A method, device, equipment and storage medium for identifying rapid alternation events of drought and flood

Abstract

The present invention discloses a method, device, equipment and storage medium for identifying drought-flood rapid alternation events. By obtaining the historical measured precipitation data of each meteorological station in the target basin, according to the historical measured precipitation data, the standardized weighted average precipitation index corresponding to each meteorological station is calculated; based on the rotated empirical orthogonal decomposition method, spatial partitioning processing is carried out on the target basin to obtain a plurality of target sub-basins, and the target standardized weighted average precipitation index corresponding to each meteorological station in each target sub-basin is obtained; feature extraction is respectively carried out on the target standardized weighted average precipitation index to obtain the flood characteristics and drought characteristics corresponding to each target sub-basin; based on the flood characteristics and drought characteristics, drought-flood rapid alternation events are identified for each target sub-basin, and the occurrence frequency of drought-flood rapid alternation events in each target sub-basin is counted; compared with the prior art, the technical solution of the present invention can improve the recognition accuracy of drought-flood rapid alternation events.

Description

Technical Field

[0001] The present invention relates to the technical field of meteorological information processing and analysis, and particularly to a method, device, equipment and storage medium for identifying dry-wet abrupt transition events. Background Art

[0002] Under the background of global climate change and rapidly developing social economy, river basins are facing challenges such as increasing extreme precipitation events, enhanced and frequent drought and flood events, and the phenomenon of dry-wet abrupt transition; however, there are some problems in the existing analysis methods for dry-wet abrupt transition events in river basins, such as the irrationality of the overall spatial or administrative division of river basins, and the lack of sufficient in-depth understanding of the spatio-temporal evolution law of dry-wet abrupt transition events.

[0003] In order to correctly understand the spatio-temporal evolution law of dry-wet abrupt transition events in river basins and take effective preventive and response measures, scholars at home and abroad have conducted a large number of studies on the risk of meteorological disasters in river basins. However, the existing research mainly focuses on qualitative or semi-quantitative methods, analyzing and identifying single factors or single indicators; adaptive drought indicators are mostly used for drought risk assessment, while flood disasters mainly rely on flood characteristics and hydrological frequency calculation. There is relatively little research on dry-wet abrupt transition events, and currently, risk assessment is mostly carried out using relevant indicators.

[0004] However, under the dual influence of climate change and human activities, the water resource system has characteristics such as spatio-temporal heterogeneity, risk diversity and multi-dimensionality. Therefore, how to comprehensively consider the background environment in which the risk of the research object is located, and develop the most suitable multi-index and multi-dimensional risk analysis method to improve the accuracy of identifying dry-wet abrupt transition events, so as to provide a scientific basis for the comprehensive management of river basins, is a technical problem that urgently needs to be solved at present. Summary of the Invention

[0005] The technical problem to be solved by the present invention is: to provide a method, device, equipment and storage medium for identifying dry-wet abrupt transition events, which can improve the accuracy of identifying dry-wet abrupt transition events.

[0006] To solve the above technical problem, the present invention provides a method for identifying dry-wet abrupt transition events, including:

[0007] Obtain the historical measured precipitation data of each meteorological station in the target river basin, and calculate the standardized weighted average precipitation index corresponding to each meteorological station according to the historical measured precipitation data;

[0008] Based on the rotated empirical orthogonal decomposition method, perform spatial division processing on the target river basin to obtain a plurality of target sub-basins, and obtain the target standardized weighted average precipitation index corresponding to each meteorological station in each target sub-basin;

[0009] Feature extraction is respectively performed on the target standardized weighted average precipitation index to obtain the flood characteristics and drought characteristics corresponding to each target sub-basin;

[0010] Based on the flood characteristics and the drought characteristics, identification of rapid alternation events between drought and flood is performed on each target sub-basin, and the occurrence frequency of the rapid alternation events between drought and flood in each target sub-basin is counted.

[0011] In a possible implementation manner, historical measured precipitation data of each meteorological station in the target basin is obtained, and according to the historical measured precipitation data, the standardized weighted average precipitation index corresponding to each meteorological station is calculated, specifically including:

[0012] Obtain the historical measured precipitation data corresponding to each meteorological station in the target basin, where the historical measured precipitation data includes historical daily measured precipitation data corresponding to a plurality of preset historical years;

[0013] Based on a preset weighted average precipitation index calculation formula, calculate the weighted average precipitation index corresponding to the historical daily measured precipitation data;

[0014] Obtain the first weighted average precipitation index on the same day within a plurality of preset historical years, perform gamma distribution fitting processing on the first weighted average precipitation index to obtain the daily fitted weighted average precipitation index corresponding to the plurality of preset historical years;

[0015] Perform normal standardization on the daily fitted weighted average precipitation index to obtain a daily standardized weighted average precipitation index, and integrate all the daily standardized weighted average precipitation indices within each preset historical year to obtain the standardized weighted average precipitation index corresponding to each meteorological station for each preset historical year.

[0016] In a possible implementation manner, based on a preset weighted average precipitation index calculation formula, calculate the weighted average precipitation index corresponding to the historical daily measured precipitation data, specifically including:

[0017] Obtain the first date corresponding to the historical daily measured precipitation data, and obtain the first historical daily measured precipitation data corresponding to each day within a preset time period before the first date;

[0018] Input the historical daily measured precipitation data and the first historical daily measured precipitation data into a preset weighted average precipitation index calculation formula, and calculate the weighted average precipitation index corresponding to the historical daily measured precipitation data; where the preset weighted average precipitation index calculation formula is as follows:

[0019]

[0020] wherein, WAP is the weighted average precipitation index, and w n =(1 - α)α n is the weight of the previous rainfall, and α is a parameter representing the attenuation of the weight over time. P n is the measured data of the first historical daily precipitation corresponding to the nth day before the first date, N is the preset time period, and is the total number of days of the previous precipitation affecting the current drought and flood status.

[0021] In a possible implementation, based on the rotated empirical orthogonal decomposition method, the target basin is spatially divided to obtain multiple target sub - basins, specifically including:

[0022] Calculate the covariance of the standardized weighted average precipitation index to obtain the covariance matrix corresponding to the standardized weighted average precipitation index;

[0023] Perform eigenvalue decomposition on the covariance matrix to obtain multiple eigenvalues and the eigenvectors corresponding to each eigenvalue, and based on the eigenvalues and the eigenvectors, determine multiple principal components;

[0024] Perform rotation processing on the multiple principal components respectively to obtain the eigen - modes corresponding to each principal component, and based on the eigen - modes, perform spatial division processing on the target basin to obtain multiple target sub - basins.

[0025] In a possible implementation, feature extraction is performed on the target standardized weighted average precipitation index to obtain the flood characteristics and drought characteristics corresponding to each target sub - basin, specifically including:

[0026] Set the first truncation coefficient and the second truncation coefficient;

[0027] Based on the first truncation coefficient, perform feature extraction on the target standardized weighted average precipitation index. When there is a daily standardized weighted average precipitation index in the target standardized weighted average precipitation index that is not less than the first truncation coefficient, obtain the flood characteristics corresponding to each target sub - basin;

[0028] Based on the second truncation coefficient, perform feature extraction on the target standardized weighted average precipitation index. When there is a daily standardized weighted average precipitation index in the target standardized weighted average precipitation index that is not greater than the second truncation coefficient, obtain the drought characteristics corresponding to each target sub - basin.

[0029] In a possible implementation, based on the flood characteristics and the drought characteristics, identify the rapid transition events of drought and flood for each target sub - basin, specifically including:

[0030] Obtain the flood characteristics and the drought characteristics, where the flood characteristics include the flood duration, and the flood duration includes the flood start time and the flood end time; the drought characteristics include the drought duration, and the drought duration includes the drought start time and the drought end time;

[0031] Calculate a first minimum time interval between the flood end time and the drought start time, and calculate a second minimum time interval between the drought end time and the flood start time;

[0032] Compare the first minimum time interval and the second minimum time interval with a preset time threshold respectively. If the first minimum time interval is not greater than the preset time threshold, or the second minimum time interval is not greater than the preset time threshold, it is determined that there is a rapid alternation event of drought and flood in the target sub-basin, otherwise, it is determined that there is no rapid alternation event of drought and flood in the target sub-basin.

[0033] In a possible implementation manner, after identifying the rapid alternation event of drought and flood for each target sub-basin, it further includes:

[0034] When it is determined that there is a rapid alternation event of drought and flood in the target sub-basin, calculate the intensity of the rapid alternation event of drought and flood corresponding to the rapid alternation event of drought and flood, and determine the intensity level of the rapid alternation event of drought and flood based on the intensity of the rapid alternation event of drought and flood;

[0035] Among them, the calculation of the intensity of the rapid alternation event of drought and flood corresponding to the rapid alternation event of drought and flood specifically includes:

[0036] Obtain the flood characteristics and the drought characteristics, where the flood characteristics further include the flood intensity; the drought characteristics further include the drought intensity;

[0037] When it is determined that there is a rapid alternation event of drought and flood in the target sub-basin, obtain the number of days of the rapid alternation interval and the duration of the rapid alternation event corresponding to the rapid alternation event of drought and flood, and determine a first rapid alternation time point and a second rapid alternation time point of the duration of the rapid alternation event based on the duration of the rapid alternation event, where the duration of the rapid alternation event is determined by the start time of the rapid alternation event of drought and flood and the end time of the rapid alternation event of drought and flood;

[0038] When it is determined that there is the flood characteristic between the start time of the rapid alternation event of drought and flood and the first rapid alternation time point, obtain all first flood intensities within the time period from the start time of the rapid alternation event of drought and flood to the first rapid alternation time point, perform an accumulation process on all the first flood intensities to obtain a first accumulated flood intensity value, and obtain all first drought intensities between the second rapid alternation time point and the end time of the rapid alternation event of drought and flood, perform an accumulation process on all the first drought intensities to obtain a first accumulated drought intensity value;

[0039] Substitute the number of days between rapid alternations of drought and flood, the duration of rapid alternations of drought and flood, the cumulative value of the first flood intensity, and the cumulative value of the first drought into a preset calculation formula for the intensity of rapid alternations of drought and flood events to obtain the first intensity of rapid alternations of drought and flood events corresponding to the rapid alternations of drought and flood events;

[0040] When it is determined that there is the drought feature between the start time of the rapid alternations of drought and flood events and the first rapid alternations of drought and flood time point, obtain all the second drought intensities within the time period from the start time of the rapid alternations of drought and flood events to the first rapid alternations of drought and flood time point, perform cumulative processing on all the second drought intensities to obtain a cumulative value of the second drought intensity, and obtain all the second flood intensities between the second rapid alternations of drought and flood time point and the end time of the rapid alternations of drought and flood events, perform cumulative processing on all the second flood intensities to obtain a cumulative value of the second flood intensity;

[0041] Substitute the number of days between rapid alternations of drought and flood, the duration of rapid alternations of drought and flood, the cumulative value of the second drought intensity, and the cumulative value of the second flood into a preset calculation formula for the intensity of rapid alternations of drought and flood events to obtain the second intensity of rapid alternations of drought and flood events corresponding to the rapid alternations of drought and flood events.

