noted that the application scenarios described in the following embodiments of the application are used to more clearly illustrate the technical solutions of the embodiments of the application, and do not constitute a limitation on the technical solutions provided by the embodiments of the application. It can be known by those skilled in the art that the technical solutions provided by the embodiments of the application are also applicable to similar technical problems as new application scenarios appear.

[0039] The method for identifying an asymmetric meteorological flood-drought abrupt change event provided by the application will be described in detail below.

[0040] As Figure 1As shown, the method comprises steps S110-S130.

[0041] S110, processing the first precipitation data of the target region in the preset time to obtain the second precipitation data of the ten-scale time series.

[0042] In the present application, the target region can be understood as the region where a certain river basin is located, such as the middle and lower reaches of the Yangtze River, the preset time includes one month, several months, half a year, one year and more than one year, and the first precipitation data can be understood as the daily-scale long-sequence precipitation data collected by the target region in the preset time, i.e. the daily average collected precipitation data of the collection site in the target region in the preset time. At the same time, the first precipitation data can also be understood as the total precipitation data of the target region in the preset time, which can be selected according to actual application, and the present application does not make specific limitation.

[0043] Specifically, the present application can process the first precipitation data of the target region in the preset time in units of ten, which can be specifically summed to obtain the second precipitation data of the ten-scale time series. Wherein, the second precipitation data can be understood as the ten-scale time series precipitation data of the target region in the preset time, i.e. the precipitation data collected by the collection site in the target region in the preset time every ten.

[0044] S120, according to the second precipitation data, generating a first standardized precipitation index of the target region in a single ten-scale time series and a second standardized precipitation index of the target region in a multi-ten-scale time series.

[0045] In the present application, the first standardized precipitation index can be understood as being used for identifying the flood event of the target region, which can be characterized by SPI-1x; the second standardized precipitation index can be understood as being used for identifying the drought event of the target region, which can be characterized by SPI-6x.

[0046] Specifically, in the process of identifying the rapid transition event of flood and drought, the commonly used standardized precipitation index (SPI) is usually selected for identifying the rapid transition event of flood and drought, while the present application uses the single-ten-scale SPI for identifying the flood event and uses the two-month (i.e. 6-ten) scale SPI for identifying the drought event. Wherein, a single ten can be understood as 10 days, and multiple tens can be understood as multiple tens of days. The multiple tens mentioned in the present application can be understood as 6 tens, i.e. the second standardized precipitation index can be understood as the standardized precipitation index of the target region in 60 days, and the first standardized precipitation index can be understood as the standardized precipitation index of the target region in 10 days.

[0047] S130, determining a flood event of the target region in a time sequence in the preset time according to the first standardized precipitation index, and determining a drought event of the target region in the time sequence in the preset time according to the second standardized precipitation index.

[0048] Specifically, when the first standardized precipitation index and the second standardized precipitation index are used to determine the flood event and the drought event respectively, the run theory can be used to identify the flood event and the drought event. When the first standardized precipitation index is greater than 1, it can be determined that the flood occurs; when the second standardized precipitation index is less than -1, it can be determined that the drought occurs.

[0049] S140, identifying a flood-drought rapid transition event of the target region in the preset time according to the flood event and the drought event of the target region in the time sequence in the preset time.

[0050] Specifically, after the flood event and the drought event of the target region in the time sequence in the preset time are determined by the first standardized precipitation index and the second standardized precipitation index, whether the flood-drought rapid transition event occurs in the preset time and the number of times of the flood-drought rapid transition event occurring in the preset time can be accurately determined through the adjacent flood event and drought event in the time sequence, so that the corresponding features of the flood-drought rapid transition event can be accurately extracted for subsequent risk assessment of extreme events and development of disaster prevention and mitigation measures, which has important theoretical significance and application value.

[0051] In some embodiments, the first precipitation data includes a long sequence of daily third precipitation data; the first precipitation data of the target region in the preset time is processed to obtain the second precipitation data of the time sequence in the decade scale, including: in the preset time, obtaining the long sequence of daily third precipitation data of the target region; and summing the third precipitation data to obtain the second precipitation data of the time sequence in the decade scale.

