Regional inconsistent flood frequency calculation method and system

Abstract

The invention relates to a regional inconsistent flood frequency calculation method and system. The method comprises the following steps: collecting data of annual maximum peak flood flow of a hydrometric station in a target drainage basin over the years; obtaining an annual maximum peak discharge sequence of the target watershed hydrological station, and screening climate factors related to the maximum peak discharge sequence by taking the annual maximum peak discharge sequence as basic data; constructing a regional non-consistent flood frequency calculation model by considering the influence of correlation and climatic factors among hydrometric stations of the target drainage basin; and obtaining a flood frequency calculation result based on the regional non-consistency flood frequency calculation model of different pooling scenes. According to the method, the extreme flood correlation and the climate factor influence among the stations are comprehensively considered, the influence of the climate factor on the extreme flood event frequency of each station in the drainage basin can be quantitatively analyzed, the result uncertainty is greatly reduced, and the calculation precision is improved.

Description

Technical Field

[0001] The invention belongs to the technical field of water conservancy engineering, and in particular relates to a method and system for calculating regional inconsistency flood frequency. Background Art

[0002] In recent decades, with the intensification of climate change, the consistency assumption of flood sequences has been questioned, and the traditional flood frequency calculation method based on the consistency assumption is no longer applicable in the changing environment.

[0003] The single-station non-consistent flood frequency calculation model based on the time-varying moment method has large uncertainty in its results and low calculation accuracy, and its application in engineering design reference is very limited.

[0004] Therefore, it is of great significance to consider both the influence of climate factors and the correlation between sites in a changing environment and construct a regional inconsistent flood frequency calculation model to improve the calculation accuracy of flood frequency calculation. Summary of the invention

[0005] In order to make up for the defects of the prior art, the present invention provides a method and system for calculating regional inconsistency flood frequency.

[0006] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0007] In a first aspect, a method for calculating regional inconsistency flood frequency is provided, comprising:

[0008] Collect historical data on the annual maximum flood peak flow at hydrological stations in the target river basin;

[0009] The annual maximum flood peak flow sequence of the target basin hydrological station is obtained based on the historical data of the annual maximum flood peak flow. The climate factors related to the maximum flood peak flow sequence are screened out based on the annual maximum flood peak flow sequence as the basic data.

[0010] Considering the correlation between hydrological stations in the target basin and the influence of climate factors, a regional inconsistent flood frequency calculation model is constructed. The regional inconsistent flood frequency calculation model includes no pooling scenario, partial pooling scenario and full pooling scenario.

[0011] Based on the regional inconsistent flood frequency calculation model for no pooling scenario, partial pooling scenario and full pooling scenario, a regional inconsistent extreme flood frequency analysis was carried out, and the flood frequency calculation results for no pooling scenario, partial pooling scenario and full pooling scenario were obtained.

[0012] Furthermore, the annual maximum flood peak flow sequence Y obeys the log-normal distribution, and the probability density function expression of Y is:

[0013] ;

[0014] in, is the location parameter of the lognormal distribution; is the scale parameter.

[0015] Furthermore, the regional non-consistent flood frequency calculation model includes a first-layer model structure and a second-layer model structure.

[0016] The first-level model structure is the annual maximum flood peak flow sequence of the target basin hydrological station It obeys the lognormal distribution, and the expression is:

[0017] ;

[0018] in, is the location parameter, s represents the site number of the target basin hydrological station, s=1, 2, ..., K, t represents the year sequence number, N represents the normal distribution, represents the correlation between hydrological stations in the target basin, which is the covariance matrix of the K×K multivariate normal distribution, ; represents the climate factor in year t, is the first parameter of the s site, is the second parameter of the s site;

[0019] The second layer model structure is Subject to hyperparameters and The normal distribution of , , , and is a fixed value, Normal distribution , It follows the inverse Wishart distribution, , is a K×K symmetric positive definite matrix, for degrees of freedom.

[0020] Furthermore, the expression of the regional non-uniform flood frequency calculation model without pooling scenario is:

[0021] ;

[0022] ;

[0023] ;

[0024] ;

[0025] in, is the scale parameter of the first station, is the scale parameter of site s.

