Method, system and storage medium for restoring sediment concentration of plain river

Abstract

The application relates to a plain river sediment concentration recovery method, a system and a storage medium, the method comprising the following steps: reading historical hydrological data of a hydrological station, including daily flow and daily sediment rate; defining a target period and a candidate period; obtaining a comprehensive similarity; selecting a candidate year or a candidate year set with the maximum comprehensive similarity as a reference hydrological year of the target period; respectively performing fitting on a correlation function curve; calculating and supplementing the sediment concentration of the target period; and performing pseudo-missing test. The application considers the water and sediment characteristics of dry and flood periods, can effectively control the reconstructed annual total sediment discharge, and has smaller daily process error and high efficiency in filling the missing historical sediment data.

Description

Technical Field

[0001] This application relates to the field of hydrological sediment information, and in particular to a method, system and storage medium for restoring sediment concentration in plain rivers based on similar daily average flow processes. Background Technology

[0002] In hydrological monitoring and water resources management, sediment data is often incomplete, especially in earlier observation years or periods with inadequate monitoring. Current technologies primarily rely on sediment concentration (SSC) and flow rate. Imputation is performed using empirical statistical relationships, but due to SSC and The nonlinear relationship and interannual differences in flow processes limit the accuracy of reconstruction. Existing methods use similar hydrological year interpolation to reconstruct missing SSCs, but these only fit the SSC with... The single curve relationship between them does not take into account the different mechanisms of action of different flow size segments, and does not comprehensively utilize multiple similarity indicators to accurately match similar hydrological years, resulting in large errors in reconstructing missing sediment data during dry or flood seasons. Summary of the Invention

[0003] The purpose of this application is to overcome the shortcomings of the existing technology and provide a method, system and storage medium for restoring sediment concentration in plain rivers based on the similarity of daily average flow processes, which can more accurately reconstruct sediment data for historical missing periods.

[0004] To achieve the above objectives, this application provides the following technical solution:

[0005] In a first aspect, embodiments of this application provide a method for restoring the sediment content of plain rivers, comprising the following steps:

[0006] Step 1. Read the daily flow data from the hydrological station. With daily sediment transport rate Historical hydrological data, The missing year is defined as the target period. A complete year is defined as the candidate period;

[0007] Step 2. Calculate the Nash Sutcliffe efficiency (NSE), Kling Gupta efficiency (KGE), and Pearson correlation coefficient (ρ) for the annual flow series of each target period and candidate period to obtain the comprehensive similarity; select the candidate year or set of candidate years with the highest comprehensive similarity as the reference hydrological year for that target period.

[0008] Step 3. Determine the bed-forming flow rate within the reference hydrological year. The flow sequence in the reference hydrological year is divided into... low flow rate and high flow level; for two levels of flow, respectively and fitting of the power function curve of the correlation;

[0009] Step 4. Based on the segmented power function curve, the sediment discharge rate of the corresponding time step is calculated for the flow data of the target period ; the sediment concentration is calculated and supplemented for the target period;

[0010] Step 5. Perform pseudo-missing test, if the error index does not meet the threshold, adjust the comprehensive similarity weight parameter w or the reference hydrological year set parameter k and return to step 2 until the threshold is met.

[0011] In the step 2,

[0012] The comprehensive similarity is:

[0013] ,

[0014] wherein, is a weight coefficient, and satisfies , the initial value is set to 0.4, 0.3, 0.3.

[0015] In the step 2, the first name is taken as the reference hydrological year before the comprehensive similarity.

[0016] In the step 3, the bed-building flow is calculated in the following manner: the average of the highest two months of monthly average water level in the reference hydrological year is calculated as the bankfull water level, and the bankfull flow is obtained by searching the water level-flow relationship of the hydrological station, that is, the bed-building flow;

[0017] ,

[0018] wherein, is the average water level of the highest two months of monthly average water level in the reference hydrological year, is the water level-flow relationship function of the hydrological station;

[0019] In the low flow level, the power function is used to fit the data in the reference year and , to obtain the parameter ; in the high flow level, the power function is used to fit the data in the reference year and , to obtain the parameter .

[0020] In the step 5, the error threshold is: the relative error of annual total sediment discharge ​Daily sediment content process At the same time, the total annual sediment transport volume and daily process error are controlled.

[0021] Secondly, embodiments of this application provide a system for restoring sediment content in plain rivers, comprising:

[0022] The hydrological data reading module is used to read the daily flow data from the hydrological station. With daily sediment transport rate Historical hydrological data, The missing year is defined as the target period. A complete year is defined as the candidate period;

[0023] The comprehensive similarity calculation module is used to calculate the Nash Sutcliffe efficiency (NSE), Kling Gupta efficiency (KGE), and Pearson correlation coefficient (ρ) for the annual flow series of each target period and candidate period to obtain the comprehensive similarity; the candidate year or set of candidate years with the highest comprehensive similarity is selected as the reference hydrological year for the target period.

