Method, system and equipment for controlling salt pressing flow and medium

Abstract

The invention discloses a salt pressure flow control method, system and device and a medium, and the control method comprises the steps: obtaining a preset salinity threshold value, and estuary tide level data, estuary salt tide data and historical tide data of a tidal estuary; tide level prediction is carried out on the historical tide data to obtain predicted tide level data, and the predicted tide level data are used for indicating the tide level of the tidal estuary at the future moment; inputting the predicted tide level data, the salinity threshold value, the estuary tide level data and the estuary salt tide data into a trained saltwater pressure flow analysis model for saltwater pressure flow inversion analysis to obtain a saltwater pressure flow analysis result; and according to the saltwater pressure flow analysis result, saltwater pressure control is performed on the tidal estuary. According to the control method for the saltwater pressure flow, the prediction precision of the saltwater pressure flow can be effectively improved, and the saltwater pressure effect of an estuary area is improved. The invention relates to the technical field of hydrology science.

Description

Technical Field

[0001] The present invention relates to the field of hydrological science and technology, and in particular to a method, system, equipment and medium for controlling pressure-salt flow. Background Art

[0002] With the impact of global climate change and human activities on water resources and environment, the problem of saltwater intrusion in estuary areas has become more and more serious. Saltwater intrusion in estuaries not only affects the domestic water use of local residents, but also has an adverse impact on agricultural irrigation, industrial water use and the ecological environment. In order to effectively control saltwater intrusion, reducing saltwater flow has become the key to water resources management.

[0003] At present, the existing technology is usually based on empirical models or simulation trials. It predicts the compressed saline flow through historical empirical analysis of estuary salinity under different hydrological conditions, and then uses the analyzed and predicted compressed saline flow to control the estuary salt tide. This method is difficult to cope with complex dynamic changes and often cannot effectively capture the complex nonlinear relationship between the hydrodynamics and salt tide interaction in the estuary area. The accuracy of the predicted compressed saline flow is unsatisfactory, and the compressed saline effect in the estuary area is not good.

[0004] Therefore, the problems existing in the prior art still need to be solved and optimized. Summary of the invention

[0005] The purpose of the present invention is to solve one of the technical problems existing in the related art to at least a certain extent.

[0006] To this end, an object of an embodiment of the present invention is to provide a method, system, device and medium for controlling pressure-salt flow, wherein the method for controlling pressure-salt flow can effectively improve the prediction accuracy of pressure-salt flow and improve the pressure-salt effect in the estuary area.

[0007] In order to achieve the above technical objectives, the technical solutions adopted by the embodiments of the present application include:

[0008] In a first aspect, an embodiment of the present application provides a method for controlling a pressure-salt flow rate, comprising:

[0009] Acquire a preset salinity threshold, as well as estuary tide level data, estuary salt tide data and historical tide data of a tidal estuary, wherein the estuary tide level data is used to indicate the current tidal tide level of the tidal estuary, and the estuary salt tide data is used to indicate the current tidal salinity of the tidal estuary;

[0010] Performing tide level prediction on the historical tide data to obtain predicted tide level data, wherein the predicted tide level data is used to indicate the tide level of the tidal estuary at a future time;

[0011] Inputting the predicted tide level data, the salinity threshold, the estuary tide level data and the estuary saltwater tide data into a trained pressure-salt flow analysis model to perform pressure-salt flow inversion analysis to obtain a pressure-salt flow analysis result;

[0012] According to the pressure-salinity flow analysis results, pressure-salinity control is performed on the tidal estuary.

[0013] In addition, the method for controlling the pressure-salt flow rate according to the above embodiment of the present application may also have the following additional technical features:

[0014] Further, in one embodiment of the present application, the performing tide level prediction on the historical tide data to obtain predicted tide level data includes:

[0015] Separating the historical tidal data into tidal components to obtain a plurality of tidal component data;

[0016] According to a preset tide prediction function, tide level is extrapolated for all the tidal component data to obtain the predicted tide level data.

[0017] Further, in one embodiment of the present application, the step of performing tide level calculation on all the tidal tidal data according to a preset tide level prediction function to obtain the predicted tide level data includes:

[0018] Performing tidal harmonic analysis on all the tidal tidal data to obtain the tidal amplitude, tidal frequency and tidal phase angle corresponding to each tidal tidal data;

[0019] According to the tide prediction function, tide level is calculated for all the tidal amplitudes, tidal frequencies and tidal phase angles to obtain the predicted tide level data.

