Method and device for determining application range of Chicago rain pattern

Abstract

The invention relates to the technical field of rain pattern simulation, in particular to a method and device for determining the application range of a Chicago rain pattern, and the method comprises the steps: collecting rainfall data of various durations in a target time period, and determining a sample set containing peak rainfall of various durations based on the rainfall data; obtaining the joint probability distribution of any two kinds of historical peak rainfall according to the sample set containing various kinds of historical peak rainfall, and obtaining the co-occurrence probability of any two kinds of historical peak rainfall corresponding to the same recurrence period based on the joint probability distribution; whether the co-occurrence probability is larger than a certain threshold value or not is judged, if the co-occurrence probability is larger than the certain threshold value, the Chicago rain pattern is applicable, and if not, the Chicago rain pattern is not applicable. Therefore, the problems that in the related technology, the Chicago rain pattern often shows the single-peak thin-tip feature and does not conform to the actual situation, the application range of the Chicago rain pattern cannot be quantitatively delimited, quantitative analysis of the application range of the Chicago rain pattern cannot be achieved and the like are solved.

Description

Technical Field

[0001] The present application relates to the technical field of rainfall prediction, and in particular to a method and device for determining the applicable scope of Chicago rain patterns. Background Art

[0002] In recent years, due to global climate change and the acceleration of human activities, flood disasters have occurred more and more frequently and with greater severity worldwide, which has posed a great challenge to urban flood prevention and disaster reduction measures. Floods are often inevitable and unexpected, however, they can be controlled through appropriate measures to minimize losses and damages. Flood risk assessment is one of the important steps in responding to disasters. People can use the results of the assessment to determine the potential risk location and extent, and take engineering and non-engineering measures to control or mitigate disasters based on this.

[0003] Among the related technologies, rainfall models can be constructed based on numerical analysis methods and artificial intelligence technologies to simulate rainfall, such as hydrological and hydrodynamic models based on physical mechanisms and numerical prediction models based on machine learning. These models have laid a solid foundation for flood risk assessment. Among them, the Chicago rainfall pattern is the most widely used rainstorm pattern design.

[0004] However, in the relevant technology, the Chicago rainfall pattern often presents a single-peak sharp and thin feature, which does not conform to the actual situation, and it is also impossible to quantitatively define the applicable scope of the Chicago rainfall pattern. There is an urgent need for improvement to achieve quantitative analysis of the applicable scope of the Chicago rainfall pattern. Summary of the invention

[0005] The present application provides a method and device for determining the applicable scope of the Chicago rain pattern, so as to solve the problems in the related art that the Chicago rain pattern often presents a single-peak sharp and thin feature, which does not conform to the actual situation, and it is impossible to quantitatively define the applicable scope of the Chicago rain pattern and realize quantitative analysis of the applicable scope of the Chicago rain pattern.

[0006] The first aspect of the present application provides a method for determining the applicable scope of the Chicago rain pattern, comprising the following steps: collecting rainfall data of various durations within a target time period, and determining a sample set containing the various duration peak rainfalls based on the rainfall data; obtaining a joint probability distribution of any of the duration peak rainfalls based on the sample set containing the various duration peak rainfalls, and determining the co-occurrence probability of any two duration peak rainfalls corresponding to the same recurrence period based on the joint probability distribution; judging whether the co-occurrence probability is greater than a preset threshold value, if the co-occurrence probability is greater than the preset threshold value, the Chicago rain pattern is applicable, otherwise, the Chicago rain pattern is not applicable.

[0007] Optionally, in one embodiment of the present application, the collecting of rainfall data of various durations within a target time period and determining a sample set of various duration peak rainfalls based on the rainfall data include: obtaining the rainfall events in which the various duration peak rainfalls are located within the target time period based on the rainfall data; obtaining an initial sample set of the various duration peak rainfalls after sliding according to the sliding of the target time step and the target sliding step in the rainfall events; and integrating the initial sample set to obtain the sample set containing the various duration peak rainfalls that meets the non-repetition condition.

[0008] Optionally, in one embodiment of the present application, the joint probability distribution of any two of the peak rainfall durations is obtained based on the sample set containing various peak rainfall durations, including: based on the sample set, using a parameter estimation method to solve the marginal probability distribution of the various peak rainfall durations; based on the marginal probability distribution, using a copula function to solve the joint probability distribution of any two of the peak rainfall durations in the sample set.