[0052] In the present application, the first precipitation data can include a plurality of third precipitation data, and the first precipitation data can also be understood as the total precipitation data of the target region in the preset time, and the third precipitation data can be understood as the daily precipitation data of the target region in the preset time, i.e. the precipitation data characterized by a long sequence of daily scale.

[0053] Specifically, in the process of processing the first precipitation data of the target region in the preset time to obtain the second precipitation data of the time sequence in the decade scale, the long sequence of daily third precipitation data of the target region in the preset time can be obtained, and then the third precipitation data is summed to obtain the second precipitation data of the time sequence in the decade scale.

[0054] In some embodiments, according to the second precipitation data, the first standardized precipitation index of the target region in the single-decade time series and the second standardized precipitation index of the target region in the multi-decade time series are generated by: summing the second precipitation data in the single-decade time series by using a multi-decade sliding window to obtain fourth precipitation data in the multi-decade time series; and processing the second precipitation data and the fourth precipitation data by using a standardized precipitation index algorithm to obtain the first standardized precipitation index of the target region in the single-decade time series and the second standardized precipitation index of the target region in the multi-decade time series.

[0055] Specifically, since the time scales used by the application to identify flood events and drought events are different, in the process of identifying flood events, the precipitation index of the flood event is generated by processing the first precipitation data in the single-decade time series, and the precipitation index of the drought event is generated by processing the precipitation data in the multi-decade time series. Therefore, after obtaining the second precipitation data in the single-decade time series, the application determines the specific value of the multi-decade corresponding to the drought event, such as 6 decades. At this time, a sliding window with a preset length (such as two months) can be used to sum adjacent multiple second precipitation data to obtain third precipitation data in the multi-decade (6-decade) time series. Then, the second precipitation data and the third precipitation data are processed to obtain the first standardized precipitation index corresponding to the flood event and the second standardized precipitation index corresponding to the drought event.

[0056] In some embodiments, the second precipitation data and the fourth precipitation data are processed by using a standardized precipitation index algorithm to obtain the first standardized precipitation index of the target region in the single-decade time series and the second standardized precipitation index of the target region in the multi-decade time series, including: processing the second precipitation data and the fourth precipitation data by using a probability density function to determine the first distribution probability of the target region in the single-decade time series and the second distribution probability of the target region in the multi-decade time series; and performing normal standardization on the first distribution probability and the second distribution probability to determine the first standardized precipitation index and the second standardized precipitation index.

[0057] In the application, since the distribution of precipitation is generally not a normal distribution, but a skewed distribution, in the process of precipitation analysis and drought monitoring and evaluation, the change of precipitation can be described by using a distribution probability, and specifically, a The probability density function of the distribution is used to process the second precipitation data and the fourth precipitation data respectively to determine the first distribution probability of the target region under a single-decade time sequence and the second distribution probability under a multi-decade time sequence respectively; and the first distribution probability and the second distribution probability are processed by normal standardization to determine the first standardized precipitation index and the second standardized precipitation index.

[0058] Specifically, in the process of calculating the first standardized precipitation index and the second standardized precipitation index, the probability density function of the distribution can be used to describe the change of the precipitation, and then inverse standardization processing is performed. The specific steps are as follows:

[0059] Suppose that the cumulative precipitation in a period of time is a random variable , then the corresponding distribution probability density function is:

[0060] , x>0 (D.1)

[0061] In the formula, the distribution is a scale parameter and a shape parameter, and can be estimated by maximum likelihood method, as follows:

[0062] (D.2)

[0063] (D.3)

[0064] Wherein:

[0065] (D.4)

[0066] In the formula, is a sample sequence of the precipitation, and is the sample mean.

[0067] After the parameters are determined, the probability density function is used to obtain the cumulative probability density of the random variable less than a specific precipitation by using a numerical integration method:

[0068] (D.5)

[0069] The probability of the precipitation being 0 is calculated as follows:

[0070] (D.6)

[0071] In the formula, represents the number of samples with the precipitation being 0, and is the total number of samples.​

[0072] Finally, the cumulative probability function is inversely normalized, that is:

[0073] (D.7)

[0074] Approximate solution can be obtained:

[0075] (D.8)

[0076] In the formula, F is the probability obtained by formula (D.5) or formula (D.6); when , the value is , ; when , .