[0026] Furthermore, the expression of the regional non-uniform flood frequency calculation model for the partial pooling scenario is:

[0027] ;

[0028] ;

[0029] ;

[0030] ;

[0031] ;

[0032] .

[0033] Furthermore, the expression of the regional non-uniform flood frequency calculation model for the full pooling scenario is:

[0034] ;

[0035] ;

[0036] ;

[0037] ;

[0038] Second parameter for all sites same.

[0039] In a second aspect, a regional non-consistent flood frequency calculation system is provided, comprising:

[0040] The data collection module is used to collect historical data of the annual maximum flood peak flow of the hydrological stations in the target river basin;

[0041] The data processing module is used to obtain the annual maximum flood peak flow sequence of the target basin hydrological station based on the historical data of the annual maximum flood peak flow, and to screen out the climate factors related to the maximum flood peak flow sequence based on the annual maximum flood peak flow sequence;

[0042] The model building module is used to consider the correlation between hydrological stations in the target basin and the influence of climate factors, and to build a regional inconsistent flood frequency calculation model. The regional inconsistent flood frequency calculation model includes no pooling scenario, partial pooling scenario and full pooling scenario;

[0043] The flood frequency calculation module is used to perform regional inconsistent extreme flood frequency analysis based on the regional inconsistent flood frequency calculation model of no pooling scenario, partial pooling scenario and full pooling scenario, and obtain the flood frequency calculation results of no pooling scenario, partial pooling scenario and full pooling scenario.

[0044] Furthermore,

[0045] The annual maximum flood peak flow sequence Y obeys the log-normal distribution, and the probability density function expression of Y is:

[0046] ;

[0047] in, is the location parameter of the lognormal distribution; is the scale parameter.

[0048] Furthermore, the regional non-consistent flood frequency calculation model includes a first-layer model structure and a second-layer model structure;

[0049] The first-level model structure is the annual maximum flood peak flow sequence of the target basin hydrological station It obeys the lognormal distribution, and the expression is:

[0050] ;

[0051] in, is the location parameter, s represents the site number of the target basin hydrological station, s=1, 2, ..., K, t represents the year sequence number, N represents the normal distribution, represents the correlation between hydrological stations in the target basin, which is the covariance matrix of the K×K multivariate normal distribution, ; represents the climate factor in year t, is the first parameter of the s site, is the second parameter of the s site;

[0052] The second layer model structure is Subject to hyperparameters and The normal distribution of , , , and is a fixed value, Normal distribution , It follows the inverse Wishart distribution, , is a K×K symmetric positive definite matrix, for degrees of freedom.

[0053] Furthermore,

[0054] The expression of the regional non-uniform flood frequency calculation model without pooling scenario is:

[0055] ;

[0056] ;

[0057] ;

[0058] ;

[0059] in, is the scale parameter of the first station, is the scale parameter of site s;

[0060] The expression of the regional non-uniform flood frequency calculation model for the partial pooling scenario is:

[0061] ;

[0062] ;

[0063] ;

[0064] ;

[0065] ;

[0066] ;

[0067] The expression of the regional non-uniform flood frequency calculation model for the full pooling scenario is:

[0068] ;

[0069] ;

[0070] ;

[0071] ;

[0072] Second parameter for all sites same.

[0073] The beneficial effects achieved by the present invention are:

[0074] Collect historical data of annual maximum flood peak flow of hydrological stations in the target basin; obtain the annual maximum flood peak flow sequence of hydrological stations in the target basin based on historical data of annual maximum flood peak flow, and screen out climate factors related to the maximum flood peak flow sequence based on the annual maximum flood peak flow sequence; consider the correlation between hydrological stations in the target basin and the influence of climate factors, and construct a regional inconsistent flood frequency calculation model, which includes no pooling scenario, partial pooling scenario and full pooling scenario; based on the regional inconsistent flood frequency calculation model of no pooling scenario, partial pooling scenario and full pooling scenario, perform regional inconsistent extreme flood frequency analysis, and obtain flood frequency calculation results of no pooling scenario, partial pooling scenario and full pooling scenario. Comprehensively consider the correlation of extreme floods between stations and the influence of climate factors, and can quantitatively analyze the influence of climate factors on the frequency of extreme flood events at each station in the basin, and greatly reduce the uncertainty of the results and improve the calculation accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0075] Figure 1 A flow chart of a method for calculating flood frequency of regional inconsistency according to the present invention;

[0076] Figure 2 It is a structural diagram of the regional inconsistency flood frequency calculation system of the present invention. DETAILED DESCRIPTION

[0077] The present invention will be further described below in conjunction with the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and cannot be used to limit the protection scope of the present invention.