[0009] Optionally, in one embodiment of the present application, the expression of the co-occurrence probability may be, but is not limited to,:

[0010]

[0011] Among them, A and B represent the rainfall of two durations under the design return period, F(·,·) is the joint probability distribution function of rainfall of any two durations, and F(·) is the marginal probability distribution function of rainfall of various durations.

[0012] The second aspect of the present application provides a device for determining the applicable scope of the Chicago rain pattern, including: a collection module, used to collect rainfall data of various durations within a target time period, and determine a sample set containing the various duration peak rainfalls based on the rainfall data; a generation module, used to obtain a joint probability distribution of any two duration peak rainfalls according to the sample set containing the various duration peak rainfalls, and based on the joint probability distribution, determine the co-occurrence probability of any two duration peak rainfalls corresponding to the same recurrence period; a judgment module, used to judge whether the co-occurrence probability is greater than a preset threshold value, if the co-occurrence probability is greater than the preset threshold value, the Chicago rain pattern is applicable, otherwise, the Chicago rain pattern is not applicable.

[0013] Optionally, in one embodiment of the present application, the acquisition module includes: a first generating unit, used to obtain the rainfall events in which the various duration peak rainfalls are located within the target time period based on the rainfall data; a second generating unit, used to obtain an initial sample set of the various duration peak rainfalls after slip according to the slip of the target time step and the target slip step in the rainfall events; and a third generating unit, used to integrate the initial sample set to obtain the sample set containing the various duration peak rainfalls that meets the non-repetition condition.

[0014] Optionally, in one embodiment of the present application, the generation module includes: a first solving unit, used to solve the marginal probability distribution of the various duration peak rainfalls according to the sample set using a parameter estimation method; and a second solving unit, used to solve the joint probability distribution of any two duration peak rainfalls in the sample set based on the marginal probability distribution using a copula function.

[0015] Optionally, in one embodiment of the present application, the expression of the co-occurrence probability may be, but is not limited to,:

[0016]

[0017] Among them, A and B represent the rainfall of two durations under the design return period, F(·,·) is the joint probability distribution function of rainfall of any two durations, and F(·) is the marginal probability distribution function of rainfall of various durations.

[0018] A third aspect of the present application provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method for determining the applicable scope of the Chicago rain pattern as described in the above embodiment.

[0019] The fourth aspect of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, which, when executed by a processor, implements the above method for determining the applicable scope of the Chicago rain pattern.

[0020] The fifth aspect of the present application provides a computer program product, including a computer program, which, when executed, implements the above method for determining the applicable scope of the Chicago rain pattern.

[0021] The embodiment of the present application can determine a sample set containing peak rainfalls of various durations through the collected rainfall data of various durations within the target time period, and then obtain the co-occurrence probability of any two peak rainfalls corresponding to the same recurrence period, and when the co-occurrence probability is greater than a certain threshold, the Chicago rain type is applicable, otherwise, the Chicago rain type is not applicable, thereby achieving scientific guidance on the use of the Chicago rain type and avoiding the blind use of the Chicago rain type. Thus, the problem that the Chicago rain type often presents a single peak sharp and thin type feature in the related art is solved, which does not conform to the actual situation, and it is impossible to quantitatively define the applicable scope of the Chicago rain type, and to achieve quantitative analysis of the applicable scope of the Chicago rain type.

[0022] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0024] Figure 1 A flowchart of a method for determining the applicable range of a Chicago rain pattern provided according to an embodiment of the present application;

[0025] Figure 2 A probability heat map of various rainfall return periods coexisting for 2 years, 3 years, 4 years, 5 years, 10 years, and 20 years according to an embodiment of the present application;

[0026] Figure 3 A flowchart of the working principle of a method for determining the applicable range of Chicago rain pattern provided according to an embodiment of the present application;

[0027] Figure 4 A block diagram of a device for determining the applicable range of a Chicago rain pattern according to an embodiment of the present application;