[0042] The present invention also provides an identification device for rapid alternations of drought and flood events, including: a standardized weighted average precipitation index calculation module, a basin division module, a feature extraction module, and a rapid alternations of drought and flood event identification module;

[0043] Among them, the standardized weighted average precipitation index calculation module is used to obtain the measured historical precipitation data of each meteorological station in the target basin, and calculate the standardized weighted average precipitation index corresponding to each meteorological station according to the measured historical precipitation data;

[0044] The basin division module is used to perform spatial division processing on the target basin based on the rotated empirical orthogonal decomposition method to obtain a plurality of target sub-basins, and obtain the target standardized weighted average precipitation index corresponding to each meteorological station in each target sub-basin;

[0045] The feature extraction module is used to respectively extract features from the target standardized weighted average precipitation index to obtain the flood feature and drought feature corresponding to each target sub-basin;

[0046] The rapid alternations of drought and flood event identification module is used to identify rapid alternations of drought and flood events for each target sub-basin based on the flood feature and the drought feature, and count the occurrence frequency of the rapid alternations of drought and flood events in each target sub-basin.

[0047] In a possible implementation, the standardized weighted average precipitation index calculation module is used to obtain the measured historical precipitation data of each meteorological station in the target basin, and calculate the standardized weighted average precipitation index corresponding to each meteorological station according to the measured historical precipitation data, specifically including:

[0048] Obtain the measured historical precipitation data corresponding to each meteorological station in the target basin, where the measured historical precipitation data includes the measured daily precipitation data corresponding to multiple preset historical years;

[0049] Based on the preset weighted average precipitation index calculation formula, calculate the weighted average precipitation index corresponding to the measured historical daily precipitation data;

[0050] Obtain the first weighted average precipitation index on the same day within multiple preset historical years, perform gamma distribution fitting on the first weighted average precipitation index, and obtain the daily fitted weighted average precipitation index corresponding to the multiple preset historical years;

[0051] Perform normal standardization on the daily fitted weighted average precipitation index to obtain the daily standardized weighted average precipitation index, and integrate all the daily standardized weighted average precipitation indices within each preset historical year to obtain the standardized weighted average precipitation index corresponding to each meteorological station for each preset historical year.

[0052] In a possible implementation, the standardized weighted average precipitation index calculation module is used to calculate the weighted average precipitation index corresponding to the measured historical daily precipitation data based on the preset weighted average precipitation index calculation formula, specifically including:

[0053] Obtain the first date corresponding to the measured historical daily precipitation data, and obtain the first measured historical daily precipitation data corresponding to each day within a preset time period before the first date;

[0054] Input the measured historical daily precipitation data and the first measured historical daily precipitation data into the preset weighted average precipitation index calculation formula, and calculate the weighted average precipitation index corresponding to the measured historical daily precipitation data; where the preset weighted average precipitation index calculation formula is as follows:

[0055]

[0056] In the formula, WAP is the weighted average precipitation index, w n =(1-α)α n is the weight of the previous rainfall, α is a parameter characterizing the attenuation of the weight over time, P nis the measured historical precipitation data on the first historical day corresponding to the nth day before the first date. N is a preset time period, which is the total number of days of precipitation in the early stage affecting the current drought and flood status.

[0057] In a possible implementation manner, the basin division module is used to perform spatial division processing on the target basin based on the rotated empirical orthogonal decomposition method to obtain multiple target sub-basins, specifically including:

[0058] Calculate the covariance of the standardized weighted average precipitation index to obtain the covariance matrix corresponding to the standardized weighted average precipitation index;

[0059] Perform eigenvalue decomposition on the covariance matrix to obtain multiple eigenvalues and the eigenvectors corresponding to each eigenvalue, and determine multiple principal components based on the eigenvalues and the eigenvectors;

[0060] Perform rotation processing on the multiple principal components respectively to obtain the eigenmodes corresponding to each principal component, and perform spatial division processing on the target basin based on the eigenmodes to obtain multiple target sub-basins.

[0061] In a possible implementation manner, the feature extraction module is used to extract features from the target standardized weighted average precipitation index to obtain the flood characteristics and drought characteristics corresponding to each target sub-basin, specifically including:

[0062] Set a first truncation coefficient and a second truncation coefficient;

[0063] Extract features from the target standardized weighted average precipitation index based on the first truncation coefficient. When there is a daily standardized weighted average precipitation index in the target standardized weighted average precipitation index that is not less than the first truncation coefficient, obtain the flood characteristics corresponding to each target sub-basin;

[0064] Extract features from the target standardized weighted average precipitation index based on the second truncation coefficient. When there is a daily standardized weighted average precipitation index in the target standardized weighted average precipitation index that is not greater than the second truncation coefficient, obtain the drought characteristics corresponding to each target sub-basin.

[0065] In a possible implementation manner, the drought-flood rapid transition event recognition module is used to recognize drought-flood rapid transition events for each target sub-basin based on the flood characteristics and the drought characteristics, specifically including:

[0066] Obtain the flood characteristics and the drought characteristics, where the flood characteristics include the flood duration, and the flood duration includes the flood start time and the flood end time; the drought characteristics include the drought duration, and the drought duration includes the drought start time and the drought end time;

[0067] Calculate the first minimum time interval between the end time of the flood and the start time of the drought, and calculate the second minimum time interval between the end time of the drought and the start time of the flood;

[0068] Compare the first minimum time interval and the second minimum time interval with a preset time threshold respectively. If the first minimum time interval is not greater than the preset time threshold, or the second minimum time interval is not greater than the preset time threshold, it is determined that there is a rapid alternation event of drought and flood in the target sub-basin; otherwise, it is determined that there is no rapid alternation event of drought and flood in the target sub-basin.

[0069] In a possible implementation manner, after the rapid alternation event recognition module is used to recognize the rapid alternation event of drought and flood for each target sub-basin, it is further used for:

[0070] When it is determined that there is a rapid alternation event of drought and flood in the target sub-basin, calculate the intensity of the rapid alternation event of drought and flood corresponding to the rapid alternation event, and determine the intensity level of the rapid alternation event based on the intensity of the rapid alternation event;

[0071] Among them, calculating the intensity of the rapid alternation event of drought and flood corresponding to the rapid alternation event of drought and flood specifically includes:

[0072] Obtain the flood characteristics and the drought characteristics, where the flood characteristics further include the flood intensity; the drought characteristics further include the drought intensity;

[0073] When it is determined that there is a rapid alternation event of drought and flood in the target sub-basin, obtain the number of days of the rapid alternation interval and the duration of the rapid alternation event corresponding to the rapid alternation event of drought and flood, and determine the first rapid alternation time point and the second rapid alternation time point of the duration of the rapid alternation event based on the duration of the rapid alternation event, where the duration of the rapid alternation event is determined by the start time and the end time of the rapid alternation event of drought and flood;

[0074] When it is determined that there are the flood characteristics between the start time of the rapid alternation event of drought and flood and the first rapid alternation time point, obtain all the first flood intensities within the time period from the start time of the rapid alternation event of drought and flood to the first rapid alternation time point, perform an accumulation process on all the first flood intensities to obtain a first flood intensity accumulation value, and obtain all the first drought intensities between the second rapid alternation time point and the end time of the rapid alternation event of drought and flood, perform an accumulation process on all the first drought intensities to obtain a first drought intensity accumulation value;

[0075] Substitute the number of days between drought-flood rapid alternations, the duration of drought-flood rapid alternations, the cumulative value of the first flood intensity, and the cumulative value of the first drought into a preset calculation formula for the intensity of drought-flood rapid alternation events to obtain the first drought-flood rapid alternation event intensity corresponding to the drought-flood rapid alternation event;

[0076] When it is determined that there is a drought feature between the start time of the drought-flood rapid alternation event and the first drought-flood rapid alternation time point, obtain all the second drought intensities within the time period from the start time of the drought-flood rapid alternation event to the first drought-flood rapid alternation time point, perform an accumulation process on all the second drought intensities to obtain a cumulative value of the second drought intensity, and obtain all the second flood intensities between the second drought-flood rapid alternation time point and the end time of the drought-flood rapid alternation event, perform an accumulation process on all the second flood intensities to obtain a cumulative value of the second flood intensity;

[0077] Substitute the number of days between drought-flood rapid alternations, the duration of drought-flood rapid alternations, the cumulative value of the second drought intensity, and the cumulative value of the second flood into a preset calculation formula for the intensity of drought-flood rapid alternation events to obtain the second drought-flood rapid alternation event intensity corresponding to the drought-flood rapid alternation event.

[0078] The present invention also provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the method for identifying drought-flood rapid alternation events as described in any one of the above.