[0078] like Figure 1 As shown, an embodiment of the present invention provides a method for calculating regional inconsistency flood frequency, including:

[0079] 101. Collect historical data on the annual maximum flood peak flow at hydrological stations in the target river basin;

[0080] The annual maximum flood peak flow data of the target basin hydrological station within the preset year period is obtained by searching the known hydrological information database.

[0081] 102. Obtain the annual maximum flood peak flow sequence of the target basin hydrological station based on the historical data of annual maximum flood peak flow. Use the annual maximum flood peak flow sequence as the basic data to screen out the climate factors related to the maximum flood peak flow sequence.

[0082] Taking the annual maximum flood peak flow series of hydrological stations as the basic data, the climate factors with significant correlation with the annual maximum flood peak flow series of most stations in the target basin were screened out; this climate factor is a large-scale climate index and serves as a covariate in the regional non-uniform flood frequency calculation model.

[0083] 103. Considering the correlation between hydrological stations in the target basin and the influence of climate factors, a regional non-uniform flood frequency calculation model is constructed;

[0084] The annual maximum flood peak flow sequence Y obeys the log-normal distribution LN (Log-normal), and the probability density function expression of Y is:

[0085] ;

[0086] in, is the location parameter of the lognormal distribution; is the scale parameter;

[0087] The regional non-consistent flood frequency calculation model includes the first-layer model structure and the second-layer model structure.

[0088] The first-level model structure is the annual maximum flood peak flow sequence of the target basin hydrological station It obeys the lognormal distribution, and the expression is:

[0089] ;

[0090] in, is the location parameter, s represents the site number of the target basin hydrological station, s=1, 2, ..., K, t represents the year sequence number, N represents the normal distribution, represents the correlation between hydrological stations in the target basin, which is the covariance matrix of the K×K multivariate normal distribution, ; represents the climate factor in year t, is the first parameter of the s site, is the second parameter of the s site;

[0091] The second layer model structure is Subject to hyperparameters and The normal distribution of , , , and is a fixed value, Normal distribution , It follows the inverse Wishart distribution, , is a K×K symmetric positive definite matrix, for degrees of freedom;

[0092] In the regional non-consistent flood frequency calculation model, three situations are considered according to the degree of comprehensive site information, namely:

[0093] 1. Regional non-uniform flood frequency calculation model for no pooling scenario (No Pooling Model)

[0094] In this model, the correlation between sites is not considered. It is assumed that each site is independent and has no correlation. The annual maximum flood peak flow series of each site is used to construct a frequency calculation model separately.

[0095] The expression of the regional non-uniform flood frequency calculation model without pooling scenario is:

[0096] ;

[0097] ;

[0098] ;

[0099] ;

[0100] in, is the scale parameter of the first station, is the scale parameter of site s;

[0101] 2. Regional non-uniform flood frequency calculation model for partial pooling scenario (Partial Pooling Model)

[0102] In this model, the correlation between stations is considered to reflect the homogeneous response characteristics of the annual maximum flood peak flow series of each station in the region to climate factors, and the individual differences of extreme floods at each station are also considered;

[0103] The expression of the regional non-uniform flood frequency calculation model for the partial pooling scenario is:

[0104] ;

[0105] ;

[0106] ;

[0107] ;

[0108] ;

[0109] ;

[0110] 3. Regional non-uniform flood frequency calculation model for full pooling scenario (Full Pooling Model)

[0111] In this model, only the homogeneous response characteristics of the annual maximum flood peak flow series of each station in the region to climate factors are considered, and the individual differences of extreme floods at the stations are not considered;

[0112] The expression of the regional non-uniform flood frequency calculation model for the full pooling scenario is:

[0113] ;

[0114] ;

[0115] ;

[0116] ;

[0117] Second parameter for all sites The extreme floods at all stations respond to climate factors in the same way.