[0028] Figure 5 It is a schematic diagram of the structure of an electronic device provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0029] The embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0030] The following describes the method and device for determining the applicable scope of the Chicago rain pattern of the embodiment of the present application with reference to the accompanying drawings. In view of the problem that the Chicago rain pattern mentioned in the above background technology often presents a single peak sharp thin type feature, which does not conform to the actual situation, and it is impossible to quantitatively define the applicable scope of the Chicago rain pattern, and realize the quantitative analysis of the applicable scope of the Chicago rain pattern, the present application provides a method for determining the applicable scope of the Chicago rain pattern, in which a sample set containing various duration peak rainfalls can be determined by collecting various duration rainfall data in the target time period, and then the co-occurrence probability of any two duration peak rainfalls corresponding to the same recurrence period can be obtained, and when the co-occurrence probability is greater than a certain threshold, the Chicago rain pattern is applicable, otherwise, the Chicago rain pattern is not applicable, thereby achieving scientific guidance on the use of the Chicago rain pattern and avoiding the blind use of the Chicago rain pattern. As a result, the problem that the Chicago rain pattern often presents a single peak sharp thin type feature, which does not conform to the actual situation, and it is impossible to quantitatively define the applicable scope of the Chicago rain pattern, and realize the quantitative analysis of the applicable scope of the Chicago rain pattern in the related technology is solved.

[0031] Specifically, Figure 1 The present invention is a flowchart of a method for determining the applicable scope of the Chicago rain pattern according to an embodiment of the present application.

[0032] like Figure 1 As shown, the method for determining the applicable scope of the Chicago rain pattern includes the following steps:

[0033] In step S101, rainfall data of various durations within a target time period are collected, and sample sets of peak rainfalls of various durations are determined based on the rainfall data.

[0034] It can be understood that the target time period of the embodiment of the present application can be but is not limited to three months, six months, one year, five years, ten years, etc., which can be set by technicians in this field according to actual conditions, and this application does not make any specific restrictions.

[0035] In addition, the various durations in the embodiments of the present application may include but are not limited to 5 minutes, 10 minutes, 15 minutes, 20 minutes, 30 minutes, 45 minutes, 60 minutes, 90 minutes, 120 minutes, etc., which can be specifically set by technicians in this field according to actual conditions, and this application does not impose any specific restrictions.

[0036] As a possible implementation method, the present application determines a sample set of peak rainfall amounts of various durations by collecting rainfall data of various durations within a target time period.

[0037] Optionally, in one embodiment of the present application, rainfall data of various durations within a target time period are collected, and sample sets of various duration peak rainfalls are determined based on the rainfall data, including: obtaining rainfall events in which various duration peak rainfalls are located within the target time period based on the rainfall data; obtaining an initial sample set of various duration peak rainfalls after sliding according to the sliding of the target time step and the target sliding step in the rainfall events; and integrating the initial sample set to obtain a sample set of various duration peak rainfalls that meets the non-repetition condition.

[0038] During the actual implementation process, the embodiment of the present application can obtain the rainfall events with various duration peak rainfalls within the target time period based on the rainfall data, and then obtain the initial sample set after sliding through sliding, and integrate the initial sample set to obtain a sample set that meets the non-repetition condition.

[0039] For example, the embodiment of the present application can filter out the largest one or more rainfall events of 5 minutes, 10 minutes, 15 minutes, 20 minutes, 30 minutes, 45 minutes, 60 minutes, 90 minutes, and 120 minutes each year based on the rainfall data of the XX station within 20 years. For example, the largest rainfall of 5 minutes occurs in the first event of the first year, and its rainfall duration is 180 minutes.

[0040] Furthermore, the embodiment of the present application adopts 120 minutes as the target time step and 1 minute as the target sliding step to slide in the obtained rainfall events, and finds the 120-minute rainfall data sequence with the largest total rainfall as the initial sample. If the total rainfall duration corresponding to the rainfall event is less than 120 minutes, it can be padded with 0 to make up 120 minutes, and then the initial sample is obtained. Among them, after the embodiment of the present application obtains 60 initial samples in the first rainfall with a rainfall duration of 180 minutes, the initial sample set of various duration peak rainfalls after sliding can be determined.

[0041] Furthermore, the embodiment of the present application integrates the initial sample set based on the principle of non-repetition to obtain sample sets of various duration peak rainfalls. For example, if the rainfall events of the maximum 5-minute rainfall and the maximum 10-minute rainfall are exactly the same, one of the rainfall events can be analyzed to obtain the sample set.

[0042] In step S102, a joint probability distribution of any two duration peak rainfalls is obtained based on a sample set including various duration peak rainfalls, and the co-occurrence probability of any two duration peak rainfalls corresponding to the same recurrence period is obtained based on the joint probability distribution.