[0024] The curve fitting module determines the bed-forming flow rate within a reference hydrological year. The flow sequence in the reference hydrological year is divided into... low flow rate and High traffic levels; for the two levels of traffic, respectively... and Fitting the power function curve of the correlation;

[0025] The sediment concentration calculation module calculates the sediment transport rate for each time step based on the piecewise power function curve for the flow data during the target period. ; through sand content Calculate and supplement the sediment concentration for the target period;

[0026] The pseudo-missing data detection module performs a pseudo-missing data detection. If the error index does not meet the threshold, it adjusts the comprehensive similarity weight parameter w or the reference hydrological year set parameter k and returns to step 2 until the threshold is met.

[0027] Thirdly, embodiments of this application provide a computer-readable storage medium storing program code, which, when executed by a processor, implements the steps of the plain river sediment content restoration method described above.

[0028] Compared with the prior art, the beneficial effects of the present invention are:

[0029] The application improves the accuracy and stability of the reconstruction of missing data of historical sediment by multi-index similarity matching and segmented power function fitting of daily flow process, and takes into account the sediment transport mechanism in dry flood period. The pseudo-missing data test and feedback adjustment mechanism can control the reconstructed annual total sediment transport volume and daily process error, and effectively meet the demand of water resources and sediment management for high-precision sediment concentration data. BRIEF DESCRIPTION OF DRAWINGS

[0030] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiments of the present application will be briefly introduced as follows. It should be understood that the following drawings only show some embodiments of the present application, and therefore should not be regarded as a limitation on the scope. Other related drawings can also be obtained by those skilled in the art without creative labor on the premise of the drawings.

[0031] Figure 1 is a specific flow chart of the method of the present application;

[0032] Figure 2 is a schematic diagram of the water level-discharge relationship curve of Yichang Station in 1981;

[0033] Figure 3 is a power function curve fitting result of the relationship between the daily sediment concentration and the daily flow of Yichang Station in 1981; and

[0034] Figure 4 is a fitting scatter plot of Yichang Station in 1958; and

[0035] Figure 5 is a sediment concentration process diagram of Yichang Station in 1958. DETAILED DESCRIPTION

[0036] The technical solutions in the embodiments of the present application will be described below in combination with the drawings in the embodiments of the present application. It should be noted that similar reference numerals and letters represent similar items in the following drawings, and therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings.

[0037] The term "comprising" or "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such a process, method, article or device. Without more limitations, the element defined by the statement "including a" does not exclude the presence of another identical element in the process, method, article or device including the element. ​​

[0038] The terms “first,” “second,” etc., are used only to distinguish one entity or operation from another, and should not be construed as indicating or implying relative importance, nor as requiring or implying any such actual relationship or order between these entities or operations.

[0039] The specific implementation process for this application is as follows: Figure 1 The steps are as follows:

[0040] Step 1: Read the daily flow data from the hydrological station. With daily sediment transport rate Historical hydrological data, The missing year is defined as the target period. A complete year is defined as a candidate period.

[0041] In this embodiment, taking the Yichang Hydrological Station as an example, the daily flow and sediment data for 1958 and 1976–1990 are read in. Assuming that the sediment data for 1958 is missing, then 1958 is the target period (the missing sediment data needs to be reconstructed), and 1976 to 1990 is the candidate period.

[0042] Step 2: Calculate the Nash Sutcliffe efficiency (NSE), Kling Gupta efficiency (KGE), and Pearson correlation coefficient (ρ) for the annual flow series of each target period and candidate period to obtain the comprehensive similarity; select the candidate year or set of candidate years with the highest comprehensive similarity as the reference hydrological year for the target period.

[0043] In this embodiment, 1958 was used as the target period. The NSE, KGE, and Pearson correlation coefficients of the 1958 flow rate and the daily flow rates from 1976 to 1990 were calculated respectively, and the comprehensive similarity was synthesized according to the weight w (0.4:0.3:0.3). The year with the highest result was 1981 (NSE: 0.761, KGE: 0.803, Pr: 0.857, comprehensive similarity 0.8024), followed by 1980 and 1987. For ease of explanation, k=1 is taken here, that is, the top one in comprehensive similarity is taken as the reference hydrological year.

[0044] Step 3: Determine the bed-forming flow rate within the reference hydrological year. The flow sequence in the reference hydrological year is divided into... low flow rate and High traffic levels; for the two levels of traffic, respectively... and Fitting the power function curve of the correlation;

[0045] in:

[0046] Bed flow The calculation method is as follows: the average of the two months with the highest monthly average water level in the reference hydrological year is used as the flat beach water level, and the flat beach flow is found through the water level-flow relationship of the hydrological station, which is the bed-forming flow.

