Rainfall session automatic division method and equipment based on basin flood response time

Abstract

The invention discloses a rainfall session automatic division method and device based on basin flood response time, and relates to the field of hydrological analysis and meteorological monitoring. The flood response time is calculated in combination with the drainage basin characteristics, the rainfall events are automatically divided according to the flood response time and the rainfall intensity threshold value, a more accurate rainfall event division result can be provided in combination with the rainfall data and the drainage basin characteristics, the adaptability and reliability of rainfall event division are improved, and the rainfall event division efficiency is improved. The method can be further applied to hydrological models, flood forecasting, disaster early warning and the like.

Description

Technical Field

[0001] The present application relates to the fields of hydrological analysis and meteorological monitoring, and in particular to a method and device for automatically dividing rainfall events based on basin flood response time. Background Art

[0002] Existing rainfall event classification methods usually classify rainfall events based on fixed rainfall intensity or time intervals, without considering the hydrological response characteristics of the basin. When dealing with extreme weather events, this method can easily lead to the division of rainfall events not conforming to the actual flood response law of the basin, thus affecting the accuracy of flood forecasting and water resources management. Therefore, there is a need for an automatic rainfall event classification method based on the basin flood response time, which combines rainfall data and basin characteristics to provide more accurate rainfall event classification results, so as to improve the adaptability and reliability of rainfall event classification. Summary of the invention

[0003] The purpose of this application is to provide a method and device for automatically dividing rainfall events based on basin flood response time, so as to improve the adaptability and reliability of rainfall event division.

[0004] To achieve the above objectives, this application provides the following solutions.

[0005] In a first aspect, the present application provides a method for automatically dividing rainfall events based on basin flood response time, comprising:

[0006] Calculate flood response time of watersheds based on the area, slope and length of river channels in the target area;

[0007] Obtain hourly rainfall data of the target area and form a rainfall data sequence;

[0008] Preprocessing the rainfall data sequence to obtain a preprocessed rainfall data sequence;

[0009] According to the flood response time and the rainfall intensity threshold, the preprocessed rainfall data sequence is divided into rainfall events to obtain rainfall data subsequences of different rainfall events.

[0010] In a second aspect, the present application provides a computer device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-mentioned method for automatically dividing rainfall events based on basin flood response time.

[0011] According to the specific embodiments provided in this application, this application has the following technical effects.

[0012] The present application provides a method and device for automatically dividing rainfall events based on the flood response time of a watershed. The present application calculates the flood response time in combination with the watershed characteristics, and automatically divides rainfall events according to the flood response time and the rainfall intensity threshold. The present application combines rainfall data and watershed characteristics to provide more accurate rainfall event division results, improves the adaptability and reliability of rainfall event division, and can be further applied to hydrological models, flood forecasts, and disaster warnings. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0014] Figure 1 A flowchart of a method for automatically dividing rainfall events based on basin flood response time is provided in accordance with an embodiment of the present application.

[0015] Figure 2 A schematic diagram of the structure of a computer device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0016] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0017] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0018] In an exemplary embodiment, Figure 1 As shown, a method for automatically dividing rainfall events based on basin flood response time is provided, including the following steps 101 to 104.

[0019] Step 101, calculating the flood response time of the watershed according to the area, slope and river length of the watershed in the target area.

[0020] Step 102, obtaining hourly rainfall data of the target area to form a rainfall data sequence.

[0021] Step 103: preprocess the rainfall data sequence to obtain a preprocessed rainfall data sequence.

[0022] Step 104 , dividing the preprocessed rainfall data sequence into rainfall events according to the flood response time and the rainfall intensity threshold, to obtain rainfall data subsequences of different rainfall events.

[0023] By implementing the above steps 101 to 104, rainfall data can be automatically acquired and pre-processed, and rainfall events can be automatically divided according to the set interval time and rainfall intensity threshold.

[0024] The rainfall interval time is a period of no rainfall between two independent rainfall events. The embodiment of the present application determines the independence of rainfall events by setting the flood response time as the minimum interval time.

[0025] In another exemplary embodiment of the present application, in step 101, the flood response time of the watershed is estimated based on the area, slope, river length and other characteristics of the watershed.

[0026] When the target area is a mountainous watershed, the flood response time is estimated using the SCS method, with the following formula.

[0027]

[0028] Where: T response is the flood response time (hours), L is the length of the river in the watershed within the target area (meters), S is the slope of the watershed in the target area (%), and H is the height difference of the watershed in the target area (meters).