[0043] Among them, the expression of co-occurrence probability can be but is not limited to:

[0044]

[0045] Among them, A and B represent the rainfall of two durations under the design return period, F(·,·) is the joint probability distribution function of rainfall of any two durations, and F(·) is the marginal probability distribution function of rainfall of various durations.

[0046] In the actual implementation process, the embodiment of the present application can obtain the joint probability distribution of any two duration peak rainfalls based on a sample set containing various duration peak rainfalls, and then study the co-occurrence probability of other duration peak rainfalls corresponding to the same return period when a certain duration satisfies a certain return period rainfall condition, wherein the certain return period rainfall condition can be set by technicians in this field according to actual conditions, and this application does not make specific restrictions. In addition, the expression of the co-occurrence probability of the embodiment of the present application can be, but is not limited to,:

[0047]

[0048] Among them, A and B represent the rainfall of two durations in the design return period, F(·,·) is the joint probability distribution function of rainfall of various durations, and F(·) is the marginal probability distribution function of rainfall of various durations.

[0049] For example, the present application embodiment can calculate the probability that the return period of various rainfall durations will co-occur in 2 years, 3 years, 4 years, 5 years, 10 years, and 20 years. Specifically, Figure 2 As shown. Among them, Figure 2 (a) is a probability heat map of various rainfall return periods occurring in the same period of 2 years provided according to an embodiment of the present application; Figure 2 (b) is a probability heat map of various rainfall return periods occurring in the same period of 3 years provided according to an embodiment of the present application; Figure 2 (c) is a probability heat map of various rainfall return periods occurring in the same period of 4 years provided according to an embodiment of the present application; Figure 2 (d) is a probability heat map of various rainfall return periods occurring in the same period of 5 years provided according to an embodiment of the present application; Figure 2 (e) is a probability heat map of various rainfall return periods occurring in the same decade according to one embodiment of the present application; Figure 2 (f) is a probability heat map of various rainfall return periods coexisting for 20 years according to an embodiment of the present application.

[0050] Optionally, in one embodiment of the present application, a joint probability distribution of any two peak rainfall durations is obtained based on a sample set containing various peak rainfall durations, including: based on the sample set, using a parameter estimation method to solve the marginal probability distribution of various peak rainfall durations; based on the marginal probability distribution, using a copula function to solve the joint probability distribution of any two peak rainfall durations in the sample set.

[0051] As a possible implementation method, the embodiment of the present application can use the Spearman correlation analysis method to calculate the correlation of the sample sets of various duration peak rainfalls, and then use the parameter estimation method to solve the marginal probability distribution of various duration peak rainfalls, and then use the copula function to solve the joint probability distribution of any two various duration peak rainfalls.

[0052] Among them, the copula function is to transform the random vector x1,x2,...,x n The joint distribution function F(x1,x2,...,x n ) and their respective edge functions F1, F2, ..., F n The connection function connected, that is, the function C(u1,u2,...,u n ),make

[0053] F(x1,x2,L x n )=C(F1(x1),F2(x2),L,F n (x n )),

[0054] Furthermore, in the embodiments of the present application, the copula function may include but is not limited to Frank Copula, Clayton Copula, Gumbel Copula, etc., and the present application does not impose any specific limitation.

[0055] In step S103, it is determined whether the co-occurrence probability is greater than a preset threshold. If the co-occurrence probability is greater than the preset threshold, the Chicago rain pattern is applicable; otherwise, the Chicago rain pattern is not applicable.

[0056] As a possible implementation method, the embodiment of the present application can determine the duration and recurrence range of the applicable Chicago rain pattern through a certain threshold value. The certain threshold value can be set by a person skilled in the art according to actual conditions, and the present application does not impose any specific limitation.

[0057] For example, the embodiment of the present application can use 60% of the co-occurrence probability as a certain threshold. If the co-occurrence probability is greater than 60%, it is considered that the Chicago rain type is applicable. If the co-occurrence probability is less than 60%, it is considered that the Chicago rain type is not applicable. Based on this, the embodiment of the present application can draw an applicable table of the applicable range of the Chicago rain type, as shown in Table 1. Table 1 is a Chicago rain type applicable range table provided according to an embodiment of the present application.

[0058] Table 1

[0059] Return period (years) 2 3 4 5 10 Duration (min) 120 60 45 30 30

[0060] The working principle of the method for determining the applicable scope of the Chicago rain pattern proposed in the embodiment of the present application is described in detail below with reference to a specific embodiment.