[0077] In the formula, c0=2.515517, c1=0.802853, c2=0.010328, d1=1.432788, d2=0.189269, d3=0.001308.

[0078] Further, the Z value obtained by formula (D.8) is the first standardized precipitation index and the second standardized precipitation index mentioned in the application.

[0079] Wherein, the drought and flood grade division table based on the SPI index is shown in Table 1:

[0080] Table 1 Drought and flood grade division based on SPI index

[0081]

[0082] In some embodiments, according to the flood and drought events on the time series of the target region within the preset time, the drought-flood rapid transition event of the target region within the preset time is identified, including: according to the flood and drought events on the time series of the target region within the preset time, determining the first interval time between adjacent flood and drought events on the time series, and the second interval time of the drought development period corresponding to the drought event; according to the first interval time and the second interval time, determining the target interval time between adjacent flood and drought events on the time series; if the target interval time exceeds a preset threshold, it is determined that the target region has a drought-flood rapid transition event within the preset time.

[0083] Specifically, in the process of identifying the flood-drought abrupt transition event of the target region in the preset time, after identifying the flood event and the drought event of the target region in the time sequence in the preset time, the first interval time between adjacent flood events and drought events in the time sequence is determined according to the flood event and the drought event of the target region in the time sequence in the preset time. Since the SPI sequence of 6 months is used for drought, the first month of the drought development period is taken as the starting point of drought in the calculation of the interval, and therefore the second interval time of the drought development period corresponding to the drought event needs to be determined, and the first interval time is subtracted by the second interval time, and then the target interval time between adjacent flood events and drought events in the time sequence can be obtained. Then it is judged whether the target interval time exceeds the preset threshold value, if it exceeds, it is determined that the target region has the flood-drought abrupt transition event in the preset time. The second interval time can be 5 months, and the preset threshold value can be 3 months, that is, the interval between flood and drought does not exceed 1 month, which is used to judge the abrupt transition process.

[0084] In some embodiments, after identifying the flood-drought abrupt transition event of the target region in the preset time according to the first standardized precipitation index and the second standardized precipitation index, the fifth precipitation data between the flood event and the drought event corresponding to the flood-drought abrupt transition event is obtained, and at least one of the duration, the abrupt transition period, the abrupt transition point, the average intensity and the intensity of the flood-drought abrupt transition event of the target region is determined according to the fifth precipitation data.

[0085] Specifically, after identifying the flood-drought abrupt transition event of the target region in the preset time, the event feature extraction of the flood-drought abrupt transition event is needed, so as to facilitate the subsequent research on the spatio-temporal evolution characteristics and influence of the flood-drought abrupt transition event, and the risk assessment of extreme events, the development of disaster prevention and mitigation measures have important theoretical significance and application value.

[0086] In the present application, after identifying the flood-drought abrupt transition event of the target region in the preset time, the fifth precipitation data between the flood event and the drought event corresponding to the flood-drought abrupt transition event can be obtained, and at least one of the duration, the abrupt transition period, the abrupt transition point, the average intensity and the intensity of the flood-drought abrupt transition event of the target region is determined according to the fifth precipitation data, and at least one of the duration, the abrupt transition period, the abrupt transition point, the average intensity and the intensity of the flood-drought abrupt transition event is extracted as the event feature, so as to facilitate the subsequent research on the spatio-temporal evolution characteristics and influence of the flood-drought abrupt transition event, and then facilitate the corresponding measures for the subsequent risk assessment of extreme events, the development of disaster prevention and mitigation measures.