[0079] The present invention also provides a computer-readable storage medium, which includes a stored computer program. When the computer program runs, it controls the device where the computer-readable storage medium is located to execute the method for identifying drought-flood rapid alternation events as described in any one of the above.

[0080] An identification method, device, equipment, and storage medium for drought-flood rapid alternation events according to an embodiment of the present invention have the following beneficial effects compared with the prior art:

[0081] By calculating the standardized weighted average precipitation index of meteorological stations and performing spatial partitioning processing based on the rotated empirical orthogonal decomposition method, multiple target sub-basins are obtained. Then, feature extraction is performed on the standardized weighted average precipitation index of each target sub-basin to obtain flood characteristics and drought characteristics. In this way, the risk background environment of the basin can be comprehensively considered from multiple indicators and dimensions, so as to accurately identify the rapid alternation events of drought and flood and their occurrence frequencies in the subsequent process; and through the identification and frequency statistics of the rapid alternation events of drought and flood, this method can provide a scientific basis for the comprehensive management of the basin. It can help decision-makers more accurately understand the occurrence of rapid alternation events of drought and flood in different sub-basins and their spatio-temporal evolution laws. In this way, corresponding preventive and response measures can be taken to better manage the water resources system of the basin; and when performing spatial partitioning, the rotated empirical orthogonal decomposition method is adopted, which can avoid the heterogeneity within the administrative region compared with the existing technology that divides based on administrative regions, more accurately reflect the meteorological characteristics within the basin, and improve the accuracy of identifying rapid alternation events of drought and flood in the subsequent target sub-basins. BRIEF DESCRIPTION OF THE DRAWINGS

[0082] Figure 1 is a schematic flowchart of an embodiment of a method for identifying rapid alternation events of drought and flood provided by the present invention;

[0083] Figure 2 is a schematic structural diagram of an embodiment of a device for identifying rapid alternation events of drought and flood provided by the present invention;

[0084] Figure 3 is a schematic diagram of the first five spatial modal eigenvectors of the SWAP in the Lancang River Basin in an embodiment provided by the present invention;

[0085] Figure 4 is a schematic diagram of the extraction of characteristic variables of rapid alternation events of drought and flood based on the run theory in an embodiment provided by the present invention;

[0086] Figure 5 is a spatial distribution map of the frequencies of rapid alternation events of drought and flood at different levels based on the SWAP identification results in an embodiment provided by the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0087] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0088] Embodiment 1, see Figure 1 , Figure 1It is a schematic flowchart of an embodiment of a method for identifying dry-wet abrupt transition events provided by the present invention. As Figure 1 shown, the method includes steps 101 to 104, which are specifically as follows:

[0089] Step 101: Obtain the historical measured precipitation data of each meteorological station in the target basin, and calculate the standardized weighted average precipitation index corresponding to each meteorological station according to the historical measured precipitation data.

[0090] In one embodiment, dry-wet abrupt transition events usually occur under rapid changes in precipitation, including the following two situations: (1) From drought to flood: When the drought period ends, if extreme precipitation events such as heavy rain and rainstorm suddenly occur, it may cause the dry soil to be unable to absorb a large amount of water quickly, resulting in floods and inundation disasters; (2) From flood to drought: After the flood event ends, if there is no precipitation for a long time, the soil will gradually lose moisture and the vegetation cannot recover, which may lead to the occurrence of drought disasters; Based on the above, the occurrence of a dry-wet disaster is not only affected by the current precipitation, but also related to the previous dry-wet state. Therefore, in this embodiment, starting from the precipitation situation in the basin, the identification of dry-wet abrupt transition events is studied.

[0091] In one embodiment, select the target basin for research, and obtain the historical measured precipitation data corresponding to each meteorological station in the target basin, where the historical measured precipitation data includes the historical daily measured precipitation data corresponding to multiple preset historical years. Preferably, the multiple preset historical years are consecutive years.

[0092] In one embodiment, based on a preset weighted average precipitation index calculation formula, calculate the weighted average precipitation index corresponding to the historical daily measured precipitation data.

[0093] Specifically, the magnitude of precipitation is a necessary but not sufficient condition for judging the dry-wet state of the day, and the dry-wet state also depends on the reserve status of the previous water storage; the change of the previous water storage is a decaying process. Assume that the decay process of the water storage is proportional to the precipitation. Based on this relationship, a simple physical model is set as:

[0094]

[0095] In the formula, f(t) is the dry-wet intensity at time t, which is positively correlated with the rainfall P(t) at time t; ―bf(t) means the decay of the water storage at time t, such as water evaporation, soil infiltration, etc.; b is a coefficient greater than 0, and the larger it is, the stronger the decay factor.

[0096] After integral transformation of the above physical model, it can be changed to:

[0097]

[0098] After performing derivations, discretizations, and other transformations on the above formula, the current drought-flood state f 0 can be simplified to:

[0099]

[0100] In the formula, a = e ―b·Δt (a < 1), (Δt is the interval time, taking 1 day, which is a parameter representing the contribution or attenuation of previous precipitation to the current drought-flood, P n is the precipitation in the previous n days, and N is the total number of days of precipitation in the early stage affecting the current drought-flood state.

[0101] To simplify the accumulation process and obtain a relative value, the above formula is averaged according to the weight coefficient to obtain the calculation formula for the weighted average precipitation index, as shown below:

[0102]

[0103] In the formula, WAP is the weighted average precipitation index, w n = (1 - α)α n is the weight of the previous rainfall, and α is a parameter representing the attenuation of the weight over time, P n is the measured data of the first historical daily precipitation corresponding to the nth day before the first date, and N is the preset time period, which is the total number of days of precipitation in the early stage affecting the current drought-flood state.

[0104] Specifically, since the selection of the parameter α is not very sensitive to drought-flood identification, especially the identification of severe drought-flood events, α is set to 0.9 according to experience.

[0105] As can be seen from the above formula, the impact of recent daily precipitation on the current day's drought-flood shows an exponential decrease. Based on the attenuation coefficient α and by selecting an appropriate value of N, the weights for N days can be calculated. Based on the weights and by selecting an appropriate value of N, as shown in Table 1, Table 1 is the weight table of recent daily water volume.

[0106] Table 1:

[0107]

[0108] Based on Table 1, the weight of the current day is 10%, while the weight of the 43rd day before the current day for the current day's drought-flood decreases to 0.1%, and drops sharply to 0.01% by the 65th day before, with a negligible effect. Therefore, based on the results in Table 1, N = 44 is taken.

[0109] Specifically, obtain the first date corresponding to the measured historical daily precipitation data, and obtain the first measured historical daily precipitation data corresponding to each day within a preset time period before the first date; input the measured historical daily precipitation data and the first measured historical daily precipitation data into a preset weighted average precipitation index calculation formula to calculate the weighted average precipitation index corresponding to the measured historical daily precipitation data.

[0110] Preferably, obtain the first measured historical daily precipitation data corresponding to each day within 44 days before the first date.

[0111] In one embodiment, obtain the first weighted average precipitation index on the same day within multiple preset historical years, perform gamma distribution fitting on the first weighted average precipitation index to obtain the daily fitted weighted average precipitation index corresponding to the multiple preset historical years.

[0112] In one embodiment, perform normal standardization on the daily fitted weighted average precipitation index to obtain the daily standardized weighted average precipitation index, and integrate all the daily standardized weighted average precipitation indices within each preset historical year to obtain the standardized weighted average precipitation index corresponding to each preset historical year for each meteorological station.

[0113] Specifically, the standardized weighted average precipitation index (SWAP) is used to measure the current drought and flood status; this indicator is based on an idea of water income and decline, and characterizes the current drought and flood conditions according to the current and previous precipitation, and can analyze the dry and wet conditions of the region on a daily scale.

[0114] Specifically, when performing normal standardization on the daily fitted weighted average precipitation index, obtain the first year corresponding to the daily fitted weighted average precipitation index, obtain all the daily fitted weighted average precipitation indices corresponding to the first year, calculate the mean of all the daily fitted weighted average precipitation indices to obtain the mean of the daily fitted weighted average precipitation index in the first year, calculate the standard deviation of all the daily fitted weighted average precipitation indices based on all the daily fitted weighted average precipitation indices, calculate the first difference between the daily fitted weighted average precipitation index and the mean of the daily fitted weighted average precipitation index in the first year, and divide the first difference by the standard deviation to obtain the daily standardized weighted average precipitation index corresponding to the daily fitted weighted average precipitation index. Based on the above normal standardization process, convert the daily fitted weighted average precipitation index of each meteorological station in the preset year into a standard normal distribution with a mean of 0 and a standard deviation of 1.

[0115] Step 102: Perform spatial partitioning on the target basin based on the rotated empirical orthogonal function (REOF) method to obtain multiple target sub-basins, and obtain the target standardized weighted average precipitation index corresponding to each meteorological station in each target sub-basin.

[0116] When performing spatial partitioning of a basin in the prior art, it is generally carried out according to administrative regions. The administrative division may not coincide with the natural geographical boundary of the basin, resulting in the inability to accurately reflect the characteristics of the hydrological process, precipitation distribution, etc. within the basin. There may be multiple different basins or sub-basins within an administrative region, and these sub-basins may have significant differences in terms of hydrological characteristics, precipitation distribution, etc. Analyzing the entire administrative region as a unit may ignore this spatial heterogeneity, making the subsequent identification results of drought-flood rapid transition events in the region too general or confused. Therefore, in this embodiment, the rotated empirical orthogonal function (REOF) method is used to perform spatial partitioning on the target basin based on the standardized weighted average precipitation index of each preset historical year corresponding to each meteorological station obtained in Step 101 to obtain multiple target sub-basins.