[0061] in, Figure 3 The flowchart is a working principle of a method for determining the applicable scope of the Chicago rain pattern provided according to an embodiment of the present application.

[0062] Step S301: Obtain rainfall data of various durations within a target time period.

[0063] That is to say, the embodiment of the present application can filter out the annual maximum rainfall events of 5min, 10min, 15min, 20min, 30min, 45min, 60min, 90min, and 120min based on the rainfall data of XX station within 20 years.

[0064] Step S302: Determine an initial sample set including peak rainfalls of various durations.

[0065] That is to say, the embodiment of the present application can use 120 minutes as the target time step and 1 minute as the target sliding step to slide in the obtained rainfall events, and find the 120-minute rainfall data sequence with the largest total rainfall as the initial sample. If the total rainfall duration corresponding to the rainfall event is less than 120 minutes, it can be padded with 0 to make up 120 minutes, thereby obtaining the initial sample.

[0066] Step S303: forming a sample set.

[0067] That is to say, in the embodiment of the present application, the sample set in step S302 can be integrated according to the principle of non-repetition to form a sample set.

[0068] Step S304: Calculate the correlation between peak rainfalls of various durations.

[0069] That is to say, the embodiment of the present application may use the Spearman correlation analysis method to calculate the correlation of various duration peak rainfalls in step S303.

[0070] Step S305: Solve the marginal probability distribution of peak rainfall of various durations.

[0071] That is to say, the embodiment of the present application can use the parameter estimation method to solve the marginal probability distribution of peak rainfalls of various durations in step S304.

[0072] Step S306: Solve the joint probability distribution of any two duration peak rainfalls.

[0073] That is to say, the embodiment of the present application can use the copula function to solve the joint probability distribution of any two peak rainfalls of various durations in step S304, and calculate the probability of co-occurrence of peak rainfalls of other durations corresponding to the same return period when a certain duration satisfies a rainfall condition of a certain return period. Then, the embodiment of the present application obtains the probability of co-occurrence of the return period of rainfalls of various durations of 2 years, 3 years, 4 years, 5 years, 10 years, and 20 years by calculation, which is as follows Figure 2 The expression of the co-occurrence probability in the embodiment of the present application is as shown above, and no redundant description is given here.

[0074] Step S307: Set a certain threshold to determine the duration and recurrence range of the Chicago rain pattern.

[0075] That is to say, the embodiment of the present application can use the co-occurrence probability of 60% as a certain threshold value. If the co-occurrence probability is greater than 60%, it is considered that the Chicago rain type is applicable, and if the co-occurrence probability is less than 60%, it is considered that the Chicago rain type is not applicable. Based on this, the embodiment of the present application can draw an applicable table of the applicable range of the Chicago rain type, as shown in Table 1.

[0076] According to the method for determining the applicable scope of the Chicago rain pattern proposed in the embodiment of the present application, a sample set containing peak rainfalls of various durations can be determined by collecting rainfall data of various durations within the target time period, and then the co-occurrence probability of any two peak rainfalls corresponding to the same recurrence period can be obtained. When the co-occurrence probability is greater than a certain threshold, the Chicago rain pattern is applicable, otherwise, the Chicago rain pattern is not applicable, thereby achieving scientific guidance on the use of the Chicago rain pattern and avoiding the blind use of the Chicago rain pattern. Thus, the problem that the Chicago rain pattern often presents a single peak, sharp and thin type feature in the related art is solved, which does not conform to the actual situation, and it is impossible to quantitatively define the applicable scope of the Chicago rain pattern, and to achieve quantitative analysis of the applicable scope of the Chicago rain pattern is solved.

[0077] Next, a device for determining the applicable range of the Chicago rain pattern proposed in an embodiment of the present application will be described with reference to the accompanying drawings.

[0078] Figure 4 It is a block diagram of a device for determining the applicable range of the Chicago rain pattern provided according to an embodiment of the present application.

[0079] like Figure 4 As shown, the device 10 for determining the applicable range of the Chicago rain pattern includes: a collection module 100 , a generation module 200 and a judgment module 300 .

[0080] The collection module 100 is used to collect rainfall data of various durations within a target time period, and determine a sample set containing peak rainfall amounts of various durations based on the rainfall data.