[0087] In some embodiments, according to the fifth precipitation data, determining at least one of the duration, the transition period, the transition point, the average intensity and the intensity of the flood-drought transition event in the target region comprises: determining the duration of the flood-drought transition event, the first time of the flood event and the second time of the drought event in the flood-drought transition event according to the fifth precipitation data; the first time comprises the first start time and the first end time of the flood event, and the second time comprises the second start time and the second end time of the drought event; determining the duration of the target region in the flood-drought transition event according to the first start time and the second end time, and determining the transition period and the transition point according to the first end time and the second start time; determining the average intensity according to the first start time, the first end time, the second start time and the duration; and determining the intensity according to the first standardized precipitation index and the second standardized precipitation index corresponding to the flood-drought transition event.

[0088] In the present application, the first time comprises the first start time and the first end time of the flood event, and the second time comprises the second start time and the second end time of the drought event. The duration defined as the length of the period between the start time of the flood in the event and the end time of the drought, if the start time of the flood is later than the start time of the drought, the duration is the duration of the drought event. The duration It can be expressed by the following formula:

[0089]

[0090] wherein, the end time of the drought, the start time of the flood.

[0091] The transition period defined as the intermediate period between the end time of the flood and the start time of the drought, the transition period It can be expressed by the following formula:

[0092]

[0093] wherein, the start time of the drought, the end time of the flood.

[0094] The average intensity defined as the difference between the sum of the SPI-1x of each decade during the flood and the sum of the SPI-6x of each decade during the drought in the event divided by the difference between the duration and the transition period, and the specific definition is as follows:

[0095]

[0096] the average intensity, , respectively are the start and end time of flooding in the event, , respectively are the start and end time of drought in the event, is the duration of the flood-drought abrupt transition event, denotes the SPI-1x value corresponding to the i th decade, denotes the SPI-6x value corresponding to the j th decade.

[0097] In some embodiments, the intensity is determined according to the first and second standardized precipitation indices corresponding to the flood-drought abrupt transition event, comprising: determining a first target precipitation index and a second target precipitation index from the plurality of first and second standardized precipitation indices of the target region within the preset time; and determining the intensity according to the first and second target precipitation indices.

[0098] Specifically, since there can be multiple flood events and multiple drought events in the target region within the preset time, the intensity of the flood-drought abrupt transition event can be determined according to the maximum first standardized precipitation index value and the minimum second standardized precipitation index value in the flood event in the process of determining the intensity according to the first and second standardized precipitation indices corresponding to the flood-drought abrupt transition event, i.e., determining a first target precipitation index and a second target precipitation index from the plurality of first and second standardized precipitation indices of the target region within the preset time, and finally determining the intensity according to the first and second target precipitation indices. The first target precipitation index is selected from the plurality of first standardized precipitation indices, and the first target precipitation index can be the maximum precipitation index in the plurality of first standardized precipitation indices; the second target precipitation index is selected from the plurality of second standardized precipitation indices, and the second target precipitation index can be the minimum precipitation index in the plurality of second standardized precipitation indices.

[0099] In this application, the intensity is defined as half of the difference between the maximum SPI-1x value in the flood period and the minimum SPI-6x value in the drought period, and the formula is as follows:

[0100]

[0101] wherein, is the intensity of the event, denotes the maximum value in the sequence, denotes the minimum value in the sequence, the value of corresponds to the decade corresponding to the flood period, the value of corresponds to the decade corresponding to the drought period.

[0102] The following application selects a certain regional middle and lower reaches as an example to illustrate the identification method of the asymmetric meteorological flood-drought rapid transition event provided by the application, and the specific steps are as follows:

[0103] (1) Select high-precision long-duration (1960-2023) daily precipitation product CHM_PRE v2, extract the grid data of the middle and lower reaches of a certain region, and calculate the area average precipitation. Further process the data into decadal time series to obtain the decadal precipitation sequence as shown in Figure 2 ;

[0104] (2) Calculate the single-decadal SPI-1x sequence and the 6-decadal SPI-6x sequence respectively, and mark the flood and drought events. The figures shown in Figure 3 and Figure 4 are presented, it can be found that flood events occurred in late January, early February, late March, late April, mid-June and late November 2022, and drought events occurred from mid-August to mid-November;

[0105] (3) Set the maximum interval to 3 decadal, identify the flood-drought rapid transition event based on the marked flood and drought events. Since the SP1-6x value is the window cumulative value of the current decadal and the previous 5 decadal, the previous 5 decadal of the drought event is the drought development period, and the calculation interval should be deducted. A total of 38 events are identified by calculation, and the event process is shown in Figure 5 , the flood period is marked as 1, the rapid transition process is marked as 0, and the drought period is marked as -1;

[0106] (4) Based on the identified flood-drought rapid transition event, calculate the event duration, average intensity, intensity, and rapid transition point. The characteristics of the 38 flood-drought rapid transition events are shown in Table 2.