[0029] When the target area is a plain basin, the Giandotti formula is used to estimate the flood response time. The Giandotti formula is:

[0030]

[0031] Where: T response is the flood response time (hours), A is the area of ​​the basin in the target area (square kilometers), L is the length of the river channel in the basin in the target area (meters), S is the slope of the basin in the target area (%), and H is the height difference of the basin in the target area (meters).

[0032] In another exemplary embodiment of the present application, in step 102, hourly rainfall data in a designated area (target area) is collected, and the data sources include weather stations, radar observations, or satellite remote sensing data.

[0033] In another exemplary embodiment of the present application, in step 103, the original hourly rainfall data is preprocessed to remove noise, correct abnormal values, and ensure the accuracy and continuity of the data. Smoothing is used to reduce short-term fluctuations in the data and ensure that the trend of the rainfall data is clear, as follows:

[0034] 3.1 Noise Removal

[0035] Noise is usually introduced by sensor failure, environmental interference or data transmission errors. For rainfall data, noise appears as abnormal instantaneous rainfall intensity or discontinuous data points. The moving average method is used to remove noise from the data. The specific steps include:

[0036] Step 201, select a preset window size.

[0037] Step 202: For each noise data, calculate the average value of the noise data and several hourly rainfall data before and after it.

[0038] Step 203, using the average value to replace the original noise data.

[0039] The average value calculation formula is:

[0040]

[0041] Among them, P smoothed (t) is the average value, P(i) is the hourly rainfall data at the i-th moment in the preset window, N is the size of the preset window, k is half of the window range, and t is the moment when the noise data is located.

[0042] 3.2 Correction of outliers

[0043] Outliers may be caused by sensor failure, extreme weather events, or data recording errors. The interquartile range method (IQR) is often used to identify outliers, which includes the following steps:

[0044] Step 301, sorting data: sorting each hourly rainfall data in the denoised rainfall data sequence in ascending order to obtain a target sequence.

[0045] Step 301, find the median: if the number of data in the target sequence is an odd number, the median is the number in the middle of the target sequence. If the number of data in the target sequence is an even number, the median is the average of the two numbers in the middle of the target sequence.

[0046] Step 302, segment the target sequence: the first quartile (Q1) is the median of the left part of the target sequence median, that is, the median of the first half of the data. The third quartile (Q3) is the median of the right part of the target sequence median, that is, the median of the second half of the data.

[0047] Step 303, calculate the interquartile range (IQR): IOR = Q3 - Q1.

[0048] Step 304, setting the lower limit and upper limit of abnormal value detection, the specific formula is:

[0049] P L =Q1-1.5IOR

[0050] P U =Q3+1.5IOR

[0051] Among them, P L is the lower limit of outlier detection, P U is the upper limit of outlier detection, IOR is the interquartile range of the denoised hourly rainfall data, Q1 and Q3 are the first and third quartiles of the denoised hourly rainfall data, respectively.

[0052] Step 305, anomaly detection: hourly rainfall data exceeding the lower limit and upper limit of anomaly detection are considered as anomalies.

[0053] Step 306, outlier processing: filling the outliers by interpolation.

[0054] 3.3 Smoothing

[0055] Smoothing is used to reduce short-term fluctuations in the data and make the rainfall trend clearer. The Savitzky-Golay filter is used to smooth the data while retaining the overall trend of the data, including the following steps:

[0056] Step 401, selecting a suitable filter window size.

[0057] Step 402: For each time point, fit a polynomial curve within the filter window.

[0058] Step 403: Replace the original data with the fitted polynomial curve value.

[0059] The general form of the fitted polynomial is:

[0060] P(t)=a0+a1t+a2t 2 +…+a n t n

[0061] Among them, P(t) is the rainfall data at time t obtained by fitting, a0, a1,…, a n are the coefficients of the fitted polynomial.

[0062] 3.4 Ensure data continuity

[0063] Missing data usually occurs when the sensor fails or the data transmission is interrupted. Linear interpolation is used to handle missing data. The steps are as follows:

[0064] For a missing data point, select the two known data points before and after it.

[0065] Compute the complement using the linear formula:

[0066]

[0067] Among them, P(t missing ) is the missing data time t missing The filling value is P(t1) which is the hourly rainfall data at the moment t1 before the missing data moment, and P(t2) which is the hourly rainfall data at the moment t2 after the missing data moment.