[0118] It should be noted that the goodness of fit evaluation of all models is based on the Akaike Information Criterion (AIC) and the Deviation Information Criterion (DIC). The model with the minimum AIC value and DIC value is the optimal regional non-consistent extreme flood frequency calculation model, as shown in Table 1.

[0119]

[0120] In the table, the DIC value of the partial pooling model is 1298 and the AIC value is 2081, which is the smallest among the three models. Therefore, the regional non-uniform flood frequency calculation model of the partial pooling scenario is the optimal one.

[0121] 104. Based on the regional inconsistent flood frequency calculation model of no pooling scenario, partial pooling scenario and full pooling scenario, the regional inconsistent extreme flood frequency analysis is carried out to obtain the flood frequency calculation results of no pooling scenario, partial pooling scenario and full pooling scenario.

[0122] It should be noted that based on the regional inconsistent flood frequency calculation model of three different scenarios, the regional inconsistent extreme flood frequency analysis in the target basin was carried out to obtain the influence of climate driving factors on each station under the no pooling scenario, partial pooling scenario and full pooling scenario. The uncertainty intervals of the flood frequency calculation models under the partial pooling scenario and the full pooling scenario are shown in Figure 2, as well as the 0.99 flood quantile values ​​and inconsistent return period results of each station in the target basin. Through practical analysis, it is determined that the uncertainty intervals of the design results under the partial pooling model and the full pooling model are significantly smaller than the uncertainty intervals of the no-pooling model. This shows that the regional inconsistent flood frequency calculation models under the partial pooling scenario and the full pooling scenario have higher simulation accuracy in flood frequency calculation and uncertainty analysis.

[0123] The principles of the embodiments of the present invention are:

[0124] Collect the historical data of the annual maximum flood peak flow of the hydrological stations in the target basin; obtain the annual maximum flood peak flow sequence of the hydrological stations in the target basin based on the historical data of the annual maximum flood peak flow, and screen out the climate factors related to the maximum flood peak flow sequence based on the annual maximum flood peak flow sequence; consider the correlation between the hydrological stations in the target basin and the influence of climate factors, and construct a regional inconsistent flood frequency calculation model, which includes no pooling scenario, partial pooling scenario and full pooling scenario; based on the regional inconsistent flood frequency calculation model of no pooling scenario, partial pooling scenario and full pooling scenario, perform regional inconsistent extreme flood frequency analysis, and obtain the flood frequency calculation results of no pooling scenario, partial pooling scenario and full pooling scenario; by comparing the flood frequency calculation results of no pooling scenario, partial pooling scenario and full pooling scenario, analyze the influence of climate factors on the extreme flood frequency of the target basin. Comprehensively considering the correlation of extreme floods between stations and the influence of climate factors, it is possible to quantitatively analyze the influence of climate factors on the frequency of extreme flood events at each station in the basin, and greatly reduce the uncertainty of the results and improve the calculation accuracy.

[0125] Combined with the above Figure 1 The method for calculating regional inconsistency flood frequency described in the embodiment is described below. The system for calculating regional inconsistency flood frequency is described by way of an embodiment.

[0126] like Figure 2 As shown, an embodiment of the present invention provides a regional inconsistency flood frequency calculation system, including:

[0127] The data collection module 201 is used to collect the historical data of the annual maximum flood peak flow of the hydrological station in the target river basin;

[0128] The data processing module 202 is used to obtain the annual maximum flood peak flow sequence of the target basin hydrological station based on the historical data of the annual maximum flood peak flow, and to screen out the climate factors related to the maximum flood peak flow sequence based on the annual maximum flood peak flow sequence;

[0129] The model building module 203 is used to consider the correlation between the hydrological stations in the target basin and the influence of climate factors, and to build a regional non-consistent flood frequency calculation model, wherein the regional non-consistent flood frequency calculation model includes a no pooling scenario, a partial pooling scenario, and a full pooling scenario;

[0130] The flood frequency calculation module 204 is used to perform regional inconsistent extreme flood frequency analysis based on the regional inconsistent flood frequency calculation model of the no-pooling scenario, partial-pooling scenario and full-pooling scenario, and obtain the flood frequency calculation results of the no-pooling scenario, partial-pooling scenario and full-pooling scenario.