[0107] Table 2 Characteristics of the 38 identified flood-drought rapid transition events

[0108]

[0109] The application takes the flood-drought rapid transition event in 2022 as an example to present the development process of the flood-drought rapid transition event as shown in Figure 6 , the flood event and the drought event lasted for 16 decadal from mid-June to mid-November, the flood period was in mid-June, the drought development period was from late June to early August, and the drought period was from mid-August to mid-November; at the same time, the rapid transition period of the flood-drought event lasted for 5 decadal, the rapid transition point was in late July, the average intensity was 2.59, and the intensity was 2.58.

[0110] In the asymmetric meteorological waterlogging and drought abrupt change event identification method provided in the embodiments of the present application, the first precipitation data of a target region in a preset time is processed in a time scale to obtain second precipitation data of a ten-day time series, and based on an asymmetric manner, first standardized precipitation indices of the target region in a single ten-day time series and second standardized precipitation indices of the target region in a multi-ten-day time series are generated according to the second precipitation data, then a waterlogging event and a drought event of the target region in the preset time in a time series are determined according to the first standardized precipitation indices and the second standardized precipitation indices, and finally, a waterlogging and drought abrupt change event of the target region in the preset time can be accurately identified according to the waterlogging event and the drought event of the target region in the preset time in the time series, which has important theoretical significance and application value for risk assessment of extreme events and development of disaster prevention and mitigation measures.

[0111] The embodiments of the present application also provide an asymmetric meteorological waterlogging and drought abrupt change event identification device 200, which is used to execute any one of the foregoing asymmetric meteorological waterlogging and drought abrupt change event identification methods.

[0112] Specifically, refer to Figure 7 , Figure 7 FIG. 1 is a schematic block diagram of an asymmetric meteorological waterlogging and drought abrupt change event identification device 200 provided in the embodiments of the present application.

[0113] As Figure 7 shown, the asymmetric meteorological waterlogging and drought abrupt change event identification device 200 provided in the present application includes a processing unit 210, a generating unit 220, a determining unit 230 and an identifying unit 240.

[0114] The processing unit 210 is configured to process first precipitation data of a target region in a preset time to obtain second precipitation data of a ten-day time series; the generating unit 220 is configured to generate first standardized precipitation indices of the target region in a single ten-day time series and second standardized precipitation indices of the target region in a multi-ten-day time series according to the second precipitation data; the determining unit 230 is configured to determine a waterlogging event of the target region in the preset time in a time series according to the first standardized precipitation indices, and determine a drought event of the target region in the preset time in the time series according to the second standardized precipitation indices; and the identifying unit 240 is configured to identify a waterlogging and drought abrupt change event of the target region in the preset time according to the waterlogging event and the drought event of the target region in the preset time in the time series.

[0115] The asymmetric meteorological waterlogging and drought sudden change event identification device 200 provided by the embodiment can process the first precipitation data of the target region in the preset time on a time scale to obtain second precipitation data of a ten-day time series, and generate a first standardized precipitation index of the target region in a single ten-day time series and a second standardized precipitation index of the target region in a multi-ten-day time series based on an asymmetric manner according to the second precipitation data, and then determine a waterlogging event and a drought event of the target region in the preset time on a time series according to the first standardized precipitation index and the second standardized precipitation index, and finally, according to the waterlogging event and the drought event of the target region in the preset time on the time series, the waterlogging and drought sudden change event of the target region in the preset time can be accurately identified, which has important theoretical significance and application value for risk assessment of extreme events and development of disaster prevention and mitigation measures.