[0068] In another exemplary embodiment, in step 104, after a rainfall event ends, if the rainfall interval T interval If no effective rainfall occurs within 2 hours (the rainfall intensity is lower than the threshold), the two rainfall events are considered to be independent events. In the embodiment of the present application, the rainfall interval time T interval Set to the above flood response time, that is, T interval =T response .

[0069] The rainfall start time is the key point in defining a rainfall event, which is determined by setting the rainfall intensity threshold and the basin flood response time. min , such as 0.1 mm / hour). When the rainfall intensity P(t) in the hourly rainfall data exceeds P min If rainfall continues within the basin flood response time, then this moment is determined as the start time of the rainfall event. Specifically, the hourly rainfall data is traversed, and when the following conditions are met, this moment is recorded as the start time of the rainfall event.

[0070] T start =min(t) when P(t)>P min and

[0071] Among them, T start is the starting time of the rainfall event, P min is the rainfall intensity threshold, P(t) is the rainfall intensity at time t, P(t+T response ) is the time t+T response The rainfall intensity, T response Flood response time.

[0072] The end time of rainfall is defined as the last effective rainfall time of a rainfall event, which is determined by combining rainfall intensity and basin flood response time. min , and if there is no effective rainfall in the next basin response time, this moment is considered to be the end time of the rainfall event. Specifically, the hourly rainfall data is traversed, and when the following conditions are met, this moment is recorded as the end time of the rainfall event.

[0073] T end =max(t) when P(t) <P min and

[0074] Among them, T end The end time of the rainfall event.

[0075] The above step 104 is specifically as follows:

[0076] Step 501: When the rainfall in the rainfall data is interrupted and the time without rainfall is greater than the intermittent time threshold, it is determined that the new rainfall event is over.

[0077] Step 502: Mark each divided rainfall event with its starting time T start and T end .

[0078] In another exemplary embodiment, feature parameter extraction is further performed after the above step 104, wherein the feature parameters include:

[0079] (1) Rainfall duration: the total duration of a rainfall event.

[0080] (2) Total rainfall: the accumulated rainfall during a rainfall event.

[0081] (3) Maximum rainfall intensity: the maximum rainfall intensity recorded during a rainfall event.

[0082] (4) Peak rainfall period: the time when the rainfall intensity reaches its peak during a rainfall event.

[0083] (5) Rainfall start and end time: the start and end time of a rainfall event.

[0084] In another exemplary embodiment, different rainfall events are classified according to criteria such as rainfall intensity and duration, and the classification results are stored in a database. The analysis results can be used as input to hydrological models, flood forecasts, or disaster warning systems.

[0085] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Figure 2As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for automatically dividing rainfall events based on basin flood response time is implemented.

[0086] Those skilled in the art will understand that Figure 2 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components. In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0087] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0088] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0089] The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but is not limited thereto.

[0090] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0091] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A method for automatically dividing rainfall events based on basin flood response time, characterized in that: include: Calculate flood response time of watersheds based on the area, slope and length of river channels in the target area; Obtain hourly rainfall data of the target area and form a rainfall data sequence; Preprocessing the rainfall data sequence to obtain a preprocessed rainfall data sequence; According to the flood response time and the rainfall intensity threshold, the preprocessed rainfall data sequence is divided into rainfall events to obtain rainfall data subsequences of different rainfall events.

2. The method for automatically dividing rainfall events based on basin flood response time according to claim 1 is characterized in that: When the target area is a mountainous basin, the calculation formula for flood response time is: Among them, T response is the flood response time, S is the slope of the watershed in the target area, L is the length of the river channel in the watershed in the target area, and H is the height difference of the watershed in the target area; When the target area is a plain basin, the calculation formula for flood response time is: Where A is the area of ​​the watershed in the target area.

3. The method for automatically dividing rainfall events based on basin flood response time according to claim 1 is characterized in that: Preprocessing the rainfall data sequence to obtain a preprocessed rainfall data sequence specifically includes: The moving average method is used to remove the noise data in the rainfall data sequence to obtain the denoised rainfall data sequence; Fill the abnormal data in the denoised rainfall data sequence by interpolation method to obtain the abnormal corrected rainfall data sequence; Smoothing the rainfall data sequence after abnormal correction to obtain a smoothed rainfall data sequence; The linear interpolation method is used to process the missing data in the smoothed rainfall data series to obtain the preprocessed rainfall data series.