[0117] The rotated empirical orthogonal function (REOF) method is a statistical method based on data characteristics. By analyzing precipitation data, it can identify different precipitation patterns and spatial characteristics. The REOF method, which focuses on representing the spatial correlation distribution structure, is developed based on the Empirical Orthogonal Function (EOF). The Empirical Orthogonal Function (EOF) is a method that uses a few spatial modes with fewer numbers to describe the original variable field and basically covers the information of the original variable field, which can play a role in reducing the dimension of data. Although the Empirical Orthogonal Function (EOF) is widely used, it also has limitations. In addition to the fact that the zoning results cannot clearly represent the characteristics of different geographical regions, different selections of regional characteristics when expanding the Empirical Orthogonal Function (EOF) will also result in different similarities in reflecting the true distribution structure, and there are sampling errors. However, the rotated empirical orthogonal function (REOF) method can make up for the limitations of the Empirical Orthogonal Function (EOF). The rotated spatial distribution structure is clear, which can not only reflect the changes in different regions but also the relevant distribution conditions in different regions, and the error is very small, which is more conducive to zoning the research elements. Therefore, the obtained target sub-basins are more in line with the actual situation of precipitation distribution, which helps to better understand and explain the precipitation changes within the basin.

[0118] In one embodiment, when performing spatial partitioning on the target basin based on the rotated empirical orthogonal function (REOF) method, covariance calculation is carried out on the standardized weighted average precipitation index (SWAP) to obtain the covariance matrix corresponding to the standardized weighted average precipitation index; eigenvalue decomposition is performed on the covariance matrix to obtain a plurality of eigenvalues and the eigenvectors corresponding to each eigenvalue, and based on the eigenvalues and the eigenvectors, a plurality of principal components are determined; rotation processing is respectively performed on the plurality of principal components to obtain the eigenmodes corresponding to each principal component, and spatial partitioning is performed on the target basin based on the eigenmodes to obtain a plurality of target sub-basins.

[0119] Specifically, when determining a plurality of eigenmodes based on the eigenvalues and the eigenvectors, by sorting the plurality of eigenvalues according to the numerical magnitude, the eigenvectors corresponding to the top preset number of eigenvalues are selected, and the principal components corresponding to each eigenvector are determined to obtain a plurality of principal components.

[0120] Specifically, after rotation processing is performed on the plurality of principal components to obtain the eigenmodes corresponding to each principal component, it further includes: calculating the explained variance ratio and variance contribution rate of the rotated principal components to the total variability; this can help determine the number of retained principal components, and usually the principal components with an explained variance greater than a certain threshold (e.g., 70%) are selected; according to the rotated principal components and their corresponding load matrices, the spatial structure and precipitation variation characteristics represented by each principal component are interpreted. The climate phenomena corresponding to different modes can be understood by observing the spatio-temporal distribution of the modal time coefficients.

[0121] In this embodiment, taking the spatial partitioning of the Lancang River Basin based on the rotated empirical orthogonal function (REOF) method for the standardized weighted average precipitation index (SWAP) as an example:

[0122] Performing REOF decomposition on the SWAP of 42 meteorological stations in the Lancang River Basin from 1960 to 2014, as shown in Table 2. Table 2 is a data table of the variance contribution and cumulative variance contribution before and after rotation of the first 5 principal components. The cumulative explained variance contribution of the first 5 components before and after rotation accounts for 71.2% of the total variance, and the variance contribution of each component after rotation is more uniform than before rotation.

[0123] Table 2:

[0124]

[0125] Different modes correspond to different spatial regions, such as Figure 3 shown Figure 3 is a schematic diagram of the eigenvectors of the first five spatial modes of the SWAP in the Lancang River Basin; in the figure, the first five rotated spatial mode features are presented in space. It can be seen from the figure that the rotated loads are relatively concentrated.

[0126] The five spatial modes sorted by variance contribution are as follows: The load center area of the first spatial mode is located in the Weixi-Dali section of Yunnan Province at the mid-lower reaches connection of the Lancang River Basin. After rotation, the variance contribution rate of this mode is 22.0%; the load center area of the second spatial mode is the Lincang area of Yunnan Province in the northwest of the lower reaches of the Lancang River. After rotation, the variance contribution rate of this mode is 19.7%; the load center area of the third spatial mode is the Pu'er and Xishuangbanna areas of Yunnan Province in the southeast of the lower reaches of the Lancang River Basin. After rotation, the variance contribution rate of this mode is 13.1%; the load center area of the fourth mode is the Chamdo area of the Tibet Autonomous Region in the mid-upper reaches of the Lancang River Basin. After rotation, the variance contribution rate of this mode is 8.3%; the load center area of the fifth mode is the Yushu area of Qinghai Province in the upper reaches of the Lancang River Basin. After rotation, the variance contribution rate of this mode is 8.1%. Among them, the variance contribution rates of the first, second, and third spatial modes located in Yunnan Province reach 54.8%, indicating that Yunnan Province is the area where droughts and floods often occur in the Lancang River area. Based on the query of historical data (Yunnan Volume, 2006), it is consistent with the actual situation. Therefore, the research results can well reflect the spatial distribution of droughts and floods in the Lancang River Basin. The five regions divided according to the high-load areas basically do not overlap. Therefore, the results of this zoning can be used as a reference for the spatial distribution of droughts and floods in the Lancang River Basin, and based on this, further research will be carried out. In the following research, the first to fifth spatial modes will be called the Dali area, the Lincang area, the Xishuangbanna area, the Chamdo area, and the Yushu area in sequence.

[0127] Step 103: Respectively perform feature extraction on the target standardized weighted average precipitation index to obtain the flood characteristics and drought characteristics corresponding to each target sub-basin.

[0128] In one embodiment, when performing feature extraction on the target standardized weighted average precipitation index, the run theory is used to identify and extract the relevant characteristics of drought-flood abrupt change events; the run theory is a time series analysis method, which according to the classification standard, through setting coefficients as truncation levels, performs feature truncation.

[0129] In this embodiment, a first truncation coefficient and a second truncation coefficient are set; preferably, the first truncation coefficient is set to 0.5, and the second truncation coefficient is set to -0.5.

[0130] In one embodiment, based on the first truncation coefficient, feature extraction is performed on the target standardized weighted average precipitation index. When there is a daily standardized weighted average precipitation index in the target standardized weighted average precipitation index that is not less than the first truncation coefficient, the flood characteristics corresponding to each target sub-basin are obtained.

[0131] Specifically, when SWAP≥0.5, flood characteristics are presented.

[0132] Specifically, obtain the target standardized weighted average precipitation index corresponding to each meteorological station in a single target sub-watershed, sort the target standardized weighted average precipitation index in chronological order from early to late, and traverse the target standardized weighted average precipitation index based on the first truncation coefficient. When it is detected that the daily standardized weighted average precipitation index is not less than the first truncation coefficient, record the date of the current daily standardized weighted average precipitation index as the flood start time until it is detected that the daily standardized weighted average precipitation index is less than the first truncation coefficient, and record the date of the current daily standardized weighted average precipitation index as the flood end time. Based on the flood start time and the flood end time, determine the flood duration of the current flood event.

[0133] Specifically, calculate the first cumulative amount of the target standardized weighted average precipitation index corresponding to each day during the flood duration, obtain the absolute value of the first cumulative amount, and use the absolute value of the first cumulative amount as the flood intensity corresponding to the current flood event.

[0134] Specifically, use the flood start time, the flood end time, and the flood intensity as the flood characteristics corresponding to each flood event.

[0135] Specifically, when a flood event is detected, record the flood event number corresponding to the current flood event.

[0136] Specifically, based on two adjacent flood events, also obtain the first flood end time corresponding to the previous flood event and the first flood start time corresponding to the subsequent flood event; based on the first flood end time and the first flood start time, calculate the flood event interval time between two adjacent flood events.

[0137] In one embodiment, perform feature extraction on the target standardized weighted average precipitation index based on the second truncation coefficient. When there is a daily standardized weighted average precipitation index in the target standardized weighted average precipitation index that is not greater than the second truncation coefficient, obtain the drought characteristics corresponding to each target sub-watershed.

[0138] Specifically, when SWAP ≤ -0.5, drought characteristics are presented.

[0139] Specifically, obtain the target standardized weighted average precipitation index corresponding to each meteorological station in a single target sub-watershed, sort the target standardized weighted average precipitation index in chronological order from early to late, and traverse the target standardized weighted average precipitation index based on the second truncation coefficient. When it is detected that the daily standardized weighted average precipitation index is not greater than the second truncation coefficient, record the date of the current daily standardized weighted average precipitation index as the drought start time until it is detected that the daily standardized weighted average precipitation index is greater than the second truncation coefficient, and record the date of the current daily standardized weighted average precipitation index as the drought end time. Based on the drought start time and the drought end time, determine the drought duration of the current drought event; as Figure 4 shown Figure 4 is a schematic diagram for extracting characteristic variables of drought-flood abrupt alternation events based on the run theory.

[0140] Specifically, calculate the second cumulative amount of the target standardized weighted average precipitation index corresponding to each day during the drought duration, obtain the absolute value of the second cumulative amount, and use the absolute value of the second cumulative amount as the drought intensity corresponding to the current drought event.

[0141] Specifically, use the drought start time, the drought end time, and the drought intensity as the flood characteristics corresponding to each drought event.

[0142] Specifically, when a drought event is detected, record the drought event number corresponding to the current drought event.

[0143] Specifically, based on two adjacent drought events, also obtain the first drought end time corresponding to the previous drought event and the first drought start time corresponding to the subsequent drought event; based on the first drought end time and the first drought start time, calculate the drought event interval time between two adjacent drought events.

[0144] Step 104: Based on the flood characteristics and the drought characteristics, identify drought-flood abrupt alternation events for each target sub-watershed, and count the occurrence frequency of the drought-flood abrupt alternation events in each target sub-watershed.

[0145] In one embodiment, obtain the flood characteristics and the drought characteristics, where the flood characteristics include the flood duration, and the flood duration includes the flood start time and the flood end time; the drought characteristics include the drought duration, and the drought duration includes the drought start time and the drought end time.