[0116] It should be noted that the specific implementation process of the asymmetric meteorological waterlogging and drought sudden change event identification device 200 and each unit can be clearly understood by those skilled in the art, which can be referred to the corresponding description in the foregoing method embodiments, and will not be described here for the convenience and brevity of description.

[0117] The asymmetric meteorological waterlogging and drought sudden change event identification device 200 can be implemented in the form of a computer program, which can run on an electronic device as shown in the figure. Figure 8

[0118] Please refer to Figure 8 , Figure 8 is a schematic block diagram of the electronic device 300 provided by the embodiment.

[0119] Please refer to Figure 8 , the electronic device 300 includes a processor 302, a memory and a network interface 305 connected through a system bus 301, wherein the memory can include a storage medium 303 and an internal memory 304.

[0120] The storage medium 303 can store an operating system 3031 and a computer program 3032. The computer program 3032 is executed to make the processor 302 execute the asymmetric meteorological waterlogging and drought sudden change event identification method.

[0121] The processor 302 is used to provide computing and control capabilities to support the operation of the entire device 300.

[0122] The internal memory 304 provides an environment for the running of the computer program 3032 in the non-volatile storage medium 303, and the computer program 3032 is executed by the processor 302 to make the processor 302 execute the asymmetric meteorological waterlogging and drought sudden change event identification method.

[0123] ​The network interface 305 is configured to perform network communication, such as providing transmission of data information, etc. Those skilled in the art can understand that Figure 8 The structure shown in FIG. 3 is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the device 300 to which the scheme of the present application is applied. Specifically, the device 300 can include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0124] The processor 302 is configured to run the computer program 3032 stored in the memory to implement the following functions: processing the first precipitation data of the target region in a preset time to obtain second precipitation data in a ten-day time series; generating, according to the second precipitation data, a first standardized precipitation index of the target region in a single ten-day time series and a second standardized precipitation index of the target region in a multi-ten-day time series; determining a flood event of the target region in a time series in the preset time according to the first standardized precipitation index, and determining a drought event of the target region in the time series in the preset time according to the second standardized precipitation index; and identifying a flood-drought acute transition event of the target region in the preset time according to the flood event and the drought event of the target region in the time series in the preset time.

[0125] Those skilled in the art can understand that Figure 8 The embodiments of the device 300 shown in FIG. 3 do not constitute a limitation on the specific constitution of the device 300. In other embodiments, the device 300 can include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components. For example, in some embodiments, the device 300 can only include the memory and the processor 302. In such embodiments, the structure and functions of the memory and the processor 302 are consistent with those of the memory and the processor 302 shown in the embodiments, and will not be described here again. Figure 8 The embodiments of the device 300 shown in FIG. 3 do not constitute a limitation on the specific constitution of the device 300. In other embodiments, the device 300 can include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components. For example, in some embodiments, the device 300 can only include the memory and the processor 302. In such embodiments, the structure and functions of the memory and the processor 302 are consistent with those of the memory and the processor 302 shown in the embodiments, and will not be described here again.

[0126] It should be understood that, in the embodiments of the present application, the processor 302 can be a central processing unit (CPU), and the processor 302 can also be other general-purpose processors 302, digital signal processors 302 (DSP), application specific integrated circuits (ASIC), ready programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The general-purpose processor 302 can be a microprocessor or any conventional processor 302, etc.

[0127] According to an aspect of the present application, a computer program product or computer program is also provided, which comprises computer instructions stored in a computer readable storage medium. A processor of an electronic device reads the computer instructions from the computer readable storage medium, and the processor executes the computer instructions to cause the electronic device to perform the following steps: processing first precipitation data of a target region in a preset time to obtain second precipitation data in a ten-day time series; generating, according to the second precipitation data, a first standardized precipitation index of the target region in a single ten-day time series and a second standardized precipitation index of the target region in a multi-ten-day time series; determining a flood event of the target region in a time series in the preset time according to the first standardized precipitation index, and determining a drought event of the target region in the time series in the preset time according to the second standardized precipitation index; and identifying a flood-drought rapid transition event of the target region in the preset time according to the flood event and the drought event of the target region in the time series in the preset time.