[0081] The generation module 200 is used to obtain the joint probability distribution of any two duration peak rainfalls based on a sample set containing various duration peak rainfalls, and to obtain the co-occurrence probability of any two duration peak rainfalls corresponding to the same recurrence period based on the joint probability distribution.

[0082] The judgment module 300 is used to judge whether the co-occurrence probability is greater than a preset threshold. If the co-occurrence probability is greater than the preset threshold, the Chicago rain pattern is applicable; otherwise, the Chicago rain pattern is not applicable.

[0083] Optionally, in one embodiment of the present application, the acquisition module 100 includes: a first generation unit, a second generation unit and a third generation unit.

[0084] The first generating unit is used to obtain the rainfall events with various duration peak rainfalls within the target time period based on the rainfall data.

[0085] The second generation unit is used to obtain an initial sample set of peak rainfalls of various durations after the slip according to the slip of the target time step and the target slip step in the rainfall event.

[0086] The third generating unit is used to integrate the initial sample set to obtain a sample set containing peak rainfalls of various durations that meets the non-repetitive condition.

[0087] Optionally, in one embodiment of the present application, the generation module 200 includes: a first solution unit and a second solution unit.

[0088] The first solving unit is used to solve the marginal probability distribution of peak rainfall of various durations based on the sample set by using the parameter estimation method.

[0089] The second solving unit is used to solve the joint probability distribution of any two duration peak rainfalls in the sample set by using the copula function based on the marginal probability distribution.

[0090] Optionally, in one embodiment of the present application, the expression of the co-occurrence probability may be, but is not limited to,:

[0091]

[0092] Among them, A and B represent the rainfall of two durations under the design return period, F(·,·) is the joint probability distribution function of rainfall of any two durations, and F(·) is the marginal probability distribution function of rainfall of various durations.

[0093] It should be noted that the above explanations and descriptions of the embodiment of the method for determining the applicable scope of the Chicago rain pattern are also applicable to the device for determining the applicable scope of the Chicago rain pattern of this embodiment, and will not be repeated here.

[0094] According to the device for determining the applicable scope of the Chicago rain pattern proposed in the embodiment of the present application, a sample set containing peak rainfalls of various durations can be determined by collecting rainfall data of various durations within the target time period, thereby obtaining the co-occurrence probability of any two peak rainfalls corresponding to the same recurrence period, and when the co-occurrence probability is greater than a certain threshold, the Chicago rain pattern is applicable, otherwise, the Chicago rain pattern is not applicable, thereby achieving scientific guidance on the use of the Chicago rain pattern and avoiding the blind use of the Chicago rain pattern. Thus, the problem that the Chicago rain pattern often presents a single peak, sharp and thin type feature in the related art is solved, which does not conform to the actual situation, and it is impossible to quantitatively define the applicable scope of the Chicago rain pattern, and to achieve quantitative analysis of the applicable scope of the Chicago rain pattern is solved.

[0095] Figure 5 This is a schematic diagram of the structure of an electronic device provided according to an embodiment of the present application. The electronic device may include:

[0096] A memory 501 , a processor 502 , and a computer program stored in the memory 501 and executable on the processor 502 .

[0097] When the processor 502 executes the program, the method for determining the applicable range of the Chicago rain pattern provided in the above embodiment is implemented.

[0098] Furthermore, the electronic device further comprises:

[0099] The communication interface 503 is used for communication between the memory 501 and the processor 502 .

[0100] The memory 501 is used to store computer programs that can be executed on the processor 502 .

[0101] The memory 501 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0102] If the memory 501, the processor 502 and the communication interface 503 are implemented independently, the communication interface 503, the memory 501 and the processor 502 can be connected to each other through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 5Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0103] Optionally, in a specific implementation, if the memory 501, the processor 502 and the communication interface 503 are integrated on a chip, the memory 501, the processor 502 and the communication interface 503 can communicate with each other through an internal interface.

[0104] The processor 502 may be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0105] The embodiment of the present application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above method for determining the applicable scope of the Chicago rain pattern.

[0106] The embodiment of the present application also provides a computer program product, including a computer program, which, when executed, implements the above method for determining the applicable scope of the Chicago rain pattern.

[0107] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0108] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0109] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or N executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0110] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purpose of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or N wirings (electronic devices), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways as necessary and then storing it in a computer memory.