[0020] Further, in one embodiment of the present application, the trained pressure-salt flow analysis model is obtained by the following steps:

[0021] Obtaining original tide level training data, original saltwater tide training data and historical flow data of the tidal estuary,

[0022] Performing data preprocessing on the original tide level training data to obtain target tide level training data, and performing data preprocessing on the original saltwater tide training data to obtain target saltwater tide training data;

[0023] Inputting the target tide level training data and the target saltwater tide training data into the initialized pressure-saltwater flow analysis model to obtain analysis flow data;

[0024] According to the historical flow data and the analyzed flow data, the parameters of the initialized pressure-salt flow analysis model are updated to obtain the trained pressure-salt flow analysis model.

[0025] Furthermore, in one embodiment of the present application, data preprocessing is performed on the historical target data to obtain historical training data, including:

[0026] Performing data cleaning on the historical target data to obtain first intermediate data;

[0027] Performing data smoothing processing on the first intermediate data to obtain second intermediate data;

[0028] performing data standardization on the second intermediate data to obtain the historical training data;

[0029] Wherein, the historical target data is the original tide level training data or the original saltwater tide training data.

[0030] Further, in the embodiment of the present application, the parameters of the initialized compressed-salt flow analysis model are updated according to the historical flow data and the analyzed flow data to obtain the trained compressed-salt flow analysis model, including:

[0031] Determining a target loss value based on the historical flow data and the analyzed flow data;

[0032] According to the target loss value, the initialized pressure-salt flow analysis model is updated to obtain the trained pressure-salt flow analysis model.

[0033] Furthermore, in one embodiment of the present application, the tide prediction function is expressed as:

[0034]

[0035] Where H(·) is the predicted tide data at the future time t; t is the total number of tidal data; f i is the harmonic constant corresponding to the i-th tidal data; H i is the tidal amplitude of the i-th tidal data; ω i is the tidal frequency of the i-th tidal data; g i is the tidal phase angle of the i-th tidal data; t is the future time.

[0036] In a second aspect, an embodiment of the present application provides a pressure-salt flow control system, including:

[0037] A first processing unit is used to obtain a preset salinity threshold, and estuary tide level data, estuary salt tide data and historical tidal data of a tidal estuary, wherein the estuary tide level data is used to indicate the current tidal tide level of the tidal estuary, and the estuary salt tide data is used to indicate the current tidal salinity of the tidal estuary;

[0038] A second processing unit is used to perform tide level prediction on the historical tide data to obtain predicted tide level data, wherein the predicted tide level data is used to indicate the tide level of the tidal estuary at a future time;

[0039] A third processing unit is used to input the predicted tide level data, the salinity threshold, the estuary tide level data and the estuary saltwater tide data into the trained pressure-salt flow analysis model to perform pressure-salt flow inversion analysis to obtain a pressure-salt flow analysis result;

[0040] The fourth processing unit is used to perform pressure-salinity control on the tidal estuary according to the pressure-salinity flow analysis result.

[0041] In a third aspect, an embodiment of the present application further provides an electronic device, including:

[0042] at least one processor;

[0043] at least one memory for storing at least one program;

[0044] When the at least one program is executed by the at least one processor, the at least one processor implements the method of the first aspect described above.

[0045] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, which stores a program executable by a processor, and the program executable by the processor is used to implement the method of the first aspect when executed by the processor.

[0046] The advantages and benefits of the present application will be partially given in the following description, and partially become apparent from the following description, or be understood through the practice of the present application:

[0047] The embodiments of the present application disclose a method, system, device and medium for controlling a pressure-salinity flow, wherein the control method comprises obtaining a preset salinity threshold, and estuary tide level data, estuary salt tide data and historical tidal data of a tidal estuary, wherein the estuary tide level data is used to indicate the current tidal level of the tidal estuary, and the estuary salt tide data is used to indicate the current tidal salinity of the tidal estuary; performing tidal level prediction on the historical tidal data to obtain predicted tidal level data, wherein the predicted tidal level data is used to indicate the tidal level of the tidal estuary at a future time; inputting the predicted tidal level data, the salinity threshold, the estuary tide level data and the estuary salt tide data into a trained pressure-salinity flow analysis model to perform a pressure-salinity flow inversion analysis to obtain a pressure-salinity flow analysis result; and performing pressure-salinity control on the tidal estuary according to the pressure-salinity flow analysis result. This control method predicts the predicted tide level data at future times through historical tidal data, and then inputs the predicted tide level data, salinity threshold, estuary tide level data and estuary salt tide data into the pressure-salinity flow analysis model for pressure-salinity flow inversion analysis. It can calculate the minimum pressure-salinity flow required to meet the salinity requirements in the estuary area at future times earlier, with high prediction accuracy, which is beneficial to improving the pressure-salinity effect on the estuary area. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the embodiments of the present application or the drawings of the related technical solutions in the prior art are introduced below. It should be understood that the drawings introduced below are only for the convenience of clearly expressing some embodiments of the technical solutions of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0049] Figure 1 A schematic flow chart of a method for controlling a pressure-salt flow rate provided in an embodiment of the present application;

[0050] Figure 2 A schematic diagram of the structure of a pressure-salt flow control system provided in an embodiment of the present application;

[0051] Figure 3 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0052] 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 only used to explain the present application, and are not to be construed as limitations on the present application. For the step numbers in the following embodiments, they are only provided for the convenience of explanation, and the order between the steps is not limited in any way, and the execution order of each step in the embodiment can be adaptively adjusted according to the understanding of those skilled in the art.

[0053] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0054] The following first introduces the technical terms involved in the embodiments of the present application:

[0055] Salty flow reduction refers to the process of increasing the freshwater runoff in the river channel by dispatching upstream reservoirs in tidal estuary areas, thereby suppressing the upstream flow of salty tides and moving the salt boundary below the water intake to ensure the flow used for normal water intake.

[0056] At present, the existing technology is usually based on empirical models or simulation trials. It predicts the compressed saline flow through historical empirical analysis of estuary salinity under different hydrological conditions, and then uses the analyzed and predicted compressed saline flow to control the estuary salt tide. This method is difficult to cope with complex dynamic changes and often cannot effectively capture the complex nonlinear relationship between the hydrodynamics and salt tide interaction in the estuary area. The accuracy of the predicted compressed saline flow is unsatisfactory, and the compressed saline effect in the estuary area is not good.

[0057] In addition, for the monitoring of estuarine saltwater tides, the existing technology is usually based on hydrodynamic mechanism models or existing data-driven machine learning models. Among them, the hydrodynamic mechanism model (such as a two-dimensional hydrodynamic model or a three-dimensional hydrodynamic model) is usually based on the hydrodynamic characteristics of the estuarine water body, and uses partial differential equations to describe the interaction of factors such as water flow, tides, and saltwater tides. Specifically, upstream flow, tidal conditions, wind fields, salinity and other parameters are used as inputs of the hydrodynamic mechanism model, and the propagation and changes of saltwater tides are predicted by solving the hydrodynamic equations. Although this method can more accurately describe the hydrodynamic and saltwater tide changes in the estuarine area, it has a large amount of calculation, strong parameter dependence, and poor adaptability. In addition, the machine learning model is trained through a large amount of historical data, and the changes in saltwater concentration in the estuary area are predicted by inputting information such as upstream flow and tidal conditions. The existing data-driven machine learning model needs to use upstream flow, tidal conditions, etc. as input to predict the changes in downstream saltwater tides. However, due to the unidirectional nature of the prediction results (such as upstream flow determines downstream saltwater tides), the model cannot reversely deduce the upstream flow, the model's generalization ability is limited, and the prediction accuracy is unsatisfactory.

[0058] In view of this, an embodiment of the present invention provides a control method, system, device and medium for pressure-salt flow, wherein the control method predicts the predicted tide level data at a future time through historical tidal data, and then inputs the predicted tide level data, salinity threshold, estuary tide level data and estuary salt tide data into a pressure-salt flow analysis model for pressure-salt flow inversion analysis, which can calculate earlier the minimum pressure-salt flow required for the estuary area to meet the salinity requirements at a future time, with high prediction accuracy, which is beneficial to improving the pressure-salt effect on the estuary area. In addition, the control method is based on reverse thinking, and determines the tide level data and salt tide data as the input of the pressure-salt flow analysis model, which can effectively overcome the limitations of existing hydrodynamic mechanism models or data-driven machine learning models in estuary salt tide monitoring, and is beneficial to achieve accurate and dynamic control of the pressure-salt flow.