[0146] Specifically, for the flood characteristics and the drought characteristics, obtain adjacent first flood events and first drought events, obtain the first flood characteristics corresponding to the first flood events and the first drought characteristics corresponding to the first drought events, extract the corresponding flood duration, flood start time, and flood end time from the first flood characteristics, and extract the corresponding drought duration, drought start time, and drought end time from the first drought characteristics.

[0147] In one embodiment, calculate the first minimum time interval between the flood end time and the drought start time, and calculate the second minimum time interval between the drought end time and the flood start time.

[0148] Specifically, for adjacent first flood events and first drought events, it is possible that the first flood event is before and the first drought event is after; it is also possible that the first drought event is before and the first flood event is after.

[0149] Specifically, calculate the first minimum time interval between the flood end time and the drought start time corresponding to adjacent first flood events and first drought events, and calculate the second minimum time interval between the drought end time and the flood start time corresponding to adjacent first flood events and first drought events.

[0150] In one embodiment, compare the first minimum time interval and the second minimum time interval with a preset time threshold respectively. If the first minimum time interval is not greater than the preset time threshold, or the second minimum time interval is not greater than the preset time threshold, it is determined that there is a rapid alternation event of drought and flood in the target sub-basin; otherwise, it is determined that there is no rapid alternation event of drought and flood in the target sub-basin.

[0151] Specifically, the rapid alternation of drought and flood refers to the situation where drought and flood alternate within a period of time. In this embodiment, a rapid alternation event of drought and flood is defined as: within a certain period of time, the whole process that a flood (drought) event occurs within 5 days (one pentad) after the end of a drought (flood) event. The start time of the rapid alternation event of drought and flood is the start time of the drought (flood) event, and the end time is the end time of the flood (drought) event; preferably, the preset time threshold is set to 5 days.

[0152] Specifically, identify the whole process that a flood (drought) event occurs within 5 days (one pentad) after the end of a drought (flood) event as a rapid alternation event of drought and flood.

[0153] In one embodiment, after identifying the dry-wet abrupt transition events for each target sub-watershed, when it is determined that there is a dry-wet abrupt transition event in the target sub-watershed, the intensity of the dry-wet abrupt transition event corresponding to the dry-wet abrupt transition event is calculated, and based on the intensity of the dry-wet abrupt transition event, the intensity level of the dry-wet abrupt transition event is determined.

[0154] In one embodiment, the flood characteristics and the drought characteristics are obtained, wherein the flood characteristics further include the flood intensity; the drought characteristics further include the drought intensity.

[0155] Specifically, when it is determined that there is a dry-wet abrupt transition event in the target sub-watershed, the dry-wet abrupt transition interval days and the dry-wet abrupt transition duration corresponding to the dry-wet abrupt transition event are obtained, and based on the dry-wet abrupt transition duration, the first dry-wet abrupt transition time point and the second dry-wet abrupt transition time point of the dry-wet abrupt transition duration are determined.

[0156] The dry-wet abrupt transition duration is determined by the start time and the end time of the dry-wet abrupt transition event; the dry-wet abrupt transition duration is the duration of the dry-wet abrupt transition event, that is, the number of days from the start time of the dry-wet abrupt transition event to the end time of the dry-wet abrupt transition event.

[0157] The dry-wet abrupt transition interval days are the number of days from the end time of the previous disaster event to the start time of the next disaster event in the i-th dry-wet abrupt transition event, where the disaster events are drought events and flood events.

[0158] The first dry-wet abrupt transition time point is the end time of the previous disaster event in the i-th dry-wet abrupt transition event; the second dry-wet abrupt transition time point is the end time of the next disaster event in the i-th dry-wet abrupt transition event.

[0159] Specifically, when it is determined that there are the flood characteristics between the start time of the dry-wet abrupt transition event and the first dry-wet abrupt transition time point, all the first flood intensities within the start time of the dry-wet abrupt transition event to the first dry-wet abrupt transition time point are obtained, and the all first flood intensities are subjected to an accumulation process to obtain a first flood intensity accumulation value, and all the first drought intensities between the second dry-wet abrupt transition time point and the end time of the dry-wet abrupt transition event are obtained, and the all first drought intensities are subjected to an accumulation process to obtain a first drought intensity accumulation value.

[0160] For the drought-flood rapid alternation event, it may be that the flood event comes first and the drought event follows; or it may be that the drought event comes first and the flood event follows. Therefore, by determining whether there is the flood characteristic or the drought characteristic between the start time of the drought-flood rapid alternation event and the first drought-flood rapid alternation time point, it can be determined which disaster event comes first and which disaster event follows in the current drought-flood rapid alternation event. Preferably, it can also be determined whether there is the flood characteristic or the drought characteristic between the second drought-flood rapid alternation time point and the end time of the drought-flood rapid alternation event to determine the order of the two disaster events.

[0161] If the flood event comes first, the start time of the drought-flood rapid alternation event is the start time of the flood event, and the first drought-flood rapid alternation time point is the end time of the flood event; all the first flood intensities within the time period from the start time of the drought-flood rapid alternation event to the first drought-flood rapid alternation time point are the flood intensities corresponding to each day within the entire flood event. By performing an accumulation process on the flood intensities corresponding to each day within the entire flood event, the first flood intensity is obtained.

[0162] If the drought event comes after, the end time of the drought-flood rapid alternation event is the end time of the drought event, and the second drought-flood rapid alternation time point is the start time of the drought event; all the first drought intensities between the second drought-flood rapid alternation time point and the end time of the drought-flood rapid alternation event are the drought intensities corresponding to each day within the entire drought event. By performing an accumulation process on the drought intensities corresponding to each day within the entire drought event, the first drought intensity is obtained.

[0163] Specifically, substitute the drought-flood rapid alternation interval days, the drought-flood rapid alternation duration, the accumulated value of the first flood intensity, and the accumulated value of the first drought into the preset drought-flood rapid alternation event intensity calculation formula to obtain the first drought-flood rapid alternation event intensity corresponding to the drought-flood rapid alternation event.

[0164] Specifically, when it is determined that there is the drought characteristic between the start time of the drought-flood rapid alternation event and the first drought-flood rapid alternation time point, obtain all the second drought intensities within the time period from the start time of the drought-flood rapid alternation event to the first drought-flood rapid alternation time point, perform an accumulation process on all the second drought intensities to obtain the accumulated value of the second drought intensity, and obtain all the second flood intensities between the second drought-flood rapid alternation time point and the end time of the drought-flood rapid alternation event, and perform an accumulation process on all the second flood intensities to obtain the accumulated value of the second flood intensity.

[0165] If a drought event occurs first, the start time of the drought-flood rapid transition event is the start time of the drought event, and the first drought-flood rapid transition time point is the end time of the drought event; all the second drought intensities within the period from the start time of the drought-flood rapid transition event to the first drought-flood rapid transition time point are the drought intensities corresponding to each day within the entire drought event. By performing an accumulation process on the drought intensities corresponding to each day within the entire drought event, the second drought intensity is obtained.

[0166] If a flood event occurs later, the end time of the drought-flood rapid transition event is the end time of the flood event, and the second drought-flood rapid transition time point is the start time of the flood event; all the second flood intensities between the second drought-flood rapid transition time point and the end time of the drought-flood rapid transition event are the flood intensities corresponding to each day within the entire flood event. By performing an accumulation process on the flood intensities corresponding to each day within the entire flood event, the second flood intensity is obtained.

[0167] Specifically, substitute the number of days of the drought-flood rapid transition interval, the duration of the drought-flood rapid transition, the cumulative value of the second drought intensity, and the cumulative value of the second flood into the preset calculation formula for the intensity of the drought-flood rapid transition event to obtain the second drought-flood rapid transition event intensity corresponding to the drought-flood rapid transition event.

[0168] Specifically, the preset calculation formula for the intensity of the drought-flood rapid transition event is as follows:

[0169]

[0170] In the formula, S ci is the intensity of the i-th rapid transition event; ∑SWAP e represents the cumulative value of the intensity between the start time of the drought-flood rapid transition event and the first drought-flood rapid transition time point, and ∑SWAP l represents the cumulative value of the intensity between the second drought-flood rapid transition time point and the end time of the drought-flood rapid transition event; D i is the duration of the drought-flood rapid transition, and L i is the number of days of the drought-flood rapid transition interval.

[0171] In an embodiment, when determining the intensity level of the drought-flood rapid transition event based on the intensity of the drought-flood rapid transition event, compare the intensity of the drought-flood rapid transition event with the drought-flood rapid transition intensity range in the preset drought-flood rapid transition event intensity level division table to determine the drought-flood rapid transition intensity range corresponding to the intensity of the drought-flood rapid transition event. Based on the drought-flood rapid transition intensity range, obtain the corresponding intensity level of the drought-flood rapid transition event; as shown in Table 3, Table 3 is the drought-flood rapid transition event intensity level division table.

[0172] Table 3:

[0173]

[0174] In one embodiment, by counting the occurrence frequencies of drought-flood rapid alternation events corresponding to different intensity levels of drought-flood rapid alternation events in each target sub-basin, and analyzing the spatio-temporal evolution law of drought-flood rapid alternation events in the basin based on the identified occurrence frequencies of drought-flood rapid alternation events at different levels in each space, it is helpful to comprehensively and systematically understand the change law and evolution trend of extreme hydrological events in the basin under the background of global climate change and rapid social and economic development. It can provide an important scientific basis for flood control, drought relief and disaster reduction in the basin, and has great significance for the analysis and prevention of drought-flood rapid alternation disasters and ensuring regional water security.