[0128] Those skilled in the art can understand that all or part of the processes in the method of implementing the above embodiments can be completed by a computer program instructing related hardware. The computer program comprises program instructions, and the computer program can be stored in a storage medium, which is a computer readable storage medium. The program instructions are executed by at least one processor in the computer system to implement the process steps of the above method embodiments.

[0129] In another embodiment of the present application, a computer storage medium is provided. The storage medium can be a non-volatile computer readable storage medium or a volatile storage medium. The storage medium stores a computer program 3032, wherein the computer program 3032 is executed by a processor 302 to implement the following steps: processing first precipitation data of a target region in a preset time to obtain second precipitation data in a ten-day time series; generating, according to the second precipitation data, a first standardized precipitation index of the target region in a single ten-day time series and a second standardized precipitation index of the target region in a multi-ten-day time series; determining a flood event of the target region in a time series in the preset time according to the first standardized precipitation index, and determining a drought event of the target region in the time series in the preset time according to the second standardized precipitation index; and identifying a flood-drought rapid transition event of the target region in the preset time according to the flood event and the drought event of the target region in the time series in the preset time.

[0130] The storage medium can be a U disk, a mobile hard disk, a read-only memory (ROM), a magnetic disk or an optical disk, and various computer readable storage media that can store program codes.

[0131] According to one aspect of the present application, there is also provided a system for identifying an asymmetric meteorological flood-drought abrupt change event, which is applied to the method for identifying an asymmetric meteorological flood-drought abrupt change event. The method processes first precipitation data of a target region in a preset time on a time scale to obtain second precipitation data of a ten-day time series, and generates a first standardized precipitation index of the target region in a single ten-day time series and a second standardized precipitation index of the target region in a multi-ten-day time series based on an asymmetric manner according to the second precipitation data. Then, a flood event and a drought event of the target region in the preset time on a time series are determined according to the first standardized precipitation index and the second standardized precipitation index. Finally, a flood-drought abrupt change event of the target region in the preset time can be accurately identified according to the flood event and the drought event of the target region in the preset time on the time series, which has important theoretical significance and application value for risk assessment of extreme events and development of disaster prevention and mitigation measures.

[0132] Those skilled in the art can understand that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be realized in electronic hardware, computer software or a combination of both. In order to clearly illustrate the interchangeability of hardware and software, the components and steps of each example have been described in the above description in general terms. Whether the functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. A person skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0133] In several embodiments provided in the present application, it should be understood that the disclosed apparatus and method can be implemented in other ways. For example, the apparatus embodiments described above are only schematic. For example, the division of each unit is only a logical function division, and actual implementation can have another division manner. For example, a plurality of units or components can be combined or integrated into another system, or some features can be omitted or not implemented.

[0134] The steps in the method embodiments of the present application can be adjusted, combined and reduced in sequence according to actual needs. The units in the apparatus embodiments of the present application can be combined, divided and reduced according to actual needs. In addition, each functional unit in each embodiment of the present application can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit.

[0135] The integrated unit, if implemented in the form of a software function unit and sold or used as an independent product, can be stored in a storage medium. Based on such an understanding, the technical solutions of the present application essentially or say the part that contributes to the prior art, or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a plurality of instructions for causing an electronic device (which can be a personal computer, a terminal, or a network device, etc.) to execute all or part of the steps of the method provided by the various embodiments of the present application.