[0131] The principles of the embodiments of the present invention are:

[0132] The data collection module 201 collects the historical data of the annual maximum flood peak flow of the hydrological station in the target basin; the data processing module 202 obtains the annual maximum flood peak flow sequence of the hydrological station in the target basin based on the historical data of the annual maximum flood peak flow, and uses the annual maximum flood peak flow sequence as the basic data to screen out the climate factors related to the maximum flood peak flow sequence; the model construction module 203 considers the correlation between the hydrological stations in the target basin and the influence of climate factors to construct a regional inconsistent flood frequency calculation model; the flood frequency calculation module 204 conducts regional inconsistent extreme flood frequency analysis based on the regional inconsistent flood frequency calculation model of the no pooling scenario, partial pooling scenario and full pooling scenario, and obtains the flood frequency calculation result. Comprehensively considering the correlation between extreme floods and the influence of climate factors between each station, it can quantitatively analyze the influence of climate factors on the frequency of extreme flood events at each station in the basin, and greatly reduce the uncertainty of the results and improve the calculation accuracy.

[0133] Combination Figure 2 The embodiments shown are preferably some embodiments of the present invention.

[0134] The annual maximum flood peak flow sequence Y obeys the log-normal distribution, and the probability density function expression of Y is:

[0135] ;

[0136] in, is the location parameter of the lognormal distribution; is the scale parameter.

[0137] Combination Figure 2 In the embodiment shown, preferably, in some embodiments of the present invention, the regional non-consistent flood frequency calculation model includes a first layer model structure and a second layer model structure;

[0138] The first-level model structure is the annual maximum flood peak flow sequence of the target basin hydrological station It obeys the lognormal distribution, and the expression is:

[0139] ;

[0140] in, is the location parameter, s represents the site number of the target basin hydrological station, s=1, 2, ..., K, t represents the year sequence number, N represents the normal distribution, represents the correlation between hydrological stations in the target basin, which is the covariance matrix of the K×K multivariate normal distribution, ; represents the climate factor in year t, is the first parameter of the s site, is the second parameter of the s site;

[0141] The second layer model structure is Subject to hyperparameters and The normal distribution of , , , and is a fixed value, Normal distribution , It follows the inverse Wishart distribution, , is a K×K symmetric positive definite matrix, for degrees of freedom.

[0142] The expression of the regional non-uniform flood frequency calculation model without pooling scenario is:

[0143] ;

[0144] ;

[0145] ;

[0146] ;

[0147] in, is the scale parameter of the first station, is the scale parameter of site s;

[0148] The expression of the regional non-uniform flood frequency calculation model for the partial pooling scenario is:

[0149] ;

[0150] ;

[0151] ;

[0152] ;

[0153] ;

[0154] ;

[0155] The expression of the regional non-uniform flood frequency calculation model for the full pooling scenario is:

[0156] ;

[0157] ;

[0158] ;

[0159] ;

[0160] Second parameter for all sites same.

[0161] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0162] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0163] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0164] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0165] The above are merely embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention are included in the scope of the claims of the present invention to be approved.

Claims

1. A method for calculating regional inconsistency flood frequency, characterized in that: include: Collect historical data on the annual maximum flood peak flow at hydrological stations in the target river basin; According to the historical data of the annual maximum flood peak flow, the annual maximum flood peak flow sequence of the hydrological station in the target basin is obtained, and the climate factors related to the maximum flood peak flow sequence are screened out based on the annual maximum flood peak flow sequence as the basic data; Considering the correlation between the hydrological stations in the target watershed and the influence of the climate factors, a regional inconsistent flood frequency calculation model is constructed, wherein the regional inconsistent flood frequency calculation model includes a no pooling scenario, a partial pooling scenario, and a full pooling scenario; Based on the regional inconsistent flood frequency calculation model of the no-pooling scenario, the partial pooling scenario and the full pooling scenario, a regional inconsistent extreme flood frequency analysis is performed to obtain the flood frequency calculation results of the no-pooling scenario, the partial pooling scenario and the full pooling scenario.

2. The method for calculating regional inconsistency flood frequency according to claim 1, characterized in that: The annual maximum flood peak flow sequence Y obeys the log-normal distribution, and the probability density function expression of Y is: ； Among them, the is the location parameter of the lognormal distribution; is the scale parameter.