[0175] For the spatio-temporal distribution law of drought-flood rapid alternation events, taking the spatio-temporal distribution law of different drought-flood rapid alternation levels in the Lancang River Basin as an example for illustration:

[0176] Such as Figure 5 shown, Figure 5 is the spatial distribution map of the occurrence frequencies of drought-flood rapid alternation events at different levels based on the SWAP identification results. It can be seen from the figure that the occurrence frequency of mild drought-flood rapid alternation events in the Lancang River Basin is very high, with an average frequency of 23 times per decade, that is, 2.3 mild drought-flood rapid alternation events occur annually, and the occurrence frequency is as high as 88.7%. Among them, the Yushu area showed a "rising - falling - rising" fluctuation trend during 1960 - 2009, and reached the maximum value of the occurrence frequency of mild rapid alternation events in the basin, which was 35, during 1970 - 1979. The Chamdo area was relatively stable within 50 years, and the event occurrence frequency was stable at 15 - 20 times. The Dali area showed a curve-like trend of "high at both ends and low in the middle" during the research period, and the occurrence frequency of mild rapid alternation events has been increasing in recent years. The Lincang area showed a "falling - rising - falling" fluctuation trend during the research period, and reached the minimum frequency of 15 times in the basin during 1980 - 1989. The Xishuangbanna area was similar to the Lincang area. After reaching the highest frequency value in the region during 1960 - 1969, it showed a downward trend and stabilized below 20 times.

[0177] The average occurrence frequency of moderate drought-flood rapid alternation events in the basin is 18 times, that is, 1.8 moderate drought-flood rapid alternation events occur annually, and the occurrence frequency is as high as 91.3%. It is mainly concentrated in the middle and lower reaches of the basin. The Yushu area reached the regional maximum value of 19 times in the 1980s. The Chamdo area showed a significant upward trend before the 21st century, and the disaster occurrence frequency was very high. It didn't start to slowly decrease until the 21st century. The Dali area has maintained a relatively high frequency since the 1970s. The occurrence frequency of moderate disasters in the Lincang area during the research period was very high, and the average frequency per decade was basically 21 times. The Xishuangbanna area showed a change process of "low at both ends and high in the middle". During 1970 - 1999, the disaster occurrence frequency per decade was above 20, that is, about two drought-flood rapid alternation events occurred annually.

[0178] The average occurrence frequency of severe drought-flood rapid alternation events in the basin is 3 times, that is, severe drought-flood rapid alternation events occur 3 times per decade, and the incidence rate is 28%; the change process curve of the occurrence frequency of severe drought-flood rapid alternation events in Yushu area is similar to its mild process curve, reaching the regional maximum value of 6 times in the 1970s and the regional minimum value of 1 time in the 1990s; the Changdu area shows an upward trend during 1960 - 2009 and reaches the maximum frequency of severe events in the basin in the 21st century; the severe rapid alternation events in Dali area show a stable state in 50 years, with an average frequency of 3 - 4 times; the Lincang area fluctuates between 2 - 4 times and shows an upward trend in recent years; due to abundant water volume, the frequency of rapid alternation events in Xishuangbanna area has always been relatively high, and there is only a slight decline in the 1990s.

[0179] Extreme drought-flood rapid alternation events did not occur before 1980. With the intensification of climate change, the problems of precipitation uncertainty and unevenness became prominent, and extreme drought-flood rapid alternation events began to occur in the Lancang River Basin; in the 1990s, a severe drought-flood rapid alternation event occurred in the Changdu area and the Xishuangbanna area in 1993 and 1998 respectively. In the early 21st century, an extreme rapid alternation event occurred in Xishuangbanna again.

[0180] From the decadal analysis, in the 1960s of the 20th century, the Changdu area belonged to the region with the lowest risk in the entire Lancang River Basin, and the occurrence frequencies of mild, moderate and severe rapid alternation events were all at relatively low levels, while the Dali and Lincang areas belonged to the regions with relatively high risks; the situation in the 1970s of the 20th century was more serious than that in the 1960s. Among them, the rapid alternation events in the Yushu area increased rapidly, with frequent mild and severe rapid alternation events. The occurrence frequencies of events in the middle and lower reaches of the Lancang River Basin in Yunnan Province (Dali area, Lincang area and Xishuangbanna area) also became higher, and the lower the downstream, the higher the occurrence frequency of events; in the 1980s, the mild rapid alternation events slowed down, but the moderate events increased; in the 1990s, the situation in the Yushu area was more moderate, with almost no rapid alternation events above severe level. The moderate rapid alternation events occurred about once a year, and the occurrence frequencies of moderate rapid alternation events in the remaining areas were almost twice that of it; in the 2010s of the 21st century, the moderate rapid alternation events began to decrease, but the mild, severe and even extreme events all began to increase, resulting in the total number of events reaching a new historical high.

[0181] Example 2, see Figure 2 , Figure 2 is a schematic structural diagram of an embodiment of an identification device for drought-flood rapid alternation events provided by the present invention. As Figure 2 shown, the device includes a standardized weighted average precipitation index calculation module 201, a basin division module 202, a feature extraction module 203 and a drought-flood rapid alternation event identification module 204, specifically as follows:

[0182] The standardized weighted average precipitation index calculation module 201 is used to obtain the measured historical precipitation data of each meteorological station in the target basin, and calculate the standardized weighted average precipitation index corresponding to each meteorological station according to the measured historical precipitation data.

[0183] The basin division module 202 is used to perform spatial division processing on the target basin based on the rotated empirical orthogonal decomposition method to obtain a plurality of target sub-basins, and obtain the target standardized weighted average precipitation index corresponding to each meteorological station in each target sub-basin.

[0184] The feature extraction module 203 is used to extract features from the target standardized weighted average precipitation index respectively to obtain the flood characteristics and drought characteristics corresponding to each target sub-basin.

[0185] The drought-flood rapid transition event identification module 204 is used to identify drought-flood rapid transition events for each target sub-basin based on the flood characteristics and the drought characteristics, and count the occurrence frequency of the drought-flood rapid transition events in each target sub-basin.

[0186] In one embodiment, the standardized weighted average precipitation index calculation module 201 is used to obtain the measured historical precipitation data of each meteorological station in the target basin, and calculate the standardized weighted average precipitation index corresponding to each meteorological station according to the measured historical precipitation data. Specifically, it includes: obtaining the measured historical precipitation data corresponding to each meteorological station in the target basin, where the measured historical precipitation data includes the measured historical daily precipitation data corresponding to a plurality of preset historical years; calculating the weighted average precipitation index corresponding to the measured historical daily precipitation data based on a preset weighted average precipitation index calculation formula; obtaining the first weighted average precipitation index on the same day within a plurality of preset historical years, performing gamma distribution fitting processing on the first weighted average precipitation index to obtain the daily fitted weighted average precipitation index corresponding to the plurality of preset historical years; performing normal standardization on the daily fitted weighted average precipitation index to obtain the daily standardized weighted average precipitation index, and integrating all the daily standardized weighted average precipitation indices within each preset historical year to obtain the standardized weighted average precipitation index corresponding to each preset historical year for each meteorological station.

[0187] In one embodiment, the standardized weighted average precipitation index calculation module 201 is configured to calculate the weighted average precipitation index corresponding to the historical daily measured precipitation data based on a preset weighted average precipitation index calculation formula, specifically including: obtaining a first date corresponding to the historical daily measured precipitation data, and obtaining first historical daily measured precipitation data corresponding to each day within a preset time period before the first date; inputting the historical daily measured precipitation data and the first historical daily measured precipitation data into the preset weighted average precipitation index calculation formula to calculate the weighted average precipitation index corresponding to the historical daily measured precipitation data; wherein, the preset weighted average precipitation index calculation formula is as follows:

[0188]

[0189] In the formula, WAP is the weighted average precipitation index, w n =(1-α)α n is the weight of the previous rainfall, α is a parameter representing the attenuation of the weight over time, P n is the first historical daily measured precipitation data corresponding to the nth day before the first date, N is the preset time period, and is the total number of days of the previous precipitation affecting the current drought and flood status.

[0190] In one embodiment, the watershed division module 202 is configured to perform spatial division processing on the target watershed based on the rotated empirical orthogonal decomposition method to obtain a plurality of target sub-watersheds, specifically including: calculating the covariance of the standardized weighted average precipitation index to obtain a covariance matrix corresponding to the standardized weighted average precipitation index; performing eigenvalue decomposition on the covariance matrix to obtain a plurality of eigenvalues and eigenvectors corresponding to each eigenvalue, and determining a plurality of principal components based on the eigenvalues and the eigenvectors; respectively performing rotation processing on the plurality of principal components to obtain eigenmodes corresponding to each principal component, and performing spatial division processing on the target watershed based on the eigenmodes to obtain a plurality of target sub-watersheds.

[0191] In one embodiment, the feature extraction module 203 is configured to extract features from the target standardized weighted average precipitation index to obtain flood features and drought features corresponding to each target sub-basin, specifically including: setting a first truncation coefficient and a second truncation coefficient; extracting features from the target standardized weighted average precipitation index based on the first truncation coefficient, and when there is a daily standardized weighted average precipitation index in the target standardized weighted average precipitation index that is not less than the first truncation coefficient, obtaining the flood features corresponding to each target sub-basin; extracting features from the target standardized weighted average precipitation index based on the second truncation coefficient, and when there is a daily standardized weighted average precipitation index in the target standardized weighted average precipitation index that is not greater than the second truncation coefficient, obtaining the drought features corresponding to each target sub-basin.

[0192] In one embodiment, the flood-drought rapid transition event recognition module 204 is configured to recognize flood-drought rapid transition events for each target sub-basin based on the flood features and the drought features, specifically including: obtaining the flood features and the drought features, where the flood features include the flood duration, and the flood duration includes the flood start time and the flood end time; the drought features include the drought duration, and the drought duration includes the drought start time and the drought end time; calculating a first minimum time interval between the flood end time and the drought start time, and calculating a second minimum time interval between the drought end time and the flood start time; comparing the first minimum time interval and the second minimum time interval with a preset time threshold respectively, and if the first minimum time interval is not greater than the preset time threshold, or the second minimum time interval is not greater than the preset time threshold, it is determined that there is a flood-drought rapid transition event in the target sub-basin, otherwise, it is determined that there is no flood-drought rapid transition event in the target sub-basin.