[0136] The above is merely specific embodiments of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present application, and these modifications or replacements shall be encompassed within the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A method of identifying asymmetric meteorological drought-flood rapid transition events, characterized in that, The method comprises: processing first precipitation data of a target region in a preset time to obtain second precipitation data of a ten-day scale time sequence; generating, according to the second precipitation data, a first standardized precipitation index of the target region in a single ten-day scale time sequence and a second standardized precipitation index of the target region in a multi-ten-day scale time sequence; determining, according to the first standardized precipitation index, a flood event of the target region in a time sequence in the preset time, and determining, according to the second standardized precipitation index, a drought event of the target region in the time sequence in the preset time; identifying, according to the flood event and the drought event of the target region in the time sequence in the preset time, a flood-drought abrupt change event of the target region in the preset time; wherein, after the flood-drought abrupt change event of the target region in the preset time is identified according to the first standardized precipitation index and the second standardized precipitation index, the method further comprises: obtaining fifth precipitation data between the flood event and the drought event corresponding to the flood-drought abrupt change event; determining, according to the fifth precipitation data, at least one of a duration, an abrupt change period, an abrupt change point, an average intensity and an intensity of the flood-drought abrupt change event of the target region; the determining, according to the fifth precipitation data, of at least one of the duration, the abrupt change period, the abrupt change point, the average intensity and the intensity of the flood-drought abrupt change event of the target region comprises: determining, according to the fifth precipitation data, the duration of the flood-drought abrupt change event, a first time of the flood event and a second time of the drought event in the flood-drought abrupt change event; the first time comprises a first start time and a first end time of the flood event, and the second time comprises a second start time and a second end time of the drought event; determining, according to the first start time and the second end time, the duration of the target region in the flood-drought abrupt change event, and determining, according to the first end time and the second start time, the abrupt change period and the abrupt change point; determining, according to the first start time, the first end time, the second start time and the duration, the average intensity; determining, according to the first standardized precipitation index and the second standardized precipitation index corresponding to the flood-drought abrupt change event, the intensity.

2. The method of asymmetric weather drought flood event identification of claim 1, wherein, The first precipitation data comprises third precipitation data of a long sequence of daily scales; the processing of the first precipitation data of the target region in the preset time to obtain the second precipitation data of the ten-day scale time sequence comprises: obtaining, in the preset time, the third precipitation data of the long sequence of daily scales of the target region; summing the third precipitation data to obtain the second precipitation data of the ten-day scale time sequence.

3. The method of asymmetric weather drought flood event identification of claim 1, wherein, The generating, according to the second precipitation data, of the first standardized precipitation index of the target region in a single ten-day scale time sequence and the second standardized precipitation index of the target region in a multi-ten-day scale time sequence comprises: summing the second precipitation data of the ten-day scale time sequence by using a multi-ten-day sliding window to obtain fourth precipitation data in the multi-ten-day scale time sequence; The second precipitation data and the fourth precipitation data are processed using a standardized precipitation index algorithm to obtain the first standardized precipitation index of the target area under the single-ten-day time series and the second standardized precipitation index under the multi-ten-day time series.

4. The method of asymmetric weather drought flood event identification of claim 3, wherein, The process of using a standardized precipitation index algorithm to process the second and fourth precipitation data respectively yields the first standardized precipitation index for the target area at a single-ten-day time series and the second standardized precipitation index at a multi-ten-day time series, including: The probability density function of the distribution is used to process the second precipitation data and the fourth precipitation data respectively to determine the first distribution probability of the target area under the single-ten-day scale time series and the second distribution probability under the multi-ten-day scale time series respectively; The first and second distribution probabilities are respectively normalized to determine the first and second standardized precipitation indices.

5. The method of claim 1, wherein the asymmetric weather event is a drought event. The step of identifying abrupt shifts between flood and drought events in the target area within a preset time period, based on flood and drought events in the target area over a preset time period, includes: Based on the flood and drought events in the target area over a preset time period, determine the first interval between adjacent flood and drought events in the time series, and the second interval between the drought development period corresponding to the drought event; Based on the first interval time and the second interval time, the target interval time between adjacent flood events and drought events in the time series is determined; If the target interval exceeds a preset threshold, it is determined that a sudden shift from flood to drought event occurs in the target area within the preset time.

6. The method of asymmetric weather drought flood event identification of claim 1, wherein, The determination of the intensity based on the first standardized precipitation index and the second standardized precipitation index corresponding to the sudden shift from drought to flood includes: A first target precipitation index and a second target precipitation index are determined from multiple first standardized precipitation indices and multiple second standardized precipitation indices of the target area within the preset time period; The intensity is determined based on the first target precipitation index and the second target precipitation index.

7. A system for identifying asymmetric meteorological drought-flood rapid-onset events, characterized by, The method for identifying asymmetric meteorological events that rapidly shift from flood to drought, as described in any one of claims 1-6.

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