[0047] At low flow rates, use power functions. For reference mid-year and The data is fitted to obtain parameters. At high flow rates, use power functions. For reference mid-year and The data is fitted to obtain parameters. .

[0048] In this example, the average monthly water level for the two highest months in 1981 was approximately 53m. The flood discharge at the flat beach was determined using the water level-discharge relationship of this hydrological station. (See...) Figure 2 This translates to a bed-forming flow rate of 50,000 m³ / s. For the two-stage flow rates in 1981, Q and... For fitting of the power function curve of the correlation, see Figure 3 .

[0049] parameter They are respectively: 2.737919796570220

[0050] parameter They are respectively: 3.382084382418810

[0051] Step 4: For the flow data of the target time period, calculate the sediment transport rate for the corresponding time step based on the piecewise power function curve. ; through sand content Calculate and supplement the sediment content for the target period.

[0052] This embodiment is as follows: Through step 4, utilizing the system constructed in 1981... and The correlation power function curve, combined with the flow process for the target period of 1958, yielded the results for 1958. and Scattered points, such as Figure 4 As shown by the center dot. Since the 1958 sediment data actually exists, it was incorporated into... Figure 4 As shown by the triangles in the figure, the scatter points generated by the method of this application have good consistency with the measured scatter points, and the triangle points are distributed on both sides of the circle. Furthermore, through sand content... The calculated sediment content in 1958 was as follows: Figure 5The real sediment concentration in 1958 is also shown in the circle dot. Figure 5 The sediment concentration process generated by the method of the application is consistent with the measured process, as shown by the triangle in the figure.

[0053] Step 5, perform pseudo-missing test, if the error index does not meet the threshold value, adjust the comprehensive similarity weight or the reference hydrological year set and return to step 2 until the threshold value is met.

[0054] In this embodiment, 1958 is set as a pseudo-missing year, and the error evaluation index is calculated by reconstructing according to the method of the application, as in the previous steps 1-4, the difference between the reconstructed sediment discharge in 1958 and the real value is 5.2%, and the NSE index is 0.716, both of which meet the error index threshold value requirement, so the model can be directly used without adjusting the w and k parameters.

[0055] The embodiment of the application provides a plain river sediment concentration restoration system based on daily average flow process similarity, which comprises,

[0056] The hydrological data reading module is used to read the historical hydrological data of the hydrological station, including daily flow and daily sediment rate , and defines the missing year as the target period, and defines the complete year as the candidate period;

[0057] The comprehensive similarity calculation module is used to calculate the Nash Sutcliffe efficiency NSE, the Kling Gupta efficiency KGE and the Pearson correlation coefficient ρ of the annual flow sequence of each target period and candidate period respectively, to obtain the comprehensive similarity; the candidate year or candidate year set with the maximum comprehensive similarity is selected as the reference hydrological year of the target period;

[0058] The curve fitting module determines the bed-forming flow in the reference hydrological year, and divides the flow sequence in the reference hydrological year into low flow level and high flow level; for the two levels of flow, the fitting of the power function curve of the and correlation relationship is performed respectively;

[0059] The sediment concentration calculation module calculates the sediment rate of the corresponding time step based on the segmented power function curve for the flow data of the target period; The sediment concentration is calculated and supplemented for the sediment concentration of the target period.

[0060] The pseudo missing test module performs a pseudo missing test. If the error index does not satisfy a threshold value, the comprehensive similarity weight parameter w or the reference hydrological year set parameter k is adjusted, and the process returns to step 2 until the threshold value is satisfied.

[0061] The embodiment of the present application provides a computer readable storage medium, which stores program codes. The program codes are executed by a processor to implement the steps of the plain river sediment concentration restoration method based on daily flow process similarity.

[0062] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system or a computer program product. Therefore, the present application can adopt a completely hardware embodiment, a completely software embodiment or an embodiment combining software and hardware aspects. Moreover, the present application can adopt a computer program product in the form of being implemented on one or more computer usable storage media containing computer usable program codes (including but not limited to disk memory, CD-ROM, optical memory, etc.).

[0063] The present application is described with reference to flowcharts and / or block diagrams of the method, device (system) and computer program product according to the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams and the combination of the flows and / or blocks 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 produce a device implemented in the flowcharts and / or block diagrams. Figure 1 The function specified in one or more flows and / or blocks. Figure 1 The function specified in one or more flows and / or blocks.

[0064] These computer program instructions can also be stored in a computer readable memory capable of guiding a computer or other programmable data processing device to work in a specific way, so that the instructions stored in the computer readable memory produce a product including instruction devices, which implement the functions specified in the flowcharts and / or block diagrams. Figure 1 The function specified in one or more flows and / or blocks. Figure 1 The function specified in one or more flows and / or blocks.