[0193] In one embodiment, after the flood-drought rapid transition event recognition module 204 recognizes flood-drought rapid transition events for each target sub-basin, it is further configured to: when it is determined that there is a flood-drought rapid transition event in the target sub-basin, calculate the intensity of the flood-drought rapid transition event corresponding to the flood-drought rapid transition event, and determine the intensity level of the flood-drought rapid transition event based on the intensity of the flood-drought rapid transition event.

[0194] In one embodiment, calculating the corresponding intensity of the drought-flood rapid transition event specifically includes: obtaining the flood characteristics and the drought characteristics, where the flood characteristics further include the flood intensity; the drought characteristics further include the drought intensity; when it is determined that there is a drought-flood rapid transition event in the target sub-basin, obtaining the drought-flood rapid transition interval days and the drought-flood rapid transition duration corresponding to the drought-flood rapid transition event, and based on the drought-flood rapid transition duration, determining the first drought-flood rapid transition time point and the second drought-flood rapid transition time point of the drought-flood rapid transition duration, where the drought-flood rapid transition duration is determined by the start time and the end time of the drought-flood rapid transition event; when it is determined that there are the flood characteristics between the start time of the drought-flood rapid transition event and the first drought-flood rapid transition time point, obtaining all the first flood intensities within the period from the start time of the drought-flood rapid transition event to the first drought-flood rapid transition time point, performing an accumulation process on all the first flood intensities to obtain a first flood intensity accumulation value, and obtaining all the first drought intensities between the second drought-flood rapid transition time point and the end time of the drought-flood rapid transition event, performing an accumulation process on all the first drought intensities to obtain a first drought intensity accumulation value; substituting the drought-flood rapid transition interval days, the drought-flood rapid transition duration, the first flood intensity accumulation value, and the first drought accumulation value into a preset drought-flood rapid transition event intensity calculation formula to obtain the first drought-flood rapid transition event intensity corresponding to the drought-flood rapid transition event; when it is determined that there are the drought characteristics between the start time of the drought-flood rapid transition event and the first drought-flood rapid transition time point, obtaining all the second drought intensities within the period from the start time of the drought-flood rapid transition event to the first drought-flood rapid transition time point, performing an accumulation process on all the second drought intensities to obtain a second drought intensity accumulation value, and obtaining all the second flood intensities between the second drought-flood rapid transition time point and the end time of the drought-flood rapid transition event, performing an accumulation process on all the second flood intensities to obtain a second flood intensity accumulation value; substituting the drought-flood rapid transition interval days, the drought-flood rapid transition duration, the second drought intensity accumulation value, and the second flood accumulation value into a preset drought-flood rapid transition event intensity calculation formula to obtain the second drought-flood rapid transition event intensity corresponding to the drought-flood rapid transition event.

[0195] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working process of the above-described device can refer to the corresponding process in the foregoing method embodiment, and will not be elaborated herein.

[0196] It should be noted that the embodiments of the above drought-flood rapid transition event recognition device are merely illustrative. The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0197] Based on the embodiments of the above method for identifying dry-wet abrupt alternation events, another embodiment of the present invention provides an identification terminal device for dry-wet abrupt alternation events. The identification terminal device for dry-wet abrupt alternation events includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, the method for identifying dry-wet abrupt alternation events according to any embodiment of the present invention is implemented.

[0198] Exemplarily, in this embodiment, the computer program may be divided into one or more modules. The one or more modules are stored in the memory and executed by the processor to complete the present invention. The one or more modules may be a series of computer program instruction segments capable of performing specific functions, and these instruction segments are used to describe the execution process of the computer program in the identification terminal device for dry-wet abrupt alternation events.

[0199] The identification terminal device for dry-wet abrupt alternation events may be a computing device such as a desktop computer, a notebook, a palm computer, and a cloud server. The identification terminal device for dry-wet abrupt alternation events may include, but is not limited to, a processor and a memory.

[0200] The so-called processor may be a central processing unit (CPU), or may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The processor is the control center of the identification terminal device for dry-wet abrupt alternation events, and connects various parts of the entire identification terminal device for dry-wet abrupt alternation events through various interfaces and lines.

[0201] The memory can be used to store the computer programs and / or modules. By running or executing the computer programs and / or modules stored in the memory, and invoking the data stored in the memory, the processor realizes various functions of the recognition terminal device for drought-flood abrupt alternation events. The memory mainly includes a program storage area and a data storage area. Among them, the program storage area can store an operating system, application programs required for at least one function, etc.; the data storage area can store data created according to the use of the mobile phone, etc. In addition, the memory can include high-speed random access memory, and can also include non-volatile memory, such as a hard disk, memory, plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, Flash Card, at least one magnetic disk storage device, flash device, or other volatile solid-state storage devices.

[0202] Based on the above embodiments of the recognition method for drought-flood abrupt alternation events, another embodiment of the present invention provides a storage medium, which includes a stored computer program. When the computer program runs, it controls the device where the storage medium is located to execute the recognition method for drought-flood abrupt alternation events in any embodiment of the present invention.

[0203] In this embodiment, the above storage medium is a computer-readable storage medium. The computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file, or some intermediate form, etc. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium, etc. It should be noted that the content included in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electrical carrier signals and telecommunication signals.

[0204] In summary, a method, device, equipment and storage medium for identifying dry-wet abrupt alternation events provided by the present invention obtain the historical measured precipitation data of each meteorological station in the target basin, calculate the standardized weighted average precipitation index corresponding to each meteorological station according to the historical measured precipitation data; perform spatial division processing on the target basin based on the rotated empirical orthogonal decomposition method to obtain multiple target sub-basins, and obtain the target standardized weighted average precipitation index corresponding to each meteorological station in each target sub-basin; respectively extract features from the target standardized weighted average precipitation index to obtain the flood characteristics and drought characteristics corresponding to each target sub-basin; based on the flood characteristics and drought characteristics, identify dry-wet abrupt alternation events for each target sub-basin, and count the occurrence frequency of dry-wet abrupt alternation events in each target sub-basin; compared with the prior art, the technical solution of the present invention can improve the recognition accuracy of dry-wet abrupt alternation events.

[0205] The above are only the preferred embodiments of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the technical principle of the present invention, several improvements and substitutions can be made, and these improvements and substitutions should also be regarded as the protection scope of the present invention.

Claims

1. A method for identifying dry-wet abrupt transition events, characterized in that, it includes: Obtain the historical measured precipitation data of each meteorological station in the target basin, and calculate the standardized weighted average precipitation index corresponding to each meteorological station according to the historical measured precipitation data; Based on the rotated empirical orthogonal decomposition method, perform spatial partitioning processing on the target basin to obtain multiple target sub-basins, and obtain the target standardized weighted average precipitation index corresponding to each meteorological station in each target sub-basin; Extract features from the target standardized weighted average precipitation index respectively to obtain the flood characteristics and drought characteristics corresponding to each target sub-basin; When extracting features from the target standardized weighted average precipitation index, use the run theory to identify and extract relevant features of dry-wet abrupt transition events; Based on the flood characteristics and the drought characteristics, identify dry-wet abrupt transition events for each target sub-basin, and count the occurrence frequency of the dry-wet abrupt transition events in each target sub-basin; Extracting features from the target standardized weighted average precipitation index to obtain the flood characteristics and drought characteristics corresponding to each target sub-basin specifically includes: Set a first truncation coefficient and a second truncation coefficient; Extract features from the target standardized weighted average precipitation index based on the first truncation coefficient. When there is a daily standardized weighted average precipitation index in the target standardized weighted average precipitation index that is not less than the first truncation coefficient, obtain the flood characteristics corresponding to each target sub-basin; Extract features from the target standardized weighted average precipitation index based on the second truncation coefficient. When there is a daily standardized weighted average precipitation index in the target standardized weighted average precipitation index that is not greater than the second truncation coefficient, obtain the drought characteristics corresponding to each target sub-basin; Based on the flood characteristics and the drought characteristics, identifying dry-wet abrupt transition events for each target sub-basin specifically includes: Obtain the flood characteristics and the drought characteristics, where the flood characteristics include the flood duration, and the flood duration includes the flood start time and the flood end time; the drought characteristics include the drought duration, and the drought duration includes the drought start time and the drought end time; Calculate the first minimum time interval between the flood end time and the drought start time, and calculate the second minimum time interval between the drought end time and the flood start time; Compare the first minimum time interval and the second minimum time interval with a preset time threshold respectively. If the first minimum time interval is not greater than the preset time threshold, or the second minimum time interval is not greater than the preset time threshold, it is determined that there is a dry-wet abrupt transition event in the target sub-basin, otherwise, it is determined that there is no dry-wet abrupt transition event in the target sub-basin; After identifying dry-wet abrupt transition events for each target sub-basin, it further includes: When it is determined that there is a dry-wet abrupt transition event in the target sub-basin, calculate the intensity of the dry-wet abrupt transition event corresponding to the dry-wet abrupt transition event, and determine the intensity level of the dry-wet abrupt transition event based on the intensity of the dry-wet abrupt transition event; Among them, calculating the corresponding intensity of the drought-flood rapid transition event specifically includes: Obtaining the flood characteristics and the drought characteristics, wherein the flood characteristics further include the flood intensity; the drought characteristics further include the drought intensity; When it is determined that there is a drought-flood rapid transition event in the target sub-basin, obtaining the drought-flood rapid transition interval days and the drought-flood rapid transition duration corresponding to the drought-flood rapid transition event, and based on the drought-flood rapid transition duration, determining the first drought-flood rapid transition time point and the second drought-flood rapid transition time point of the drought-flood rapid transition duration, wherein the drought-flood rapid transition duration is determined by the start time and the end time of the drought-flood rapid transition event; When it is determined that there are the flood characteristics between the start time of the drought-flood rapid transition event and the first drought-flood rapid transition time point, obtaining all the first flood intensities within the time period from the start time of the drought-flood rapid transition event to the first drought-flood rapid transition time point, performing an accumulation process on all the first flood intensities to obtain a first flood intensity accumulation value, and obtaining all the first drought intensities between the second drought-flood rapid transition time point and the end time of the drought-flood rapid transition event, performing an accumulation process on all the first drought intensities to obtain a first drought intensity accumulation value; Substituting the drought-flood rapid transition interval days, the drought-flood rapid transition duration, the first flood intensity accumulation value and the first drought accumulation value into a preset drought-flood rapid transition event intensity calculation formula to obtain the first drought-flood rapid transition event intensity corresponding to the drought-flood rapid transition event; When it is determined that there are the drought characteristics between the start time of the drought-flood rapid transition event and the first drought-flood rapid transition time point, obtaining all the second drought intensities within the time period from the start time of the drought-flood rapid transition event to the first drought-flood rapid transition time point, performing an accumulation process on all the second drought intensities to obtain a second drought intensity accumulation value, and obtaining all the second flood intensities between the second drought-flood rapid transition time point and the end time of the drought-flood rapid transition event, performing an accumulation process on all the second flood intensities to obtain a second flood intensity accumulation value; Substituting the drought-flood rapid transition interval days, the drought-flood rapid transition duration, the second drought intensity accumulation value and the second flood accumulation value into a preset drought-flood rapid transition event intensity calculation formula to obtain the second drought-flood rapid transition event intensity corresponding to the drought-flood rapid transition event.