[0059] Reference Figure 1 In an embodiment of the present application, a method for controlling a pressure-salt flow rate includes:

[0060] Step 110, obtaining a preset salinity threshold, as well as estuary tide level data, estuary salt tide data and historical tidal data of a tidal estuary, wherein the estuary tide level data is used to indicate the current tidal tide level of the tidal estuary, and the estuary salt tide data is used to indicate the current tidal salinity of the tidal estuary;

[0061] In an embodiment of the present application, the preset salinity threshold may be the critical salinity at the water intake in the estuary area of ​​a tidal estuary, and the salinity threshold may be any one of 0.3%, 0.5%, 0.8%, etc.; in addition, in actual applications, since the salinity of the estuary area is mainly affected by the chlorine content of the water in the estuary area, the preset salinity threshold may also be a chlorine content threshold, and its specific value may be 250 mg / L, etc. The examples in this application are for illustration only and are not intended to limit the present application.

[0062] It can be understood that a tidal estuary can be a river section where a river flows into the sea and is affected by tides, and the water level and salinity of the tidal estuary vary with tidal fluctuations and runoff size; the estuary tide level data can be the tidal tide level of the tidal estuary at the current moment, and the estuary salt tide data can be the tidal salinity of the tidal estuary at the current moment, and the tidal salinity can be the salinity of the water body in the tidal estuary, or the chlorine content of the water body in the tidal estuary, or a combination of the salinity and chlorine content of the water body in the tidal estuary.

[0063] It should be noted that the historical tidal data may include a historical tidal level set of the tidal estuary, which may be a set of tidal level data of the tidal estuary in the recent period, or a set of tidal level data of the tidal estuary in the same period in previous years; or, the historical tidal level set may also be a set of tidal level data of the tidal estuary in the recent period and tidal level data of the same period in previous years, and this application example is for illustration only.

[0064] Step 120: performing tide level prediction on the historical tide data to obtain predicted tide level data, wherein the predicted tide level data is used to indicate the tide level of the tidal estuary at a future time;

[0065] In an embodiment of the present application, the tide level prediction can be based on the historical tide level data to predict the tide level of the tidal estuary at a future time, so as to obtain the predicted tide level data, wherein the future time can be a future time point or a future time period. Specifically, the predicted tide level data of the embodiment of the present application can be the tide level of the tidal estuary within the next three days, or the tide level of the tidal estuary within a certain day in the future, or the tide level of the tidal estuary at a certain point in the future.

[0066] In some embodiments, performing tide level prediction on the historical tide data to obtain predicted tide level data includes:

[0067] A1, performing tidal separation on the historical tidal data to obtain a plurality of tidal separation data;

[0068] In an embodiment of the present application, step A1 may be to separate each tidal component data in the historical tidal data. The historical tidal data may be regarded as the superposition of tidal component data of multiple simple harmonic oscillations, thereby obtaining a plurality of tidal component data.

[0069] A2. According to a preset tide prediction function, tide level is calculated for all the tide data to obtain the predicted tide data.

[0070] Furthermore, the step A2, performing tide level calculation on all the tidal data according to a preset tide level prediction function to obtain the predicted tide level data, includes:

[0071] A21, performing tidal harmonization analysis on all the tidal tidal data to obtain the tidal amplitude, tidal frequency and tidal phase angle corresponding to each tidal tidal data;

[0072] A22. According to the tide prediction function, the tide level is calculated for all the tidal amplitudes, the tidal frequencies and the tidal phase angles to obtain the predicted tide level data.

[0073] In an embodiment of the present application, step A21 can be to perform tidal harmonization analysis on each tidal component data separately. Specifically, the tidal harmonization analysis on the tidal component data can be achieved by any one of Darwin analysis method, Doodson analysis method, least squares method, Fourier analysis method, spectral analysis method, etc., so as to obtain the tidal component data, tidal frequency and tidal phase angle corresponding to each tidal component data.

[0074] It can be understood that step A22 can be to input the tidal amplitude, tidal frequency and tidal phase angle corresponding to each tidal component data into the tide level prediction function to obtain the intermediate predicted tide level corresponding to each tidal component data, and then perform cumulative summation operation on the intermediate predicted tide level corresponding to each tidal component data to obtain the predicted tide level data.