3. The method for calculating regional inconsistency flood frequency according to claim 2, characterized in that: The regional inconsistency flood frequency calculation model includes a first-layer model structure and a second-layer model structure. The first-layer model structure is the annual maximum flood peak flow sequence of the target basin hydrological station. It obeys the lognormal distribution, and the expression is: ； Among them, the is a location parameter, s represents the site number of the target basin hydrological station, s=1, 2, ..., K, t represents the year sequence number, N represents normal distribution, represents the correlation between the hydrological stations in the target basin, which is the covariance matrix of the K×K multivariate normal distribution. ; represents the climate factor of year t, is the first parameter of the s site, is the second parameter of the s site; The second layer model structure is Subject to hyperparameters and The normal distribution of , , , and stated is a fixed value, Normal distribution , It follows the inverse Wishart distribution, , is a K×K symmetric positive definite matrix, For the degrees of freedom.

4. The method for calculating regional inconsistency flood frequency according to claim 3, characterized in that: The expression of the non-uniform flood frequency calculation model for the region without pooling scenario is: ； ； ； ； Among them, the is the scale parameter of the first site, is the scale parameter of the s site.

5. The method for calculating regional inconsistency flood frequency according to claim 3, characterized in that: The expression of the regional non-uniform flood frequency calculation model for the partial pooling scenario is: ； ； ； ； ； 。 6. The method for calculating regional inconsistency flood frequency according to claim 3, characterized in that: The expression of the regional non-uniform flood frequency calculation model for the full pooling scenario is: ； ； ； ； The second parameter for all sites same.

7. A regional non-consistent flood frequency calculation system, characterized in that: include: The data collection module is used to collect historical data of the annual maximum flood peak flow of the hydrological stations in the target river basin; A data processing module, used to obtain the annual maximum flood peak flow sequence of the target basin hydrological station according to the historical data of the annual maximum flood peak flow, and to screen out the climate factors related to the maximum flood peak flow sequence based on the annual maximum flood peak flow sequence; A model building module, for considering the correlation between the hydrological stations in the target basin and the influence of the climate factors, and building a regional inconsistent flood frequency calculation model, wherein the regional inconsistent flood frequency calculation model includes a no pooling scenario, a partial pooling scenario, and a full pooling scenario; The flood frequency calculation module is used to perform regional inconsistent extreme flood frequency analysis based on the regional inconsistent flood frequency calculation model of the no-pooling scenario, the partial pooling scenario and the full pooling scenario, and obtain the flood frequency calculation results of the no-pooling scenario, the partial pooling scenario and the full pooling scenario.

8. The regional non-consistent flood frequency calculation system according to claim 7, characterized in that: The annual maximum flood peak flow sequence Y obeys the log-normal distribution, and the probability density function expression of Y is: ； Among them, the is the location parameter of the lognormal distribution; is the scale parameter.

9. The regional inconsistency flood frequency calculation system according to claim 8, characterized in that: The regional inconsistency flood frequency calculation model includes a first-layer model structure and a second-layer model structure; The first-layer model structure is the annual maximum flood peak flow sequence of the target basin hydrological station. It obeys the lognormal distribution, and the expression is: ； Among them, the is a location parameter, s represents the site number of the target basin hydrological station, s=1, 2, ..., K, t represents the year sequence number, N represents normal distribution, represents the correlation between the hydrological stations in the target basin, which is the covariance matrix of the K×K multivariate normal distribution. ; represents the climate factor of year t, is the first parameter of the s site, is the second parameter of the s site; The second layer model structure is Subject to hyperparameters and The normal distribution of , , , and stated is a fixed value, Normal distribution , It follows the inverse Wishart distribution, , is a K×K symmetric positive definite matrix, For the degrees of freedom.

10. The regional inconsistency flood frequency calculation system according to claim 9, characterized in that: The expression of the non-uniform flood frequency calculation model for the region without pooling scenario is: ； ； ； ； Among them, the is the scale parameter of the first site, is the scale parameter of the s site; The expression of the regional non-uniform flood frequency calculation model for the partial pooling scenario is: ； ； ； ； ； ； The expression of the regional non-uniform flood frequency calculation model for the full pooling scenario is: ； ； ； ； The second parameter for all sites same.

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