2. A method for identifying a drought-flood rapid transition event according to claim 1, characterized in that obtaining the historical measured precipitation data of each meteorological station in the target basin, and calculating the corresponding standardized weighted average precipitation index of each meteorological station according to the historical measured precipitation data, specifically including: obtaining the historical measured precipitation data corresponding to each meteorological station in the target basin, wherein the historical measured precipitation data includes the historical daily measured precipitation data corresponding to a plurality of preset historical years; calculating the weighted average precipitation index corresponding to the historical daily measured precipitation data based on a preset weighted average precipitation index calculation formula; Obtain the first weighted average precipitation index on the same day within multiple preset historical years, perform gamma distribution fitting on the first weighted average precipitation index, and obtain the daily fitted weighted average precipitation index corresponding to the multiple preset historical years; Perform normal standardization on the daily fitted weighted average precipitation index to obtain the daily standardized weighted average precipitation index, and integrate all the daily standardized weighted average precipitation indices within each preset historical year to obtain the standardized weighted average precipitation index of each preset historical year corresponding to each meteorological station.

3. A method for identifying sudden drought-flood transition events according to claim 2, characterized in that, Based on a preset weighted average precipitation index calculation formula, calculate the weighted average precipitation index corresponding to the historical daily precipitation measured data, specifically including: Obtain the first date corresponding to the historical daily precipitation measured data, and obtain the first historical daily precipitation measured data corresponding to each day within a preset time period before the first date; Input the historical daily precipitation measured data and the first historical daily precipitation measured data into a preset weighted average precipitation index calculation formula, and calculate the weighted average precipitation index corresponding to the historical daily precipitation measured data; wherein, the preset weighted average precipitation index calculation formula is as follows: ； In the formula, is the weighted average precipitation index, is the weight of the previous rainfall, is a parameter characterizing the decay of the weight over time, is the measured data of the first historical daily precipitation corresponding to the nth day before the first date, and N is a preset time period, which is the total number of days of the previous precipitation affecting the current drought and flood status.

4. A method for identifying sudden drought-flood transition events according to claim 1, characterized in that, Based on the rotated empirical orthogonal decomposition method, perform spatial partitioning on the target basin to obtain multiple target sub-basins, specifically including: Calculate the covariance of the standardized weighted average precipitation index to obtain the covariance matrix corresponding to the standardized weighted average precipitation index; Perform eigenvalue decomposition on the covariance matrix to obtain multiple eigenvalues and eigenvectors corresponding to each eigenvalue, and determine multiple principal components based on the eigenvalues and the eigenvectors; Perform rotation processing on the multiple principal components respectively to obtain the eigenmodes corresponding to each principal component, and perform spatial partitioning on the target basin based on the eigenmodes to obtain multiple target sub-basins.

5. An apparatus for identifying sudden drought-flood transition events, characterized in that, including: A standardized weighted average precipitation index calculation module, a basin partitioning module, a feature extraction module, and a sudden drought-flood transition event identification module; Among them, the standardized weighted average precipitation index calculation module is used to obtain the historical precipitation measured data of each meteorological station in the target basin, and calculate the standardized weighted average precipitation index corresponding to each meteorological station according to the historical precipitation measured data; The basin partitioning module is used to perform spatial partitioning on the target basin based on the rotated empirical orthogonal decomposition method to obtain multiple target sub-basins, and obtain the target standardized weighted average precipitation index corresponding to each meteorological station in each target sub-basin; The feature extraction module is used to perform feature extraction on the target standardized weighted average precipitation index respectively to obtain the flood characteristics and drought characteristics corresponding to each target sub-basin; When extracting features from the target standardized weighted average precipitation index, the run theory is used to identify and extract relevant features of drought-flood abrupt change events; The drought-flood abrupt change event recognition module is used to recognize drought-flood abrupt change events for each target sub-basin based on the flood characteristics and the drought characteristics, and count the occurrence frequency of the drought-flood abrupt change events in each target sub-basin; Feature extraction is performed on the target standardized weighted average precipitation index to obtain the flood characteristics and drought characteristics corresponding to each target sub-basin, specifically including: Set a first truncation coefficient and a second truncation coefficient; Based on the first truncation coefficient, perform feature extraction on the target standardized weighted average precipitation index. When there is a daily standardized weighted average precipitation index in the target standardized weighted average precipitation index that is not less than the first truncation coefficient, obtain the flood characteristics corresponding to each target sub-basin; Based on the second truncation coefficient, perform feature extraction on the target standardized weighted average precipitation index. When there is a daily standardized weighted average precipitation index in the target standardized weighted average precipitation index that is not greater than the second truncation coefficient, obtain the drought characteristics corresponding to each target sub-basin; Based on the flood characteristics and the drought characteristics, perform drought-flood abrupt change event recognition on each target sub-basin, specifically including: Obtain the flood characteristics and the drought characteristics, where the flood characteristics include the flood duration, and the flood duration includes the flood start time and the flood end time; the drought characteristics include the drought duration, and the drought duration includes the drought start time and the drought end time; Calculate the first minimum time interval between the flood end time and the drought start time, and calculate the second minimum time interval between the drought end time and the flood start time; Compare the first minimum time interval and the second minimum time interval with a preset time threshold respectively. If the first minimum time interval is not greater than the preset time threshold, or the second minimum time interval is not greater than the preset time threshold, it is determined that there is a drought-flood abrupt change event in the target sub-basin, otherwise, it is determined that there is no drought-flood abrupt change event in the target sub-basin; After performing drought-flood abrupt change event recognition on each target sub-basin, it further includes: When it is determined that there is a drought-flood abrupt change event in the target sub-basin, calculate the intensity of the drought-flood abrupt change event corresponding to the drought-flood abrupt change event, and determine the intensity level of the drought-flood abrupt change event based on the intensity of the drought-flood abrupt change event; Among them, the calculation of the intensity of the drought-flood abrupt change event corresponding to the drought-flood abrupt change event specifically includes: Obtain the flood characteristics and the drought characteristics, where the flood characteristics further include the flood intensity; the drought characteristics further include the drought intensity; When it is determined that there is a rapid alternation of drought and flood in the target sub-watershed, obtain the number of days of the rapid alternation of drought and flood and the duration of the rapid alternation of drought and flood corresponding to the rapid alternation of drought and flood event, and based on the duration of the rapid alternation of drought and flood, determine the first rapid alternation of drought and flood time point and the second rapid alternation of drought and flood time point of the duration of the rapid alternation of drought and flood, wherein the duration of the rapid alternation of drought and flood is determined by the start time and the end time of the rapid alternation of drought and flood event; When it is determined that there is the flood characteristic between the start time of the rapid alternation of drought and flood event and the first rapid alternation of drought and flood time point, obtain all the first flood intensities within the time period from the start time of the rapid alternation of drought and flood event to the first rapid alternation of drought and flood time point, perform an accumulation process on all the first flood intensities to obtain a first flood intensity accumulation value, and obtain all the first drought intensities between the second rapid alternation of drought and flood time point and the end time of the rapid alternation of drought and flood event, perform an accumulation process on all the first drought intensities to obtain a first drought intensity accumulation value; Substitute the number of days of the rapid alternation of drought and flood, the duration of the rapid alternation of drought and flood, the first flood intensity accumulation value and the first drought accumulation value into a preset rapid alternation of drought and flood event intensity calculation formula to obtain a first rapid alternation of drought and flood event intensity corresponding to the rapid alternation of drought and flood event; When it is determined that there is the drought characteristic between the start time of the rapid alternation of drought and flood event and the first rapid alternation of drought and flood time point, obtain all the second drought intensities within the time period from the start time of the rapid alternation of drought and flood event to the first rapid alternation of drought and flood time point, perform an accumulation process on all the second drought intensities to obtain a second drought intensity accumulation value, and obtain all the second flood intensities between the second rapid alternation of drought and flood time point and the end time of the rapid alternation of drought and flood event, perform an accumulation process on all the second flood intensities to obtain a second flood intensity accumulation value; Substitute the number of days of the rapid alternation of drought and flood, the duration of the rapid alternation of drought and flood, the second drought intensity accumulation value and the second flood accumulation value into a preset rapid alternation of drought and flood event intensity calculation formula to obtain a second rapid alternation of drought and flood event intensity corresponding to the rapid alternation of drought and flood event.

6. A terminal device Characterized in that it includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and when the processor executes the computer program, it implements the method for identifying a rapid alternation of drought and flood event as described in any one of claims 1 to 4.

7. A computer-readable storage medium Characterized in that the computer-readable storage medium includes a stored computer program, wherein when the computer program runs, it controls the device where the computer-readable storage medium is located to execute the method for identifying a rapid alternation of drought and flood event as described in any one of claims 1 to 4.

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