[0075] For example, the tide prediction function is expressed as:

[0076]

[0077] Where H(·) is the predicted tide data at the future time t; t is the total number of tidal data; f i is the harmonic constant corresponding to the i-th tidal data; H i is the tidal amplitude of the i-th tidal data; ω i is the tidal frequency of the i-th tidal data; g i is the tidal phase angle of the i-th tidal data; t is the future time.

[0078] Step 130, inputting the predicted tide level data, the salinity threshold, the estuary tide level data and the estuary saltwater tide data into the trained pressure-salt flow analysis model to perform pressure-salt flow inversion analysis to obtain a pressure-salt flow analysis result;

[0079] In an embodiment of the present application, the predicted tide level data, salinity threshold, estuary tide level data and estuary saltwater tide data can be input into a trained pressure-salt flow analysis model for pressure-salt flow inversion analysis to obtain the pressure-salt flow analysis results, wherein the predicted tide level data is the tide level at a future moment, and the salinity threshold is the salinity at the same moment as the predicted tide level data.

[0080] In some embodiments, the trained pressure-salt flow analysis model is obtained by the following steps:

[0081] B1, obtaining the original tide level training data, original saltwater tide training data and historical flow data of the tidal estuary,

[0082] In an embodiment of the present application, the original tide training data and the original saltwater tide training data may be data directly collected by sensors in the tidal estuary area, specifically, the hourly tide level and hourly saltwater tide of the tidal estuary 15 minutes before the current time; the historical flow data may be the upstream flow data corresponding to the original tide training data and the original saltwater tide training data.

[0083] B2, performing data preprocessing on the original tide level training data to obtain target tide level training data, and performing data preprocessing on the original saltwater tide training data to obtain target saltwater tide training data;

[0084] Furthermore, the historical target data is preprocessed to obtain historical training data, including:

[0085] B21. Clean the historical target data to obtain first intermediate data;

[0086] B22, performing data smoothing processing on the first intermediate data to obtain second intermediate data;

[0087] B23, performing data standardization on the second intermediate data to obtain the historical training data;

[0088] Wherein, the historical target data is the original tide level training data or the original saltwater tide training data.

[0089] In an embodiment of the present application, if the historical target data is the original tide training data, step B21 may be to perform missing value detection on the original tide training data, so as to remove the missing values ​​in the original tide training data and obtain the first intermediate data; then, step B22 may be to perform outlier detection on the first intermediate data, and smooth the outliers in the original tide training data through a smoothing operation to reduce noise interference and obtain the second intermediate data; step B23 may be to standardize the tide data in the second intermediate data so that the input tide data has a consistent scale and obtain the historical training data, at which time the historical training data may be the target tide training data.

[0090] It is understandable that if the historical target data is the original saltwater tide training data, then its content is similar to the aforementioned original tide level training data, and can be simply deduced by analogy. In addition, in the embodiment of the present application, the historical flow data can also be preprocessed to obtain the historical flow data after data preprocessing, and the specific data preprocessing method is similar to the content of the aforementioned historical target data.

[0091] B3, inputting the target tide level training data and the target saltwater tide training data into the initialized pressure-salt flow analysis model to obtain analysis flow data;

[0092] In an embodiment of the present application, the initialized pressure-salt flow analysis model can be a long short-term memory network (LSTM) model, and step B3 can be to input the target tide level training data and the target salt tide training data into the initialized pressure-salt flow analysis model for flow analysis and prediction, and capture the connection between tide level, salt tide and other data at different time points through the initialized pressure-salt flow analysis model, so as to obtain the analysis flow data output by the initialized pressure-salt flow analysis model.

[0093] B4. Update the parameters of the initialized compressed-salt flow analysis model according to the historical flow data and the analyzed flow data to obtain the trained compressed-salt flow analysis model.

[0094] In an embodiment of the present application, the model parameters of the initialized compressed-salt flow analysis model can be updated by measuring the deviation between the historical flow data and the analyzed flow data at the same time point, so as to obtain the compressed-salt flow analysis model of the training number.

[0095] Furthermore, the step B4, updating the parameters of the initialized pressure-salt flow analysis model according to the historical flow data and the analysis flow data to obtain the trained pressure-salt flow analysis model, includes:

[0096] B41. Determine a target loss value based on the historical flow data and the analyzed flow data;

[0097] B42. According to the target loss value, the initialized pressure-salt flow analysis model is updated to obtain the trained pressure-salt flow analysis model.