4. The method for automatically dividing rainfall events based on basin flood response time according to claim 3 is characterized in that: The moving average method is used to remove the noise data in the rainfall data sequence to obtain the denoised rainfall data sequence, which specifically includes: Perform a moving average denoising operation on each noise data in the rainfall data sequence to obtain the denoised hourly rainfall data; The moving average denoising operation includes: Calculate the average value of each hourly rainfall data in the preset window with the noise data as the midpoint in the rainfall data sequence; The noise data is replaced by the mean value.

5. The method for automatically dividing rainfall events based on basin flood response time according to claim 3 is characterized in that: The abnormal data in the denoised rainfall data sequence is filled by interpolation method to obtain the abnormal corrected rainfall data sequence, which specifically includes: The upper and lower limits of outlier detection are calculated using the following formula; P L =Q1-1.5IOR; P U =Q3+1.5IOR; Among them, P L is the lower limit of outlier detection, P U is the upper limit of outlier detection, IOR is the interquartile range of the denoised hourly rainfall data, Q1 and Q3 are the first and third quartiles of the denoised hourly rainfall data, respectively; According to the upper and lower limits of abnormal value detection, abnormal data in the denoised rainfall data sequence are detected; The interpolation method is used to fill in the abnormal data in the denoised rainfall data series.

6. The method for automatically dividing rainfall events based on basin flood response time according to claim 3 is characterized in that: The rainfall data sequence after abnormal correction is smoothed to obtain the smoothed rainfall data sequence, which specifically includes: Perform polynomial fitting on the hourly rainfall data at each moment in the filter window in the rainfall data sequence after abnormal correction to obtain a fitting function; The hourly rainfall data at each moment in the filter window is replaced by the value of the fitting function at the corresponding moment to obtain the smoothed rainfall data sequence.

7. The method for automatically dividing rainfall events based on basin flood response time according to claim 3 is characterized in that: The linear interpolation method is used to process the missing data in the smoothed rainfall data sequence to obtain the preprocessed rainfall data sequence, which specifically includes: According to the hourly rainfall data at the moment before and after the missing data moment in the smoothed rainfall data sequence, the filling value of the missing data moment is calculated using the following formula to fill the missing data moment; Among them, P(t missing ) is the missing data time t missing The filling value is P(t1) which is the hourly rainfall data at the moment t1 before the missing data moment, and P(t2) which is the hourly rainfall data at the moment t2 after the missing data moment.

8. The method for automatically dividing rainfall events based on basin flood response time according to claim 1 is characterized in that: According to the flood response time and rainfall intensity threshold, the preprocessed rainfall data sequence is divided into rainfall events to obtain rainfall data subsequences of different rainfall events, specifically including: Initialize the preprocessed rainfall data sequence as the target sequence; Traversing the target sequence, determining a moment in the target sequence that satisfies the following conditions as the start time of the rainfall event; T start =min(t) when P(t)>P min and Among them, T start is the starting time of the rainfall event, P min is the rainfall intensity threshold, P(t) is the rainfall intensity at time t, P(t+T response ) is the time t+T response The rainfall intensity, T response for flood response time; From the start time, traverse the target sequence and determine the time in the target sequence that satisfies the following conditions as the end time of the rainfall event; T end =max(t) when P(t) <P min and Among them, T end is the end time of the rainfall event; Extracting hourly rainfall data between the start time and the end time of a rainfall event in a target sequence to form a rainfall data subsequence of the rainfall event; The hourly rainfall data before the end time of the rainfall event in the target sequence is deleted, and the step of "traversing the target sequence and determining the moment in the target sequence that meets the following conditions as the start time of the rainfall event" is returned until the time length of the target sequence is less than the flood response time.

9. The method for automatically dividing rainfall events based on basin flood response time according to claim 1 is characterized in that: According to the flood response time and the rainfall intensity threshold, the preprocessed rainfall data sequence is divided into rainfall events to obtain rainfall data subsequences of different rainfall events, and then the following is further included: Feature extraction is performed on the rainfall data subsequence of each rainfall event to obtain characteristic parameters of each rainfall event; the characteristic parameters include: rainfall duration, total rainfall, maximum rainfall intensity, peak rainfall period and rainfall start and end time.

10. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method for automatically dividing rainfall events based on basin flood response time as described in any one of claims 1 to 9.

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