[0065] These computer program instructions can also be loaded into a computer or other programmable data processing device, so that a series of operation steps are performed on the computer or other programmable device to produce a computer implemented process, so that the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in the flowcharts and / or block diagrams. Figure 1 The function specified in one or more flows and / or blocks. Figure 1 The function specified in one or more flows and / or blocks.

[0066] In one typical arrangement, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0067] Memory can include non-persistent memory and / or volatile memory, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM), electrically programmable read only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), flash memory, or other memory technologies. The memory is an example of computer readable media.

[0068] Computer readable media includes permanent and non-permanent, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD), or other optical storage, magnetic cassettes, magnetic tapes, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information accessible to a computing device. According to the definition herein, computer readable media does not include transitory media, such as modulated data signals and carrier waves.

[0069] The above only describes the embodiments of the present application and is not used to limit the protection scope of the present application. For those skilled in the art, the present application can have various modifications and changes. Any modification, equivalent replacement, improvement, etc. within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for restoring sediment content in plain rivers, characterized in that, The method comprises the following steps: Step 1. Read the hydrograph station containing daily flow with daily sediment rate and historical hydrological data, define the missing years as target periods, and define the complete years as candidate periods; ​​ Step 2. Nash Sutcliffe efficiency NSE, Kling Gupta efficiency KGE and Pearson correlation coefficient p are calculated respectively for each target period and the annual flow sequence of the candidate period to obtain a comprehensive similarity; a candidate year or a candidate year set with the maximum comprehensive similarity is selected as the reference hydrological year of the target period; Step 3. In the reference hydrological year, determine the bed-building discharge , and divide the discharge series in the reference hydrological year into low discharge levels and high discharge levels; for the two levels of discharge, respectively, carry out and correlation power function curve fitting; Step 4. Calculate the sediment discharge of each time step based on the piecewise power function curve for the flow data of the target period ; Calculate and supplement the sediment concentration of the target period by the sediment discharge ​ Step 5. Pseudo-loss verification is performed, if the error index does not satisfy the threshold value, the comprehensive similarity weight parameter w or the reference hydrological year set parameter k is adjusted, and then step 2 is returned until the threshold value is satisfied; In the step 2, The comprehensive similarity is: ， wherein, are weight coefficients, and satisfy The initial values are set as 0.4, 0.3, 0.

3. The step 2 before taking comprehensive similarity Name as the reference hydrological year; The bed-building flow in step 3 The calculation method is as follows: the average of the highest two months of the monthly average water level in the reference hydrological year is calculated as the bankfull water level, the bankfull flow is found through the water level-flow relationship of the hydrological station, and the bankfull flow is the bed-building flow. ， wherein, is the average water level of the two months with the highest average water level in the reference hydrological year, is the water level-discharge relationship function of the hydrological station; At low flow levels, a power function is used to the reference year and data to obtain parameters ; at high flow levels, a power function is used to the reference year and data to obtain parameters ; The error threshold in step 5 is: relative error of annual sediment discharge , daily sediment concentration process , while controlling the error of reconstructed annual sediment discharge and daily process.

2. A system for restoring sediment concentration in a plain river for implementing the method of claim 1, characterized by, The method comprises the following steps, The hydrological data reading module is used to read the daily flow data from the hydrological station. With daily sediment transport rate Historical hydrological data, The missing year is defined as the target period. A complete year is defined as the candidate period; A comprehensive similarity calculation module is configured to calculate Nash Sutcliffe efficiency NSE, Kling Gupta efficiency KGE and Pearson correlation coefficient p respectively for each target period and the annual flow sequence of the candidate period to obtain a comprehensive similarity; a candidate year or a candidate year set with the maximum comprehensive similarity is selected as the reference hydrological year of the target period; a curve fitting module, in the reference hydrological year, determining the bed-building discharge , and dividing the discharge sequence in the reference hydrological year into low discharge levels and high discharge levels; for the two levels of discharge, respectively, fitting the power function curve of and correlation relationship The sediment concentration calculation module calculates the sediment discharge rate of the corresponding time step based on the piecewise power function curve respectively for the flow data of the target period ; the sediment concentration of the target period is calculated and supplemented by the sediment concentration ​ A pseudo-loss verification module is configured to perform pseudo-loss verification, if the error index does not satisfy the threshold value, the comprehensive similarity weight parameter w or the reference hydrological year set parameter k is adjusted, and then step 2 is returned until the threshold value is satisfied.

3. A computer-readable storage medium, characterized in that, The computer readable storage medium stores program code, and the program code is executed by the processor to realize the steps of the plain river sediment concentration restoration method in claim 1.

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