[0098] In the embodiment of the present application, the historical flow data can be used as the label corresponding to the target tide training data and the target saltwater training data. The prediction accuracy of the pressure-salt flow analysis model for the required pressure-salt flow is measured by measuring the degree of deviation between the historical flow data and the analytical flow data. The smaller the degree of deviation between the historical flow data and the analytical flow data, the higher the prediction accuracy of the pressure-salt flow analysis model for the required pressure-salt flow. Conversely, the greater the degree of deviation between the historical flow data and the analytical flow data, the lower the prediction accuracy of the pressure-salt flow analysis model for the required pressure-salt flow. Therefore, in the embodiment of the present application, a target loss value can be determined based on the historical flow data and the analytical flow data. The loss function used to determine the target loss value can specifically be a mean square error (MSE) function. The example of the present application is only for illustration and does not make specific restrictions on the loss function used.

[0099] It is understandable that after determining the target loss value, the relevant parameters of the pressure-salt flow analysis model can be updated by the back propagation algorithm, thereby improving the performance of the pressure-salt flow analysis model. In the embodiment of the present application, the training method can be carried out in a cyclic iteration, that is, the parameters of the pressure-salt flow analysis model can be updated round by round. Exemplarily, for example, multiple target tide training data, target salt tide training data and historical flow data can be obtained, and then these data are divided into different training data groups, and the corresponding target loss value is first calculated using the data of a training data group to update the parameters of a round of pressure-salt flow analysis model. Then, based on the updated pressure-salt flow analysis model, the corresponding target loss value is calculated using the data of another training data group, and the parameters of a round of pressure-salt flow analysis model are continued to be updated. In this way, the trained pressure-salt flow analysis model is obtained by cyclic iteration. Here, the conditions for determining the end of training can be set according to actual needs. For example, in some embodiments, the target round of training iteration can be set, the iteration round can be recorded during the training process, and the parameters of the model are updated each time, and the iteration round can be added by 1. If the iteration round reaches the target round after the current model parameters are updated, the training can be considered to be completed and a trained pressure-salt flow analysis model is obtained; if the iteration round does not reach the target round after the current model parameters are updated, iterative training can continue. In some embodiments, a test data set can also be obtained to detect the prediction accuracy of the pressure-salt flow analysis model through the test data set. Each time the model parameters are updated, the test data set is used for detection. If the prediction accuracy obtained by the test meets the pre-set index requirements after the current model parameters are updated, the training can be considered to be completed and a trained pressure-salt flow analysis model is obtained; if the prediction accuracy obtained by the test does not meet the pre-set index requirements after the current model parameters are updated, iterative training can continue. Of course, the above embodiments are only used to exemplify the process of updating the pressure-salt flow analysis model parameters in this application, and do not mean to limit its specific implementation.

[0100] Step 140: Perform pressure-salinity control on the tidal estuary according to the pressure-salinity flow analysis result.

[0101] In an embodiment of the present application, after obtaining the pressure-salinity flow analysis results, a flow control instruction for the upstream reservoir group can be generated based on the pressure-salinity flow analysis results. By controlling the gates of several reservoirs in the upstream reservoir group, the pressure-salinity flow flowing into the tidal estuary at future times can be controlled, so that the salinity of the water body in the tidal estuary is less than or equal to a preset salinity threshold, thereby achieving pressure-salinity control of the tidal estuary.

[0102] It should be noted that in practical applications, real-time estuary tide data, real-time saltwater data and historical tide data of tidal estuaries can be continuously obtained, and by continuously performing tide prediction and pressure-salinity flow inversion analysis, the real-time dynamically changing pressure-salinity flow can be obtained and pressure-salinity control of the tidal estuary can be achieved based on the pressure-salinity flow.

[0103] A pressure-salt flow control system proposed according to an embodiment of the present application is described in detail below with reference to the accompanying drawings.