[0111] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above embodiment, the N steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented by hardware, as in another embodiment, it can be implemented by any one or a combination of multiple of the following technologies known in the art: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0112] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0113] In addition, each functional unit in each embodiment of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0114] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present application. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A method for determining the applicable scope of Chicago rain pattern, characterized in that: The following steps are involved: Collect rainfall data of various durations within a target time period, and determine a sample set containing peak rainfall amounts of various durations based on the rainfall data; Obtaining a joint probability distribution of any two of the peak rainfalls according to the sample set containing various peak rainfalls, and obtaining the co-occurrence probability of the two peak rainfalls corresponding to the same return period based on the joint probability distribution; It is determined whether the co-occurrence probability is greater than a preset threshold value. If the co-occurrence probability is greater than the preset threshold value, the Chicago rain pattern is applicable; otherwise, the Chicago rain pattern is not applicable.

2. The method for determining the applicable range of the Chicago rain pattern according to claim 1, characterized in that: The collecting of rainfall data of various durations within the target time period, and determining the sample set containing peak rainfall amounts of various durations based on the rainfall data, includes: Based on the rainfall data, obtain the rainfall events with various duration peak rainfalls within the target time period; According to the sliding of the target time step and the target sliding step in the rainfall event, an initial sample set of the peak rainfalls of various durations after the sliding is obtained; The initial sample set is integrated to obtain the sample set containing peak rainfall amounts of various durations that meets the non-repetitive condition.

3. The method for determining the applicable range of the Chicago rain pattern according to claim 1, characterized in that: The method of obtaining the joint probability distribution of any two peak rainfall durations according to the sample set containing various peak rainfall durations includes: According to the sample set, using parameter estimation method to solve the marginal probability distribution of the various duration peak rainfalls; Based on the marginal probability distribution, the copula function is used to solve the joint probability distribution of any two duration peak rainfalls in the sample set.

4. The method for determining the applicable range of the Chicago rain pattern according to claim 1, characterized in that: The expression of the co-occurrence probability is: Among them, A and B represent the rainfall of two durations under the design return period, F(·,·) is the joint probability distribution function of rainfall of any two durations, and F(·) is the marginal probability distribution function of rainfall of various durations.

5. A device for determining the applicable range of Chicago rain pattern, characterized in that: include: A collection module, used for collecting rainfall data of various durations within a target time period, and determining a sample set including peak rainfall amounts of various durations based on the rainfall data; A generating module, configured to obtain a joint probability distribution of any two of the peak rainfalls of various durations according to the sample set containing the peak rainfalls of various durations, and obtain a co-occurrence probability of the two peak rainfalls of various durations corresponding to the same return period based on the joint probability distribution; The judging module is used to judge whether the co-occurrence probability is greater than a preset threshold value. If the co-occurrence probability is greater than the preset threshold value, the Chicago rain pattern is applicable; otherwise, the Chicago rain pattern is not applicable.

6. The device for determining the applicable range of Chicago rain pattern according to claim 5, characterized in that: The acquisition module comprises: A first generating unit is used to obtain the rainfall events where the various duration peak rainfalls are located within the target time period based on the rainfall data; A second generating unit is used to obtain an initial sample set of the various duration peak rainfalls after sliding according to the sliding of the target time step and the target sliding step in the rainfall event; The third generating unit is used to integrate the initial sample set to obtain the sample set containing peak rainfalls of various durations that meets the non-repetitive condition.

7. The device for determining the applicable range of Chicago rain pattern according to claim 5, characterized in that: The generating module comprises: A first solving unit is used to solve the marginal probability distribution of the peak rainfalls of various durations by using a parameter estimation method according to the sample set; The second solving unit is used to solve the joint probability distribution of any two duration peak rainfalls in the sample set by using a copula function based on the marginal probability distribution.

8. The device for determining the applicable range of Chicago rain pattern according to claim 5, characterized in that: The expression of the co-occurrence probability is: Among them, A and B represent the rainfall of two durations under the design return period, F(·,·) is the joint probability distribution function of rainfall of any two durations, and F(·) is the marginal probability distribution function of rainfall of various durations.

9. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method for determining the applicable scope of the Chicago rain pattern as described in any one of claims 1 to 4.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the method for determining the applicable range of the Chicago rain pattern as described in any one of claims 1 to 4.

11. A computer program product, characterized in that It comprises a computer program, which, when executed, is used to implement the method for determining the applicable range of the Chicago rain pattern as claimed in any one of claims 1 to 4.

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