[0104] Reference Figure 2 A pressure-salt flow control system proposed in an embodiment of the present application includes:

[0105] The first processing unit 101 is used to obtain a preset salinity threshold, and estuary tide level data, estuary salt tide data and historical tidal data of a tidal estuary, wherein the estuary tide level data is used to indicate the current tidal level of the tidal estuary, and the estuary salt tide data is used to indicate the current tidal salinity of the tidal estuary;

[0106] A second processing unit 102 is used to perform tide level prediction on the historical tide data to obtain predicted tide level data, wherein the predicted tide level data is used to indicate the tide level of the tidal estuary at a future time;

[0107] The third processing unit 103 is used to input the predicted tide level data, the salinity threshold, the estuary tide level data and the estuary saltwater tide data into the trained pressure-salt flow analysis model to perform pressure-salt flow inversion analysis to obtain a pressure-salt flow analysis result;

[0108] The fourth processing unit 104 is used to perform pressure-salinity control on the tidal estuary according to the pressure-salinity flow analysis result.

[0109] It can be understood that the contents of the above method embodiments are all applicable to the present system embodiments, the functions specifically implemented by the present system embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0110] Reference Figure 3 , the embodiment of the present application further provides an electronic device, including:

[0111] at least one processor 201;

[0112] At least one memory 202, used to store at least one program;

[0113] When the at least one program is executed by the at least one processor 201, the at least one processor 201 implements the above method embodiment.

[0114] Similarly, it can be understood that the contents of the above method embodiments are all applicable to the present device embodiments, the functions specifically implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0115] The embodiment of the present application further provides a computer-readable storage medium, in which a program executable by the processor 201 is stored. The program executable by the processor 201 is used to implement the above-mentioned method embodiment when executed by the processor 201.

[0116] Similarly, the contents of the above method embodiments are all applicable to the computer-readable storage medium embodiments. The functions specifically implemented by the computer-readable storage medium embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0117] In some selectable embodiments, the function / operation mentioned in the block diagram may not occur in the order mentioned in the operation diagram. For example, depending on the function / operation involved, the two boxes shown in succession can actually be executed substantially simultaneously or the boxes can sometimes be executed in reverse order. In addition, the embodiment presented and described in the flow chart of the application is provided by way of example, for the purpose of providing a more comprehensive understanding of technology. The disclosed method is not limited to the operation and logic flow presented herein. Selectable embodiments are expected, wherein the order of various operations is changed and the sub-operation of a part described as a larger operation is performed independently.

[0118] In addition, although the present application is described in the context of functional modules, it should be understood that, unless otherwise specified, one or more of the functions and / or features can be integrated into a single physical device and / or software module, or one or more functions and / or features can be implemented in a separate physical device or software module. It is also understood that a detailed discussion of the actual implementation of each module is unnecessary for understanding the present application. More specifically, in view of the properties, functions, and internal relationships of the various functional modules in the device disclosed herein, the actual implementation of the module will be understood within the conventional techniques of the engineer. Therefore, those skilled in the art can implement the present application set forth in the claims without excessive experimentation using ordinary techniques. It is also understood that the specific concepts disclosed are merely illustrative and are not intended to limit the scope of the present application, which is determined by the full scope of the attached claims and their equivalents.

[0119] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method of the embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0120] 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 conjunction with such instruction execution systems, devices or apparatuses. For the purposes 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 conjunction with such instruction execution systems, devices or apparatuses.

[0121] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (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 a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0122] 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-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: 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.

[0123] In the above description of this specification, the description with reference to the terms "one embodiment / example", "another embodiment / example" or "certain embodiments / 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 representation of the above terms does 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 more embodiments or examples in a suitable manner.

[0124] Although the embodiments of the present application have been shown and described, those skilled in the art will appreciate that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present application, and that the scope of the present application is defined by the claims and their equivalents.

[0125] The above is a specific description of the preferred implementation of the present application, but the present application is not limited to the embodiments. Technical personnel familiar with the field can make various equivalent modifications or substitutions without violating the spirit of the present application. These equivalent modifications or substitutions are all included in the scope defined by the claims of the present application.

Claims

1. A method for controlling pressure-salt flow, characterized in that: include: Acquire a preset salinity threshold, as well as estuary tide level data, estuary salt tide data and historical tide data of a tidal estuary, wherein the estuary tide level data is used to indicate the current tidal tide level of the tidal estuary, and the estuary salt tide data is used to indicate the current tidal salinity of the tidal estuary; Performing tide level prediction on the historical tide data to obtain predicted tide level data, wherein the predicted tide level data is used to indicate the tide level of the tidal estuary at a future time; Inputting the predicted tide level data, the salinity threshold, the estuary tide level data and the estuary saltwater tide data into a trained pressure-salt flow analysis model to perform pressure-salt flow inversion analysis to obtain a pressure-salt flow analysis result; According to the pressure-salinity flow analysis results, pressure-salinity control is performed on the tidal estuary.

2. The method for controlling the pressure-salt flow rate according to claim 1, characterized in that: The step of performing tide level prediction on the historical tide data to obtain predicted tide level data comprises: Separating the historical tidal data into tidal components to obtain a plurality of tidal component data; According to a preset tide prediction function, tide level is extrapolated for all the tidal component data to obtain the predicted tide level data.

3. The method for controlling the pressure-salt flow rate according to claim 2, characterized in that: The step of calculating the tide level of all the tidal data according to the preset tide level prediction function to obtain the predicted tide level data includes: Performing tidal harmonic analysis on all the tidal tidal data to obtain the tidal amplitude, tidal frequency and tidal phase angle corresponding to each tidal tidal data; According to the tide prediction function, tide level is calculated for all the tidal amplitudes, tidal frequencies and tidal phase angles to obtain the predicted tide level data.

4. The method for controlling the pressure-salt flow rate according to claim 1, characterized in that: The trained pressure-salt flow analysis model is obtained by the following steps: Obtaining original tide level training data, original saltwater tide training data and historical flow data of the tidal estuary, Performing data preprocessing on the original tide level training data to obtain target tide level training data, and performing data preprocessing on the original saltwater tide training data to obtain target saltwater tide training data; Inputting the target tide level training data and the target saltwater tide training data into the initialized pressure-saltwater flow analysis model to obtain analysis flow data; According to the historical flow data and the analyzed flow data, the parameters of the initialized pressure-salt flow analysis model are updated to obtain the trained pressure-salt flow analysis model.

5. The method for controlling the pressure-salt flow rate according to claim 4, characterized in that: Perform data preprocessing on historical target data to obtain historical training data, including: Performing data cleaning on the historical target data to obtain first intermediate data; Performing data smoothing processing on the first intermediate data to obtain second intermediate data; performing data standardization on the second intermediate data to obtain the historical training data; Wherein, the historical target data is the original tide level training data or the original saltwater tide training data.

6. The method for controlling the pressure-salt flow rate according to claim 4, characterized in that: The step of updating the parameters of the initialized compressed-salt flow analysis model according to the historical flow data and the analyzed flow data to obtain the trained compressed-salt flow analysis model comprises: Determining a target loss value based on the historical flow data and the analyzed flow data; According to the target loss value, the initialized pressure-salt flow analysis model is updated to obtain the trained pressure-salt flow analysis model.

7. The method for controlling the pressure-salt flow rate according to claim 3, characterized in that: The tide prediction function is expressed as: Where H(·) is the predicted tide data at the future time t; t is the total number of tidal data; f i is the harmonic constant corresponding to the i-th tidal data; H i is the tidal amplitude of the i-th tidal data; ω i is the tidal frequency of the i-th tidal data; g i is the tidal phase angle of the i-th tidal data; t is the future time.

8. A pressure-salt flow control system, characterized in that: include: A first processing unit is used to obtain a preset salinity threshold, and estuary tide level data, estuary salt tide data and historical tidal data of a tidal estuary, wherein the estuary tide level data is used to indicate the current tidal tide level of the tidal estuary, and the estuary salt tide data is used to indicate the current tidal salinity of the tidal estuary; A second processing unit is used to perform tide level prediction on the historical tide data to obtain predicted tide level data, wherein the predicted tide level data is used to indicate the tide level of the tidal estuary at a future time; A third processing unit is used to input the predicted tide level data, the salinity threshold, the estuary tide level data and the estuary saltwater tide data into the trained pressure-salt flow analysis model to perform pressure-salt flow inversion analysis to obtain a pressure-salt flow analysis result; The fourth processing unit is used to perform pressure-salinity control on the tidal estuary according to the pressure-salinity flow analysis result.

9. An electronic device, characterized in that: include: at least one processor; at least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the method according to any one of claims 1 to 7.

10. A computer-readable storage medium storing a program executable by a processor, characterized in that: The program executable by the processor is used to implement the method according to any one of claims 1 to 7 when executed by the processor.

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